Reliability Graph Bounds for Aircraft Network Analysis
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Solution Overview
Problem
Current reliability estimation methods for large composite aircraft current return networks are inadequate due to the complexity of manual translations, computational limitations, and the inability of existing tools to handle large fault tree models or reliability block diagrams, leading to impractical and error-prone assessments.
Innovation Solution
A computer-based method using a reliability graph solver within the SHARPE software package that employs heuristic algorithms to select important paths and cutsets, calculating upper and lower bounds for reliability estimation, thereby approximating the exact solution for large composite aircraft current return network models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual translation of large aircraft current return network into fault tree model is performed, then reliability assessment can be conducted, but the process becomes prohibitively complex, error-prone, and difficult to maintain
Solution Approach 1:
The patent replaces manual mechanical translation processes with automated computer-based algorithms that convert network models into fault tree models and reliability graphs, eliminating human error and reducing complexity while maintaining reliability assessment capability
Solution Approach 2:
The system performs self-service by automatically generating fault tree models and reliability analyses from network data without requiring manual intervention, making the process maintainable and scalable
2Reliability
If currently available fault tree solvers are used to handle large fault tree models, then reliability calculation can be performed, but computational capacity is exceeded and solutions cannot be obtained
Solution Approach 1:
The patent segments the large reliability computation problem into smaller manageable components by decomposing the network into subgraphs and computing reliability bounds for each segment independently, then combining results to obtain overall system reliability
Solution Approach 2:
Instead of computing exact reliability which requires excessive computational power, the patent computes partial solutions in the form of upper and lower bounds that provide sufficient reliability information for certification with much lower computational requirements
3Reliability
If reliability block diagram method is used for aircraft CRN, then reliability estimation can be achieved, but size and computational throughput limitations prevent handling of large networks
Solution Approach 1:
The patent replaces traditional reliability block diagram methods with a novel reliability graph approach that uses automated algorithms to compute reliability bounds, dramatically improving computational throughput for large networks while maintaining estimation accuracy
4Measurement precision
If exact reliability solution is computed for large composite aircraft CRN model, then precise reliability value is obtained, but computation time becomes unreasonably long
Solution Approach 1:
The patent computes partial reliability information in the form of upper and lower bounds rather than exact values, providing sufficiently precise reliability estimates for certification purposes while reducing computation time from unreasonably long to practical levels
Solution Approach 2:
The patent segments the computation into independent bound calculations that can be performed efficiently without requiring exhaustive exact solution methods, achieving practical precision with acceptable computation time
Data Source
AI summary
A computer-based method for determining a probability that no path exists from a starting node to a target node within a network of nodes and directional links between pairs of nodes. The nodes and directional links form paths of a reliability graph and the method is performed using a computer coupled to a database. The method includes selecting a set of paths between the starting node and the target node that have been determined to be reliable, calculating a reliability of the union of the selected path sets, setting an upper bound for unreliability of the set of all paths, selecting a set of minimal cutsets from all cutsets that lie between the starting node and the target node, calculating the probability of the union of the minimal cutsets, and setting a lower bound for the unreliability of the set of all cutsets.