Sequential-Modular Process Simulator Calculation Order Management
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Solution Overview
Problem
Commercially available sequential-modular (SM) process simulators lack functionality for users to view and modify calculation sequencing and recycle convergence specifications, particularly in chemical process simulations with recycle loops, leading to inefficient calculations and lack of user guidance in managing recycle streams.
Innovation Solution
The proposed solution involves partitioning the directed graph (DG) into a directed acyclic graph (DAG) by decomposing it into strongly connected components (SCCs) and SCC groups, allowing users to graphically display and modify the calculation order within SCCGs, which includes specifying tear streams and recycle convergence specifications, thereby managing calculation dependencies and improving simulation efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the sequential-modular method is used to solve process flowsheets, then robustness is improved, but calculation speed deteriorates
Solution Approach 1:
The patent segments the calculation process into distinct phases: initialization phase using sequential-modular method, followed by a solution phase using equation-oriented method. This segmentation allows each method to be applied where it is most effective - SM for robust initialization and EO for fast final solution.
Solution Approach 2:
The patent performs preliminary initialization using the sequential-modular method to establish a good initial guess before applying the equation-oriented method. This preliminary action ensures that the EO method starts from a favorable position, improving both convergence reliability and reducing subsequent calculation time.
2Ease of operation
If users cannot modify calculation sequencing, then ease of operation is improved, but adaptability deteriorates
Solution Approach 1:
The patent implements dynamic calculation sequencing where the calculation order is not fixed but can be automatically adjusted based on the process flowsheet structure. The system dynamically determines the optimal calculation sequence by analyzing component dependencies and recycle loop configurations, allowing adaptability while maintaining ease of operation.
Solution Approach 2:
The patent allows modification of calculation parameters including calculation sequencing order, convergence criteria, and tear stream selection. Users can adjust these parameters to adapt the simulation to different process configurations and performance requirements while maintaining a user-friendly interface.
3Manufacturing precision
If recycle loops are present in the flowsheet, then process representation accuracy is improved, but calculation complexity increases
Solution Approach 1:
The patent extracts recycle loops from the main calculation sequence and handles them through iterative convergence procedures. By separating the recycle stream calculations from the forward calculation pass, the system can accurately represent processes with recycle loops while managing calculation complexity through structured iteration.
Solution Approach 2:
The patent implements feedback mechanisms through iterative convergence of recycle streams. The calculation results from downstream components are fed back to upstream components in recycle loops, and this feedback process continues until convergence is achieved, ensuring accurate process representation while systematically managing the increased calculation complexity.
4Productivity
If the equation-oriented method is used, then calculation speed is improved, but reliability deteriorates
Solution Approach 1:
The patent performs preliminary initialization using the robust sequential-modular method to establish a good initial guess before applying the fast equation-oriented method. This preliminary action ensures that the EO method starts from a favorable position, improving both convergence reliability and reducing subsequent calculation time.
Solution Approach 2:
The patent uses the sequential-modular initialization results as an intermediary to bridge between the robust but slow SM method and the fast but sensitive EO method. This intermediary step transfers the reliability advantage of SM to the EO method's starting conditions, allowing EO to achieve its speed advantage without sacrificing convergence reliability.
Data Source
AI summary
A method of chemical process simulation includes providing a Sequential-Modular process simulator having a simulation algorithm. Responsive to receiving a process flowsheet creating a directed graph (DG) which represents a topology of the process flowsheet with components interconnected as nodes and process streams including recycle streams represented as cycles, with dependencies between process streams adding cycles. Partitioning the components into a first portion including strongly-connected component groups (SCCGs) along with individual components. An initial location is provided for each cycles for the SCCGs to generate a directed acyclic graph (DAG). An initial calculation order is determined for the flowsheet from the DAG, including an order for calculation within the SCCGs themselves. The SCCGs and components as nodes and process streams as edges with a graphical indication representing each cycle for the SCCGs along with the initial calculation order are graphically displayed, wherein the initial calculation order is user modifiable.