System Dynamics Model Integration via Data Exchanger
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Solution Overview
Problem
Current system dynamics modeling lacks the ability to integrate non-subscripted and subscripted models effectively, limiting control over data exchange and time looping during simulation, which restricts the analysis of complex systems at various levels of detail.
Innovation Solution
A method is introduced that involves defining and executing both non-subscripted and subscripted system dynamics models, with a data exchanger and loop program to manage the interaction and output of these models, allowing for the integration and aggregation of simulation results across different models and time periods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple system dynamics models are integrated to simulate complex systems at various levels of detail, then the analysis capability and understanding of system behavior are improved, but the device complexity and difficulty of controlling data exchange increase
Solution Approach 1:
The patent segments the complex system simulation into multiple independent system dynamics models (non-subscripted and subscripted models) that can be executed separately and then integrated. Each model operates at different levels of detail, allowing independent development, verification, and execution while maintaining overall system analysis capability.
Solution Approach 2:
The patent introduces intermediary components including a data exchanger that manages data flow between models, a results aggregator that consolidates outputs from multiple models, and a loop program that coordinates execution. These intermediaries simplify the integration process by providing standardized interfaces and control mechanisms.
2Reliability
If data exchange between non-subscripted and subscripted models is controlled, then the simulation accuracy and reliability are improved, but the device complexity increases
Solution Approach 1:
The data exchanger is designed as a universal component that handles multiple functions: data transformation between different model formats, timing synchronization, and coordinate mapping. This multi-functional approach reduces the need for separate control mechanisms for each data exchange scenario.
Solution Approach 2:
The patent employs parameter transformation mechanisms where the data exchanger converts data between different parameter representations used by non-subscripted and subscripted models. This includes transforming coordinate systems, time scales, and data formats to ensure compatibility while maintaining data integrity.
3Measurement precision
If time looping is controlled during model execution, then the simulation precision and system performance understanding are improved, but the loss of time increases
Solution Approach 1:
The loop program implements periodic execution of models with controlled time stepping, allowing the system to advance through simulation time in manageable intervals. This periodic action enables precision control over when data is exchanged and when results are aggregated, balancing accuracy requirements with execution efficiency.
Solution Approach 2:
The system performs preliminary actions by pre-processing input data, pre-defining time loops and execution parameters, and pre-establishing data exchange protocols before simulation begins. This preparation reduces the computational burden during actual execution and minimizes unnecessary processing time.
4Adaptability or versatility
If multiple models are executed with different time periods, then the adaptability to various system dynamics is improved, but the device complexity and coordination difficulty increase
Solution Approach 1:
The system implements dynamic time period adjustment where each model can operate with its own time scale appropriate to its specific dynamics. The loop program dynamically coordinates these different time periods, allowing fast processes to be simulated with smaller time steps while slow processes use larger time steps, optimizing both accuracy and efficiency.
Data Source
AI summary
A method for simulating complex systems over time using a system dynamics approach is provided including defining a first model of a complex system, the first model having a first model variable; defining a second model of the complex system, the second model having a second model variable; executing the first model by modifying the first model variable to obtain a first model output; executing the second model by passing the first model output to the second model and modifying the second model variable based the first model output to obtain a second model output; defining a simulation result based on the first and second model outputs; and outputting the simulation result. Furthermore, the first model is either a non-subscripted system dynamics model or a subscripted system dynamics model, and the second model is either a non-scripted system dynamics model or a scripted system dynamics model.