Aspen PIMS: Advanced Optimization Features

Learn the differences between standard Aspen PIMS using Distributed Recursion and Aspen PIMS Advanced Optimization using the XNLP framework. Learn to troubleshoot suboptimal solutions inherent to non-linear optimization problems.

Audience:

Participants will typically know how to use Aspen PIMS and want to take advantage of the expanded capabilities of the Aspen PIMS Advanced Optimization software.

Training Details

  • Course Id:

    RPA221

  • Duration:

    2 day(s)

  • CEUs Awarded:

    1.4

  • Level:

    Intermediate

Benefits

  • Review limitations of Distributed Recursion modeling framework and motivations for introducing Advanced Optimization
  • Gain familiarity with the XNLP and XSLP technologies
  • Use Advanced Optimization Analysis tools to evaluate deviations from optimal solution
  • Execute different Global Optimization procedures
  • Add and edit non-linear formulas to model
  • Attach external models, use them for simulation and optimization
  • Set Up and run High Performance Computing architecture

Approach

  • Class lectures describe the differences between standard Aspen PIMS using Distributed Recursion and Aspen PIMS Advanced Optimization using the XNLP framework, and focus on the use of the new functionality
  • The features of Aspen PIMS Advanced Optimization are thoroughly described in lectures and demonstrations
  • Class problems are designed to familiarize the student with the features of Aspen PIMS Advanced Optimization. Time is allotted to allow the student to explore these features 

Pre-requisites

Must have attended RPA101 Aspen PIMS: Introduction to Refinery Planning.

Agenda

Introduction to Aspen PIMS Advanced Optimization
  • Describe the limitations of the existing modeling and solution framework (DR)
  • Discuss some of the solutions to these limitations
  • List the advantages of moving to PIMS-AO

Migrating a PIMS Model to PIMS-AO
  • Review the DR model looking for any indications of poor model structure
  • Discuss DR warning messages that indicate a potential problem
  • Ensure DR model is running well and producing a good solution
  • Switch to PIMS-AO and review any new messages
  • Develop a generalized input solution to initialize PIMS-AO
  • Review recommended model settings

Global Optimization
  • Identify local optima problem
  • Compare global optimization techniques in Distributive Recursion and Advanced Optimization
  • Apply different Global Optimization techniques in Advanced Optimization
  • Workshop: Working with Local Optima in DR and PIMS-AO

Advanced Optimization Analysis
  • Identify solution analysis methods available in Distributive Recursion and Advanced Optimization
  • Apply correct solution analysis technique to corresponding type of problem
  • Set up Advanced Optimization Analysis
  • Evaluate results of Advanced Optimization Analysis
  • Workshop: Parametric Analysis
  • Workshop: Goal Programming
  • Workshop: Ranging Analysis
  • Workshop: FeedStock Basket Reduction

Modeling and Solution Technology: XNLP and XSLP
  • Differentiate key aspects of Distributive Recursion vs. XNLP
  • Apply the different Initialization methods to start a run in XNLP
  • Identify XSLP linearized structure and key convergence parameters
  • Track linear and nonlinear model equations using Matrix Analyzer and PIMS-AO Execution Report
  • Access key XNLP and XSLP settings
  • Gain familiarity with main issues when converting from Distributive Recursion to XNLP
  • Workshop: Initialization Methods in XNLP-
  • Workshop: Model diagnostics and infeasibility troubleshooting in PIMS-AO.

High Performance Computing
  • Use new XLP Matrix Generator functionality
  • Use Parallel Processor architecture for running multiple cases and Global Optimization Multistart for the flowsheet

Nonlinear Formulation
  • Identify main sources of nonlinearities in models
  • Differentiate non-linear modeling tools in Distributive Recursion and Advanced Optimization
  • Add and edit non-linear formulas
  • Connect external non-linear models to a PIMS model
  • Use external models for optimization and/or for simulation
  • Workshop: Throughput Dependent Yields
  • Workshop: Quality Cross Product
  • Workshop: Feed Dependent Utility
  • Workshop: Using An External Model

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Aspen Technology, Inc. awards Continuing Education Units (CEUs) for training classes conducted by our organization. One CEU is granted for every 10 hours of class participation.