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    <title>Transport Research International Documentation (TRID)</title>
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    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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      <title>Field Live-Load Testing and Advanced Analysis of Concrete T-Beam Bridges to Extend Service Life</title>
      <link>https://trid.trb.org/View/2662983</link>
      <description><![CDATA[Concrete T-beam bridges are an important class of structures that has seen limited investigation. These structures are often perceived as quite robust and are in good condition, but possess very low rating factors based on conventional analysis per the AASHTO Manual for Bridge Evaluation (2011). Testing of five T-beam bridges conducted in summer 2017 indicated that conventionally calculated rating factors are generally low for T-beam bridges. However, all of the tested bridges were un-skewed, and the effect of skew angle has not been quantified. Further, the reliance on non-destructive live-load testing (NDLLT) to modify rating factors can be costly. Finally, the use of NDLLT to modify rating factors requires the extrapolation of service-load strain data to predict bridge capacity, and at capacity, the bridges will generally experience significant nonlinearity. These research questions were addressed with a three-phase approach. In the first phase, UMaine engineers instrumented and field load-tested five, cast-in-place, simple span, skewed concrete T-beam bridges. In the second phase of this project, the NDLLT results from the five skewed bridges were used in conjunction with prior NDLLT of non-skewed T-beam bridges to assess differences in behavior caused by a skewed alignment. In addition, detailed, linearly elastic, 3D finite-element models of all 10 bridges were developed. In the final phase of the project, a novel, nonlinear finite-element modeling strategy was developed that permits the accurate inclusion of inherent ductility and a realistic assessment of capacity under the application of factored loads. This method, termed Proxy Finite Element Analysis (PFEA), enhances our ability to rationally assess bridge capacity without relying on NDLLT. PFEA was validated through comparison with experimental data both from the testing conducted in this study and from strength tests of beams and bridges performed by others. Ultimately, PFEA was used to re-compute flexural rating factors for all ten T-beam bridges considered in this study, and generally indicated less-conservative predictions of bridge capacity than NDLLT. This is consistent with PFEA’s explicit consideration of nonlinear structural response and the fact that NDLLT relies on linear extrapolation. PFEA was also used to examine the shear rating factors of the 10 bridges subjected to NDLLT, and indicated generally higher shear rating factors.]]></description>
      <pubDate>Thu, 12 Feb 2026 08:52:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2662983</guid>
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    <item>
      <title>Condition assessment of existing bridges : serviceability limit state (SLS) loading and non‐destructive test (NDT) methods : testbed and demolition of the Kalix Bridge : final report</title>
      <link>https://trid.trb.org/View/2666527</link>
      <description><![CDATA[The direct socio‐economic impact of loss of capacity on aging infrastructure systems has motivated a continuous revision and update of current design standards and guidelines of critical network components subjected to long‐term deterioration processes. The analysis and evaluation of crucial structural assets, such as prestressed concrete bridges, should be conceived in such a way as to provide engineering practitioners with theoretically consistent and easy‐to‐apply methodologies to prevent and mitigate the catastrophic consequences that may unfold while in service. In this regard, significant efforts are currently being directed toward the definition of risk‐ based design practices for bridges that are currently reaching the end of their service life. Consistent with these research efforts, this document presents a framework for evaluating the capacity of existing prestressed bridges, using the Kalix Bridge as a testbed. This includes a condition assessment of the bridge by means of non‐destructive testing (NDT). The Kalix Bridge is ideal for a case study because it must be demolished in a controlled manner for environmental reasons, so the prestressed reinforcement's condition can be systematically inspected in detail and compared to NDT predictions. Many NDT tools are rarely used in practice, mainly because of lack of trust in the results they produce. This is a rare opportunity to improve understanding of their readiness to identify the condition of reinforcement inside the concrete. This case study will involve first studying the original documentation and existing inspection protocols to better understand the rationale of the bridge's design, location of the prestressing reinforcement, and known issues. In addition, numerical models were created and calibrated following an extensive experimental campaign that was developed to estimate material properties by means of several core extractions and a proof loading test performed with the aim of evaluating the structural response of the bridge under serviceability loading conditions.]]></description>
      <pubDate>Thu, 05 Feb 2026 08:33:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2666527</guid>
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    <item>
      <title>Numerical analysis of fatigue performance of steel fiber reinforced concrete pavement based on microscopic crack growth theory</title>
      <link>https://trid.trb.org/View/2606328</link>
      <description><![CDATA[The fatigue performance of rigid pavements on steel bridge decks remains an underexplored area, with most existing research focusing on flexible pavement systems and simplified macroscopic models. This study presents a refined mesoscale numerical framework for analyzing fatigue crack propagation in steel fiber reinforced concrete (SFRC) pavements using fracture mechanics and the extended finite element method (XFEM). A three-dimensional local model of an SFRC-orthotropic steel deck system was developed, incorporating moving load simulations to determine critical stress locations. Parameters such as steel fiber volume content, yield strength, and aspect ratio were systematically varied to evaluate their effects on crack propagation behavior and fatigue life. Model predictions were validated against experimental fatigue test results, showing strong agreement in crack path and fatigue life estimates. The findings indicate that increasing steel fiber content from 0.5% to 2.0% progressively enhances fatigue resistance, with simulated fatigue life improvements of 51%, 28%, and 20% over the 0.5%-1.0%, 1.0%-1.5%, and 1.5%-2.0% intervals, respectively, while higher fiber strength and optimized aspect ratios further improve performance. The proposed methodology provides a reliable tool for optimizing SFRC pavement design and offers practical guidance for extending the fatigue life of steel bridge decks.]]></description>
      <pubDate>Mon, 29 Dec 2025 09:35:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2606328</guid>
    </item>
    <item>
      <title>Chloride Ingress in De-Icing Salt-Exposed Bridge: Numerical Modeling and Field Investigations</title>
      <link>https://trid.trb.org/View/2572110</link>
      <description><![CDATA[This research focuses on assessing the durability of various components of an onshore section of the Original Champlain Bridge in Montreal, specifically in relation to chloride ingress from de-icing salting operations. Chloride penetration in both the original and repaired concrete are both numerically modelled and measured. The transport characteristics of repaired and original parts of the concrete were determined using non-destructive air permeability tests and used in the TransChlor® to predict chloride ingress into the air-exposed repaired sections and underlying unrepaired sections over the service life of the bridge. By selecting appropriate boundary conditions, and historical climatic data, the predicted chloride profiles are shown to be a close match to core sample data from both the repaired and unrepaired sections of structural elements. This research proposes a blind a-priori prediction method for analyzing and predicting chloride ingress in ageing concrete structures as opposed to a-posteriori predictions made by matching chloride profiles obtained from cores, which is a common practice in the literature. Furthermore, it was clearly demonstrated that cathodic protection is effective in preventing chloride ingress into concrete. However, the ability to predict chloride ingress in the presence of cathodic protection was identified as a gap in current chloride ingress models such as TransChlor®, and an objective for future research.]]></description>
      <pubDate>Tue, 29 Jul 2025 09:49:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2572110</guid>
    </item>
    <item>
      <title>Experimental Study on Fatigue Behavior of Deep-Reinforced Concrete Beams with Corroded Reinforcement</title>
      <link>https://trid.trb.org/View/2550918</link>
      <description><![CDATA[RC deep beams are critical load-bearing elements in bridge structures, designed to sustain heavy loads over short spans while being exposed to cyclic loading and aggressive corrosive environments during their service life. This study presents an experimental investigation into the fatigue performance of RC deep beams under varying degrees of reinforcement corrosion. The specimens were subjected to sinusoidal cyclic loading, ranging from 10% to 60% of the beam’s ultimate capacity, at a frequency of 3 Hz. Tensile reinforcements were artificially corroded using the accelerated current method with a 5% NaCl solution as the electrolyte. The fatigue behavior of the corroded beams was evaluated, focusing on the mode of failure, progression of deflection and strain with cycles, stiffness degradation, and fatigue life. The result showed that the fatigue life of corroded specimens decreased by approximately 12%–87% as the reinforcement mass loss increased from 1.7% to 10.1%. While all specimens exhibited the characteristic failure mode of tensile reinforcement fracture, corrosion-induced effects, including bond strength deterioration, stiffness reduction, and longitudinal cracking, significantly impacted the failure mode of beams. To simulate more realistic conditions, the research further explores how the structural behavior is altered when corrosion and fatigue simultaneously progress. A comparative analysis quantifies the additional damage sustained by specimens exposed to simultaneous corrosion-fatigue loading relative to pre-corroded beams before fatigue testing. The relationship between the degree of corrosion and fatigue life degradation demonstrated that approximately 1% rebar mass loss resulted in a 6.9% reduction in fatigue life for pre-corroded specimens, compared with a significantly higher reduction of 40.5% for specimens undergoing simultaneous corrosion. This emphasizes the critical need to investigate the coupled effects of corrosion and cyclic loading on degradation mechanisms over service life. Furthermore, the results demonstrate that overlooking the synergistic interaction between fatigue and corrosion results in a significant overestimation of fatigue life, leading to substantial inaccuracies in the performance predictions for RC bridges subjected to corrosive environments.]]></description>
      <pubDate>Tue, 29 Jul 2025 09:27:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2550918</guid>
    </item>
    <item>
      <title>Shear Condition Classification of Cracked Reinforced Concrete Beams Using Machine Learning</title>
      <link>https://trid.trb.org/View/2550291</link>
      <description><![CDATA[RC bridges represent about 40% of the US bridge inventory, with many of these bridges reaching or surpassing their design service life. As a result, there is a significant number of structures that require fast and accurate structural evaluation. Shear deficiencies can pose a higher safety risk than flexure deficiencies since shear failures are sudden. This study correlates shear crack width with shear condition and proposes a machine-learning framework to place RC beams into shear condition categories using quantitative estimates of shear, stiffness, and stirrup strain histories. The results of the proposed framework are compared with those from existing quantitative and qualitative assessment methodologies. The quantitative predictions of residual shear capacity and stiffness by the proposed framework are closer to experimental measurements than the ones by the existing methodologies. The qualitative condition classifications of the framework indicate less urgency for repair compared with the ones of the existing methodologies. The proposed framework enables the ranking of bridges within the same shear condition category due to its quantitative nature, and it has been implemented in a software application and can be used to set priorities for repair.]]></description>
      <pubDate>Tue, 29 Jul 2025 09:27:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2550291</guid>
    </item>
    <item>
      <title>Optimizing the Data Collection for the Service Life Prediction of Concrete Port Infrastructure</title>
      <link>https://trid.trb.org/View/2559446</link>
      <description><![CDATA[For Port Authorities, waterfront assets like quay walls, wharves, and jetties are the pivot of their business cases. The Port’s income will depend on whether the asset is capable of performing adequately during the lease period of the tenant. When not properly maintained, the harsh conditions of the maritime environment will cause major deterioration of the assets. Being able to predict when to intervene with maintenance is key for asset managers. Starting in 2011, the Port of Rotterdam initiated the KMS (Kademuren Modellering Systeem) program, which aimed to assist asset managers in their effort to optimize the prediction of needed maintenance of concrete waterfront structures. The software portion of the KMS program focused on connecting the port legacy system to the service-life prediction model and risk calculation expert applications. At the heart of the KMS, an advanced reactive transport model called STADIUM was used to simulate the exposure to brackish water and seawater to the port infrastructure and predict degradation mechanisms, such as rebar corrosion. To feed the service-life prediction model, information on the in-place concrete is essential. Accordingly, a specific inspection protocol was put in place to collect information relevant to the predictive model. Base information needed to perform service-life predictions includes concrete properties, such as porosity and diffusion coefficient and steel reinforcement cover. This initial KMS inspection program relied heavily on coring and laboratory testing. Yearly inspections allowed gathering information on multiple quay wall sections built at different times and exposed to different environments, ranging from low salinity ones to the seawater of the North Sea. The initial inspection procedure was first optimized by performing statistical analyses of the data gathered in the first six years of the KMS program. This allowed reducing coring operations by half. To refine the information collected on site, coring was replaced using non-destructive tests, which not only helped to compensate for the reduced number of cores but also added new layers of information that greatly enhanced the service-life predictions of the different concrete structures. Non-destructive tests performed on site at this point consisted of corrosion potential and ground-penetrating radar measurements. The third phase of the KMS inspection program is underway and aims to completely eliminate coring activities. Instead, service-life analysis will rely solely on a minimal amount of material collected on site and almost exclusively on non-destructive surface testing. In addition to the tests cited earlier, surface resistivity measurements were added to the program as a means to evaluate concrete properties without extracting cores. The combination of past data with on-site non-destructive testing generates more meaningful data that improves service-life predictions, compared to the initial coring program. This, in turn, leads to a better estimation of the different quay walls’ service-life, which helps managers optimize structure maintenance budgets and extend the service-life of key assets. More importantly, in the ever-present context of global warming, optimizing existing resources instead of building new ones fits perfectly in a sustainable approach to human activities.]]></description>
      <pubDate>Mon, 23 Jun 2025 15:53:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2559446</guid>
    </item>
    <item>
      <title>Modeling the Time-Dependent Variation of Road Salt Concentrations Using Analytical and Machine-Learning Approaches to Advance Service Life Predictions for Concrete Structures</title>
      <link>https://trid.trb.org/View/2452566</link>
      <description><![CDATA[The exposure of concrete structures to environmental and climatic conditions is detrimental to their durability. In northern climates, the key contributor to their degradation is corrosion of the reinforcing steel because of chloride ions originating from de-icing salts applied on roadways during the winter season. In consequence, a key input parameter for predicting the time to the initiation of corrosion for concrete elements is the time history of the concentration of chloride ions at their surfaces. To investigate this issue, a specialized mobile monitoring station was deployed along a roadway over several winter seasons to collect data on salting operations, weather conditions, and the temporal variation of chloride ion levels on the roadway. At first, salting operations were monitored, and then exploratory and machine-learning algorithms were applied to develop relationships between weather conditions, road conditions, and chloride ion concentrations. The first proposed model is based on the simulation modeling approach, while the second is based on the machine-learning XGBoost model. The findings demonstrate that both models can predict the variation of salt concentration on the road surface as a function of time after a salting operation. By accounting for the time dependency of surface chloride in service life models, more accurate predictions of corrosion initiation time are possible, since the rate of penetration of chloride ions is highly dependent on wetting/drying cycles throughout the winter.]]></description>
      <pubDate>Thu, 14 Nov 2024 09:49:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/2452566</guid>
    </item>
    <item>
      <title>Development of Approaches to Quantify Superloads and Their Impacts on the Iowa Road Infrastructure System</title>
      <link>https://trid.trb.org/View/2438068</link>
      <description><![CDATA[Superheavy loading vehicles, commonly referred to as superloads, exhibit non-standardized loading configurations along with high gross vehicle weights and axle loadings, all of which may cause unexpected distresses on Iowa road infrastructure systems compared to those caused by conventional vehicle class types categorized by the Federal Highway Administration. Superloads encompass various types of vehicles, including implements of husbandry and superheavy loads, prevalent in the Midwestern region of the United States. The determination of critical load factors affecting road damage due to superloads is intricate due to their non-standardized loading configurations and high loading capacities. This study developed methodologies to quantify superloads and evaluate their impact on Iowa’s road infrastructure, encompassing jointed plain concrete pavements, flexible pavements, and granular roads. It employed extensive mechanistic-based numerical analysis, life-cycle cost analysis, artificial intelligence (AI)-based predictive modeling, forensic investigations, field data analysis, and prototype tool development, with the research aimed at comprehensively evaluating superload impacts on various road types and structures. Through extensive numerical analyses, incorporating both mechanistic and empirical methodologies, critical findings regarding the effects of different superload types on pavement and granular road distress, associated treatment cost, and service life reduction emerged. Moreover, the Road Infrastructure-Superload Analysis Tool (RISAT) developed in this study has the potential to provide a user-friendly platform for engineers and planners to evaluate structural damages and associated treatment costs induced by superload traffic. The integration of AI-based predictive models into the RISAT enables users to input pavement and superload properties to obtain highly accurate predictions of pavement damages, treatment costs, and service life reductions. Incorporating field data into the RISAT also enhanced its reliability and applicability to pavement management practices, providing engineers and planners with valuable insights for informed decision-making regarding pavement design, maintenance, and rehabilitation strategies.]]></description>
      <pubDate>Fri, 11 Oct 2024 13:04:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2438068</guid>
    </item>
    <item>
      <title>Assessment of residual prestress in existing concrete bridges: The Kalix bridge</title>
      <link>https://trid.trb.org/View/2383883</link>
      <description><![CDATA[The direct socio-economic consequences of the deterioration of aging infrastructure systems have triggered a continuous process of revising and updating current design standards and guidelines for critical network components. Specifically, long-term degradation processes demand the analysis and evaluation of vital structural assets such as prestressed concrete bridges. It is crucial to develop theoretically consistent, user-friendly, and non-destructive methodologies that engineering professionals can employ to prevent and mitigate potential catastrophic outcomes during the service life of these bridges. This study provides a thorough review of the available testing methods employed over the years for prestressed concrete bridges and introduces a comprehensive framework for evaluating existing methods for residual prestress force assessment. Through a multi-criteria selection process, the three most feasible tests were designed and carried out on an existing 66-year-old balanced cantilever box girder bridge exposed to freezing temperatures that affected the instrumentation plan and test execution. Finally, predictive models compliant with standard codes were calibrated based on the experimental results and the life cycle loss of prestress forces was evaluated to assess relevant bounding intervals. Findings reveal limited on-site testing and discrepancies between calculated residual forces and predictions by standard codes. The saw cut method showed a 18% difference from the initial applied prestress according to the prestress protocol, suggesting the use of a cover meter and concrete modulus evaluation for improved accuracy. The strand cutting method resulted in a 14% difference, emphasizing the need for stress redistribution assessment. The second-order deflection method showed a 6% difference, indicating a focus on enhanced boundary conditions and thorough sensitivity analysis for future investigations.]]></description>
      <pubDate>Thu, 22 Aug 2024 15:08:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2383883</guid>
    </item>
    <item>
      <title>Concrete Deck Waterproofing Efficiency of the Confederation Bridge after 25 Years in Service</title>
      <link>https://trid.trb.org/View/2374124</link>
      <description><![CDATA[Road structures such as bridges and viaducts with a concrete deck must be protected from the aggressions of water often loaded with chloride ions due to the use of de-icing salts in winter maintenance. The lifespan of the waterproofing systems and the wearing courses covering them is usually 20 to 25 years compared to the design periods most often of a hundred years for this type of structure. These protection interventions are therefore very important to ensure the life of the structure without resorting to heavy and costly repairs. The high-performance concrete deck of the Confederation Bridge, linking the provinces of New Brunswick and Prince Edward Island, received at the end of its construction in 1997, the application of a multilayer waterproofing system. by fully mechanized applications at high speeds. This waterproofing-wearing course system practiced by the Vinci group for more than 35 years, has been evaluated by the National Research Council Canada (NRCC), by the British Board of Agreement (BBA) and has the various French accreditations. This article reviews the original construction stages as well as the periodic maintenance interventions to date, presents the results of performance monitoring tests of the waterproofing layers with measurements of the vertical gradients in chloride and sodium ion concentrations, measurements of watertightness under high pressures as well as the levels of oxidation of the different layers. Finally, the description of the validation trial for the renewal works of the wearing course scheduled for 2025 is summarized as well as the predictions of the complete life of the waterproofing system.]]></description>
      <pubDate>Thu, 13 Jun 2024 09:46:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2374124</guid>
    </item>
    <item>
      <title>Predicting Concrete Bridge Deck Deterioration: A Hyperparameter Optimization Approach</title>
      <link>https://trid.trb.org/View/2352958</link>
      <description><![CDATA[Concrete bridge decks are critical transportation infrastructure components where deterioration can compromise structural integrity and public safety. This study develops machine learning (ML) models using the National Bridge Inventory (NBI) to classify deck conditions and predict deterioration trajectories. Models were tested and trained on inspection records from over 28,786 bridges in Michigan over 23 years, from 1992 to 2015. Eleven approaches were evaluated after hyperparameter optimization, based on 10-fold cross-validation, including logistic regression, gradient boosting, AdaBoost, random forest, extra trees, K-nearest neighbors, naive Bayes, decision tree, LightGBM, CatBoost, and bagging. Model effectiveness was assessed using accuracy, recall, F1-score, and area under the curve. Results indicate the optimized CatBoost classifier achieved 96.66% testing accuracy in rating deck conditions. The incorporation of hyperparameter optimization has significantly enhanced the overall predictive performance of the models, ensuring robust and reliable deterioration forecasting. The research sheds light on crucial factors such as deck age, area, and average daily traffic, contributing to a more comprehensive understanding of the factors influencing bridge deck condition ratings. These insights inform preventative maintenance planning to extend service life. This work pioneers a data-driven framework to forecast concrete deterioration, empowering officials with precise predictions to optimize infrastructure management under budget constraints. The approach provides a promising decision-support tool for sustainable infrastructure.]]></description>
      <pubDate>Wed, 15 May 2024 10:11:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2352958</guid>
    </item>
    <item>
      <title>Behavior of basalt-FRP reinforced self-compacting concrete (SCC) deck slabs in a real bridge considering arching action</title>
      <link>https://trid.trb.org/View/2350968</link>
      <description><![CDATA[Fiber Reinforced Polymer (FRP) material is advocated for use in bridge structures to solve the corrosion and degradation problem of conventional steel reinforcements, thereby improving its durability and service life. Also, compared with ordinary concrete, self-compacting concrete (SCC) mixed with abundant industrial waste materials is expected to achieve sustainable development of concrete infrastructure. However, the research examining the performance of FRP reinforced SCC slabs in a real bridge is rather limited. This paper describes the application of basalt-FRP (BFRP) in a real bridge deck slab cast with low energy SCC. Since few studies have considered arching action on a real bridge deck slab, this paper aims at extending previous laboratory research using glass-FRP (GFRP) and BFRP reinforcement in in-plane restrained slabs to real bridge deck slabs. This study primarily investigates the serviceability behavior of real bridge deck slabs and utilizes the arching theory to predict their ultimate bearing capacity. The bearing capacities of real bridge deck slabs have been compared with the current specification requirements and the predictions considering arching theory. The test results indicate that a significantly low percentage of FRP reinforcement is possible in real bridge deck slabs due to the advantageous arching action.]]></description>
      <pubDate>Fri, 19 Apr 2024 09:48:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2350968</guid>
    </item>
    <item>
      <title>Increasing the Lifespan and Resiliency of Bridge Superstructure Concrete Through Durability-Based Performance Evaluation</title>
      <link>https://trid.trb.org/View/2344964</link>
      <description><![CDATA[This research project, aligned with the National Center for Infrastructure Transformation's (NCIT's) focus on "Improving Durability and Extending the Life of Transportation Infrastructure," seeks to do a durability-based performance evaluation of the selected bridge deck concrete mixes and identify the deficiencies (if any) and areas of improvements for extending service life. The project aims to extend a previously developed durability evaluation Tool (TxDOT Tool) to predict four pivotal durability indicators [e.g., estimation of optimum SCM dosage for mitigating ASR, shrinkage-based cracking potential prediction, measuring formation factor-based transport properties (diffusion and sorptivity) followed by corrosion and F-T durability predictions] followed by service life evaluation under ambient field (temperature/RH), chloride, and freeze-thaw exposure conditions during the mix design stage for the selected deck mixes. Traditional ASTM/AASHTO tests will also be conducted to validate whether the Tool-based durability predictions are acceptable instead of conducting long-term laboratory testing. With parallel efforts, the performance of the selected bridges will be examined by analyzing the NDT-based condition assessment data along with consideration of the accelerated testing data (i.e., deck deterioration progression driven by live-load-induced damage) obtained by the BEAST and ADTT and environmental conditions data, leading to the development of adjusted models for predicting future performance and remaining service life. The remaining service life based on these adjusted field models will then be used to adjust the Tool-based material-level service life predictions, which is expected to improve service life predictions during the mix design stage leading to the benefits of extending bridge deck lifespan, optimizing investments, reducing disruptions, and ensuring safer commutes for the public.]]></description>
      <pubDate>Wed, 28 Feb 2024 11:52:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2344964</guid>
    </item>
    <item>
      <title>Application of a Sequence-Free Iterative Structural Identification Framework for Reserve Capacity Estimation of a Steel-Concrete Composite Bridge</title>
      <link>https://trid.trb.org/View/1994668</link>
      <description><![CDATA[Most civil engineering structures are designed using justifiably conservative models with the goal of achieving life-safety. The use of conservative models during design and safe construction practices creates reserve capacity enabling structures to last well beyond their design life. Understanding structural behaviour can enhance the effectiveness of asset-management tasks such as retrofit or replacement of these structures. With advances in sensing and computing technology, it is now possible to interpret vast amounts of measurement data to evaluate structural performance. In this paper, the application of a sequence-free iterative structural identification framework on a steel-concrete composite bridge is presented. The iterative nature of decision-making is illustrated through varying conditions during the service life of the bridge, in this case increased traffic intensity. The engineer utilises new information as it becomes available to update knowledge of structural behaviour and thus update predictions of reserve capacity.]]></description>
      <pubDate>Mon, 30 Jan 2023 16:47:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/1994668</guid>
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