In-situ Calibrated Models for Multi-Component Physics Simulation

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Solution Overview

Problem

System simulations involving multiple components are resource-intensive and time-consuming due to complex interactions between components, necessitating a more efficient method for modeling individual components.

Innovation Solution

The development of in-situ calibrated models, created through virtual experiments using physics computation models, where input parameters are defined, and result data is recorded to produce a functional representation of the component's response to varying inputs, reducing the need for rigorous iterative computations during environmental simulations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If physics computation models are used to simulate each component individually, then accurate modeling of component behavior is achieved, but simulation time and computational resources increase significantly

Engineering Contradiction:
Improveaccuracy of component modelingVSAvoidsimulation time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The patent applies preliminary action by performing comprehensive virtual experiments to generate calibrated models before the actual system simulation. The physics computation model is used to compute response surfaces for multiple input parameters in advance, creating pre-calculated lookup tables or functional representations that can be quickly queried during system-level simulation without re-executing the full physics model each time.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent creates a simplified copy or representation of the complex physics computation model in the form of a calibrated model. This calibrated model captures the essential input-output relationships through response surfaces generated from virtual experiments, serving as an approximation that maintains accuracy while significantly reducing computational cost during system simulation.

Inventive Principle:
Principle #26Copying

2Reliability

If physics computation models simulate complex interactions between multiple components, then accurate system behavior is captured, but computational resources and time consumption increase

Engineering Contradiction:
Improveaccuracy of system simulationVSAvoidcomputational resource usage
Core Design Contradiction:
ReliabilityVSUse of energy by moving object

Solution Approach 1:

The patent segments the system simulation into two distinct phases: a calibration phase where physics computation models are used to generate calibrated models for individual components through virtual experiments, and an execution phase where these pre-computed calibrated models are queried to determine component responses. This segmentation allows complex physics computations to be performed once during calibration rather than repeatedly during system simulation.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent performs all complex physics computations and interaction analyses during the preliminary calibration phase using virtual experiments. The responses of components to various input conditions are pre-calculated and stored as calibrated models, eliminating the need to re-execute complex physics simulations during the actual system-level simulation execution.

Inventive Principle:
Principle #10Preliminary action

Data Source

PatentEP4071656A1In-situ formulation of calibrated models in multi component physics simulation
Publication Date: 2022.10.12 DASSAULT SYSTEMS AMERICAS CORP
  • EP4071656A1 patent drawingFigure 1A~1B
  • EP4071656A1 patent drawingFigure 2
  • EP4071656A1 patent drawingFigure 3

AI summary

A calibrated model is created from a physics computation model of a selected component. A setup for a virtual experiment for the selected component is received, and input parameters are defined. An output parameter to be modeled by the calibrated model is selected. The virtual experiment is conducted for the defined input parameters over a predefined range of values for a varied input parameter. Result data from the virtual experiment is recorded and used to produce the calibrated model.