Distributed Fracture Simulation Engine for Parallel Crack Analysis
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Solution Overview
Problem
Fracture simulation in complex systems is time-consuming and requires significant computational resources, as it involves simulating the behavior of multiple cracks in physical objects, which can take hours or days to complete using traditional methods.
Innovation Solution
A distributed fracture simulation engine that assigns processors based on the calculated weight value of each crack, allowing for parallel processing across multiple computing devices, thereby optimizing processor utilization and reducing simulation time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional sequential fracture simulation methods are used, then simulation accuracy is maintained, but processing time becomes excessively long and computational resources are inefficiently utilized
Solution Approach 1:
The patent divides the fracture simulation task into independent segments, with each crack simulation being processed as a separate unit by dedicated processor groups. This segmentation allows parallel execution of multiple crack simulations simultaneously, dramatically reducing total processing time while maintaining the accuracy of individual crack behavior analysis
Solution Approach 2:
The system dynamically assigns processor groups to cracks based on calculated weight values that reflect crack complexity and computational requirements. This dynamic resource allocation ensures that more computational power is allocated to complex cracks while simpler cracks receive fewer resources, optimizing overall simulation efficiency without sacrificing accuracy
2Productivity
If more processors are allocated to simulate multiple cracks in parallel, then processing time is reduced, but system complexity increases
Solution Approach 1:
The patent introduces a crack analysis software module as an intermediary that automatically calculates weight values for each crack and assigns processor groups accordingly. This intermediary layer manages the complexity of parallel processing by providing automated, rule-based resource allocation, eliminating the need for manual configuration while enabling efficient parallel simulation across multiple processors
Solution Approach 2:
The system changes the parameter of processor allocation from fixed to variable based on crack-specific weight values. By calculating and applying these weight-based parameters, the system automatically adjusts the number of processors assigned to each crack, enabling scalable parallel processing that adapts to the complexity of the simulation task without requiring complex manual intervention
Data Source
AI summary
Systems and methods are provided for simulating propagation of cracks in an object in a physical system. Data indicative of the object in the physical system is received, where the object includes a plurality of cracks. Characteristics of each of the plurality of cracks are determined based on the data, and a weight value is calculated for each of the plurality of cracks based on the determined characteristics. A group of one or more processors is assigned to simulate behavior of each crack, where a number of processors assigned to each group is based on the calculated weight value associated with that crack. Simulation data is received from each of the groups of processors, and the simulation data is stored in a non-transitory computer-readable medium.