Modeling and Monitoring of the Dynamic Response of Railroad Bridges using Wireless Smart Sensors

Railroad bridges form an integral part of railway infrastructure in the USA, carrying approximately 40 % of the ton-miles of freight. The US Department of Transportation (DOT) forecasts current rail tonnage to increase up to 88 % by 2035. Within the railway network, a bridge occurs every 1.4 miles of track, on average, making them critical elements. In an effort to accommodate safely the need for increased load carrying capacity, the Federal Railroad Association (FRA) announced a regulation in 2010 that the bridge owners must conduct and report annual inspection of all the bridges. The objective of this research is to develop appropriate modeling and monitoring techniques for railroad bridges toward understanding the dynamic responses under a moving train. To achieve the research objective, the following issues are considered specifically. For modeling, a simple, yet effective, model is developed to capture salient features of the bridge responses under a moving train. A new hybrid model is then proposed, which is a flexible and efficient tool for estimating bridge responses for arbitrary train configurations and speeds. For monitoring, measured field data is used to validate the performance of the numerical model. Further, interpretation of the proposed models showed that those models are efficient tools for predicting response of the bridge, such as fatigue and resonance. Finally, fundamental software, hardware, and algorithm components are developed for providing synchronized sensing for geographically distributed networks, as can be found in railroad bridges. The results of this research successfully demonstrate the potentials of using wirelessly measured data to perform model development and calibration that will lead to better understanding the dynamic responses of railroad bridges and to provide an effective tool for prediction of bridge response for arbitrary train configurations and speeds.National Science Foundation Grant No. CMS-0600433National Science Foundation Grant No. CMMI-0928886National Science Foundation Grant No. OISE-1107526National Science Foundation Grant No. CMMI- 0724172 (NEESR-SD)Federal Railroad Administration BAA 2010-1 projectOpe

Enrollment Management Strategies at Rural Community Colleges Resulting from the Pandemic

Higher education institutions around the world were impacted by the COVID-19 pandemic that began in early 2020. Because U.S. community colleges focus on two-year degrees and workforce development, they were affected differently than their four-year counterparts. This study examined how academic administrators at different rural community colleges in Virginia, United States, perceived enrollment management practices that were implemented or changed due to the pandemic. This sequential explanatory study\u27s first phase was quantitative and measured mid- to senior-level administrators\u27 views of how the pandemic affected their colleges\u27 enrollment management practices. The second qualitative phase resulted in five themes surrounding COVID-related enrollment management practices: a) COVID-19 led to crisis management and operations in phases; b) managing student onboarding during COVID-19; c) COVID-19 created unique challenges for community college students; d) COVID-19 affected decision-making procedures; and e) COVID-19 resulted in work/life balance issues and COVID fatigue. Implications and future directions are provided to ensure that community college enrollment managers and policymakers understand how to continue to pivot to ensure student services are maintained or enhanced during a crisis

Probabilistic Fatigue Life Updating for Railway Bridges Based on Local Inspection and Repair

Railway bridges are exposed to repeated train loads, which may cause fatigue failure. As critical links in a transportation network, railway bridges are expected to survive for a target period of time, but sometimes they fail earlier than expected. To guarantee the target bridge life, bridge maintenance activities such as local inspection and repair should be undertaken properly. However, this is a challenging task because there are various sources of uncertainty associated with aging bridges, train loads, environmental conditions, and maintenance work. Therefore, to perform optimal risk-based maintenance of railway bridges, it is essential to estimate the probabilistic fatigue life of a railway bridge and update the life information based on the results of local inspections and repair. Recently, a system reliability approach was proposed to evaluate the fatigue failure risk of structural systems and update the prior risk information in various inspection scenarios. However, this approach can handle only a constant-amplitude load and has limitations in considering a cyclic load with varying amplitude levels, which is the major loading pattern generated by train traffic. In addition, it is not feasible to update the prior risk information after bridges are repaired. In this research, the system reliability approach is further developed so that it can handle a varying-amplitude load and update the system-level risk of fatigue failure for railway bridges after inspection and repair. The proposed method is applied to a numerical example of an in-service railway bridge, and the effects of inspection and repair on the probabilistic fatigue life are discussed.ope

Structure and Aggregation of a Helix-Forming Polymer

We have studied the competition between helix formation and aggregation for a simple polymer model. We present simulation results for a system of two such polymers, examining the potential of mean force, the balance between inter and intramolecular interactions, and the promotion or disruption of secondary structure brought on by the proximity of the two molecules. In particular, we demonstrate that proximity between two such molecules can stabilize secondary structure. However, for this model, observed secondary structure is not stable enough to prevent collapse of the system into an unstructured globule.Comment: Accepted to the Journal of Chemical Physic

Righting the Balance: Gender Diversity in the Geosciences

The blatant barriers are down. Women are now routinely chief scientists on major cruises, lead field parties to all continents, and have risen to leadership positions in professional organizations, academic departments, and funding agencies. Nonetheless, barriers remain. Women continue to be under-represented in the Earth, ocean, and atmospheric sciences

A foundation for provitamin A biofortification of maize: genome-wide association and genomic prediction models of carotenoid levels.

Efforts are underway for development of crops with improved levels of provitamin A carotenoids to help combat dietary vitamin A deficiency. As a global staple crop with considerable variation in kernel carotenoid composition, maize (Zea mays L.) could have a widespread impact. We performed a genome-wide association study (GWAS) of quantified seed carotenoids across a panel of maize inbreds ranging from light yellow to dark orange in grain color to identify some of the key genes controlling maize grain carotenoid composition. Significant associations at the genome-wide level were detected within the coding regions of zep1 and lut1, carotenoid biosynthetic genes not previously shown to impact grain carotenoid composition in association studies, as well as within previously associated lcyE and crtRB1 genes. We leveraged existing biochemical and genomic information to identify 58 a priori candidate genes relevant to the biosynthesis and retention of carotenoids in maize to test in a pathway-level analysis. This revealed dxs2 and lut5, genes not previously associated with kernel carotenoids. In genomic prediction models, use of markers that targeted a small set of quantitative trait loci associated with carotenoid levels in prior linkage studies were as effective as genome-wide markers for predicting carotenoid traits. Based on GWAS, pathway-level analysis, and genomic prediction studies, we outline a flexible strategy involving use of a small number of genes that can be selected for rapid conversion of elite white grain germplasm, with minimal amounts of carotenoids, to orange grain versions containing high levels of provitamin A

The way the ball bounces: visual and auditory perception of elasticity and control of the bounce pass

Abstract. Human observers may perceive not only spatial and temporal dimensions of the environment, but also dynamic physical properties that are useful for the control of behavior. A study is presented in which visual and auditory perception of elasticity in bouncing objects, which was specified by kinematic (spatiotemporaI) patterns of object motion, were examined. In experiment 1, observers could perceive the elasticity of a bouncing ball and were able to regulate the impulse applied to the ball in a bounce pass. In experiments 2 and 3, it was demonstrated that visual perception of elasticity was based on relative height information, when it was available, and on the duration of a single period under other conditions. Observers did not make effective use of velocity information. In experiment 4, visual and auditory period information were compared and equivalent performance in both modalities was found. The results are interpreted as support for the view that dynamic properties of environmental events are perceived by means of kinematic information

Campaign Monitoring of Railroad Bridges in High-Speed Rail Shared Corridors using Wireless Smart Sensors

This report describes research results using wireless smart sensors to develop a cost-effective, practical, and portable structural health monitoring system for railroad bridges in North America. The system is designed for periodic inspection rather than as a permanent installation to enable campaign-style bridge response monitoring under in-service conditions. The system described herein measured bridge responses from a 310 feet long steel truss bridge using wireless sensors and calibrated a finite element (FE) model using the measured data to obtain global and local (at elements level) bridge responses under varied train loads and speeds. Additionally, this project developed a new simple beam model that can predict critical speeds and resonances based on train traffic properties. The results from this pilot project provide a technological foundation to develop campaign monitoring sensor technology as an important tool with which to manage railroad bridge assets.Financial support for this research was provided in part by the Federal Railroad Administration under Grant No. BAA-2010-1 No. DTFR53-13-C-00047, entitled “Campaign Monitoring of Railroad Bridges in High-Speed Rail Shared Corridors Using Wireless Smart Sensors” (Cameron Stuart, Program Manager).Ope