Constraint Management System Uncertainty Propagation
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Solution Overview
Problem
Current constraint management systems face challenges in efficiently managing uncertainty and exploring design spaces due to the intermixing of planning and computation, especially in data-dependent constraint networks, which limits the flexibility and speed of design exploration during multidisciplinary analysis.
Innovation Solution
A method and system for estimating uncertainty in data-dependent constraint networks by propagating user selections through a bipartite graph, separating computational planning from numerical solution, and using well-formed formulas to determine the applicability of equations, allowing for rapid and robust uncertainty management and efficient exploration of design spaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If computational planning and numerical solution are intermixed in constraint management systems, then the system can handle data-dependent constraints, but the flexibility and speed of design exploration is limited
Solution Approach 1:
The patent divides the constraint management system into two distinct components: a computational planning phase that determines the sequence of operations using well-formed formulas, and a numerical solution phase that executes the computations. This segmentation allows each phase to be optimized independently, improving both flexibility in planning and speed in execution, thereby resolving the contradiction between adaptability and productivity in design exploration.
2Device complexity
If traditional constraint management systems are used without separation of planning and computation, then implementation is simpler, but computational overhead increases and efficiency decreases
Solution Approach 1:
The patent applies preliminary action by performing computational planning before numerical solution. Well-formed formulas are used to pre-determine the applicability and sequence of constraints, allowing the system to avoid unnecessary computations during execution. This preliminary planning reduces computational overhead and improves efficiency without significantly increasing implementation complexity.
3Reliability
If uncertainty propagation is performed without separating planning from computation, then the system can manage uncertainty, but the exploration of large design spaces becomes computationally expensive
Solution Approach 1:
The patent segments uncertainty propagation into a planning phase where well-formed formulas determine which constraints are applicable, and an execution phase where numerical computations are performed only on relevant constraints. This segmentation reduces the number of computations required for uncertainty propagation, making it feasible to explore large design spaces without excessive computational resource consumption while maintaining reliable uncertainty management.
Data Source
AI summary
Presented are rapid and robust techniques for estimating the uncertainty in product attributes (performance, cost, etc.) during the multi-disciplinary design and analysis phase of the product life-cycle. The techniques leverage the capabilities of a preexisting constraint management system that may be used to calculate performance and cost metrics of an engineering system as a function of the design structure and operational scenarios. The techniques are particularly useful when the constraint management system is used to automate the reverse computation required when the analyst specifies cost, schedule, or performance targets using approaches such as cost as independent variable. Disclosed techniques may also be applied to constraint management systems that include compound-valued variables.