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Open access publications by faculty, postdocs, and graduate students in the Department of Civil and Environmental Engineering.

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    A Preliminary Study on the Quantitative Assessment of Building Information Modeling and Virtual Reality in Supporting Mechanical, Electrical, and Plumbing Plan Comprehension in AECO Education
    (Cureus Journal of Engineering, 2025-03-31) Aljagoub, Dyala; Na, Ri
    Mechanical, Electrical, and Plumbing (MEP) systems are complex, often leading to conflicts and cost overruns. Yet, limited literature explores how to improve MEP plan reading in the classroom. The authors sought to fill the limited research gap through a pilot quantitative comparative study. Therefore, the effectiveness of Building Information Modeling-Virtual Reality (BIM-VR) implementation in a classroom to enhance MEP plan reading comprehension and spatial cognition was investigated, as many students struggle to interpret 2D plans due to their intricate nature. BIM-VR models were developed, and a group of students with limited prior-experience were chosen to minimize prior knowledge biases. Participants were randomly assigned to control and test groups and tested in two phases. The control group was provided 2D plans only, while the test group was granted access to BIM-VR models during the post-phase. Pre- and post-quizzes and a questionnaire were used to evaluate BIM-VR effectiveness, employing appropriate statistical methods. The test group performed similarly in the pre-phase and outperformed the control group in the post-phase. The questionnaire results indicated enhanced visualization, error detection, and a positive experience. The study findings promoted the need for academia to adopt BIM-VR, specifically within the context of MEP plan reading, to prepare students for industry demands.
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    Bursting Pipes and Boiling Snow: Disaster Impacts and Adaptations in the 2021 Texas Power Crisis from the Lens of Short-Form Social Media Videos
    (Journal of Disaster Studies, 2025-02-05) Schlein, Alexa; Wang, Shengzhi; Remaker, Valerie; Tie, Ziyun; Haughey, Melinda M.; Davidson, Rachel A.; Kendra, James
    This article explores how short-form social media videos can contribute to the understanding of how people are affected by and adapt to crisis events. Applying a grounded approach, we analyzed 174 crisis-related videos shared by local Twitter users during the 2021 Texas storm and power crisis to determine how crisis impacts and adaptations are documented and portrayed. Our data include fifty-six cross-posted videos from third-party platforms, of which forty-one were from TikTok. We show that short-form videos are capable of providing wide-ranging insights into the impacts of crisis events and how people adapt to them. We provide examples with rich detail to illustrate how content creators documented the effects of their adaptations and their downstream effects. Our data include various adaptations that address the need for water, food, and shelter/warmth. Furthermore, we identify how people coped with the crisis through entertaining and humorous videos. We discovered that valuable information about crisis impacts and adaptations often appeared in the periphery of the main focus of videos. We also comment on what was missing in the social media record (e.g., more mundane impacts and adaptations), contributing to understandings about the contours and limitations of social media content in a crisis context.
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    Trust, Traffic, and Contemporary Evacuation Barriers in Hurricane Ida
    (Journal of Disaster Studies, 2025-02-05) Trivedi, Jennifer; DeYoung, Sarah; Anyidoho, Prosper; Porada, Maria; Wachtendorf, Tricia; Davidson, Rachel; Nozick, Linda
    In hurricane evacuation decision-making research, it is critical to understand complex influences and larger processes at work in shaping the decisions and experiences of people and communities in affected areas and evacuation zones. Hurricane Ida made landfall in Louisiana in 2021, in the midst of the COVID-19 pandemic, ongoing economic problems, and disruptions to trust in political officials. Gulf Coast residents made decisions about if and when to evacuate in this context. We use a framework that emphasizes the social causes of evacuation decision making, including optimism bias, compounding disasters, and situational factors. Results show that during Ida residents were navigating the relative risks, varied perceptions, and previous experiences with other disasters, compounding disasters, traffic, work and school demands, and long-term systemic problems. Understanding this reality more deeply and with a more nuanced approach to the complexities of how such perceptions and experiences affect one another, rather than viewing evacuation as a "yes or no" decision, is essential to improving disaster policies and evacuation responses, as well as our knowledge of both. This article delves deeply into the barriers to evacuation still existing in the United States, despite efforts to improve these procedures over time, particularly after Hurricane Katrina.
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    Assessing the Impact of Sand-Induced Ballast Fouling on Track Stiffness and Settlement
    (Geotechnics, 2025-01-31) Alzhrani, Mohammed A.; Palese, Joseph W.; Zarembski, Allan M.
    This study investigates the impact of sand-induced ballast fouling on railway track performance, focusing on track stiffness (modulus), settlement, and overall degradation. The research utilized an 18-cubic-foot ballast box designed to replicate real-world track conditions under controlled laboratory settings. A key focus was quantifying voids within clean ballast to establish baseline characteristics, which provided a foundation for evaluating the effects of sand fouling. Two distinct test series were conducted to comprehensively analyze track behavior. The first series investigated pre-existing fouling by thoroughly mixing sand into the ballast to achieve uniform fouling levels. The second series simulated natural fouling processes by progressively adding sand from the top of the ballast layer, mimicking real-world conditions such as those in sandy environments. These methodologies allowed for detailed analysis of changes in track stiffness, deflection, and settlement under varying fouling levels. The findings demonstrate a direct correlation between increasing sand fouling levels and heightened track stiffness and settlement. Dynamic load testing revealed that as void spaces were filled with sand, the track’s flexibility and drainage capacity was significantly compromised, leading to accelerated degradation of track geometry. Settlement patterns and deflection data provided critical insights into how fouling adversely affects track performance. These results contribute significantly to understanding the broader implications of sand-induced fouling on track degradation, offering valuable insights for railway maintenance and design improvements. By integrating void analysis, test series data, and load-deflection relationships, this study provides actionable recommendations for enhancing railway infrastructure resilience and optimizing maintenance strategies in sandy terrains.
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    Toward practical guidelines for infrared thermography of concrete bridge decks: A preliminary investigation across U.S. climate zones
    (Case Studies in Construction Materials, 2025-03-17) Aljagoub, Dyala; Na, Ri; Cheng, Chongsheng
    Delamination detection in concrete bridge decks employing IRT relies heavily on selecting favorable environmental conditions to produce the desired detection accuracy. Many studies have focused on improving IRT detection by optimizing the data collection or analysis techniques. However, there exists limited and conflicting literature on recommended data collection times. Therefore, this study evaluated favorable detection windows across the five climate zones in the U.S. using field and numerical simulation data. First, the field data was collected on two separate days to verify the numerical simulation results by developing a simulation with identical conditions. The verified numerical simulation results indicated that the simulations were representative of real-life detection patterns. So, numerical simulations for each zone and season were developed. The data collected from the numerical simulations were analyzed using the Sørensen–Dice Coefficient (SDC), comparing the known delamination location (ground-truth) to the predicted delamination through a threshold-based segmentation technique to predict favorable detection windows based on obtained accuracy. The contributions of this preliminary study are as follows: (1) a report of favorable detection windows per zone and season, which, in turn, potentially improves detection accuracy; The favorable conservative reported window for each zone was determined to be from noon to early evening, (2) provide a replicable numerical simulation process, enabling interested agencies to utilize the approach to conduct internal studies to evaluate favorable detection windows for their specific location, and (3) statistically evaluate the combined effects of ambient temperature and solar irradiance values and patterns on detection accuracy. Highlights • Uses Infrared Thermography to predict best delamination detection times across U.S. • Reported times aim to improve detection accuracy. • Statistically evaluates effect of temperature and solar irradiance on detection. • Replicable, validated method to predict detection windows in any setting or region. • Leverages IRT for cost-effective, efficient, and accurate delamination detection.
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    Determination of Bridge Elements’ Weights Using the Random Forest Algorithm
    (Journal of Performance of Constructed Facilities, 2024-12-14) Abiona, Qozeem O.; Head, Monique H.
    Significant bridge inspection data has been collected over the years at the component and element level to improve management practices in the United States. A widely adopted systematic approach to correlate the weight or importance of the bridge elements to the overall bridge performance, which influences the maintenance, repair, and replacement (MRR) schedule and resource allocation for structures, does not exist given the existing data. Some transportation agencies use a cost-based approach to assign weights to bridge elements, which can be in terms of the loss accrued during downtime or the amount needed for the replacement of the element. However, this approach does not consider the bridge elements’ structural relevance to the overall performance of the bridge. This study proposes a novel framework to synthesize component and element-level bridge data to showcase their relationship using the random forest algorithm, which is essentially an ensemble of decision trees to evaluate the importance of different elements relative to the overall condition of the bridge. The analysis focused on eight bridge design types predominant in Delaware, Maryland, Pennsylvania, Virginia, and West Virginia, and analyzed 104,699 bridge records consisting of the condition rating and element-level data from the National Bridge Inventory (NBI). The random forest algorithm showed that bridge elements’ weight (or importance) is not constant as implied by the cost-based approach; rather, bridge elements’ weight varies based on their relevance to the bridge’s structural performance. The resultant bridge elements’ weight, which is the element weight multiplied by the component weight, can be used to improve the existing Bridge Health Index (BHI) equation found in the Manual for Bridge Evaluation (MBE) using this data-driven approach. Given more available component and element-level bridge data, this formulation provides a framework for transportation personnel to determine which set of bridge elements to prioritize in their maintenance actions and ascertain if the elements receiving the highest priority in the MRR schedule and budget allocation are also the same set of elements that bridge inspection reports regard as needing attention.
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    Numerical and experimental study on the evolution of thermal contrast for infrared detection of debonding in concrete filled steel tubular structure
    (Applied Thermal Engineering, 2025-01-15) Cai, Haonan; Cheng, Chongsheng; Wang, Lilin; Zhang, Hong; Zhou, Jianting; Na, Ri; Wu, Bo
    Debonding in Concrete-Filled Steel Tubes (CFST) can reduce bridges’ overall load-bearing capacity and thus threaten the bridge’s structural safety. Infrared thermography (IRT) is widely used for CFST debonding detection due to its efficiency and non-contact advantages. However, IRT is often affected by complex environmental factors and faces challenges in achieving quantitative evaluation only based on thermal contrast. This study aims to reveal the relationship between thermal indicators and thermal contrast through numerical and experimental investigations of CFST debonding under varied mimicked climatic conditions. A 3-dimensional (3-D) heat transfer transient model of CFST is established to simulate the evolution of thermal contrast of debonding under different daily temperature variations and seasonal solar irradiance. Based on the finite element analysis results, the internal interface heat flux is found as a strong linear indicator correlating the thermal contrast to environmental factors. Model experiments then were conducted to verify the validity of this indicator. Finally, an infrared evaluation method for CFST debonding is proposed, which can linearly quantify the relationships among debonding sizes, environmental factors, and thermal contrast. Highlights • Developed a simulation model for CFST (Concrete-Filled Steel Tube) debonding. • Clarified the relationship between thermal contrast and thermal indicators. • Identified key factors influencing thermal contrast in CFST debonding regions. • Proposed an infrared evaluation method for detecting CFST debonding.
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    Can visits to certain businesses help predict evacuation decisions in real time?
    (Natural Hazards, 2025-01-06) Anyidoho, Prosper K.; Davidson, Rachel A.; Nozick, Linda K.; Trivedi, Jennifer; DeYoung, Sarah E.; Wachtendorf, Tricia
    This study aims to help understand and predict evacuation behavior by examining the relationship between evacuation decisions and visits to certain businesses using smartphone location and point of interest (POI) data collected across three hurricanes—Dorian (2019), Ida (2021), and Ian (2022)—for residents in voluntary and mandatory evacuation zones. Results from these data suggest residents visit POIs as part of preparatory activities before a hurricane impacts land. Statistical tests suggest that POI visits can be used as precursor signals for predicting evacuations in real time. Specifically, people are more likely to evacuate if they visit a gas station and are more likely to stay if they visit a grocery store, hardware store, pet store, or a pharmacy prior to landfall. Additionally, they are even less likely to leave if they visit multiple places of interest. These results provide a foundation for using smartphone location data in real time to improve predictions of behavior as a hurricane approaches.
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    Cooling-excited infrared thermography for enhancing the detection of concrete filled steel tube interfacial debonding at concrete hydration
    (Case Studies in Construction Materials, 2024-02-24) Cai, Haonan; Cheng, Chongsheng; Na, Ri; Zhang, Hong; Zhou, Jianting; Jing, Shihong; Miao, Chaojie
    Interfacial Debonding occurring in concrete-filled steel Tube (CFST) arch bridges during construction is a critical issue, which can reduce the CFST carrying capacity and thus degrade the operational lifespan of the bridge. Timely detection of this type of defect during bridge construction can be highly cost-effective but rare sensing technology was reported for detection at this stage. Infrared thermography has been recognized as a potential detection method but still faces the challenge of low thermal contrast developed from concrete hydration. This research investigates the feasibility of using hydration heat as an internal heat source and proposes water-spray cooling as an external excitation to improve infrared debonding detection. The experimental study is carried out to investigate the detectability enhancement before and after the cooling excitation in terms of different debonding sizes and thicknesses. An image enhancement method is then proposed for debonding visualization based on the temperature difference matrix. In addition, the numerical simulation is conducted to analyze the cooling effect regarding the excitation intensity variation. The findings reveal that the thermal contrast of debonding ranges from 0.1 to 0.35℃ before cooling excitation and is enhanced by 2–3 times thereafter. In addition, the developed maximum thermal contrast of debonding can be characterized through a linear relationship to the cooling excitation intensity based on numerical analysis. The proposed method shows significant feasibility for early detection of debonding in CFST during arch bridge construction, which enables a new potential for structural inspection. Highlights • Cooling excitation improves the infrared detection by 2–3 times during the hydration heat-release stage. • More temperature change is stimulated in debonding areas than in non-debonding areas by the cooling excitation. • The proposed infrared image enhancement method improves the visibility of debonding areas. • The maximum temperature difference and excitation intensity can be characterized by a linear function.
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    Experimental study on infrared detection of debonding in concrete-filled steel tubular structure under acceleratory period of hydration heat action
    (Case Studies in Construction Materials, 2024-11-01) Cheng, Chongsheng; Cheng, Xun; Zhang, Hong; Cai, Haonan; Zhou, Jianting; Na, Ri; Wu, Bo
    Concrete-filled steel tubular (CFST) Structures often face challenges with debonding during construction, which can markedly compromise the structural integrity. The hydration of concrete can generate significant heat during construction, making the infrared thermography as a potential method for the defect detection. However, effects of concrete hydration behavior, debonding size, and environmental factors on the infrared thermal imaging of CFST debonding remains unclear. This study conducted experiments using four different hydration heating rates and three debonding sizes to simulate debonding detection using infrared imaging during the hydration phase of CFST. The feasibility of the simulation approach was validated through pair-to-pair comparison, and multiple linear regression analysis was employed to evaluate the impact of these factors. The findings highlight that absolute temperature difference has the most significant impact on detection effectiveness regardless of interaction effects. In regression models without interaction, heating rate demonstrated the least impact, Whereas the model considering the interaction showed that the interaction effect of heating rate and debonding size showed a secondary effect. Further examination indicated that interaction effects decrease as heating rate and debonding size decrease.
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    Revealing the Impact of Depth and Surface Property Variations on Infrared Detection of Delamination in Concrete Structures Under Natural Environmental Conditions
    (Buildings, 2024-12-24) Cheng, Chongsheng; Chen, Dequan; Shao, Shuai; Na, Ri; Cai, Haonan; Zhou, Hongwen; Wu, Bo
    Infrared thermography (IRT) is an effective nondestructive testing method for detecting delamination in concrete structures. However, erroneous data interpretation often diminishes its practical utility due to surface irregularities (e.g., color variations) during inspection. These “noisy conditions” alter the temperature distribution of the structure under solar heating cycles, making it challenging to quantify delamination based on the developed thermal contrast (ΔT). This study experimentally investigates the impact of different surface conditions (bare concrete vs. painted surfaces) on ΔT. Artificial delamination at varying depths was simulated and tested under natural environmental conditions, where the maximum ΔT values for shallow delamination were 9.40 °C (bare concrete), 7.35 °C (yellow paint), and 5.15 °C (white paint), respectively. This study measured and analyzed the absorptivity (bare concrete: 0.652, yellow paint: 0.538, and white paint: 0.369), emissivity, and the temperature difference (δT) between non-delaminated areas and air, revealing their correlation with ΔT variation. Based on the results, three typical scenarios are proposed to correlate δT with delamination detection. These findings contribute to a better understanding of the optimal detection window and present a new approach to quantifying delamination at different time windows. The conclusion also discusses the limitations of this study and future research directions.
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    Delamination detection in concrete decks using numerical simulation and UAV-based infrared thermography with deep learning
    (Automation in Construction, 2024-12-19) Aljagoub, Dyala; Na, Ri; Cheng, Chongsheng
    The potential of concrete bridge delamination detection using infrared thermography (IRT) has grown with technological advancements. However, most current studies require an external input (subjective threshold), reducing the detection's objectivity and accuracy. Deep learning enables automation and streamlines data processing, potentially enhancing accuracy. Yet, data scarcity poses a challenge to deep learning applications, hindering their performance. This paper aims to develop a deep learning approach using supervised learning object detection models with extended data from real and simulated images. The numerical simulation image supplementation seeks to eliminate the limited data barrier by creating a comprehensive dataset, potentially improving model performance and robustness. Mask R-CNN and YOLOv5 were tested across various training data and model parameter combinations to develop an optimal detection model. Lastly, when tested, the model showed a remarkable ability to detect delamination of varying properties accurately compared to currently employed IRT techniques. Highlights • Employs Infrared Thermography with an Unmanned Aerial Vehicle (IRT-UAV) and deep learning for concrete delamination detection. • Addresses the challenge of limited training data for deep learning by integrating real and simulated images • Utilizes Mask R-CNN and YOLOv5 models, evaluated in four phases, to develop a robust delamination detection model. • Collects data from a mockup slab, two in-service bridges, and 39 numerical simulation scenarios for comprehensive analysis.
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    Insurability and government-funded mitigation: safer but costlier
    (The Geneva Papers on Risk and Insurance - Issues and Practice, 2024-11-26) Liu, Dahui; Nozick, Linda; Millea, Meghan; Kruse, Jamie; Davidson, Rachel; Trainor, Joseph; Li, Junkan; Williams, Caroline
    Hurricanes significantly harm homeowners through physical damage and long-term financial strain due to rising insurance costs, property value loss, and repair expenses. This paper focuses on the interrelated decisions of the government mitigation funding of residential acquisitions and retrofit subsidies and of price restrictions on the insurance market in eastern North Carolina to determine the financial effects on stakeholders. The introduction of these policy interventions have impacts that propagate through the system due to risk adjustments, homeowner take-up behaviour, and insurer profit-maximising behaviour. This study uses an integrated game theoretic model to demonstrate that there are cost-effective government spending levels that reduce residential loss from hurricane damage. When insurance prices are capped at preintervention levels, the number of households and their distribution of losses, which has been altered through mitigation, leads to increased insurer insolvency. When insurance prices are allowed to adjust after mitigation, some homeowners find insurance is no longer affordable. This highlights the tradeoff between ensuring insurer stability and expanding homeowner insurance accessibility.
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    REWET: A Tool to Model System Functioning and Restoration of Damaged Water Supply Systems
    (Journal of Infrastructure Systems, 2024-09-14) Naeimi, Sina; Davidson, Rachel A.
    The process of restoring water supply after service is interrupted is critical for determining the durations and spatial distribution of outages and thus the impacts that households, businesses, and others ultimately experience. Nevertheless, the restoration period is difficult to predict because it involves complex, dynamic interactions among the system hydraulics, operator restoration actions, and consumer adaptations to service interruptions. In this paper, we introduce a new computer model called Restoration of Water after an Event Tool (REWET) that (1) allows detailed representations of both the hydraulic operations of the system and the restoration process, (2) is flexible enough to apply to any system or disruptive event, enable varying levels of complexity, and allow deterministic or probabilistic analysis, and (3) is available as free, easy-to-use, open-source code. It uses pressure-demand driven hydraulic analysis and allows detailed discrete event simulation representation of the restoration process. We present case study applications of REWET for the Los Angeles water system and for a small, simple network to illustrate the tool’s functionality, flexibility, and key features.
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    Genome editing in ubiquitous freshwater Actinobacteria
    (Applied and Environmental Microbiology, 2024-10-16) Bairagi, Nachiketa; Keffer, Jessica L.; Heydt, Jordan C.; Maresca, Julia A.
    Development of genome-editing tools in diverse microbial species is an important step both in understanding the roles of those microbes in different environments, and in engineering microbes for a variety of applications. Freshwater-specific clades of Actinobacteria are ubiquitous and abundant in surface freshwaters worldwide. Here, we show that Rhodoluna lacicola and Aurantimicrobium photophilum, which represent widespread clades of freshwater Actinobacteria, are naturally transformable. We also show that gene inactivation via double homologous recombination and replacement of the target gene with antibiotic selection markers can be used in both strains, making them convenient and broadly accessible model organisms for freshwater systems. We further show that in both strains, the predicted phytoene synthase is the only phytoene synthase, and its inactivation prevents the synthesis of all pigments. The tools developed here enable targeted modification of the genomes of some of the most abundant microbes in freshwater communities. These genome-editing tools will enable hypothesis testing about the genetics and (eco)physiology of freshwater Actinobacteria and broaden the available model systems for engineering freshwater microbial communities. IMPORTANCE To advance bioproduction or bioremediation in large, unsupervised environmental systems such as ponds, wastewater lagoons, or groundwater systems, it will be necessary to develop diverse genetically amenable microbial model organisms. Although we already genetically modify a few key species, tools for engineering more microbial taxa, with different natural phenotypes, will enable us to genetically engineer multispecies consortia or even complex communities. Developing genetic tools for modifying freshwater bacteria is particularly important, as wastewater, production ponds or raceways, and contaminated surface water are all freshwater systems where microbial communities are already deployed to do work, and the outputs could potentially be enhanced by genetic modifications. Here, we demonstrate that common tools for genome editing can be used to inactivate specific genes in two representatives of a very widespread, environmentally relevant group of Actinobacteria. These Actinobacteria are found in almost all tested surface freshwater environments, where they co-occur with primary producers, and genome-editing tools in these species are thus a step on the way to engineering microbial consortia in freshwater environments.
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    Beyond the Wedge: Impact of Tidal Streams on Salinization of Groundwater in a Coastal Aquifer Stressed by Pumping and Sea-Level Rise
    (Water Resources Research, 2024-09-27) Hingst, M. C.; Housego, R. M.; He, C.; Minsley, B. J.; Ball, L. B.; Michael, H. A.
    Saltwater intrusion (SWI) is a well-studied phenomenon that threatens the freshwater supplies of coastal communities around the world. The development and advancement of numerical models has led to improved assessment of the risk of salinization. However, these studies often fail to include the impact of surface waters as potential sources of aquifer salinity and how they may impact SWI. Based on field-collected data, we developed a regional, variable-density groundwater model using SEAWAT for east Dover, Delaware. In this location, major users of groundwater from the surficial aquifer are the City of Dover and irrigation for agriculture. Our model includes salinized marshland and tidal streams, along with irrigation and municipal pumping wells. Model scenarios were run for 100 years and included changes in pumping rates and sea-level rise (SLR). We examined how these drivers of SWI affect the extent and location of salinization in the surficial aquifer by evaluating differences in chloride concentration near surface waters and the subsurface freshwater-saltwater interface. We found the presence of the marsh inverts the typical freshwater-saltwater wedge interface and that the edge of the interface did not migrate farther inland. Additionally, we found that tidal streams are the dominant pathways of SWI at our site with salinization from streams being exacerbated by SLR. Our results also show that spatial distribution of pumping affects both the magnitude and extent of salinization, with an increase in concentrated pumping leading to more intensive salinization than a more widely distributed increase of the same total pumping volume. Key Points - Presence of a saltmarsh inverts the freshwater-saltwater interface in our study location - Tidal streams contribute substantially to salinization of inland groundwater - Concentrated pumping led to more intensive salinization than widespread pumping
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    Assessing Iron Complexation by Dissolved Organic Matter Using Mediated Electrochemical Oxidation
    (ACS Earth and Space Chemistry, 2024-08-14) Hudson, Jeffrey M.; Luther, George W., III; Chin, Yu-Ping
    FeII is an abundant reductant in the environment that participates in numerous biogeochemical cycles and pollutant attenuation. FeII in aquatic environments can exist as a complex with dissolved organic matter (DOM), where organic ligands in DOM can modulate iron’s redox potential (EH) and henceforth reactivity as a reductant. Previous studies have assessed the reactivity of FeII-complexes using probe compounds, although these compounds are limited in their ability to profile FeII oxidation across multiple thermodynamic conditions (i.e., both pH and EH) and fail to validate the EH of Fe(II)-complexes via their direct measurement. This study elucidated the redox potentials of FeII-DOM complexes via mediated electrochemical oxidation (MEO) and assessed the extent of FeII oxidation at two different applied EH and pH regimes. Furthermore, we used a Nernstian-based model calibrated with a training set between known iron-ligand thermodynamic stability constants and their respective measured potentials to indirectly determine the stability constants of both FeII and FeIII-DOM complexes as a function of EH and pH. This work highlights the versatility of MEO as an electrochemical technique and is the first to assess stability constants of Fe-complexes with aquatic DOM isolates. We also discuss linkages between speciation modeling and redox reactivity of FeII.
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    Retroreflective sheeting materials as SHM passive strain sensors
    (CRC Press, 2024) Power, Hannah M.; Shenton, Harry W.
    Highly reflective Retroreflective sheeting materials (RRSM) are widely used today for roadway signs and markings. Retroreflectivity (RR), defined as the portion of light re-turned to the light source as measured in candelas per lux per square meter, can be measured quite easily in the field using a handheld retroreflectometer. Tests show that as load is applied to RRSM, the retroreflection changes, and for many types of RRSM, RR decreases with increasing tension and has a mostly linear relationship to the material strain. This opens the possibility for using RRSM as a passive strain sensor for structural health monitoring, whereby measured changes in RR of RRSM mounted to a structure can be correlated to changes in strain. The sensor would be low cost, practical, and innovative. Tension test results show that a yellow-green type XI material produced by one manufacturer has one of the highest material sensitivities (ratio of retroreflectivity to strain) of the many the authors have tested. The sensitivity of the material, denoted here as A-TXIFYG, decreases linearly after it is strained past approximately 1000 microstrain (µε). This led to testing of the material after initial straining (pre-straining). Results show that for the material to have a similar sensitivity while mounted to that of the bare material tests, it must be externally clamped to the substrate.
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    Evaluation of Flexural Performance of Slab Bridges in the Pacific Northwest Region Subjected to Long-Duration Earthquake Events
    (International Journal of Civil Infrastructure, 2024-08-08) Obayes, Shaymaa; Head, Monique
    While previous studies have explored bridge vulnerabilities, there is a notable gap in assessing the susceptibility of existing bridges, particularly slab bridges, to long-duration earthquakes in seismically active regions. This study uniquely quantifies and evaluates the impact of a moment magnitude (MW) 9.0 earthquake, characterized by its long duration, on the incipient collapse risk of slab bridges in the Pacific Northwest (PNW) region of the United States. The assessment includes potential flexural failures in slab bridge columns and the associated collapse risk. A slab bridge is modeled in OpenSees for case studies to determine vulnerability and incipient collapse risk through fragility analyses and a risk-targeted approach in accordance with the 2023 AASHTO Guide Specifications for LRFD Seismic Bridge Design. The study emphasizes the consequences of outdated seismic design standards, particularly for slab bridges constructed before the 1990s. Moreover, the findings reveal that long-duration earthquakes significantly increase the collapse risk of aging slab bridges built before the 1990s.
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    Stability of marsh edge berms constructed from fine-grained dredged sediment
    (Frontiers in Marine Science, 2024-08-28) Perkey, David W.; Tedesco, Lenore P.; Fall, Kelsey A.; Huff, Thomas P.; Chasten, Monica A.
    Due to observed impacts of sea level rise, many sediment management strategies in coastal settings are seeking ways to beneficially use locally dredged sediment in restoration, nourishment, and construction projects. The placement of sediment in shallow, near-marsh areas is a promising application of dredged material to both increase accretion and provide protection to marshes and intertidal flats in back bay areas. However, dredged material in these areas often include fine-grained (<63 μm) sediments (FGS), that frequently raise questions concerning dispersion, stability, and environmental impact of the placement project. In 2020, approximately 30,500 m3 of FGS from the New Jersey Intracoastal Waterway (NJIWW) was placed along the southern edge of Gull Island, New Jersey to evaluate the feasibility of using FGS for beneficial use projects in near marsh environments. Gull Island was experiencing extensive marsh edge erosion through margin collapse. The placement was unconfined and resulted in the formation of two intertidal muddy berm-like features up to 0.7 m thick along more than 500 m of marsh. Bathymetric surveys showed that approximately 60-70% of the berm volume remained 36 months after placement, however maximum berm thickness reduced to ~0.5 m. Field monitoring performed during construction found that turbidity plumes were localized to within 100 m of the placement site and sediment cores collected in June 2022 did not show systemic winnowing from the berm surface. Laboratory and field observations indicated that the berm material was cohesive in nature and produced large aggregates upon erosion, limiting the dispersal of FGS. Observations of current velocities and waves in the area indicate a low energy system such that the cohesive berm was largely resistant to erosion and that reduction in berm volume was largely due to consolidation and compaction. This suggests that shallow water features can be constructed with FGS in similar low energy environments with limited dispersal during and following construction, while being robust enough to help stabilize the marsh edge and improve marsh survivability against sea level rise.
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