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Coulson & Richardson’s CHEMICAL ENGINEERING VOLUME 6 Chemical Engineering, Volume 1, Sixth edition Fluid Flow, Heat Transfer and Mass Transfer J. M. Coulson and J. F. Richardson with J. R. Backhurst and J. H. Harker Chemical Engineering, Volume 2, Fifth edition Particle Technology and Separation Processes J. F. Richardson and J. H. Harker with J. R. Backhurst Chemical Engineering, Volume 3, Third edition Chemical & Biochemical Reactors & Process Control Edited by J. F. Richardson and D. G. Peacock Chemical Engineering, Second edition Solutions to the Problems in Volume 1 J. R. Backhurst and J. H. Harker with J. F. Richardson Chemical Engineering, Solutions to the Problems in Volumes 2 and 3 J. R. Backhurst and J. H. Harker with J. F. Richardson Chemical Engineering, Volume 6, Fourth edition Chemical Engineering Design R. K. Sinnott Coulson & Richardson’s CHEMICAL ENGINEERING VOLUME 6 FOURTH EDITION Chemical Engineering Design R. K. SINNOTT AMSTERDAM ž BOSTON ž HEIDELBERG ž LONDON ž NEW YORK ž OXFORD PARIS ž SAN DIEGO ž SAN FRANCISCO ž SINGAPORE ž SYDNEY ž TOKYO Linacre House, Jordan Hill, Oxford OX2 8DP 30 Corporate Drive, MA 01803 First published 1983 Second edition 1993 Reprinted with corrections 1994 Reprinted with revisions 1996 Third edition 1999 Reprinted 2001, 2003 Fourth edition 2005 Copyright 1993, 1996, 1999, 2005 R. K. Sinnott. All rights reserved The right of R. K. Sinnott to be identified as the author of this work has been asserted in accordance with the Copyright, Designs and Patents Act 1988 No part of this publication may be reproduced in any material form (including photocopying or storing in any medium by electronic means and whether or not transiently or incidentally to some other use of this publication) without the written permission of the copyright holder except in accordance with the provisions of the Copyright, Designs and Patents Act 1988 or under the terms of a licence issued by the Copyright Licensing Agency Ltd, 90 Tottenham Court Road, London, England W1T 4LP. Applications for the copyright holder’s written permission to reproduce any part of this publication should be addressed to the publisher Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone: (C44) (0)1865 843830; fax: (C44) (0)1865 853333; e-mail: permissions@elsevier.co.uk. You may also complete your request on-line via the Elsevier homepage (http://www.elsevier.com), by selecting ‘Customer Support’ and then ‘Obtaining Permissions’ British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloguing in Publication Data A catalogue record for this book is available from the Library of Congress ISBN 0 7506 6538 6 For information on all Elsevier Butterworth-Heinemann publications visit our website at http://books.elsevier.com Typeset by Laserwords Private Limited, Chennai, India Contents PREFACE TO FOURTH EDITION xvii PREFACE TO THIRD EDITION xx PREFACE TO SECOND EDITION xxi PREFACE TO FIRST EDITION xxiii SERIES EDITOR’S PREFACE xxiv ACKNOWLEDGEMENT xxv 1 Introduction to Design 1 1.1 Introduction 1 1.2 Nature of design 1 1.2.1 The design objective (the need) 3 1.2.2 Data collection 3 1.2.3 Generation of possible design solutions 3 1.2.4 Selection 4 1.3 The anatomy of a chemical manufacturing process 5 1.3.1 Continuous and batch processes 7 1.4 The organisation of a chemical engineering project 7 1.5 Project documentation 10 1.6 Codes and standards 12 1.7 Factors of safety (design factors) 13 1.8 Systems of units 14 1.9 Degrees of freedom and design variables. The mathematical representation of the design problem 15 1.9.1 Information flow and design variables 15 1.9.2 Selection of design variables 19 1.9.3 Information flow and the structure of design problems 20 1.10 Optimisation 24 1.10.1 General procedure 25 1.10.2 Simple models 25 1.10.3 Multiple variable problems 27 1.10.4 Linear programming 29 1.10.5 Dynamic programming 29 1.10.6 Optimisation of batch and semicontinuous processes 29 1.11 References 30 1.12 Nomenclature 31 1.13 Problems 32 2 Fundamentals of Material Balances 34 2.1 Introduction 34 2.2 The equivalence of mass and energy 34 2.3 Conservation of mass 34 2.4 Units used to express compositions 35 2.5 Stoichiometry 36 v 2.7 Choice of basis for calculations 40 2.8 Number of independent components 40 2.9 Constraints on flows and compositions 41 2.10 General algebraic method 42 2.11 Tie components 44 2.12 Excess reagent 46 2.13 Conversion and yield 47 2.14 Recycle processes 50 2.15 Purge 52 2.16 By-pass 53 2.17 Unsteady-state calculations 54 2.18 General procedure for material-balance problems 56 2.19 References (Further Reading) 57 2.20 Nomenclature 57 2.21 Problems 57 3 Fundamentals of Energy Balances (and Energy Utilisation) 60 3.1 Introduction 60 3.2 Conservation of energy 60 3.3 Forms of energy (per unit mass of material) 61 3.3.1 Potential energy 61 3.3.2 Kinetic energy 61 3.3.3 Internal energy 61 3.3.4 Work 61 3.3.5 Heat 62 3.3.6 Electrical energy 62 3.4 The energy balance 62 3.5 Calculation of specific enthalpy 67 3.6 Mean heat capacities 68 3.7 The effect of pressure on heat capacity 70 3.8 Enthalpy of mixtures 71 3.8.1 Integral heats of solution 72 3.9 Enthalpy-concentration diagrams 73 3.10 Heats of reaction 75 3.10.1 Effect of pressure on heats of reaction 77 3.11 Standard heats of formation 79 3.12 Heats of combustion 80 3.13 Compression and expansion of gases 81 3.13.1 Mollier diagrams 82 3.13.2 Polytropic compression and expansion 84 3.13.3 Multistage compressors 90 3.13.4 Electrical drives 93 3.14 Energy balance calculations 93 3.15 Unsteady state energy balances 99 3.16 Energy recovery 101 3.16.1 Heat exchange 101 3.16.2 Heat-exchanger networks 101 3.16.3 Waste-heat boilers 102 3.16.4 High-temperature reactors 103 3.16.5 Low-grade fuels 105 3.16.6 High-pressure process streams 107 3.16.7 Heat pumps 110 3.17 Process integration and pinch technology 111 3.17.1 Pinch technology 111 3.17.2 The problem table method 115 3.17.3 The heat exchanger network 117 3.17.4 Minimum number of exchangers 121 3.17.5 Threshold problems 123 3.17.7 Process integration: integration of other process operations 124 3.18 References 127 3.19 Nomenclature 128 3.20 Problems 130 4 Flow-sheeting 133 4.1 Introduction 133 4.2 Flow-sheet presentation 133 4.2.1 Block diagrams 134 4.2.2 Pictorial representation 134 4.2.3 Presentation of stream flow-rates 134 4.2.4 Information to be included 135 4.2.5 Layout 139 4.2.6 Precision of data 139 4.2.7 Basis of the calculation 140 4.2.8 Batch processes 140 4.2.9 Services (utilities) 140 4.2.10 Equipment identification 140 4.2.11 Computer aided drafting 140 4.3 Manual flow-sheet calculations 141 4.3.1 Basis for the flow-sheet calculations 142 4.3.2 Flow-sheet calculations on individual units 143 4.4 Computer-aided flow-sheeting 168 4.5 Full steady-state simulation programs 168 4.5.1 Information flow diagrams 171 4.6 Manual calculations with recycle streams 172 4.6.1 The split-fraction concept 172 4.6.2 Illustration of the method 176 4.6.3 Guide rules for estimating split-fraction coefficients 185 4.7 References 187 4.8 Nomenclature 188 4.9 Problems 188 5 Piping and Instrumentation 194 5.1 Introduction 194 5.2 The P and I diagram 194 5.2.1 Symbols and layout 195 5.2.2 Basic symbols 195 5.3 Valve selection 197 5.4 Pumps 199 5.4.1 Pump selection 199 5.4.2 Pressure drop in pipelines 201 5.4.3 Power requirements for pumping liquids 206 5.4.4 Characteristic curves for centrifugal pumps 208 5.4.5 System curve (operating line) 210 5.4.6 Net positive suction head (NPSH) 212 5.4.7 Pump and other shaft seals 213 5.5 Mechanical design of piping systems 216 5.5.1 Wall thickness: pipe schedule 216 5.5.2 Pipe supports 217 5.5.3 Pipe fittings 217 5.5.4 Pipe stressing 217 5.5.5 Layout and design 218 5.6 Pipe size selection 218 5.7 Control and instrumentation 227 5.7.1 Instruments 227 5.7.2 Instrumentation and control objectives 227 5.7.3 Automatic-control schemes 228 5.8.1 Level control 229 5.8.2 Pressure control 229 5.8.3 Flow control 229 5.8.4 Heat exchangers 230 5.8.5 Cascade control 231 5.8.6 Ratio control 231 5.8.7 Distillation column control 231 5.8.8 Reactor control 233 5.9 Alarms and safety trips, and interlocks 235 5.10 Computers and microprocessors in process control 236 5.11 References 238 5.12 Nomenclature 239 5.13 Problems 240 6 Costing and Project Evaluation 243 6.1 Introduction 243 6.2 Accuracy and purpose of capital cost estimates 243 6.3 Fixed and working capital 244 6.4 Cost escalation (inflation) 245 6.5 Rapid capital cost estimating methods 247 6.5.1 Historical costs 247 6.5.2 Step counting methods 249 6.6 The factorial method of cost estimation 250 6.6.1 Lang factors 251 6.6.2 Detailed factorial estimates 251 6.7 Estimation of purchased equipment costs 253 6.8 Summary of the factorial method 260 6.9 Operating costs 260 6.9.1 Estimation of operating costs 261 6.10 Economic evaluation of projects 270 6.10.1 Cash flow and cash-flow diagrams 270 6.10.2 Tax and depreciation 272 6.10.3 Discounted cash flow (time value of money) 272 6.10.4 Rate of return calculations 273 6.10.5 Discounted cash-flow rate of return (DCFRR) 273 6.10.6 Pay-back time 274 6.10.7 Allowing for inflation 274 6.10.8 Sensitivity analysis 274 6.10.9 Summary 275 6.11 Computer methods for costing and project evaluation 278 6.12 References 279 6.13 Nomenclature 279 6.14 Problems 280 7 Materials of Construction 284 7.1 Introduction 284 7.2 Material properties 284 7.3 Mechanical properties 285 7.3.1 Tensile strength 285 7.3.2 Stiffness 285 7.3.3 Toughness 286 7.3.4 Hardness 286 7.3.5 Fatigue 286 7.3.6 Creep 287 7.3.7 Effect of temperature on the mechanical properties 287 7.4 Corrosion resistance 287 7.4.1 Uniform corrosion 288 7.4.2 Galvanic corrosion 289 7.4.4 Intergranular corrosion 290 7.4.5 Effect of stress 290 7.4.6 Erosion-corrosion 291 7.4.7 High-temperature oxidation 291 7.4.8 Hydrogen embrittlement 292 7.5 Selection for corrosion resistance 292 7.6 Material costs 293 7.7 Contamination 294 7.7.1 Surface finish 295 7.8 Commonly used materials of construction 295 7.8.1 Iron and steel 295 7.8.2 Stainless steel 296 7.8.3 Nickel 298 7.8.4 Monel 299 7.8.5 Inconel 299 7.8.6 The Hastelloys 299 7.8.7 Copper and copper alloys 299 7.8.8 Aluminium and its alloys 299 7.8.9 Lead 300 7.8.10 Titanium 300 7.8.11 Tantalum 300 7.8.12 Zirconium 300 7.8.13 Silver 301 7.8.14 Gold 301 7.8.15 Platinum 301 7.9 Plastics as materials of construction for chemical plant 301 7.9.1 Poly-vinyl chloride (PVC) 302 7.9.2 Polyolefines 302 7.9.3 Polytetrafluroethylene (PTFE) 302 7.9.4 Polyvinylidene fluoride (PVDF) 302 7.9.5 Glass-fibre reinforced plastics (GRP) 302 7.9.6 Rubber 303 7.10 Ceramic materials (silicate materials) 303 7.10.1 Glass 304 7.10.2 Stoneware 304 7.10.3 Acid-resistant bricks and tiles 304 7.10.4 Refractory materials (refractories) 304 7.11 Carbon 305 7.12 Protective coatings 305 7.13 Design for corrosion resistance 305 7.14 References 305 7.15 Nomenclature 307 7.16 Problems 307 8 Design Information and Data 309 8.1 Introduction 309 8.2 Sources of information on manufacturing processes 309 8.3 General sources of physical properties 311 8.4 Accuracy required of engineering data 312 8.5 Prediction of physical properties 313 8.6 Density 314 8.6.1 Liquids 314 8.6.2 Gas and vapour density (specific volume) 315 8.7 Viscosity 316 8.7.1 Liquids 316 8.7.2 Gases 320 8.8 Thermal conductivity 320 8.8.1 Solids 320 8.8.2 Liquids 321 8.8.4 Mixtures 322 8.9 Specific heat capacity 322 8.9.1 Solids and liquids 322 8.9.2 Gases 325 8.10 Enthalpy of vaporisation (latent heat) 328 8.10.1 Mixtures 329 8.11 Vapour pressure 330 8.12 Diffusion coefficients (diffusivities) 331 8.12.1 Gases 331 8.12.2 Liquids 333 8.13 Surface tension 335 8.13.1 Mixtures 335 8.14 Critical constants 336 8.15 Enthalpy of reaction and enthalpy of formation 339 8.16 Phase equilibrium data 339 8.16.1 Experimental data 339 8.16.2 Phase equilibria 339 8.16.3 Equations of state 341 8.16.4 Correlations for liquid phase activity coefficients 342 8.16.5 Prediction of vapour-liquid equilibria 346 8.16.6 K -values for hydrocarbons 348 8.16.7 Sour-water systems (Sour) 348 8.16.8 Vapour-liquid equilibria at high pressures 348 8.16.9 Liquid-liquid equilibria 348 8.16.10 Choice of phase equilibria for design calculations 350 8.16.11 Gas solubilities 351 8.16.12 Use of equations of state to estimate specific enthalpy and density 353 8.17 References 353 8.18 Nomenclature 357 8.19 Problems 358 9 Safety and Loss Prevention 360 9.1 Introduction 360 9.2 Intrinsic and extrinsic safety 361 9.3 The hazards 361 9.3.1 Toxicity 361 9.3.2 Flammability 363 9.3.3 Explosions 365 9.3.4 Sources of ignition 366 9.3.5 Ionising radiation 368 9.3.6 Pressure 368 9.3.7 Temperature deviations 369 9.3.8 Noise 370 9.4 Dow fire and explosion index 371 9.4.1 Calculation of the Dow F & EI 371 9.4.2 Potential loss 375 9.4.3 Basic preventative and protective measures 377 9.4.4 Mond fire, explosion, and toxicity index 378 9.4.5 Summary 379 9.5 Hazard and operability studies 381 9.5.1 Basic principles 382 9.5.2 Explanation of guide words 383 9.5.3 Procedure 384 9.6 Hazard analysis 389 9.7 Acceptable risk and safety priorities 390 9.8 Safety check lists 392 9.9 Major hazards 394 9.9.1 Computer software for quantitative risk analysis 395 9.11 Problems 398 10 Equipment Selection, Specification and Design 400 10.1 Introduction 400 10.2 Separation processes 401 10.3 Solid-solid separations 401 10.3.1 Screening (sieving) 401 10.3.2 Liquid-solid cyclones 404 10.3.3 Hydroseparators and sizers (classifiers) 405 10.3.4 Hydraulic jigs 405 10.3.5 Tables 405 10.3.6 Classifying centrifuges 406 10.3.7 Dense-medium separators (sink and float processes) 406 10.3.8 Flotation separators (froth-flotation) 407 10.3.9 Magnetic separators 407 10.3.10 Electrostatic separators 408 10.4 Liquid-solid (solid-liquid) separators 408 10.4.1 Thickeners and clarifiers 408 10.4.2 Filtration 409 10.4.3 Centrifuges 415 10.4.4 Hydrocyclones (liquid-cyclones) 422 10.4.5 Pressing (expression) 426 10.4.6 Solids drying 426 10.5 Separation of dissolved solids 434 10.5.1 Evaporators 434 10.5.2 Crystallisation 437 10.6 Liquid-liquid separation 440 10.6.1 Decanters (settlers) 440 10.6.2 Plate separators 445 10.6.3 Coalescers 445 10.6.4 Centrifugal separators 446 10.7 Separation of dissolved liquids 446 10.7.1 Solvent extraction and leaching 447 10.8 Gas-solids separations (gas cleaning) 448 10.8.1 Gravity settlers (settling chambers) 448 10.8.2 Impingement separators 448 10.8.3 Centrifugal separators (cyclones) 450 10.8.4 Filters 458 10.8.5 Wet scrubbers (washing) 459 10.8.6 Electrostatic precipitators 459 10.9 Gas liquid separators 460 10.9.1 Settling velocity 461 10.9.2 Vertical separators 461 10.9.3 Horizontal separators 463 10.10 Crushing and grinding (comminution) equipment 465 10.11 Mixing equipment 468 10.11.1 Gas mixing 468 10.11.2 Liquid mixing 468 10.11.3 Solids and pastes 476 10.12 Transport and storage of materials 476 10.12.1 Gases 477 10.12.2 Liquids 479 10.12.3 Solids 481 10.13 Reactors 482 10.13.1 Principal types of reactor 483 10.13.2 Design procedure 486 10.14 References 486 10.15 Nomenclature 490 10.16 Problems 491 11.1 Introduction 493 11.2 Continuous distillation: process description 494 11.2.1 Reflux considerations 495 11.2.2 Feed-point location 496 11.2.3 Selection of column pressure 496 11.3 Continuous distillation: basic principles 497 11.3.1 Stage equations 497 11.3.2 Dew points and bubble points 498 11.3.3 Equilibrium flash calculations 499 11.4 Design variables in distillation 501 11.5 Design methods for binary systems 503 11.5.1 Basic equations 503 11.5.2 McCabe-Thiele method 505 11.5.3 Low product concentrations 507 11.5.4 The Smoker equations 512 11.6 Multicomponent distillation: general considerations 515 11.6.1 Key components 516 11.6.2 Number and sequencing of columns 517 11.7 Multicomponent distillation: short-cut methods for stage and reflux requirements 517 11.7.1 Pseudo-binary systems 518 11.7.2 Smith-Brinkley method 522 11.7.3 Empirical correlations 523 11.7.4 Distribution of non-key components (graphical method) 526 11.8 Multicomponent systems: rigorous solution procedures (computer methods) 542 11.8.1 Lewis-Matheson method 543 11.8.2 Thiele-Geddes method 544 11.8.3 Relaxation methods 545 11.8.4 Linear algebra methods 545 11.9 Other distillation systems 546 11.9.1 Batch distillation 546 11.9.2 Steam distillation 546 11.9.3 Reactive distillation 547 11.10 Plate efficiency 547 11.10.1 Prediction of plate efficiency 548 11.10.2 O’Connell’s correlation 550 11.10.3 Van Winkle’s correlation 552 11.10.4 AIChE method 553 11.10.5 Entrainment 556 11.11 Approximate column sizing 557 11.12 Plate contactors 557 11.12.1 Selection of plate type 560 11.12.2 Plate construction 561 11.13 Plate hydraulic design 565 11.13.1 Plate-design procedure 567 11.13.2 Plate areas 567 11.13.3 Diameter 567 11.13.4 Liquid-flow arrangement 569 11.13.5 Entrainment 570 11.13.6 Weep point 571 11.13.7 Weir liquid crest 572 11.13.8 Weir dimensions 572 11.13.9 Perforated area 572 11.13.10 Hole size 573 11.13.11 Hole pitch 574 11.13.12 Hydraulic gradient 574 11.13.13 Liquid throw 575 11.13.14 Plate pressure drop 575 11.13.15 Downcomer design [back-up] 577 11.14 Packed columns 587 11.14.1 Types of packing 589 11.14.3 Prediction of the height of a transfer unit (HTU) 597 11.14.4 Column diameter (capacity) 602 11.14.5 Column internals 609 11.14.6 Wetting rates 616 11.15 Column auxiliaries 616 11.16 Solvent extraction (liquid liquid extraction) 617 11.16.1 Extraction equipment 617 11.16.2 Extractor design 618 11.16.3 Extraction columns 623 11.16.4 Supercritical fluid extraction 624 11.17 References 624 11.18 Nomenclature 627 11.19 Problems 630 12 Heat-transfer Equipment 634 12.1 Introduction 634 12.2 Basic design procedure and theory 635 12.2.1 Heat exchanger analysis: the effectiveness NTU method 636 12.3 Overall heat-transfer coefficient 636 12.4 Fouling factors (dirt factors) 638 12.5 Shell and tube exchangers: construction details 640 12.5.1 Heat-exchanger standards and codes 644 12.5.2 Tubes 645 12.5.3 Shells 647 12.5.4 Tube-sheet layout (tube count) 647 12.5.5 Shell types (passes) 649 12.5.6 Shell and tube designation 649 12.5.7 Baffles 650 12.5.8 Support plates and tie rods 652 12.5.9 Tube sheets (plates) 652 12.5.10 Shell and header nozzles (branches) 653 12.5.11 Flow-induced tube vibrations 653 12.6 Mean temperature difference (temperature driving force) 655 12.7 Shell and tube exchangers: general design considerations 660 12.7.1 Fluid allocation: shell or tubes 660 12.7.2 Shell and tube fluid velocities 660 12.7.3 Stream temperatures 661 12.7.4 Pressure drop 661 12.7.5 Fluid physical properties 661 12.8 Tube-side heat-transfer coefficient and pressure drop (single phase) 662 12.8.1 Heat transfer 662 12.8.2 Tube-side pressure drop 666 12.9 Shell-side heat-transfer and pressure drop (single phase) 669 12.9.1 Flow pattern 669 12.9.2 Design methods 670 12.9.3 Kern’s method 671 12.9.4 Bell’s method 693 12.9.5 Shell and bundle geometry 702 12.9.6 Effect of fouling on pressure drop 705 12.9.7 Pressure-drop limitations 705 12.10 Condensers 709 12.10.1 Heat-transfer fundamentals 710 12.10.2 Condensation outside horizontal tubes 710 12.10.3 Condensation inside and outside vertical tubes 711 12.10.4 Condensation inside horizontal tubes 716 12.10.5 Condensation of steam 717 12.10.6 Mean temperature difference 717 12.10.7 Desuperheating and sub-cooling 717 12.10.9 Pressure drop in condensers 723 12.11 Reboilers and vaporisers 728 12.11.1 Boiling heat-transfer fundamentals 731 12.11.2 Pool boiling 732 12.11.3 Convective boiling 735 12.11.4 Design of forced-circulation reboilers 740 12.11.5 Design of thermosyphon reboilers 741 12.11.6 Design of kettle reboilers 750 12.12 Plate heat exchangers 756 12.12.1 Gasketed plate heat exchangers 756 12.12.2 Welded plate 764 12.12.3 Plate-fin 764 12.12.4 Spiral heat exchangers 765 12.13 Direct-contact heat exchangers 766 12.14 Finned tubes 767 12.15 Double-pipe heat exchangers 768 12.16 Air-cooled exchangers 769 12.17 Fired heaters (furnaces and boilers) 769 12.17.1 Basic construction 770 12.17.2 Design 771 12.17.3 Heat transfer 772 12.17.4 Pressure drop 774 12.17.5 Process-side heat transfer and pressure drop 774 12.17.6 Stack design 774 12.17.7 Thermal efficiency 775 12.18 Heat transfer to vessels 775 12.18.1 Jacketed vessels 775 12.18.2 Internal coils 777 12.18.3 Agitated vessels 778 12.19 References 782 12.20 Nomenclature 786 12.21 Problems 790 13 Mechanical Design of Process Equipment 794 13.1 Introduction 794 13.1.1 Classification of pressure vessels 795 13.2 Pressure vessel codes and standards 795 13.3 Fundamental principles and equations 796 13.3.1 Principal stresses 796 13.3.2 Theories of failure 797 13.3.3 Elastic stability 798 13.3.4 Membrane stresses in shells of revolution 798 13.3.5 Flat plates 805 13.3.6 Dilation of vessels 809 13.3.7 Secondary stresses 809 13.4 General design considerations: pressure vessels 810 13.4.1 Design pressure 810 13.4.2 Design temperature 810 13.4.3 Materials 811 13.4.4 Design stress (nominal design strength) 811 13.4.5 Welded joint efficiency, and construction categories 812 13.4.6 Corrosion allowance 813 13.4.7 Design loads 814 13.4.8 Minimum practical wall thickness 814 13.5 The design of thin-walled vessels under internal pressure 815 13.5.1 Cylinders and spherical shells 815 13.5.2 Heads and closures 815 13.5.3 Design of flat ends 817 13.5.4 Design of domed ends 818 13.5.5 Conical sections and end closures 819 13.7 Design of vessels subject to external pressure 825 13.7.1 Cylindrical shells 825 13.7.2 Design of stiffness rings 828 13.7.3 Vessel heads 829 13.8 Design of vessels subject to combined loading 831 13.8.1 Weight loads 835 13.8.2 Wind loads (tall vessels) 837 13.8.3 Earthquake loading 839 13.8.4 Eccentric loads (tall vessels) 840 13.8.5 Torque 841 13.9 Vessel supports 844 13.9.1 Saddle supports 844 13.9.2 Skirt supports 848 13.9.3 Bracket supports 856 13.10 Bolted flanged joints 858 13.10.1 Types of flange, and selection 858 13.10.2 Gaskets 859 13.10.3 Flange faces 861 13.10.4 Flange design 862 13.10.5 Standard flanges 865 13.11 Heat-exchanger tube-plates 867 13.12 Welded joint design 869 13.13 Fatigue assessment of vessels 872 13.14 Pressure tests 872 13.15 High-pressure vessels 873 13.15.1 Fundamental equations 873 13.15.2 Compound vessels 877 13.15.3 Autofrettage 878 13.16 Liquid storage tanks 879 13.17 Mechanical design of centrifuges 879 13.17.1 Centrifugal pressure 879 13.17.2 Bowl and spindle motion: critical speed 881 13.18 References 883 13.19 Nomenclature 885 13.20 Problems 889 14 General Site Considerations 892 14.1 Introduction 892 14.2 Plant location and site selection 892 14.3 Site layout 894 14.4 Plant layout 896 14.4.1 Techniques used in site and plant layout 897 14.5 Utilities 900 14.6 Environmental considerations 902 14.6.1 Waste management 902 14.6.2 Noise 905 14.6.3 Visual impact 905 14.6.4 Legislation 905 14.6.5 Environmental auditing 906 14.7 References 906 APPENDIX A: GRAPHICAL SYMBOLS FOR PIPING SYSTEMS AND PLANT 908 APPENDIX B: CORROSION CHART 917 APPENDIX C: PHYSICAL PROPERTY DATA BANK 937 APPENDIX D: CONVERSION FACTORS FOR SOME COMMON SI UNITS 958 APPENDIX F: DESIGN PROJECTS 965 APPENDIX G: EQUIPMENT SPECIFICATION (DATA) SHEETS 990 APPENDIX H: TYPICAL SHELL AND TUBE HEAT EXCHANGER TUBE-SHEET LAYOUTS 1002 AUTHOR INDEX 1007 SUBJECT INDEX 1017 CHAPTER 1 Introduction to Design 1.1. INTRODUCTION This chapter is an introduction to the nature and methodology of the design process, and its application to the design of chemical manufacturing processes. 1.2. NATURE OF DESIGN This section is a general, somewhat philosophical, discussion of the design process; how a designer works. The subject of this book is chemical engineering design, but the method- ology of design described in this section applies equally to other branches of engineering design. Design is a creative activity, and as such can be one of the most rewarding and satisfying activities undertaken by an engineer. It is the synthesis, the putting together, of ideas to achieve a desired purpose. The design does not exist at the commencement of the project. The designer starts with a specific objective in mind, a need, and by developing and evaluating possible designs, arrives at what he considers the best way of achieving that objective; be it a better chair, a new bridge, or for the chemical engineer, a new chemical product or a stage in the design of a production process. When considering possible ways of achieving the objective the designer will be constrained by many factors, which will narrow down the number of possible designs; but, there will rarely be just one possible solution to the problem, just one design. Several alternative ways of meeting the objective will normally be possible, even several best designs, depending on the nature of the constraints. These constraints on the possible solutions to a problem in design arise in many ways. Some constraints will be fixed, invariable, such as those that arise from physical laws, government regulations, and standards. Others will be less rigid, and will be capable of relaxation by the designer as part of his general strategy in seeking the best design. The constraints that are outside the designer’s influence can be termed the external constraints. These set the outer boundary of possible designs; as shown in Figure 1.1. Within this boundary there will be a number of plausible designs bounded by the other constraints, the internal constraints, over which the designer has some control; such as, choice of process, choice of process conditions, materials, equipment. Economic considerations are obviously a major constraint on any engineering design: plants must make a profit. Time will also be a constraint. The time available for completion of a design will usually limit the number of alternative designs that can be considered. 1 Plausible designs G o v e rnm e n t c o n tro ls Economic constraintsSa fe ty re gu lat ion s Resources Physical lawsStandards and codesP e rs o n n e l MaterialsProcess conditions Ch oic e o f pro ces s MethodsT im e “External” constraints “Internal” constraints Possible designs Figure 1.1. Design constraints Objective (design specification) Collection of data, physical properties design methods Generation of possible designs Selection and evaluation (optimisation) Final design Figure 1.2. The design process The stages in the development of a design, from the initial identification of the objective to the final design, are shown diagrammatically in Figure 1.2. Each stage is discussed in the following sections. Figure 1.2 shows design as an iterative procedure; as the design develops the designer will be aware of more possibilities and more constraints, and will be constantly seeking new data and ideas, and evaluating possible design solutions. Chaddock (1975) defined design as, the conversion of an ill-defined requirement into a satisfied customer. The designer is creating a design for an article, or a manufacturing process, to fulfil a particular need. In the design of a chemical process, the need is the public need for the product, the commercial opportunity, as foreseen by the sales and marketing organisation. Within this overall objective the designer will recognise sub-objectives; the requirements of the various units that make up the overall process. Before starting work the designer should obtain as complete, and as unambiguous, a statement of the requirements as possible. If the requirement (need) arises from outside the design group, from a client or from another department, then he will have to elucidate the real requirements through discussion. It is important to distinguish between the real needs and the wants. The wants are those parts of the initial specification that may be thought desirable, but which can be relaxed if required as the design develops. For example, a particular product specification may be considered desirable by the sales department, but may be difficult and costly to obtain, and some relaxation of the specification may be possible, producing a saleable but cheaper product. Whenever he is in a position to do so, the designer should always question the design requirements (the project and equipment specifications) and keep them under review as the design progresses. Where he writes specifications for others, such as for the mechanical design or purchase of a piece of equipment, he should be aware of the restrictions (constraints) he is placing on other designers. A tight, well-thought-out, comprehensive, specification of the require- ments defines the external constraints within which the other designers must work. 1.2.2. Data collection To proceed with a design, the designer must first assemble all the relevant facts and data required. For process design this will include information on possible processes, equipment performance, and physical property data. This stage can be one of the most time consuming, and frustrating, aspects of design. Sources of process information and physical properties are reviewed in Chapter 8. Many design organisations will prepare a basic data manual, containing all the process “know-how” on which the design is to be based. Most organisations will have design manuals covering preferred methods and data for the more frequently used, routine, design procedures. The national standards are also sources of design methods and data; they are also design constraints. The constraints, particularly the external constraints, should be identified early in the design process. 1.2.3. Generation of possible design solutions The creative part of the design process is the generation of possible solutions to the problem (ways of meeting the objective) for analysis, evaluation and selection. In this activity the designer will largely rely on previous experience, his own and that of others. be easily traced. The first motor cars were clearly horse-drawn carriages without the horse; and the development of the design of the modern car can be traced step by step from these early prototypes. In the chemical industry, modern distillation processes have developed from the ancient stills used for rectification of spirits; and the packed columns used for gas absorption have developed from primitive, brushwood-packed towers. So, it is not often that a process designer is faced with the task of producing a design for a completely novel process or piece of equipment. The experienced engineer will wisely prefer the tried and tested methods, rather than possibly more exciting but untried novel designs. The work required to develop new processes, and the cost, is usually underestimated. Progress is made more surely in small steps. However, whenever innovation is wanted, previous experience, through prejudice, can inhibit the generation and acceptance of new ideas; the “not invented here” syndrome. The amount of work, and the way it is tackled, will depend on the degree of novelty in a design project. Chemical engineering projects can be divided into three types, depending on the novelty involved: 1. Modifications, and additions, to existing plant; usually carried out by the plant design group. 2. New production capacity to meet growing sales demand, and the sale of established processes by contractors. Repetition of existing designs, with only minor design changes. 3. New processes, developed from laboratory research, through pilot plant, to a commercial process. Even here, most of the unit operations and process equipment will use established designs. The first step in devising a new process design will be to sketch out a rough block diagram showing the main stages in the process; and to list the primary function (objective) and the major constraints for each stage. Experience should then indicate what types of unit operations and equipment should be considered. Jones (1970) discusses the methodology of design, and reviews some of the special techniques, such as brainstorming sessions and synectics, that have been developed to help generate ideas for solving intractable problems. A good general reference on the art of problem solving is the classical work by Polya (1957); see also Chittenden (1987). Some techniques for problem solving in the Chemical Industry are covered in a short text by Casey and Frazer (1984). The generation of ideas for possible solutions to a design problem cannot be separated from the selection stage of the design process; some ideas will be rejected as impractical as soon as they are conceived. 1.2.4. Selection The designer starts with the set of all possible solutions bounded by the external constraints, and by a process of progressive evaluation and selection, narrows down the range of candidates to find the “best” design for the purpose. Possible designs (credible) within the external constraints. Plausible designs (feasible) within the internal constraints. Probable designs likely candidates. Best design (optimum) judged the best solution to the problem. The selection process will become more detailed and more refined as the design progresses from the area of possible to the area of probable solutions. In the early stages a coarse screening based on common sense, engineering judgement, and rough costings will usually suffice. For example, it would not take many minutes to narrow down the choice of raw materials for the manufacture of ammonia from the possible candidates of, say, wood, peat, coal, natural gas, and oil, to a choice of between gas and oil, but a more detailed study would be needed to choose between oil and gas. To select the best design from the probable designs, detailed design work and costing will usually be necessary. However, where the performance of candidate designs is likely to be close the cost of this further refinement, in time and money, may not be worthwhile, particularly as there will usually be some uncertainty in the accuracy of the estimates. The mathematical techniques that have been developed to assist in the optimisation of designs, and plant performance, are discussed briefly in Section 1.10. Rudd and Watson (1968) and Wells (1973) describe formal techniques for the prelim- inary screening of alternative designs. 1.3. THE ANATOMY OF A CHEMICAL MANUFACTURING PROCESS The basic components of a typical chemical process are shown in Figure 1.3, in which each block represents a stage in the overall process for producing a product from the raw materials. Figure 1.3 represents a generalised process; not all the stages will be needed for any particular process, and the complexity of each stage will depend on the nature of the process. Chemical engineering design is concerned with the selection and arrangement of the stages, and the selection, specification and design of the equipment required to perform the stage functions. Raw material storage Feed preparation Reaction Product separation Product purification Product storage Sales Recycle of unreacted material By-products Wastes Stage 1 Stage 2 Stage 3 Stage 4 Stage 5 Stage 6 Figure 1.3. Anatomy of a chemical process Stage 1. Raw material storage Unless the raw materials (also called essential materials, or feed stocks) are supplied as intermediate products (intermediates) from a neighbouring plant, some provision will interruptions in supply. Even when the materials come from an adjacent plant some provision is usually made to hold a few hours, or even days, supply to decouple the processes. The storage required will depend on the nature of the raw materials, the method of delivery, and what assurance can be placed on the continuity of supply. If materials are delivered by ship (tanker or bulk carrier) several weeks stocks may be necessary; whereas if they are received by road or rail, in smaller lots, less storage will be needed. Stage 2. Feed preparation Some purification, and preparation, of the raw materials will usually be necessary before they are sufficiently pure, or in the right form, to be fed to the reaction stage. For example, acetylene generated by the carbide process contains arsenical and sulphur compounds, and other impurities, which must be removed by scrubbing with concentrated sulphuric acid (or other processes) before it is sufficiently pure for reaction with hydrochloric acid to produce dichloroethane. Liquid feeds will need to be vaporised before being fed to gas- phase reactors, and solids may need crushing, grinding and screening. Stage 3. Reactor The reaction stage is the heart of a chemical manufacturing process. In the reactor the raw materials are brought together under conditions that promote the production of the desired product; invariably, by-products and unwanted compounds (impurities) will also be formed. Stage 4. Product separation In this first stage after the reactor the products and by-products are separated from any unreacted material. If in sufficient quantity, the unreacted material will be recycled to the reactor. They may be returned directly to the reactor, or to the feed purification and preparation stage. The by-products may also be separated from the products at this stage. Stage 5. Purification Before sale, the main product will usually need purification to meet the product specifi- cation. If produced in economic quantities, the by-products may also be purified for sale. Stage 6. Product storage Some inventory of finished product must be held to match production with sales. Provision for product packaging and transport will also be needed, depending on the nature of the product. Liquids will normally be dispatched in drums and in bulk tankers (road, rail and sea), solids in sacks, cartons or bales. The stock held will depend on the nature of the product and the market. Ancillary processes In addition to the main process stages shown in Figure 1.3, provision will have to be made for the supply of the services (utilities) needed; such as, process water, cooling offices and other accommodation, and laboratories; see Chapter 14. 1.3.1. Continuous and batch processes Continuous processes are designed to operate 24 hours a day, 7 days a week, throughout the year. Some down time will be allowed for maintenance and, for some processes, catalyst regeneration. The plant attainment; that is, the percentage of the available hours in a year that the plant operates, will usually be 90 to 95%. Attainment % D hours operated 8760 ð 100 Batch processes are designed to operate intermittently. Some, or all, the process units being frequently shut down and started up. Continuous processes will usually be more economical for large scale production. Batch processes are used where some flexibility is wanted in production rate or product speci- fication. Choice of continuous versus batch production The choice between batch or continuous operation will not be clear cut, but the following rules can be used as a guide. Continuous 1. Production rate greater than 5 ð 106 kg/h 2. Single product 3. No severe fouling 4. Good catalyst life 5. Proven processes design 6. Established market Batch 1. Production rate less than 5 ð 106 kg/h 2. A range of products or product specifications 3. Severe fouling 4. Short catalyst life 5. New product 6. Uncertain design 1.4. THE ORGANISATION OF A CHEMICAL ENGINEERING PROJECT The design work required in the engineering of a chemical manufacturing process can be divided into two broad phases. Phase 1. Process design, which covers the steps from the initial selection of the process to be used, through to the issuing of the process flow-sheets; and includes the selection, Initial evaluation. Process selection. Preliminary flow diagrams. Detailed process design. Flow-sheets. Chemical engineering equipment design and specifications. Reactors, Unit operations, Heat exchangers, Miscellaneous equipment. Materials selection. Process manuals Material and energy balances. Preliminary equipment selection and design. Process flow-sheeting. Preliminary cost estimation. Authorisation of funds. Piping and instrument design Instrument selection and specification Pumps and compressors. Selection and specification Vessel design Heat exchanger design Utilities and other services. Design and specification Electrical, Motors, switch gear, substations, etc. Piping design Structural design Plant layout General civil work. Foundations, drains, roads, etc. Buildings. Offices, laboratories, control rooms, etc. Project cost estimation. Capital authorisation Purchasing/procurement Raw material specification. (contracts) Construction Start-up Operating manuals Operation Sales Figure 1.4. The structure of a chemical engineering project this phase is the responsibility of the Process Design Group, and the work will be mainly done by chemical engineers. The process design group may also be responsible for the preparation of the piping and instrumentation diagrams. Phase 2. The detailed mechanical design of equipment; the structural, civil and electrical design; and the specification and design of the ancillary services. These activities will be the responsibility of specialist design groups, having expertise in the whole range of engineering disciplines. Other specialist groups will be responsible for cost estimation, and the purchase and procurement of equipment and materials. The sequence of steps in the design, construction and start-up of a typical chemical process plant is shown diagrammatically in Figure 1.4 and the organisation of a typical project group in Figure 1.5. Each step in the design process will not be as neatly separated from the others as is indicated in Figure 1.4; nor will the sequence of events be as clearly defined. There will be a constant interchange of information between the various design sections as the design develops, but it is clear that some steps in a design must be largely completed before others can be started. A project manager, often a chemical engineer by training, is usually responsible for the co-ordination of the project, as shown in Figure 1.5. Specialist design sections Vessels Layout Piping Heat exchangers valves fired heaters Control Civil work and instruments structures Electrical buildings Compressors and turbines Utilities pumps Process section Process evaluation Flow-sheeting Equipment specifications Construction section Construction Start-up Project manager Procurement section Estimating Inspection Scheduling Figure 1.5. Project organisation As was stated in Section 1.2.1, the project design should start with a clear specification defining the product, capacity, raw materials, process and site location. If the project is based on an established process and product, a full specification can be drawn up at the start of the project. For a new product, the specification will be developed from an economic evaluation of possible processes, based on laboratory research, pilot plant tests and product market research. Barrow (1964) and Baasel (1974). Some of the larger chemical manufacturing companies have their own project design organisations and carry out the whole project design and engineering, and possibly construction, within their own organisation. More usually the design and construction, and possibly assistance with start-up, is entrusted to one of the international contracting firms. The operating company will often provide the “know-how” for the process, and will work closely with the contractor throughout all stages of the project. 1.5. PROJECT DOCUMENTATION As shown in Figure 1.5 and described in Section 1.4, the design and engineering of a chemical process requires the co-operation of many specialist groups. Effective co- operation depends on effective communications, and all design organisations have formal procedures for handling project information and documentation. The project documen- tation will include: 1. General correspondence within the design group and with: government departments equipment vendors site personnel the client 2. Calculation sheets design calculations costing computer print-out 3. Drawings flow-sheets piping and instrumentation diagrams layout diagrams plot/site plans equipment details piping diagrams architectural drawings design sketches 4. Specification sheets for equipment, such as: heat exchangers pumps 5. Purchase orders quotations invoices All documents should be assigned a code number for easy cross referencing, filing and retrieval. Calculation sheets The design engineer should develop the habit of setting out calculations so that they can be easily understood and checked by others. It is good practice to include on calculation sufficient detail for the methods, as well as the arithmetic, to be checked. Design calcula- tions are normally set out on standard sheets. The heading at the top of each sheet should include: the project title and identification number and, most importantly, the signature (or initials) of the person who checked the calculation. Drawings All project drawings are normally drawn on specially printed sheets, with the company name; project title and number; drawing title and identification number; draughtsman’s name and person checking the drawing; clearly set out in a box in the bottom right-hand corner. Provision should also be made for noting on the drawing all modifications to the initial issue. Drawings should conform to accepted drawing conventions, preferably those laid down by the national standards. The symbols used for flow-sheets and piping and instrument diagrams are discussed in Chapter 4. Drawings and sketches are normally made on detail paper (semi-transparent) in pencil, so modifications can be easily made, and prints taken. In most design offices Computer Aided Design (CAD) methods are now used to produce the drawings required for all the aspects of a project: flow-sheets, piping and instrumen- tation, mechanical and civil work. Specification sheets Standard specification sheets are normally used to transmit the information required for the detailed design, or purchase, of equipment items; such as, heat exchangers, pumps, columns. As well as ensuring that the information is clearly and unambiguously presented, standard specification sheets serve as check lists to ensure that all the information required is included. Examples of equipment specification sheets are given in Appendix G. Process manuals Process manuals are often prepared by the process design group to describe the process and the basis of the design. Together with the flow-sheets, they provide a complete technical description of the process. Operating manuals Operating manuals give the detailed, step by step, instructions for operation of the process and equipment. They would normally be prepared by the operating company personnel, but may also be issued by a contractor as part of the contract package for a less experienced client. The operating manuals would be used for operator instruction and training, and for the preparation of the formal plant operating instructions. The need for standardisation arose early in the evolution of the modern engineering industry; Whitworth introduced the first standard screw thread to give a measure of interchangeability between different manufacturers in 1841. Modern engineering standards cover a much wider function than the interchange of parts. In engineering practice they cover: 1. Materials, properties and compositions. 2. Testing procedures for performance, compositions, quality. 3. Preferred sizes; for example, tubes, plates, sections. 4. Design methods, inspection, fabrication. 5. Codes of practice, for plant operation and safety. The terms STANDARD and CODE are used interchangeably, though CODE should really be reserved for a code of practice covering say, a recommended design or operating procedure; and STANDARD for preferred sizes, compositions, etc. All of the developed countries, and many of the developing countries, have national standards organisations, responsible for the issue and maintenance of standards for the manufacturing industries, and for the protection of consumers. In the United Kingdom preparation and promulgation of national standards are the responsibility of the British Standards Institution (BSI). The Institution has a secretariat and a number of technical personnel, but the preparation of the standards is largely the responsibility of committees of persons from the appropriate industry, the professional engineering institutions and other interested organisations. In the United States the government organisation responsible for coordinating infor- mation on standards is the National Bureau of Standards; standards are issued by Federal, State and various commercial organisations. The principal ones of interest to chemical engineers are those issued by the American National Standards Institute (ANSI), the American Petroleum Institute (API), the American Society for Testing Materials (ASTM), and the American Society of Mechanical Engineers (ASME) (pressure vessels). Burklin (1979) gives a comprehensive list of the American codes and standards. The International Organization for Standardization (ISO) coordinates the publication of international standards. All the published British standards are listed, and their scope and application described, in the British Standards Institute Catalogue; which the designer should consult. The catalogue is available online, go to the BSI group home page, www.bsi-global.com. As well as the various national standards and codes, the larger design organisations will have their own (in-house) standards. Much of the detail in engineering design work is routine and repetitious, and it saves time and money, and ensures a conformity between projects, if standard designs are used whenever practicable. Equipment manufacturers also work to standards to produce standardised designs and size ranges for commonly used items; such as electric motors, pumps, pipes and pipe fittings. They will conform to national standards, where they exist, or to those issued by trade associations. It is clearly more economic to produce a limited range of standard sizes than to have to treat each order as a special job. of a piece of equipment into the rest of the plant. For example, if a standard range of centrifugal pumps is specified the pump dimensions will be known, and this facilitates the design of the foundations plates, pipe connections and the selection of the drive motors: standard electric motors would be used. For an operating company, the standardisation of equipment designs and sizes increases interchangeability and reduces the stock of spares that have to be held in maintenance stores. Though there are clearly considerable advantages to be gained from the use of standards in design, there are also some disadvantages. Standards impose constraints on the designer. The nearest standard size will normally be selected on completing a design calculation (rounding-up) but this will not necessarily be the optimum size; though as the standard size will be cheaper than a special size, it will usually be the best choice from the point of view of initial capital cost. Standard design methods must, of their nature, be historical, and do not necessarily incorporate the latest techniques. The use of standards in design is illustrated in the discussion of the pressure vessel design standards (codes) in Chapter 13. 1.7. FACTORS OF SAFETY (DESIGN FACTORS) Design is an inexact art; errors and uncertainties will arise from uncertainties in the design data available and in the approximations necessary in design calculations. To ensure that the design specification is met, factors are included to give a margin of safety in the design; safety in the sense that the equipment will not fail to perform satisfactorily, and that it will operate safely: will not cause a hazard. “Design factor” is a better term to use, as it does not confuse safety and performance factors. In mechanical and structural design, the magnitude of the design factors used to allow for uncertainties in material properties, design methods, fabrication and operating loads are well established. For example, a factor of around 4 on the tensile strength, or about 2.5 on the 0.1 per cent proof stress, is normally used in general structural design. The selection of design factors in mechanical engineering design is illustrated in the discussion of pressure vessel design in Chapter 13. Design factors are also applied in process design to give some tolerance in the design. For example, the process stream average flows calculated from material balances are usually increased by a factor, typically 10 per cent, to give some flexibility in process operation. This factor will set the maximum flows for equipment, instrumentation, and piping design. Where design factors are introduced to give some contingency in a process design, they should be agreed within the project organisation, and clearly stated in the project documents (drawings, calculation sheets and manuals). If this is not done, there is a danger that each of the specialist design groups will add its own “factor of safety”; resulting in gross, and unnecessary, over-design. When selecting the design factor to use a balance has to be made between the desire to make sure the design is adequate and the need to design to tight margins to remain competitive. The greater the uncertainty in the design methods and data, the bigger the design factor that must be used. To be consistent with the other volumes in this series, SI units have been used in this book. However, in practice the design methods, data and standards which the designer will use are often only available in the traditional scientific and engineering units. Chemical engineering has always used a diversity of units; embracing the scientific CGS and MKS systems, and both the American and British engineering systems. Those engineers in the older industries will also have had to deal with some bizarre traditional units; such as degrees Twaddle (density) and barrels for quantity. Desirable as it may be for industry world-wide to adopt one consistent set of units, such as SI, this is unlikely to come about for many years, and the designer must contend with whatever system, or combination of systems, his organisation uses. For those in the contracting industry this will also mean working with whatever system of units the client requires. It is usually the best practice to work through design calculations in the units in which the result is to be presented; but, if working in SI units is preferred, data can be converted to SI units, the calculation made, and the result converted to whatever units are required. Conversion factors to the SI system from most of the scientific and engineering units used in chemical engineering design are given in Appendix D. Some license has been taken in the use of the SI system in this volume. Temperatures are given in degrees Celsius (ŽC); degrees Kelvin are only used when absolute temperature is required in the calculation. Pressures are often given in bar (or atmospheres) rather than in the Pascals (N/m2), as this gives a better feel for the magnitude of the pressures. In technical calculations the bar can be taken as equivalent to an atmosphere, whatever definition is used for atmosphere. The abbreviations bara and barg are often used to denote bar absolute and bar gauge; analogous to psia and psig when the pressure is expressed in pound force per square inch. When bar is used on its own, without qualification, it is normally taken as absolute. For stress, N/mm2 have been used, as these units are now generally accepted by engineers, and the use of a small unit of area helps to indicate that stress is the intensity of force at a point (as is also pressure). For quantity, kmol are generally used in preference to mol, and for flow, kmol/h instead of mol/s, as this gives more sensibly sized figures, which are also closer to the more familiar lb/h. For volume and volumetric flow, m3 and m3/h are used in preference to m3/s, which gives ridiculously small values in engineering calculations. Litres per second are used for small flow-rates, as this is the preferred unit for pump specifications. Where, for convenience, other than SI units have been used on figures or diagrams, the scales are also given in SI units, or the appropriate conversion factors are given in the text. The answers to some examples are given in British engineering units as well as SI, to help illustrate the significance of the values. Some approximate conversion factors to SI units are given in Table 1.1. These are worth committing to memory, to give some feel for the units for those more familiar with the traditional engineering units. The exact conversion factors are also shown in the table. A more comprehensive table of conversion factors is given in Appendix D. Engineers need to be aware of the difference between US gallons and imperial gallons (UK) when using American literature and equipment catalogues. Equipment quoted in an Quantity British SI unit Eng. unit approx. exact Energy 1 Btu 1 kJ 1.05506 Specific enthalpy 1 Btu/lb 2 kJ/kg 2.326 Specific heat capacity 1 Btu/lb°F 4 kJ/kg°C 4.1868 (CHU/lb°C) Heat transfer coeff. 1 Btu/ft2h°F 6 W/m2 °C 5.678 (CHU/ft2h°C) Viscosity 1 centipoise 1 mNs/m2 1.000 1 lbf/ft h 0.4 mNs/m2 0.4134 Surface tension 1 dyne/cm 1 mN/m 1.000 Pressure 1 lbf/in2 7 kN/m2 6.894 1 atm 1 bar 1.01325 105 N/m2 Density 1 lb/ft3 16 kg/m3 16.0190 1 g/cm3 1 kg/m3 Volume 1 imp gal. 4.5 ð 103 m3 4.5461 ð 103 Flow-rate 1 imp gal/m 16 m3/h 16.366 Note: 1 US gallon D 0.84 imperial gallons (UK) 1 barrel (oil) D 50 US gall ³ 0.19 m3 (exact 0.1893) 1 kWh D 3.6 MJ American catalogue in US gallons or gpm (gallons per minute) will have only 80 per cent of the rated capacity when measured in imperial gallons. The electrical supply frequency in these two countries is also different: 60 Hz in the US and 50 Hz in the UK. So a pump specified as 50 gpm (US gallons), running at 1750 rpm (revolutions per second) in the US would only deliver 35 imp gpm if operated in the UK; where the motor speed would be reduced to 1460 rpm: so beware. 1.9. DEGREES OF FREEDOM AND DESIGN VARIABLES. THE MATHEMATICAL REPRESENTATION OF THE DESIGN PROBLEM In Section 1.2 it was shown that the designer in seeking a solution to a design problem works within the constraints inherent in the particular problem. In this section the structure of design problems is examined by representing the general design problem in a mathematical form. 1.9.1. Information flow and design variables A process unit in a chemical process plant performs some operation on the inlet material streams to produce the desired outlet streams. In the design of such a unit the design calculations model the operation of the unit. A process unit and the design equations Input streams Input information Output streams Output information Unit Calculation method Figure 1.6. The “design unit” representing the unit are shown diagrammatically in Figure 1.6. In the “design unit” the flow of material is replaced by a flow of information into the unit and a flow of derived information from the unit. The information flows are the values of the variables which are involved in the design; such as, stream compositions, temperatures, pressure, stream flow-rates, and stream enthalpies. Composition, temperature and pressure are intensive variables: independent of the quantity of material (flow-rate). The constraints on the design will place restrictions on the possible values that these variables can take. The values of some of the variables will be fixed directly by process specifications. The values of other variables will be determined by “design relationships” arising from constraints. Some of the design relationships will be in the form of explicit mathematical equations (design equations); such as those arising from material and energy balances, thermodynamic relationships, and equipment performance parameters. Other relationships will be less precise; such as those arising from the use of standards and preferred sizes, and safety considerations. The difference between the number of variables involved in a design and the number of design relationships has been called the number of “degrees of freedom”; similar to the use of the term in the phase rule. The number of variables in the system is analogous to the number of variables in a set of simultaneous equations, and the number of relationships analogous to the number of equations. The difference between the number of variables and equations is called the variance of the set of equations. If Nv is the number of possible variables in a design problem and Nr the number of design relationships, then the “degrees of freedom” Nd is given by: Nd D Nv Nr 1.1 Nd represents the freedom that the designer has to manipulate the variables to find the best design. If Nv D Nr,Nd D 0 and there is only one, unique, solution to the problem. The problem is not a true design problem, no optimisation is possible. If Nv < Nr,Nd < 0, and the problem is over defined; only a trivial solution is possible. If Nv > Nr,Nd > 0, and there is an infinite number of possible solutions. However, for a practical problem there will be only a limited number of feasible solutions. The value of Nd is the number of variables which the designer must assign values to solve the problem. How the number of process variables, design relationships, and design variables defines a system can be best illustrated by considering the simplest system; a single-phase, process stream. Consider a single-phase stream, containing C components. Variable Number Stream flow-rate 1 Composition (component concentrations) C Temperature 1 Pressure 1 Stream enthalpy 1 Total, Nv D CC 4 Relationships between variables Number Composition1 1 Enthalpy2 1 Total, Nr D 2 Degrees of freedom Nd D Nv Nr D CC 4 2 D CC 2 (1) The sum of the mass or mol, fractions, must equal one. (2) The enthalpy is a function of stream composition, temperature and pressure. Specifying (CC 2) variables completely defines the stream. Flash distillation The idea of degrees of freedom in the design process can be further illustrated by consid- ering a simple process unit, a flash distillation. (For a description of flash distillation see Volume 2, Chapter 11). F2, P2, T2, (xi)2 F3, P3, T3, (xi)3 F1, P1, T1, (xi)1 q Figure 1.7. Flash distillation The unit is shown in Figure 1.7, where: F D stream flow rate, P D pressure, T D temperature, xi D concentration, component i, q D heat input. Suffixes, 1 D inlet, 2 D outlet vapour, 3 D outlet liquid. Variable Number Streams (free variables)1 3CC 21 Still pressure 1 temperature 1 heat input 1 Nr D 3CC 9 Relationship Number Material balances (each component) C Heat balance, overall 1 v l e relationships2 C Equilibrium still restriction3 4 2CC 5 Degrees of freedom Nd D 3CC 9 2CC 5 D CC 4 (1) The degrees of freedom for each stream. The total variables in each stream could have been used, and the stream relationships included in the count of relationships. This shows how the degrees of freedom for a complex unit can be built up from the degrees of freedom of its components. For more complex examples see Kwauk (1956). (2) Given the temperature and pressure, the concentration of any component in the vapour phase can be obtained from the concentration in the liquid phase, from the vapour liquid equilibrium data for the system. (3) The concept (definition) of an equilibrium separation implies that the outlet streams and the still are at the same temperature and pressure. This gives four equations: P2 D P3 D P T2 D T3 D T Though the total degrees of freedom is seen to be (CC 4) some of the variables will normally be fixed by general process considerations, and will not be free for the designer to select as “design variables”. The flash distillation unit will normally be one unit in a process system and the feed composition and feed conditions will be fixed by the upstream processes; the feed will arise as an outlet stream from some other unit. Defining the feed fixes (CC 2) variables, so the designer is left with: CC 4 CC 2 D 2 as design variables. Summary The purpose of this discussion was to show that in a design there will be a certain number of variables that the designer must specify to define the problem, and which he can manipulate to seek the best design. In manual calculations the designer will rarely feel for the problem, and can change the calculation procedure, and select the design variables, as he works through the design. He will know by experience if the problem is correctly specified. A computer, however, has no intuition, and for computer-aided design calculations it is essential to ensure that the necessary number of variables is specified to define the problem correctly. For complex processes the number of variables and relating equations will be very large, and the calculation of the degrees of freedom very involved. Kwauk (1956) has shown how the degrees of freedom can be calculated for separation processes by building up the complex unit from simpler units. Smith (1963) uses Kwauk’s method, and illustrates how the idea of “degrees of freedom” can be used in the design of separation processes. 1.9.2. Selection of design variables In setting out to solve a design problem the designer has to decide which variables are to be chosen as “design variables”; the ones he will manipulate to produce the best design. The choice of design variables is important; careful selection can simplify the design calculations. This can be illustrated by considering the choice of design variables for a simple binary flash distillation. For a flash distillation the total degrees of freedom was shown to be (CC 4), so for two components Nd D 6. If the feed stream flow, composition, temperature and pressure are fixed by upstream conditions, then the number of design variables will be: N0d D 6 CC 2 D 6 4 D 2 So the designer is free to select two variables from the remaining variables in order to proceed with the calculation of the outlet stream compositions and flows. If he selects the still pressure (which for a binary system will determine the vapour liquid equilibrium relationship) and one outlet stream flow-rate, then the outlet compo- sitions can be calculated by simultaneous solution of the mass balance and equilibrium relationships (equations). A graphical method for the simultaneous solution is given in Volume 2, Chapter 11. However, if he selects an outlet stream composition (say the liquid stream) instead of a flow-rate, then the simultaneous solution of the mass balance and v l e relationships would not be necessary. The stream compositions could be calculated by the following step-by-step (sequential) procedure: 1. Specifying P determines the v l e relationship (equilibrium) curve from experi- mental data. 2. Knowing the outlet liquid composition, the outlet vapour composition can be calcu- lated from the v l e relationship. 3. Knowing the feed and outlet compositions, and the feed flow-rate, the outlet stream flows can be calculated from a material balance. 4. An enthalpy balance then gives the heat input required. The need for simultaneous solution of the design equations implies that there is a recycle of information. Choice of an outlet stream composition as a design variable in x3 F2 F3 T P F2 (or F3) Feed Select (a) (b) F3 (or F2) x2 x3 T x2 (or x3) Direction of calculation F1 x1 P1 T1 P x2 (or x3) Feed Select Direction of calculation F1 x1 P1 T1 Figure 1.8. Information flow, binary flash distillation calculation (a) Information recycle (b) Information flow reversal effect reverses the flow of information through the problem and removes the recycle; this is shown diagrammatically in Figure 1.8. 1.9.3. Information flow and the structure of design problems It was shown in Section 1.9.2. by studying a relatively simple problem, that the way in which the designer selects his design variables can determine whether the design calculations will prove to be easy or difficult. Selection of one particular set of variables can lead to a straightforward, step-by-step, procedure, whereas selection of another set can force the need for simultaneous solution of some of the relationships; which often requires an iterative procedure (cut-and-try method). How the choice of design variables, inputs to the calculation procedure, affects the ease of solution for the general design problem can be illustrated by studying the flow of information, using simple information flow diagrams. The method used will be that given by Lee et al. (1966) who used a form of directed graph; a biparte graph, see Berge (1962). The general design problem can be represented in mathematical symbolism as a series of equations: fivj D 0 where j D 1, 2, 3,..., Nv, i D 1, 2, 3,..., Nr Consider the following set of such equations: f1v1, v2 D 0 f2v1, v2, v3, v5 D 0 f4v2, v4, v5, v6 D 0 f5v5, v6, v7 D 0 There are seven variables, Nv D 7, and five equations (relationships) Nr D 5, so the number of degrees of freedom is: Nd D Nv Nr D 7 5 D 2 The task is to select two variables from the total of seven in such a way as to give the simplest, most efficient, method of solution to the seven equations. There are twenty-one ways of selecting two items from seven. In Lee’s method the equations and variables are represented by nodes on the biparte graph (circles), connected by edges (lines), as shown in Figure 1.9. f1 v1 v1 f node v node Figure 1.9. Nodes and edges on a biparte graph Figure 1.9 shows that equation f1 contains (is connected to) variables v1 and v2. The complete graph for the set of equations is shown in Figure 1.10. f1 f2 f3 f4 v1 v2 v3 v4 v5 v6 v7 f5 Figure 1.10. Biparte graph for the complete set of equations The number of edges connected to a node defines the local degree of the node p. For example, the local degree of the f1 node is 2, pf1 D 2, and at the v5 node it is 3, pv5 D 3. Assigning directions to the edges of Figure 1.10 (by putting arrows on the lines) identifies one possible order of solution for the equations. If a variable vj is defined as an output variable from an equation fi, then the direction of information flow is from the node fi to the node vj and all other edges will be oriented into fi. What this means, mathematically, is that assigning vj as an output from fi rearranges that equation so that: fiv1, v2,... , vn D vj vj is calculated from equation fi. assigned as output variables from an f node. They are inputs to the system and their edges must be oriented into the system of equations. If, for instance, variables v3 and v4 are selected as design variables, then Figure 1.11 shows one possible order of solution of the set of equations. Different types of arrows are used to distinguish between input and output variables, and the variables selected as design variables are enclosed in a double circle. f1 f2 f3 f4 f5 v1 v2 v5 v6 v7 v3 v4 Design variables (inputs) Inputs Outputs Figure 1.11. An order of solution Tracing the order of the solution of the equations as shown in Figure 1.11 shows how the information flows through the system of equations: 1. Fixing v3 and v4 enables f3 to be solved, giving v1 as the output. v1 is an input to f1 and f2. 2. With v1 as an input, f1 can be solved giving v2; v2 is an input to f2 and f4. 3. Knowing v3, v1 and v2, f2 can be solved to give v5; v5 is an input to f4 and f5. 4. Knowing v4, v2 and v5, f4 can be solved to give v6; v6 is an input to f5. 5. Knowing v6 and v5, f5 can be solved to give v7; which completes the solution. This order of calculation can be shown more clearly by redrawing Figure 1.11 as shown in Figure 1.12. f3 f1 f2 f4 f5 v1 v2 v5 v6 v7 v3 v4 v2 v5 v3 v4 Figure 1.12. Figure 1.11 redrawn to show order of solution taneous solution of any of the equations. The fortuitous selection of v3 and v4 as design variables has given an efficient order of solution of the equations. If for a set of equations an order of solution exists such that there is no need for the simultaneous solution of any of the equations, the system is said to be “acyclic”, no recycle of information. If another pair of variables had been selected, for instance v5 and v7, an acyclic order of solution for the set of equations would not necessarily have been obtained. For many design calculations it will not be possible to select the design variables so as to eliminate the recycle of information and obviate the need for iterative solution of the design relationships. For example, the set of equations given below will be cyclic for all choices of the two possible design variables. f1x1,x2 D 0 f2x1,x3,x4 D 0 f3x2,x3,x4,x5,x6 D 0 f4x4,x5,x6 D 0 Nd D 6 4 D 2 The biparte graph for this example, with x3 and x5 selected as the design variables (inputs), is shown in Figure 1.13. f1 f2 f3 f4 x6 x4 x2 x1 x3 x5 Figure 1.13. One strategy for the solution of this cyclic set of equations would be to guess (assign a value to) x6. The equations could then be solved sequentially, as shown in Figure 1.14, to produce a calculated value for x6, which could be compared with the assumed value and the procedure repeated until a satisfactory convergence of the assumed and calculated value had been obtained. Assigning a value to x6 is equivalent to “tearing” the recycle loop at x6 (Figure 1.15). Iterative methods for the solution of equations are discussed by Henley and Rosen (1969). When a design problem cannot be reduced to an acyclic form by judicious selection of the design variables, the design variables should be chosen so as to reduce the recycle of f1 f2 f3 f4 x6 x6 x4 x2 x1 3 5 Assumed value Calculated value Figure 1.14. f4 f2 f1 f3 x6 x5 x3 x5 x6 x4 x4 x1 x3 x2 Figure 1.15. information to a minimum. Lee and Rudd (1966) and Rudd and Watson (1968) give an algorithm that can be used to help in the selection of the best design variables in manual calculations. The recycle of information, often associated with the actual recycle of process material, will usually occur in any design problem involving large sets of equations; such as in the computer simulation of chemical processes. Efficient methods for the solution of sets of equations are required in computer-aided design procedures to reduce the computer time needed. Several workers have published algorithms for the efficient ordering of recycle loops for iterative solution procedures, and some references to this work are given in the chapter on flow-sheeting, Chapter 4. 1.10. OPTIMISATION Design is optimisation: the designer seeks the best, the optimum, solution to a problem. Much of the selection and choice in the design process will depend on the intuitive judgement of the designer; who must decide when more formal optimisation techniques can be used to advantage. The task of formally optimising the design of a complex processing plant involving several hundred variables, with complex interactions, is formidable, if not impossible. The task can be reduced by dividing the process into more manageable units, identifying the key variables and concentrating work where the effort involved will give the greatest necessarily give the optimum design for the whole process. The optimisation of one unit may be at the expense of another. For example, it will usually be satisfactory to optimise the reflux ratio for a fractionating column independently of the rest of the plant; but if the column is part of a separation stage following a reactor, in which the product is separated from the unreacted materials, then the design of the column will interact with, and may well determine, the optimisation of the reactor design. In this book the discussion of optimisation methods will, of necessity, be limited to a brief review of the main techniques used in process and equipment design. The extensive literature on the subject should be consulted for full details of the methods available, and their application and limitations; see Beightler and Wilde (1967), Beveridge and Schechter (1970), Stoecker (1989), Rudd and Watson (1968), Edgar and Himmelblau (2001). The books by Rudd and Watson (1968) and Edgar and Himmelblau (2001) are particularly recommended to students. 1.10.1. General procedure When setting out to optimise any system, the first step is clearly to identify the objective: the criterion to be used to judge the system performance. In engineering design the objective will invariably be an economic one. For a chemical process, the overall objective for the operating company will be to maximise profits. This will give rise to sub-objectives, which the designer will work to achieve. The main sub-objective will usually be to minimise operating costs. Other sub-objectives may be to reduce investment, maximise yield, reduce labour requirements, reduce maintenance, operate safely. When choosing his objectives the designer must keep in mind the overall objective. Minimising cost per unit of production will not necessarily maximise profits per unit time; market factors, such as quality and delivery, may determine the best overall strategy. The second step is to determine the objective function: the system of equations, and other relationships, which relate the objective with the variables to be manipulated to optimise the function. If the objective is economic, it will be necessary to express the objective function in economic terms (costs). Difficulties will arise in expressing functions that depend on value judgements; for example, the social benefits and the social costs that arise from pollution. The third step is to find the values of the variables that give the optimum value of the objective function (maximum or minimum). The best techniques to be used for this step will depend on the complexity of the system and on the particular mathematical model used to represent the system. A mathematical model represents the design as a set of equations (relationships) and, as was shown in Section 1.9.1, it will only be possible to optimise the design if the number of variables exceeds the number of relationships; there is some degree of freedom in the system. 1.10.2. Simple models If the objective function can be expressed as a function of one variable (single degree of freedom) the function can be differentiated, or plotted, to find the maximum or minimum. trated in Example 1.1, and in the derivation of the formula for optimum pipe diameter in Chapter 5. The determination of the economic reflux ratio for a distillation column, which is discussed in Volume 2, Chapter 11, is an example of the use of a graphical procedure to find the optimum value. Example 1.1 The optimum proportions for a cylindrical container. A classical example of the optimi- sation of a simple function. The surface area, A, of a closed cylinder is: A D ð Dð L C 2 4 D2 where D D vessel diameter L D vessel length (or height) This will be the objective function which is to be minimised; simplified: fD ð L D Dð L C D 2 2 equation A For a given volume, V, the diameter and length are related by: V D 4 D2 ð L and L D 4V D2 equation B and the objective function becomes fD D 4V D C D 2 2 Setting the differential of this function zero will give the optimum value for D 4V D2 C D D 0 D D 3 √ 4V From equation B, the corresponding length will be: L D 3 √ 4V So for a cylindrical container the minimum surface area to enclose a given volume is obtained when the length is made equal to the diameter. In practice, when cost is taken as the objective function, the optimum will be nearer L D 2D; the proportions of the ubiquitous tin can, and oil drum. This is because the cost material (the surface area); see Wells (1973). If the vessel is a pressure vessel the optimum length to diameter ratio will be even greater, as the thickness of plate required is a direct function of the diameter; see Chapter 13. Urbaniec (1986) gives procedures for the optimisation of tanks and vessel, and other process equipment. 1.10.3. Multiple variable problems The general optimisation problem can be represented mathematically as: f D fv1, v2, v3,. .., vn 1.2 where f is the objective function and v1, v2, v3,... , vn are the variables. In a design situation there will be constraints on the possible values of the objective function, arising from constraints on the variables; such as, minimum flow-rates, maximum allowable concentrations, and preferred sizes and standards. Some may be equality constraints, expressed by equations of the form: m D mv1, v2, v3,. .., vn D 0 1.3 Others as inequality constraints: p D pv1, v2, v3,.. . , vn Pp 1.4 The problem is to find values for the variables v1 to vn that optimise the objective function: that give the maximum or minimum value, within the constraints. Analytical methods If the objective function can be expressed as a mathematical function the classical methods of calculus can be used to find the maximum or minimum. Setting the partial derivatives to zero will produce a set of simultaneous equations that can be solved to find the optimum values. For the general, unconstrained, objective function, the derivatives will give the critical points; which may be maximum or minimum, or ridges or valleys. As with single variable functions, the nature of the first derivative can be found by taking the second derivative. For most practical design problems the range of values that the variables can take will be subject to constraints (equations 1.3 and 1.4), and the optimum of the constrained objective function will not necessarily occur where the partial derivatives of the objective function are zero. This situation is illustrated in Figure 1.16 for a two- dimensional problem. For this problem, the optimum will lie on the boundary defined by the constraint y D a. The method of Lagrange’s undetermined multipliers is a useful analytical technique for dealing with problems that have equality constraints (fixed design values). Examples of the use of this technique for simple design problems are given by Stoecker (1989), Peters and Timmerhaus (1991) and Boas (1963a). Feasible region Minimum of function y = a f(v)v Figure 1.16. Effect of constraints on optimum of a function Search methods The nature of the relationships and constraints in most design problems is such that the use of analytical methods is not feasible. In these circumstances search methods, that require only that the objective function can be computed from arbitrary values of the independent variables, are used. For single variable problems, where the objective function is unimodal, the simplest approach is to calculate the value of the objective function at uniformly spaced values of the variable until a maximum (or minimum) value is obtained. Though this method is not the most efficient, it will not require excessive computing time for simple problems. Several more efficient search techniques have been developed, such as the method of the golden section; see Boas (1963b) and Edgar and Himmelblau (2001). Efficient search methods will be needed for multi-dimensional problems, as the number of calculations required and the computer time necessary will be greatly increased, compared with single variable problems; see Himmelblau (1963), Stoecker (1971), Beveridge and Schechter (1970), and Baasel (1974). Two variable problems can be plotted as shown in Figure 1.17. The values of the objective function are shown as contour lines, as on a map, which are slices through the three-dimensional model of the function. Seeking the optimum of such a function can be Yield contours 75% Temperature Pressure80% 85% 90% Figure 1.17. Yield as a function of reactor temperature and pressure this type of problem is the gradient method (method of steepest ascent, or descent), see Edgar and Himmelblau (2001). 1.10.4. Linear programming Linear programming is an optimisation technique that can be used when the objective function and constraints can be expressed as a linear function of the variables; see Driebeek (1969), Williams (1967) and Dano (1965). The technique is useful where the problem is to decide the optimum utilisation of resources. Many oil companies use linear programming to determine the optimum schedule of products to be produced from the crude oils available. Algorithms have been developed for the efficient solution of linear programming problems and the SIMPLEX algorithm, Dantzig (1963), is the most commonly used. Examples of the application of linear programming in chemical process plant design and operation are given by Allen (1971), Rudd and Watson (1968), Stoecker (1991), and Urbaniec (1986). 1.10.5. Dynamic programming Dynamic programming is a technique developed for the optimisation of large systems; see Nemhauser (1966), Bellman (1957) and Aris (1963). The basic approach used is to divide the system into convenient sub-systems and optimise each sub-system separately, while taking into account the interactions between the sub-systems. The decisions made at each stage contribute to the overall systems objective function, and to optimise the overall objective function an appropriate combi- nation of the individual stages has to be found. In a typical process plant system the possible number of combinations of the stage decisions will be very large. The dynamic programming approach uses Bellman’s “Principle of Optimality”,† which enables the optimum policy to be found systematically and efficiently by calculating only a fraction of the possible combinations of stage decisions. The method converts the problem from the need to deal with “N” optimisation decisions simultaneously to a sequential set of “N” problems. The application of dynamic programming to design problems is well illustrated in Rudd and Watson’s book; see also Wells (1973) and Edgar and Himmelblau (2001). 1.10.6. Optimisation of batch and semicontinuous processes In batch operation there will be periods when product is being produced, followed by non- productive periods when the product is discharged and the equipment prepared for the next batch. The rate of production will be determined by the total batch time, productive † Bellman’s (1957) principle of optimality: “An optimal policy has the property that, whatever the initial state and the initial decision are, the remaining decisions must constitute an optimal policy with regard to the state resulting from the first decision.” Batches per year D 8760 ð plant attainment batch cycle time 1.5 where the “plant attainment” is the fraction of the total hours in a year (8760) that the plant is in operation. Annual production D quantity produced per batch ð batches per year. Cost per unit of production D annual cost of production annual production rate 1.6 With many batch processes, the production rate will decrease during the production period; for example, batch reactors and plate and frame filter presses, and there will be an optimum batch size, or optimum cycle time, that will give the minimum cost per unit of production. For some processes, though they would not be classified as batch processes, the period of continuous production will be limited by gradual changes in process conditions; such as, the deactivation of catalysts or the fouling of heat-exchange surfaces. Production will be lost during the periods when the plant is shut down for catalyst renewal or equipment clean-up, and, as with batch process, there will be an optimum cycle time to give the minimum production cost. The optimum time between shut-downs can be found by determining the relationship between cycle time and cost per unit of production (the objective function) and using one of the optimisation techniques outlined in this section to find the minimum. With discontinuous processes, the period between shut-downs will usually be a function of equipment size. Increasing the size of critical equipment will extend the production period, but at the expense of increased capital cost. The designer must strike a balance between the savings gained by reducing the non-productive period and the increased investment required. 1.11. REFERENCES ALLEN, D. H. (1971) Brit. Chem. Eng. 16, 685. Linear programming models. ARIS, R. (1963) Discrete Dynamic Programming (Blaisdell). BAASEL, W. D. (1965) Chem. Eng., NY 72 (Oct. 25th) 147. Exploring response surfaces to establish optimum conditions. BAASEL, W. D. (1974) Preliminary Chemical Engineering Plant Design (Elsevier). BEIGHTLER, C. S. and WILDE, D. J. (1967) Foundations of Optimisation (Prentice-Hall). BELLMAN, R. (1957) Dynamic Programming (Princeton University, New York). BERGE, C. (1962) Theory of Graphs and its Applications (Wiley). BEVERIDGE, G. S. G. and SCHECHTER, R. S. (1970) Optimisation: Theory and Practice (McGraw-Hill). BOAS, A. H. (1963a) Chem. Eng., NY 70 (Jan. 7th) 95. How to use Lagrange multipliers. BOAS, A. H. (1963b) Chem. Eng., NY 70 (Feb. 4th) 105. How search methods locate optimum in univariate problems. BURKLIN, C. R. (1979) The Process Plant Designers Pocket Handbook of Codes and Standards (Gulf). CASEY, R. J. and FRAZER, M. J. (1984) Problem Solving in the Chemical Industry (Pitman). CHADDOCK, D. H. (1975) Paper read to S. Wales Branch, Institution of Mechanical Engineers (Feb. 27th). Thought structure, or what makes a designer tick. solving approach. DANO, S. (1965) Linear Programming in Industry (Springer-Verlag). DANTZIG, G. B. (1963) Linear Programming and Extensions (Princeton University Press). DRIEBEEK, N. J. (1969) Applied Linear Programming (Addison-Wesley). EDGAR, T. E. and HIMMELBLAU, D. M., 2nd edn (2001) Optimization of Chemical Processes (McGraw-Hill). HENLEY, E. J. and ROSEN, E. M. (1969) Material and Energy Balance Computations (Wiley). HIMMELBLAU, D. M. (1963) Ind. Eng. Chem. Process Design and Development 2, 296. Process optimisation by search techniques. JONES, C. J. (1970) Design Methods: Seeds of Human Futures (Wiley). KWAUK, M. (1956) AIChE Jl 2, 240. A system for counting variables in separation processes. LEE, W. CHRISTENSEN J. H. and RUDD, D. F. (1966): AIChE Jl 12, 1104. Design variable selection to simplify process calculations. LEE, W. and RUDD, D. F. (1966) AIChE Jl 12, 1185. On the ordering of recycle calculations. NEMHAUSER, G. L. (1966) Introduction to Dynamic Programming (Wiley). PETERS, M. S. and TIMMERHAUS, K. D. (1991) Plant Design and Economics for Chemical Engineers, 4th edn (McGraw-Hill). POLYA, G. (1957) How to Solve It, 2nd edn (Doubleday). RASE H. F and BARROW, M. H. (1964) Project Engineering (Wiley). RUDD, D. F. and WATSON, C. C. (1968) Strategy of Process Design (Wiley). SMITH, B. D. (1963) Design of Equilibrium Stage Processes (McGraw-Hill). STOECKER, W. F. (1989) Design of Thermal Systems 3rd edn (McGraw-Hill). URBANIEC, K. (1986) Optimal Design of Process Equipment (Ellis Horwood). WELLS, G. L. (1973) Process Engineering with Economic Objective (Leonard Hill). WILDE, D. J. (1964) Optimum Seeking Methods (Prentice-Hall). WILLIAMS, N. (1967) Linear and Non-linear Programming in Industry (Pitman). 1.12. NOMENCLATURE Dimensions in MLTq C Number of components D Diameter L F Stream flow rate MT1 f General function fi General function (design relationship) f1, f2 ... General functions (design relationships) L Length L Nd Degrees of freedom in a design problem N0d Degrees of freedom (variables free to be selected as design variables) Nr Number of design relationships Nv Number of variables P Pressure ML1T2 Pp Inequality constraints q Heat input, flash distillation ML2T3 T Temperature q vj Variables v1, v2 ... Variables x1,x2 ... Variables Equality constraint function Inequality constraint function Suffixes 1 Inlet, flash distillation 2 Vapour outlet, flash distillation 3 Liquid outlet, flash distillation 1.1. Given that 1 in D 25.4 mm; 1 lbm D 0.4536 kg; 1 ŽF D 0.556 ŽC; 1 cal D 4.1868 J; g D 9.807 m s2, calculate conversion factors to SI units for the following terms: i. feet ii. pounds mass iii. pounds force iv. horse power (1 HP D 550 foot pounds per second) v. psi (pounds per square inch) vi. lb ft1 s1 (viscosity) vii. poise (gm cm1 s1) viii. Btu (British Thermal Unit) ix. CHU (Centigrade Heat Unit) also known as PCU (Pound Centigrade Unit) x. Btu ft2 h1 ŽF1 (heat transfer coefficient). 1.2. Determine the degrees of freedom available in the design of a simple heat exchanger. Take the exchanger as a double-pipe exchanger transferring heat between two single-phase streams. 1.3. A separator divides a process stream into three phases: a liquid organic stream, a liquid aqueous stream, and a gas stream. The feed stream contains three compo- nents, all of which are present to some extent in the separated steams. The compo- sition and flowrate of the feed stream are known. All the streams will be at the same temperature and pressure. The phase equilibria for the three phases is available. How many design variables need to be specified in order to calculate the output stream compositions and flow rates? 1.4. A rectangular tank with a square base is constructed from 5 mm steel plates. If the capacity required is eight cubic metres determine the optimum dimensions if the tank has: i. a closed top ii. an open top. 1.5. Estimate the optimum thickness of insulation for the roof of a house, given the following information. The insulation will be installed flat on the attic floor. Overall heat transfer coefficient for the insulation as a function of thickness, U values (see Chapter 12): thickness, mm 0 25 50 100 150 200 250 U, Wm2 ŽC1 20 0.9 0.7 0.3 0.25 0.20 0.15 Average temperature difference between inside and outside of house 10 ŽC; heating period 200 days in a year. Cost of insulation, including installation, £70/m3. Capital charges (see Chapter 6) 15 per cent per year. Cost of fuel, allowing for the efficiency of the heating system, 6p/MJ. Note: the rate at which heat is being lost is given by U ðT, W/m2, where U is the overall coefficient and T the temperature difference; see Chapter 12. given the following information. The insulation will be installed flat on the attic floor. Overall heat transfer coefficient for the insulation as a function of thickness, U values (see Chapter 12): thickness, mm 0 25 50 100 150 200 250 U, Wm2 ŽC1 20 0.9 0.7 0.3 0.25 0.20 0.15 Average temperature difference between inside and outside of house 12 ŽC; heating period 250 days in a year. Cost of insulation, including installation, $120/m3. Capital charges (see chapter 6) 20 per cent per year. Cost of fuel, allowing for the efficiency of the heating system, 9c/MJ. Note: the rate at which heat is being lost is given by UðT, W/m2, where U is the overall coefficient and T the temperature difference; see Chapter 12. 1.7. What is the optimum practical shape for a dwelling, to minimise the heat losses through the building fabric? Why is this optimum shape seldom used? What people do use the optimum shape for their winter dwellings? Is heat retention their only consideration in their selection of this shape? 1.8. You are part of the design team working on a project for the manufacture of cyclohexane. The chief engineer calls you into his office and asks you to prepare an outline design for an inert gas purging and blanketing system for the reactors and other equipment, on shutdown. This request arises from a report into an explosion and fire at another site manufacturing a similar product. Following the steps given in Figure 1.2, find what you consider the best solution to this design problem. CHAPTER 2 Fundamentals of Material Balances 2.1. INTRODUCTION Material balances are the basis of process design. A material balance taken over the complete process will determine the quantities of raw materials required and products produced. Balances over individual process units set the process stream flows and compositions. A good understanding of material balance calculations is essential in process design. In this chapter the fundamentals of the subject are covered, using simple examples to illustrate each topic. Practice is needed to develop expertise in handling what can often become very involved calculations. More examples and a more detailed discussion of the subject can be found in the numerous specialist books written on material and energy balance computations. Several suitable texts are listed under the heading of “Further Reading” at the end of this chapter. The application of material balances to more complex problems is discussed in “Flow- sheeting”, Chapter 4. Material balances are also useful tools for the study of plant operation and trouble shooting. They can be used to check performance against design; to extend the often limited data available from the plant instrumentation; to check instrument calibrations; and to locate sources of material loss. 2.2. THE EQUIVALENCE OF MASS AND ENERGY Einstein showed that mass and energy are equivalent. Energy can be converted into mass, and mass into energy. They are related by Einstein’s equation: E D mc2 2.1 where E D energy, J, m D mass, kg, c D the speed of light in vacuo, 3 ð 108 m/s. The loss of mass associated with the production of energy is significant only in nuclear reactions. Energy and matter are always considered to be separately conserved in chemical reactions. 2.3. CONSERVATION OF MASS The general conservation equation for any process system can be written as: Material out D Material in C Generation Consumption Accumulation 34 mass is neither generated nor consumed; but if a chemical reaction takes place a particular chemical species may be formed or consumed in the process. If there is no chemical reaction the steady-state balance reduces to Material out D Material in A balance equation can be written for each separately identifiable species present, elements, compounds or radicals; and for the total material. Example 2.1 2000 kg of a 5 per cent slurry of calcium hydroxide in water is to be prepared by diluting a 20 per cent slurry. Calculate the quantities required. The percentages are by weight. Solution Let the unknown quantities of the 20% slurry and water be X and Y respectively. Material balance on Ca(OH)2 In Out X 20 100 D 2000 ð 5 100 a Balance on water X 100 20 100 C Y D 2000 100 5 100 b From equation a X D 500 kg. Substituting into equation b gives Y D 1500 kg Check material balance on total quantity: XC Y D 2000 500 C 1500 D 2000, correct 2.4. UNITS USED TO EXPRESS COMPOSITIONS When specifying a composition as a percentage it is important to state clearly the basis: weight, molar or volume. The abbreviations w/w and v/v are used to designate weight basis and volume basis. Example 2.2 Technical grade hydrochloric acid has a strength of 28 per cent w/w, express this as a mol fraction. Basis of calculation 100 kg of 28 per cent w/w acid. Molecular mass: water 18, HCl 36.5 Mass HCl D 100 ð 0.28 D 28 kg Mass water D 100 ð 0.72 D 72 kg kmol HCl D 28 36.5 D 0.77 kmol water D 72 18 D 4.00 Total mols D 4.77 mol fraction HCl D 0.77 4.77 D 0.16 mol fraction water D 4.00 4.77 D 0.84 Check total 1.00 Within the accuracy needed for technical calculations, volume fractions can be taken as equivalent to mol fractions for gases, up to moderate pressures (say 25 bar). Trace quantities are often expressed as parts per million (ppm). The basis, weight or volume, needs to be stated. ppm D quantity of component total quantity ð 106 Note. 1 ppm D 104 per cent. Minute quantities are sometimes quoted in ppb, parts per billion. Care is needed here, as the billion is usually an American billion (109), not the UK billion (1012). 2.5. STOICHIOMETRY Stoichiometry (from the Greek stoikeion element) is the practical application of the law of multiple proportions. The stoichiometric equation for a chemical reaction states unambiguously the number of molecules of the reactants and products that take part; from which the quantities can be calculated. The equation must balance. With simple reactions it is usually possible to balance the stoichiometric equation by inspection, or by trial and error calculations. If difficulty is experienced in balancing complex equations, the problem can always be solved by writing a balance for each element present. The procedure is illustrated in Example 2.3. Example 2.3 Write out and balance the overall equation for the manufacture of vinyl chloride from ethylene, chlorine and oxygen.
