Monetary Vulnerability Assessment for Infrastructure ROI
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods fail to provide a comprehensive and understandable measure for assessing the vulnerability of repairable infrastructure systems, particularly in capturing uncertain failure scenarios and return on investment (ROI) for infrastructure improvements across different restoration plans and system states.
Innovation Solution
A monetary vulnerability assessment (MVA) system that combines a random sampling algorithm, a calibrated asset deterioration model, and a comprehensive cost estimation module to translate system vulnerability into a tangible monetary value, enabling comparison across various service improvement or restoration plans and system states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a risk-based algorithm is used to assess infrastructure vulnerability, then the assessment can be performed with available data, but the measure remains abstract and incomparable across different systems
Solution Approach 1:
The patent transforms the abstract vulnerability measure into a concrete monetary value by changing the parameter of measurement from risk probability to expected monetary loss. This is achieved by multiplying the probability of failure by the consequence value, creating a quantifiable metric that can be compared across different infrastructure systems and restoration plans.
Solution Approach 2:
The patent introduces an intermediary conversion factor (consequence value) that bridges the gap between abstract risk assessment and tangible comparison. This intermediary element translates system-specific vulnerability metrics into a common monetary language, enabling cross-system comparability while preserving the underlying risk-based algorithm.
2Productivity
If multiple restoration plans are evaluated using different investment strategies, then comprehensive ROI analysis can be performed, but the complexity of comparing across different system states increases
Solution Approach 1:
The patent creates a universal monetary vulnerability metric that can be applied across multiple restoration plans and investment strategies. This single metric serves multiple functions: it evaluates different restoration plans, compares investment strategies, and assesses system states, thereby simplifying the complexity of comprehensive ROI analysis.
Solution Approach 2:
The patent segments the vulnerability assessment into distinct components (probability of failure, consequence value, monetary transformation) that can be independently calculated and then combined. This segmentation allows for systematic evaluation of multiple restoration plans while maintaining manageable complexity through modular computation.
3Reliability
If the uncertainty of system failure and repair duration is captured, then a more accurate vulnerability assessment can be provided, but the computational requirements and data needs increase
Solution Approach 1:
The patent applies partial action by focusing on capturing the essential uncertainty elements (failure probability and repair duration) rather than attempting to model all possible uncertainties. This selective approach provides accurate vulnerability assessment while avoiding the excessive data requirements that would result from comprehensive uncertainty modeling.
Data Source
AI summary
A method and system provide the ability to estimate the vulnerability of a repairable infrastructure system. A survival curve is constructed for one or more assets. A rehabilitation plan is prescribed for one or more failure states of the repairable infrastructure system. A cost estimation model is constructed for costs associated with the repairs for each of the failure states. A planning basis is specified. A multiple probability simulation is conducted that estimates a potential restoration cost for a possible failure. The simulation is repeated to acquire a distribution of potential restoration costs. A vulnerability estimation is determined and provided based on the distribution.