Process Simulation, Unit Operations Design and CFD

Transcription

1 Process Simulation, Unit Operations Design and CFD Flowsheet Simulation, Detailed Design and Operational Options Mike Mendez Aspen Technology, Houston, TX April 2017

2 Disclaimer Aspen Technology may provide information regarding possible future product developments including new products, product features, product interfaces, integration, design, architecture, etc. that may be represented as product roadmaps. Any such information is for discussion purposes only and does not constitute a commitment by Aspen Technology to do or deliver anything in these product roadmaps or otherwise. Any such commitment must be explicitly set forth in a written contract between the customer and Aspen Technology, executed by an authorized officer of each company. 2

3 Topics Scope of Process Simulation Heat and Material Balances Equipment Selection and Sizing Cost Estimation Operations Support Engineering Work-process Discussion and Demonstrations 3

4 Conceptual Design Data and Methods Reactions Heat and Material Balance, Flowsheet 4

5 Equipment Selection, Design and Cost Analysis What Equipment is Required? What is the Right Size How Much Will it Cost? 5

6 Models in Process Operation and Optimization Use models to actualize planning models Planning RTO Drive process closer to its constraints to increase profit Operator Advisory Provide realtime operating advice Teach engineers & operators how to run the plant Operator Training Process Model Decision Support Visualization & What-if analysis Close mass & energy balance Data Reconciliation Equipment Monitoring Process Inferential Use models as virtual sensors 6 Track state of key equipment

7 Conceptual Design Workflow Identify the appropriate Physical Property Package Assess the quality of available VLE/LLE data Identify the best reaction sequences Select the most effective separation methods Develop the flowsheet and apply PINCH analysis Select equipment, size and do preliminary cost analysis 7

8 Conceptual Design Workflow Select Components Select Components 8

9 Other Special Types of Components Ions and salts that react Polymers with MW Distribution 9

10 Design Workflow Solid Components with PSD Solid components may have particle size distribution (PSD) 10

11 Special Methods for Non-Conventional Components? From Substance to molecules? Thermodynamic Properties? C O2 N2 H2 H2O S CL 11

12 Conceptual Design Workflow Select Properties Methods Select Property Method Suitable for Process or Component Set 12

13 Conceptual Design Workflow Data Availability and Quality Check for Physical Property Parameters and Data for all Key Components 13

14 Property Parameters Required for Mass and Energy Balance Simulations For simulations that involve both mass and energy balance calculations, you must enter or retrieve from the databanks these required parameters: If you Use the standard liquid volume basis for any flowsheet or unit operation model specification For simulations that involve both mass and energy balance calculations, you must enter or retrieve from the databanks these required parameters: This table gives further information: These parameters are required Standard liquid volume parameters (VLSTD) For simulations that involve both mass and energy balance calculations, you must enter or retrieve from the databanks these required parameters: This table gives further information: Enter them on this type of Methods Parameters form Pure Component Scalar For simulations that involve both mass and energy balance calculations, you must enter or retrieve from the databanks these required parameters: This table gives further information: 14

15 Property Parameters Required for Mass and Energy Balance Simulations This table gives further information: Enter or retrieve this parameter For On this type of Methods Parameters form MW Molecular weight Pure Component Scalar PLXANT Extended Antoine vapor pressure model Pure Component T-Dependent CPIG or CPIGDP Ideal gas heat capacity model Pure Component T-Dependent DHVLWT or DHVLDP Heat of vaporization model Pure Component T-Dependent 15

16 Conceptual Design Workflow - Supplement Missing Data Properties from molecular structure Supplement missing data with published data or DECHEMA Generate missing parameters from data using Data-Regression Estimate parameters from molecular structure as method of last resource 16

17 Temperature, C Conceptual Design Workflow - VLE / LLE Analysis Residue Curves T-xy diagram for BUTANOL/WATER x bar y bar Liquid/vapor mole fraction, BUTANOL Txxy Binary Diagram Use binary and ternary analysis tools to reveal azeotropes, solubilities, and VLLE boundaries 17 Activity Coefficients at Infinite Dilution

18 THE IMPORTANCE OF ACCURATE PROPERTY CALCULATIONS (Ref. Advanced Process Engineering, AICHE, James Fair) Resulting % Error Property %Error Equip. Size Equip. Cost Thermal Conductivity Specific Heat Latent Heat of Vap Activity Coeff. 10 Sep. factor = Diffusivity Viscosity Density Surface Tension

19 Conceptual Design Workflow - VLE / LLE Analysis 19 Activity Coefficient at Infinite Dilution

20 Conceptual Design Workflow Reactions and Kinetics Equilibrium and Kinetic Reactions Kinetic Reaction Types Reactors are the heart of the process, choose wisely 20

21 Conceptual Design Workflow Biological Reactors Equilibrium and Kinetic Reactions Kinetic Reaction Types Reactors are the heart of the process, choose wisely 21

22 Conceptual Design Workflow Biological Reactors Fermentation models require special methods B I O M A S S o r E T O H R a t e t, hours Ethanol (g/l) Sugar (g/l) Biomass (g/l) ETOH Rate, g/l-hr S U G A R o r E T H A N O L 22

23 Conceptual Design Workflow Biological Reactors Logistic Model With Growth Associated Production of Ethanol 23

24 CO2 MTBE WATER Conceptual Design Workflow - Separation and Purification RECTIFR RECOVHD FUSEL-O e e e e e EXTRACT (Extract) - Profiles Composition CO2 MTBE WATER BCOVH RTRN e e e e CO2 MTBE L1 L2 S e e EXTRACT RECBTMS e BEER BEERCOL BCBOTM PUMP STRIPR STRIPBTM e e e Stage Distillation Liquid-Liquid Extraction S45 0 S HYDROCYC SOLUTION CRYSTALS CRYSTAL S1 S6 63 S4 24 Adsorption DECANTER Crystallization

25 Distillation Design Enabling Functions: Separations Synthesis Design and Rate-Based Distillation Useful for devising new separation schemes or improving existing ones. Might help reduce the number of columns in complex separations trains and still maintain the same quality of product. 25 Distillation Synthesis Conceptual design of distillation systems, most useful for nonideal, azeotropic mixtures Visibility into ternary and residue diagrams. Integrated with steady-state simulation tools Rate-Based Distillation Calculate Mass and Heat transfer rates Work with real column internals rather than theoretical stages No need to guess separation efficiencies

26 Conceptual Design Workflow Flowsheeting and Pinch Analysis Ethylene Gas from Furnace Hydrogen Ethane Ethane To Depropanizer Chiller 5 Chiller 1 Chiller 4 Chiller 2 Chiller 3 DemethanizerDeethanizer C2-Splitter Ethylene Plant Cold End Flowsheet Pinch Grand Composite Curve Pinch Heat Exchanger Network 26

27 Conceptual Design Workflow Heat Exchangers Air Cooled Fired Heater Plate Exchanger Plate Fin Shell & Tube Shell & Tube Mechanical Heat Exchangers - Design, Rate and Simulate 27

28 Rigorous Exchanger Models in Flowsheet Simulations Analyze Risk and Potential Operational Problems of Heat Exchangers Exchanger Feasibility Identify Operating Risks 28

29 STREAMS("RECOVHD").Zmn("ETHANOL") lb/lb STREAMS("RECOVHD").Zmn("CO2") lb/lb STREAMS("RECOVHD").Zmn("FUSEL") lb/lb STREAMS("RECOVHD").Zmn("H2O") lb/lb : STREAMS("RECOVHD").Zmn("ETHANOL") lb/lb Dynamic Simulation Enabling Function Dynamic response of systems (equipment and controls) Configure process control schemes that yield more stable systems, and get you closer to optimal operation. RECTIFIER prod Time Hours Time Hours 29

30 Conceptual Design Workflow Project Costs Equipment Mapping Equipment Cost 30 Relative Project Cost

31 Activated Cost Project Summary 31

32 Capacity Scaling and Capital Costs with ASW Cost estimation results shown in ASW 32

33 Models for Uncertainty Quantification or Global Optimization Rxn Conversion Variability Rxn Conversion Frequency FEED RXT Three Simultaneous Reactions 33 PRD Batch Reactor Uncertainty in Rxn Kinetic Parameters

34 Model Automated with EXCEL to Find Local and Global Optima 34

35 Reliability, Availability and Maintenance Aspen Technology, Inc. All rights reserved

36 RAM Modeling 36

37 System and Reliability Modeling Utilizes Unit Histogram 37

38 System and Reliability Modeling Pareto (Top 10) 38

39 RAM Modeling Power/Cogen During the design phase of a power generation facility, our RAM Modeling was used to determine if a utility grid connection would provide adequate electrical reliability. This option was compared to one with self-generation. For these cases, the model determined that the utility grid did provide adequate reliability and that the additional cost of adding on-site generators was unnecessary. This proved to be a significant costsavings to the company. When designing a new steam generation facility, our RAM Modeling was used to determine the size and optimal number of steam boilers. After running several alternate cases with many different size differentials and configurations, the model landed on the most economical design that would provide the required level of reliability. This could be completed for any utility plant such as air compression, power generation, co-generation, or even water supply & treatment. During the operational phase of many utility plants, demands for electricity, stream, and instrument air often increase as the customer plants grow and increase production. Our RAM Modeling has been used to help evaluate many different de-bottleneck alternatives. When the desired reliability of each alternative is achieved, completing a cost analysis is an easy way to select the most economical solution. Some examples ofthis may include: Selecting a vendor for a new skid Installing stand-by generation or diesel backups Connecting to a standby utility header Improving site recovery methods. 39

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