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X-WR-CALNAME:National Center for Transportation Infrastructure Durability & Life-Extension (TriDurLE)
X-ORIGINAL-URL:https://tridurle.wsu.edu
X-WR-CALDESC:Events for National Center for Transportation Infrastructure Durability & Life-Extension (TriDurLE)
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220901T110000
DTEND;TZID=America/Los_Angeles:20220901T120000
DTSTAMP:20260407T130434
CREATED:20220828T190413Z
LAST-MODIFIED:20221016T090648Z
UID:3231-1662030000-1662033600@tridurle.wsu.edu
SUMMARY:Rock Failure Process Analysis
DESCRIPTION:Presentation\nRock Failure Process Analysis \nA major difficulty in studying the fracture mechanisms for rock subjected to various loads is the fact that rock is a natural\, composite material which is Discontinuous\, Inhomogeneous\, Anisotropic and Not Elastic (DIANE). It is not possible to analytically examine and evaluate the mechanical behavior of a DIANE rock exhibiting an unstable failure process. The problem becomes more intractable if gas or fluid\, as in coal and gas outbursts\, hydraulic fracturing\, etc.\, is involved. In most of the cases\, analytical models have to be simplified\, ignoring important factors influencing the mechanical behavior of rock. Although much progress has been made and numerical models have provided techniques to solve fracture problems in rock\, few approaches are capable of capturing fracture initiation\, propagation and coalescence and hence of investigating fracture-induced progressive failure of rock in more realistic manner. \nNumerical models that simulate the detailed fracturing sequence are thus useful for understanding rock failure mechanisms on both the small and large scales. In this short lecture\, a numerical code\, the Rock Failure Process Analysis (RFPA) model\, is firstly introduced. Then\, examples are presented in the lecture illustrating how the overall macroscopic response of a brittle rock under different loading conditions can be simulated by integration of the interactions between smaller-scale elements. \nSpeaker\n\nChunan Tang\, PhD\, Chair Professor\nDalian University of Technology \nDr. Tang\, as a chair Professor (funded by Cheung Kong Scholar Programme from State Education Ministry)\, is the Director of the Center for Rock Instability and Seismisity Research (CRISR) and the Chair of Deep Underground Engineering Research Center of Dalian University of Technology. He was also the Vice President of the Chinese Society of Rock Mechanics. He got his Ph.D in 1988. In 1991\, he continued his post-doctoral work in Imperial College\, London\, UK (worked with Prof. J.A.Hudson). Then\, as an academic visitor\, he had lots of experience working in Canada\, Sweden\, Singapore\, Switzerland and Hong Kong. He leads several major research projects in rock mechanics and is the chief scientist for a National 973 program for fundamental research. So far\, he has published more than 300 technical papers on rock failure mechanisms and civil engineering\, and is the author of five Chinese books of rock mechanics and the principle author of “Rock Failure Mechanism” published by CRC.
URL:https://tridurle.wsu.edu/event/rock-failure-process-analysis/
ORGANIZER;CN="TriDurLE":MAILTO:jialuo.he@wsu.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221025T110000
DTEND;TZID=America/Los_Angeles:20221025T120000
DTSTAMP:20260407T130434
CREATED:20221016T085829Z
LAST-MODIFIED:20221128T222355Z
UID:3302-1666695600-1666699200@tridurle.wsu.edu
SUMMARY:Long-term Bond Characteristics of the Interface Between Substrate and Shotcrete Overlay
DESCRIPTION:Presentation\nLong-term Bond Characteristics of the Interface Between Substrate and Shotcrete Overlay \nShotcrete is becoming popular for vertical and overhead applications where conventional formwork and repairs are difficult and costly. However\, the substrate and the shotcrete overlay interface can be vulnerable\, and the bond properties in this region are not well understood. Furthermore\, the interface bond could be adversely affected by long-term freeze-thaw weathering in northern states leading to debonding from the existing substrate and corrosion of rebars. Hence\, characterization of the shotcrete-substrate interface bonds is critical for the performance evaluation of shotcrete construction. To this goal\, this study evaluated the shotcrete-concrete interface bond using four representative substrate surface preparation methods: chipped\, pressure-washed\, sandblasted\, and as-cast\, under three different loading conditions: tensile\, shear\, and Mode-II fracture. The study also investigated the long-term freeze-thaw durability of these bonds and introduced a probabilistic damage model to predict their service lives. The estimated surface texture depth and bond behavior are also correlated using laser texture scans of the substrate. Recommendations are made in terms of specifying the substrate preparation and interface bond. \nSpeaker\n\nHaifang Wen\, PhD\, PE Associate Professor\nWashington State University \nDr. Haifang Wen is currently an Associate Professor and Director of Washington Center for Asphalt Technology (AASHTO Accredited) at Department of Civil and Environmental Engineering of Washington State University and graduate coordinator of Geotechnical and Transportation Group. He teaches and researches on infrastructure materials and design. He has published more than 70 journal papers and numerous conference papers. He has made significant contribution to the utilization of sustainable infrastructure materials for construction\, based on work on NCHRP\, NSF\, FHWA\, DOTs\, local governments and industry. His research on the recycled concrete was recognized as AASHTO High Value Research Projects. A few of his papers are selected as practice-ready papers “which made a contribution to current or future problems or issue for practitioners.” He is serving as an editorial board member of International Journal of Geotechnical Engineering and Geological Engineering. He is also currently serving as a member of NCHRP 01-62\, ASCE Committee and FHWA’s STIC Committee. He has served on numerous TRB committees and NCHRP panels. He received Outstanding Faculty Researcher Award by the College of Engineering and Architecture of Washington State University and Outstanding Mentor Award. He is elected as a Fellow of ASCE in 2021.
URL:https://tridurle.wsu.edu/event/long-term-bond-characteristics-of-the-interface-between-substrate-and-shotcrete-overlay/
ORGANIZER;CN="TriDurLE":MAILTO:jialuo.he@wsu.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230224T090000
DTEND;TZID=America/Los_Angeles:20230224T100000
DTSTAMP:20260407T130434
CREATED:20230213T085616Z
LAST-MODIFIED:20230306T043644Z
UID:3418-1677229200-1677232800@tridurle.wsu.edu
SUMMARY:Decryption of Concrete Durability Deterioration Mechanisms Using Concrete Petrography and Image Analysis
DESCRIPTION:Presentation\nDecryption of Concrete Durability Deterioration Mechanisms Using Concrete Petrography and Image Analysis \nWhile good workability and mechanical performance are critical for the construction of transportation infrastructure\, the stakeholders also seek durable concrete that can last a desired service life without significant deterioration. Concrete durability comes in different forms of complex processes that commonly involve interactions between external substances (e.g.\, water\, chloride\, sulfate\, etc.) and internal material properties (e.g.\, aggregate types\, air-void system\, paste components and microstructure). For instance\, the ingress of chloride-based deicers can deteriorate concrete and facilitate steel reinforcement corrosion\, and the absorbed water in concrete can cause freeze-thaw damage in cold regions. Concrete petrography\, combined with image analysis and other techniques\, provides a powerful tool to diagnose durability related concrete deteriorations. This presentation will provide a discussion of different projects that use concrete petrography and image analysis to investigate durability mechanisms. \nSpeaker\n\nChunyu Qiao\, PhD\, Senior Associate\nWiss\, Janney\, Elstner Associates \nDr. Chunyu Qiao is a Senior Associate and Petrographer at Wiss\, Janney\, Elstner Associates. He is an associate member of ACI Committees 201 (Concrete Durability) and 365 (Service Life Prediction). He is a junior editorial board member for Journal of Infrastructure Preservation and Resilience. Dr. Qiao received his PhD from University of Science and Technology Beijing\, China. He was a visiting scholar at Purdue University from 2013 to 2015 and a postdoctoral researcher at Oregon State University from 2016 to 2018. His research interests include microscopy of cementitious materials\, transport properties of cementitious materials\, chemical admixtures\, and concrete durability. \nView the Recording of this Webinar
URL:https://tridurle.wsu.edu/event/decryption-of-concrete-durability-deterioration-mechanisms-using-concrete-petrography-and-image-analysis/
LOCATION:Webinar
ORGANIZER;CN="TriDurLE":MAILTO:jialuo.he@wsu.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230428T100000
DTEND;TZID=America/Los_Angeles:20230428T110000
DTSTAMP:20260407T130434
CREATED:20230420T062524Z
LAST-MODIFIED:20230420T062641Z
UID:3446-1682676000-1682679600@tridurle.wsu.edu
SUMMARY:Developing Enhanced Performance Curves of ITD Asphalt Pavements by Mining the Historical Data
DESCRIPTION:Presentation\nDeveloping Enhanced Performance Curves of ITD Asphalt Pavements by Mining the Historical Data \nThis presentation introduces work of a recently finished project aiming to develop reliable and realistic and enhanced performance curves for Idaho Transportation Department (ITD) asphalt pavements by mining the historical data. To this end\, the project reviewed currently applied predictive models in terms of their forms\, applications\, advantages and limitations. Besides\, a practitioner survey was conducted on the insights and experiences of users on the existing models for the basic qualities of a predictive model should have to be applied in practice. According to characteristics of historical data collected by ITD\, machine learning (ML) models of different types such as neural networks (NN) and gene expression programming (GEP) were utilized and compared with traditional models such as mechanistic-empirical models and piecewise linear regression models. In addition to model accuracy\, this project paid attention to basic applicability of predictive models\, statistical methods were utilized to check the stability\, robustness\, sensitivity\, etc. of constructed models before application. \nSpeaker\n\nYong Deng\, PhD\, Research Assistant Professor\nWashington State University \nDr. Yong Deng is currently a research assistant professor of the Department of Civil and Environmental Engineering at Washington State University (WSU) and a researcher at the National Center for Transportation Infrastructure Preservation and Life-Extension (TriDurLE). He obtained his Ph.D. and M.S. degrees in Civil Engineering from Texas A&M University in 2017 and 2020. His current research focus and interests are finite element (FE) model updating of pavement materials and structures\, data-driven models for pavement performance evaluation and prediction\, applications of artificial intelligence algorithms\, etc. \nRegister Here
URL:https://tridurle.wsu.edu/event/developing-enhanced-performance-curves-of-itd-asphalt-pavements-by-mining-the-historical-data/
ORGANIZER;CN="TriDurLE":MAILTO:jialuo.he@wsu.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230505T100000
DTEND;TZID=America/Los_Angeles:20230505T110000
DTSTAMP:20260407T130434
CREATED:20230421T051658Z
LAST-MODIFIED:20230421T051938Z
UID:3451-1683280800-1683284400@tridurle.wsu.edu
SUMMARY:Evolutionary Characteristics of Microstructural Hydration and Chloride Diffusion in UHPC
DESCRIPTION:Presentation\nEvolutionary Characteristics of Microstructural Hydration and Chloride Diffusion in UHPC \nThis webinar presents the evolutionary characteristics of microstructural hydration and chloride migration in ultra-high performance concrete (UHPC). The physicochemical interactions of constituents are simulated in conjunction with a random walk algorithm. The computed responses of the UHPC mixtures at a compressive strength varying from f’c = 149 MPa to 164 MPa are comparatively evaluated for a curing period of 28 days against those of ordinary concrete involving f’c = 30 MPa to 45 MPa. When the hydration of cementitious pastes proceeds\, the quantity of silicates becomes larger alongside irregularly dispersed byproducts (calcium silica hydrate\, C-S-H\, and calcium hydroxide\, CH). Owing to the formation of pozzolanic C-S-H consuming CH\, the silicate reactions of UHPC are less than the reactions of the ordinary concrete. The implications of tricalcium silicate (C3S) are notable for the early-age strength gain of UHPC in comparison with its dicalcium silicate (C2S) counterpart. The matured pozzolanic reactions and invariable packing density of UHPC are responsible for preserving the proportion of silica fume in the mixtures. While the volumetric increase of conventional C-S-H is not controlled by water-binder ratios of the ordinary concrete and UHPC within 2 days of hydration\, the extent of the pozzolanic C-S-H is tantamount to that of the conventional C-S-H at 28 days. Relative to UHPC\, the ordinary concrete releases more heat caused by exothermic reactions that are a function of saturated pores and silica fume. Regarding corrosion durability\, the chloride contents of a bridge deck cast with the ordinary concrete exceed the content of a deck with UHPC. As part of technology transfer\, the notion of performance-based design applies and practice guidelines are suggested. \nSpeaker\n\nYail Jimmy Kim\, PhD\, PE\, F.ACI\nUniversity of Coloroda Denver \nDr. Yail Jimmy Kim is President of the Bridge Engineering Institute\, An International Technical Society\, a Professor in the Department of Civil Engineering at the University of Colorado Denver\, Denver\, CO\, and Site Director of the National Center for Transportation Infrastructure Durability & Life-Extension (TriDurLE). He is Chair of American Concrete Institute (ACI) Subcommittee 440I (FRP-Prestressed Concrete) and past Chair of ACI Committee 345 (Concrete Bridge Construction and Preservation). He is a member of ACI Committees 342 (Evaluation of Concrete Bridges and Bridge Elements)\, 377 (Performance-Based Structural Integrity & Resilience of Concrete Structures)\, 440 (Fiber Reinforced Polymer Reinforcement)\, and Joint ACI-ASCE Committee 343 (Concrete Bridge Design). He has received the Chester Paul Siess Award for Excellence in Structural Research in 2019. His research interests encompass advanced composite materials for rehabilitation\, structural informatics\, complex systems\, and science-based structural engineering\, including statistical\, interfacial\, and quantum physics. \nJun Wang\, PhD\, Postdoctoral Fellow\nUniversity of Coloroda Denver \nDr. Jun Wang is a Post-Doctoral Fellow in the Department of Civil Engineering at the University of Colorado Denver\, Denver\, CO. She has received BS and MS from Northeast Forestry University and the University of Colorado Denver\, respectively. Her research interest includes multi-object interaction\, advanced modeling\, and concrete structures. \nRegister Here
URL:https://tridurle.wsu.edu/event/evolutionary-characteristics-of-microstructural-hydration-and-chloride-diffusion-in-uhpc/
ORGANIZER;CN="TriDurLE":MAILTO:jialuo.he@wsu.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230926T130000
DTEND;TZID=America/Los_Angeles:20230926T140000
DTSTAMP:20260407T130434
CREATED:20230824T191744Z
LAST-MODIFIED:20230824T195652Z
UID:3505-1695733200-1695736800@tridurle.wsu.edu
SUMMARY:Quantifying and Reducing Uncertainty in Resilience Assessment of Transportation Networks Using Dynamic Bayesian Network
DESCRIPTION:Presentation\nQuantifying and Reducing Uncertainty in Resilience Assessment of Transportation Networks Using Dynamic Bayesian Network \nThe Nation’s transportation systems are complex and are some of the highest-valued and largest public assets in the United States. As a result of repeated natural hazards and their significant impact on transportation functionality and socio-economic health of communities\, transportation resilience has gained increasing attention in recent years. Previous studies on transportation resilience have heavily emphasized network functionality during and/or following a scenario hazard event by implicitly assuming that sufficient knowledge of structural capacity and environmental/service conditions is available at the time of an extreme event. However\, such assumptions often fail to consider uncertainties that arise when an extreme hazard event occurs in the future. Thus\, it is essential to quantify and reduce uncertainties to better prepare for extreme events and accurately assess transportation resilience. To this end\, this study proposes a dynamic Bayesian network-based resilience assessment model for a large-scale roadway network that can explicitly quantify uncertainties in all phases of the assessment and investigate the role of inspection and monitoring programs in uncertainty reduction. Specifically\, the significance of data reliability is investigated through a sensitivity analysis\, where various sets of data having different reliability are used in updating system resilience. To evaluate the effectiveness of the model\, a benchmark problem involving a highway network in South Carolina\, USA is utilized\, showcasing the systematic quantification and reduction of uncertainties in the proposed model. The benchmark problem result shows that incorporating monitoring and inspection data on important variables could improve the accuracy of predicting the seismic resilience of the network. It also suggests the need to consider equipment reliability when designing monitoring and inspection programs. With the recent development of a wide range of monitoring and inspection techniques\, including non-destructive testing\, health monitoring equipment\, satellite imagery\, LiDAR\, etc.\, these findings can be useful in assisting transportation managers in identifying necessary equipment reliability levels and prioritizing inspection and monitoring efforts. \nSpeaker\n\nJi Yun Lee\, PhD\nWashington State University \nDr. Ji Yun Lee is an Assistant Professor in the Department of Civil and Environmental Engineering at Washington State University (WSU). Prior to joining WSU in 2017\, Dr. Lee served as a Postdoctoral Scholar in the Department of Civil and Environmental Engineering at the University of California\, Los Angeles (2016-2017) and a Visiting Faculty in the Department of Civil\, Environmental and Construction Engineering at the University of Central Florida (2015-2016). She received her Ph.D. (2015) in Civil Engineering from the Georgia Institute of Technology\, her M.S. (2011) in Civil Engineering from Stanford University\, and her B.S. (2009) in Architectural Engineering from Korea University. \nRegister Here
URL:https://tridurle.wsu.edu/event/quantifying-and-reducing-uncertainty-in-resilience-assessment-of-transportation-networks-using-dynamic-bayesian-network/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240126T140000
DTEND;TZID=America/Los_Angeles:20240126T150000
DTSTAMP:20260407T130434
CREATED:20240125T181312Z
LAST-MODIFIED:20240916T185839Z
UID:3603-1706277600-1706281200@tridurle.wsu.edu
SUMMARY:Seismic Performance of Corroded Precast Concrete Columns
DESCRIPTION:Presentation\nSeismic Performance of Corroded Precast Concrete Columns \nAccelerated Bridge Construction (ABC) results in bridges that are assembled using precast concrete elements built with better quality in significantly shorter time than cast-in-place (CIP) bridges. Despite these advantages\, ABC bridges are vulnerable to corrosion\, a phenomenon observed in CIP bridges as well. Corrosion adversely affects the lateral force and axial compression capacity of reinforced concrete columns\, posing a concern for the structural integrity of both bridge types. The columns tested in this study include: (i) a control specimen with no corrosion; (ii) a specimen exhibiting moderate corrosion (with a target 10% loss in mass of longitudinal steel reinforcement); and (iii) a specimen displaying severe corrosion (with a target 25% loss). The impressed current technique was used for accelerating corrosion of the specimens in the laboratory. A numerical model was developed to calibrate the physical experiments of the control and corroded specimens. The numerical model could predict the experimental drift ratio with satisfactory accuracy up to bar fracture. The objective of this study is to quantify the decrease in lateral force and drift ratio capacity observed in corroded reinforced concrete columns constructed through ABC methods under seismic loads. In this context the deterioration due to corrosion and subsequent earthquake damage can be considered as multiple hazards. The research findings emphasize a significant decline in the lateral displacement capacity of reinforced concrete columns subjected to moderate and severe corrosion. The numerical model was subsequently used to perform parametric studies for similar columns with higher levels of corrosion deterioration. \nSpeaker\n\nChris P. Pantelides\, PhD\, SE\, F. ASCE\, F. ACI\nUniversity of Utah \nDr. Chris P. Pantelides is a Professor in the Department of Civil Engineering at the University of Utah and Site Director of the National Center for Transportation Infrastructure Durability & Life-Extension (TriDurLE). He is a member of TRB AFF50 Committee (Seismic Design and Performance of Bridges)\, ACI Committee 374 (Performance-Based Seismic Design of Concrete Buildings)\, and ACI-ASCE joint Committee 352 (Joints and Connections in Monolithic Concrete Structures). He is the Fellow of ACI and ASCE. Dr. Pantelides received his PhD and MS in Civil Engineering from University of Missouri\, Rolla. His research interests include seismic design\, evaluation\, and rehabilitation of reinforced concrete building and bridge construction.
URL:https://tridurle.wsu.edu/event/seismic-performance-of-corroded-precast-concrete-columns/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240927T100000
DTEND;TZID=America/Los_Angeles:20240927T110000
DTSTAMP:20260407T130434
CREATED:20240916T190727Z
LAST-MODIFIED:20240916T190727Z
UID:3660-1727431200-1727434800@tridurle.wsu.edu
SUMMARY:Meta-learning-based surrogate modeling and system digital twin for life-cycle management of infrastructure systems
DESCRIPTION:Presentation\nMeta-learning-based surrogate modeling and system digital twin for life-cycle management of infrastructure systems \nLife-cycle management (LCM) is an effective tool to balance structural safety and cost. With recent advances in computational power and artificial intelligence\, applications of LCM can be extended from single structures and assets to complex networks and systems. This presentation will introduce two computational methods to enable this transformation. First\, meta-learning-based surrogate modeling is a framework to transfer knowledge from existing modeling tasks to new and similar tasks. This framework is suitable for efficient reliability analysis and optimization at a community level. It has been applied to climate change adaptation and fleet management. Second\, performance-oriented system digital twin (SDT) is a user-centric method to establish custom SDTs based on user’s modeling needs and available data sources. Based on Bayesian network\, the SDT can fuse the data and the complex model of the system. It has been applied to data-driven life-cycle risk assessment of bridge networks in Miami-Dade County. In the future\, with further development of these two computational methods\, LCM can help us move towards a smart\, sustainable\, and resilient community. \nSpeaker\n\nMinghui Cheng\, PhD\nUniversity of Miami \nDr. Minghui Cheng is an assistant professor jointly appointed by the Department of Civil & Architectural Engineering and School of Architecture at the University of Miami. Previously\, he was a postdoctoral associate at Systems Engineering\, Cornell University. He obtained his Ph.D. in Structural Engineering from Lehigh University in 2021 and his B.E. in Civil Engineering at Hunan University\, China\, in 2016. His research focuses on the system digital twin of infrastructure systems and sustainability-informed life-cycle management with an emphasis on surrogate modeling\, optimization\, and machine learning. \nRegister
URL:https://tridurle.wsu.edu/event/meta-learning-based-surrogate-modeling-and-system-digital-twin-for-life-cycle-management-of-infrastructure-systems/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20241203T113000
DTEND;TZID=America/Los_Angeles:20241203T123000
DTSTAMP:20260407T130434
CREATED:20241121T183829Z
LAST-MODIFIED:20241202T001314Z
UID:3717-1733225400-1733229000@tridurle.wsu.edu
SUMMARY:Forensic analysis of outdoor exposed legacy samples undergoing corrosion propagation
DESCRIPTION:Presentation\nForensic analysis of outdoor exposed legacy samples undergoing corrosion propagation \nForensic analysis was performed on outdoor samples that showed cracks. One or more rebars were removed from the selected samples. The outdoor samples have been exposed to seawater wet/dry cycles since 1994. In some cases\, the three top rebars were removed\, in other cases only one rebar or two rebars were removed. The surface condition upon rebar exposure was recorded by photographing the sample\, then the rebars were cleaned by sandblasting the rebars with walnut sand. The cross-section loss as a function of length was measured by using a caliper with conical tip. The pitting factor was calculated using only the sections that showed corrosion\, i.e.\, the non-corroding sections were not included to calculate the average section loss. The percentage average mass loss (η) values were estimated by using the mass of the rebar section rebar embedded with respect to the mass a non-corroding rebar of the same length. The location of the corroding section was not always at the center\, in some cases multiple sections were found to be corroding. In some instances\, a large corrosion spot (likely by coalescing several smaller ones) was observed. Electrochemical measurements were performed\, and typically a set of measurements was performed prior to terminating a rebar. Correlations of rebar potential vs. η\, corrosion current density vs. η and resistivity vs. η were prepared and included in here. There is quite a bit of scatter on these three plots suggesting that some rebars had been corroding for a longer time. \nSpeaker\n\nFrancisco J. Presuel-Moreno\, PhD\nFlorida Atlantic University \nDr. Francisco J. Presuel-Moreno is a professor in the Ocean and Mechanical Engineering department at Florida Atlantic University. Dr. Presuel received his PhD from University of South Florida. Dr. Presuel has been conducting research related to concrete durability and topics related to corrosion of reinforcing steel embedded in concrete for 30 years. \nRegister
URL:https://tridurle.wsu.edu/event/forensic-analysis-of-outdoor-exposed-legacy-samples-undergoing-corrosion-propagation/
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