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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Research in Progress (RIP)</title>
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      <title>Digital Twin and Automation of Pipeline Data for Predictive Maintenance and Risk Analysis incorporating Bayesian network</title>
      <link>https://rip.trb.org/View/2655704</link>
      <description><![CDATA[Pipeline infrastructure is critical for global energy transportation, yet aging systems face increasing degradation risks from corrosion, fatigue, and environmental factors. Recent catastrophic failures have demonstrated severe safety, environmental, and economic consequences of inadequate integrity management, with annual losses reaching billions of dollars. Despite significant advances in inspection technologies, including intelligent inspection tools and sensor networks, three fundamental challenges remain unresolved: lack of interpretability in machine learning approaches, difficulty quantifying uncertainties in defect growth predictions, and the challenge of optimizing maintenance decisions with incomplete information.

This research develops a Valuation Bayesian Network (VBN) integrated with Digital Twin technology as an automated decision-support tool for pipeline integrity management. The VBN approach provides a principled foundation for uncertainty quantification, data fusion, state estimation, prediction, and maintenance planning while maintaining interpretability. The framework incorporates probabilistic degradation and failure models, logic and relational models, and surrogate models to address key performance indicators, failure risks, and remaining life estimation.

The proposed Digital Twin architecture comprises four interconnected layers. The physical layer encompasses pipeline infrastructure with distributed sensors and expert knowledge. The simulation layer employs VBN-based probabilistic models capturing time-dependent degradation processes, where state variables, including defect depth and material properties, are modeled through Markov transition models with parameters learned from historical inspection records, pipeline failure databases, and expert elicitation. The data fusion layer performs Bayesian updating by integrating inspection data, operational history, and expert knowledge, enabling adaptive parameter calibration to capture site-specific degradation patterns. The decision layer implements maintenance optimization using value of information analysis and supports counterfactual reasoning for intervention scenarios.

This framework achieves full uncertainty propagation from measurement noise through remaining life predictions, ultimately enhancing operational safety by predicting high-risk defect development and enabling timely maintenance interventions.]]></description>
      <pubDate>Mon, 19 Jan 2026 16:27:23 GMT</pubDate>
      <guid>https://rip.trb.org/View/2655704</guid>
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    <item>
      <title>Guide for Design, Installation, and Testing of Cured In-Place Pipe Liners








</title>
      <link>https://rip.trb.org/View/2419748</link>
      <description><![CDATA[State departments of transportation (DOTs) are increasingly using trenchless strategies to rehabilitate and repair aging infrastructure. Performing pipe repairs to existing systems, as compared to pipe replacement, significantly reduces the construction time and maintenance of traffic operations and roadway reconstruction. With reduced construction time and roadway construction, pipe repairs can increase public safety and cost savings to the state DOTs. One of the most common pipe rehabilitation methods is cured in-place pipe (CIPP) liners. CIPP liners are a trenchless technology that provides a method to structurally rehabilitate existing pipes and conduits with minimal impact to the traveling public. The liner consists of a resin-impregnated material that is inserted into the existing damaged host pipe.

Research is needed to substantiate that CIPP liner technology provides the structural characteristics and durability to extend the service life of the asset. 

The objective of this research is to develop a guide for design, installation, and acceptance of CIPP liners for structural rehabilitation of existing pipelines and conduits and test methods for CIPP liner material.  ]]></description>
      <pubDate>Tue, 20 Aug 2024 09:39:08 GMT</pubDate>
      <guid>https://rip.trb.org/View/2419748</guid>
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    <item>
      <title>In Service Performance of Pipe to Structure Connections</title>
      <link>https://rip.trb.org/View/2384793</link>
      <description><![CDATA[This project shall examine installed resilient connectors and structures with typical brick and mortar connections. Field inspections and documentation will consist of locations within District 7 to investigate performance of the resilient connectors. Additional investigations will then be conducted in other locations for structures with brick-and-mortar connections. The research team shall compare the connection methods based on the field observations.]]></description>
      <pubDate>Mon, 03 Jun 2024 12:31:10 GMT</pubDate>
      <guid>https://rip.trb.org/View/2384793</guid>
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