Process Plant Sizing Across Multiple Operating Cases
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Solution Overview
Problem
Conventional methods for sizing process plants, such as air separation or natural gas plants, often require tedious iterative adjustments to accommodate multiple operating cases, making it difficult to find an optimal design that can operate effectively across all specified conditions.
Innovation Solution
A computer-implemented method that performs multiple process simulations in parallel to determine optimal values for process plant variables and parameters by modeling them in a common equation system, using a gradient-based optimization method and weighting factors to prioritize operating cases, thereby overcoming the limitations of traditional iterative methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional iterative methods are used to size process plant parameters for multiple operating cases, then the plant can be operated in all specified operating cases, but the process requires tedious manual iterations and cannot find an optimal design
Solution Approach 1:
The patent combines multiple operating case simulations into a single unified simulation run by introducing weighting factors that allow simultaneous consideration of multiple operating cases. Instead of sequentially running separate simulations for each operating case and manually adjusting parameters, the system merges all operating cases into one optimization problem that can be solved in a single computational pass, dramatically reducing the time required for plant sizing across multiple operating conditions.
2Adaptability or versatility
If iterative manual adjustment of sizing parameters is performed to accommodate all operating cases, then the plant can operate in all cases, but an optimal design cannot be found since the selected design deviates from the optimal design for several operating cases
Solution Approach 1:
The patent implements a feedback mechanism through weighting factors that quantify the importance of each operating case. The simulation system uses these weights to provide feedback during the optimization process, allowing the algorithm to automatically adjust sizing parameters to achieve an optimal balance across all operating cases. This eliminates the need for manual trial-and-error adjustments and enables the system to converge on a truly optimal design that considers all operating conditions simultaneously rather than sequentially.
Solution Approach 2:
The patent introduces weighting factors as new parameters that change the optimization landscape. By adjusting these weighting factors, the system can dynamically prioritize different operating cases and explore different regions of the design space. This parameter change approach allows the optimization algorithm to efficiently navigate toward an optimal design that balances performance across multiple operating cases, rather than getting stuck in local optima that may be optimal for one case but poor for others.
Data Source
AI summary
The present invention relates to a computer-implemented method for performing a chemical engineering process, in particular in an air separation plant or a natural gas plant, wherein a multiplicity of process simulations are performed simultaneously, in the course of each of which the process in the process plant is in each case simulated for a particular application case, wherein each application case is characterized by values of process plant variables and/or values of process parameters, wherein, in the multiplicity of process simulations, values for the process plant variables and/or for the process parameters are determined such that at least one predefined condition is met, wherein free values for process plant variables and/or process parameters are determined, and wherein dependent values for process plant variables and/or process parameters are determined from the free values for process plant variables and/or process parameters.