R-PMS System Use Cases : Model . R-PMS System - EPMS/KANPAV : System
Use Case - KANPAV-03 Estimate Remaining Life link
Properties |
Name | Value | ||||||||||||||
Description |
This Use Case is used for the Calculation of the Estimated Remaining Life of each segment per the current Segment State Vector |
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Id | UC30 | ||||||||||||||
Abstract | false | ||||||||||||||
Leaf | false | ||||||||||||||
Root | false | ||||||||||||||
Stereotypes | UseCase, Modeling | ||||||||||||||
Justification | A primary requirement for optimization of the system is to do an initial estimation of the remaining life of each segment or pavement category in the Network | ||||||||||||||
Business Model | false | ||||||||||||||
Primary Actors | Actor - KDOT PMS Modeler | ||||||||||||||
Status | Identify | ||||||||||||||
Rank | Unspecified |
Relationships Summary |
Use Case Note |
■ Inputs and Prior Actions | |||
■ Actions | |||
• for each segment | |||
♦ Grab the Current Segment State Vector: | |||
♦ Current Condition, | |||
♦ Last Major Action(LMA) | |||
♦ Predicted Future Conditions under Nominal Actions, | |||
♦ Thresholds for good to fair and fair to poor | |||
♦ Traffic Vector | |||
♦ Prediction process (Monte Carlo or ML) | |||
♦ Now | |||
♦ Next cycle | |||
♦ Threshold crossings for each variable | |||
♦ Earliest crossing determines remaining life | |||
♦ Utilize ML Algorithms in concert with or separately to Monte Carlo Calculations on existing sampled data | |||
♦ Result is a weighting on Remaining life before doing something either light or heavy | |||
■ Outputs | |||
• Remaining life prior to actions |
Actions |
Steps | |||
1. ![]() |
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2. SYSTEM for each segment | |||
2.1. Grab the Current Segment State Vector: | |||
2.1.1. Current Condition, | |||
2.1.2. Last Major Action(LMA) | |||
2.1.3. Predicted Future Conditions under Nominal Actions, | |||
2.1.4. Thresholds for good to fair and fair to poor | |||
2.1.5. Traffic Vector | |||
2.1.6. Predicted Future Conditions | |||
2.2. Prediction process | |||
2.2.1. Now (Steady State for Baseline) | |||
2.2.2. Next cycle | |||
2.2.3. Threshold crossings for each variable | |||
2.2.4. Earliest crossing determines remaining life | |||
2.2.4.1. Utilize ML Algorithms in concert with or separately to Monte Carlo Calculations on existing sampled data | |||
2.3. Merge Remaining life prior to actions into current Segment State Vector |
Details |
Name | Value | ||
Level | Subfunction | ||
Complexity | High | ||
Use Case Status | Initial | ||
Implementation Status | Scheduled | ||
Preconditions | |||
Post-conditions | |||
Author | Rick Miller and Jerry W. Manweiler, Ph.D. | ||
Assumptions |
Tagged Values |
Name | Type | Value | |||
Level | Ad Hoc Enumeration | ||||
Complexity | Ad Hoc Enumeration | ||||
Use Case Status | Ad Hoc Enumeration | ||||
Implementation Status | Ad Hoc Enumeration | ||||
Preconditions | Multi-line Text | ||||
Post-conditions | Multi-line Text | ||||
Author | Text | ||||
Assumptions | Multi-line Text |
References |
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Abstract | false | ||||||||||||||||||||||||||||||
Final Specialization | false | ||||||||||||||||||||||||||||||
Leaf | false | ||||||||||||||||||||||||||||||
Visibility | Unspecified | ||||||||||||||||||||||||||||||
Derived | false |
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Visibility | Unspecified | ||||||||||
Stereotypes | Include |
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