1 to 10 of 18 Results
Jun 26, 2023 - CAIT-UTC-REG28: Cost-effective Bridge Decks for Improved Durability and Extended Service Life
Haider Sakban; Amirali Najafi; Sophie Pastore, 2023, "Data for "CAIT-UTC-REG28: Cost-effective Bridge Decks for Improved Durability and Extended Service Life"", https://doi.org/10.7910/DVN/9DXBA9, Harvard Dataverse, V1
This project involves the experimental testing of a unique bridge deck specimen with a corrugated core that is bonded to the deck plate using structural adhesive. The specimen was supported and loaded using specially designed fixtures. Comprehensive instrumentation was implemented, including uniaxial, biaxial, and rosette strain gauges, as well as... |
Dec 7, 2022 - CAIT-UTC-REG58: Supplemental Study of Filter Technology Efficacy for Transit Vehicles to Combat the Spread of COVID-19 and Other Respiratory Infections
Mott, Shane; Mainelis, Gediminas; Han, Taewon, 2022, "Data for "CAIT-UTC-REG58: Supplemental Study of Filter Technology Efficacy for Transit Vehicles to Combat the Spread of COVID-19 and Other Respiratory Infections"", https://doi.org/10.7910/DVN/33ITLG, Harvard Dataverse, V1
The COVID-19 pandemic has been a worldwide issue that transit agencies are still struggling to find cost-efficient solutions to. Upgrading the filters used on trains and buses to reduce the airborne transmission of the SARS-CoV-2 virus as well as other infectious viruses, such as influenza, may be an effective, cost-efficient way of containing the... |
Oct 7, 2022 - CAIT-UTC-REG48: Linking Physics-Based Deterioration Model to Field-Based Condition Assessments for Improving Asset Management
Ranade, Ravi; Okumus, Pinar; Wang, Hanmin, 2022, "Data for "CAIT-UTC-REG48: Linking Physics-Based Deterioration Model to Field-Based Condition Assessments for Improving Asset Management"", https://doi.org/10.7910/DVN/FAVZKM, Harvard Dataverse, V1
Currently used asset management programs by various state departments of transportation (DOT) rely typically on field-based condition assessments (periodic inspections and deterioration curves) of bridges for planning repair and maintenance activities. However, field inspections are labor intensive and can be subjective. Furthermore, visual inspect... |
Oct 4, 2022 - CAIT-UTC-REG39: FDR Stabilizer Selection Using Simple Soil Tests
Orr, David, 2022, "Data for "CAIT-UTC-REG39: FDR Stabilizer Selection Using Simple Soil Tests"", https://doi.org/10.7910/DVN/4WZUKK, Harvard Dataverse, V1
Most local agencies that use full-depth reclamation (FDR) choose the stabilizer to be used by selecting a vendor rather than performing test on the pavement materials. Most of the methods available for selecting the technique or additive to be used rely on a sieve test and the plastic index (PI). The PI is not sensitive at the low values found in m... |
Rasool, Ghulam; Bouaynaya, Nidhal; Nasir, Abdullah; Koutsoubis, Nikolas, 2022, "Data for: "CAIT-UTC-REG54: Rotorcraft Landing Sites Identification – Scaling and Generalization of the AI Model"", https://doi.org/10.7910/DVN/ZCQNYS, Harvard Dataverse, V1
The updated information about the location and type of landing sites is essential for the Federal Aviation Administration (FAA) and the Department of Transportation (DOT). However, the acquisition, verification, and regular updating of information about landing sites are not straightforward. The lack of current and correct information on helicopter... |
Sep 15, 2022 - CAIT-UTC-REG52: Bridge Deck Surface Profile Evaluation for Rapid Screening and Deterioration Monitoring
Trias, Adriana, 2022, "Data for "CAIT-UTC-REG52: Bridge Deck Surface Profile Evaluation for Rapid Screening and Deterioration Monitoring"", https://doi.org/10.7910/DVN/6JEQJZ, Harvard Dataverse, V1
The assessment of bridge deck condition demands the development of rapid and efficient diagnosis, prognosis, and repair techniques to safely and cost-effectively extend the life-cycle of our transportation infrastructure. Without the ability to identify and characterize deficiencies at their early stages, prognosis and various repair strategies sim... |
Najafi, Amirali, 2022, "Data for "CAIT-UTC-REG65: Development of a geometric extraction framework as part of a pilot digital twin framework for open-deck rail bridges"", https://doi.org/10.7910/DVN/9BMR20, Harvard Dataverse, V1
Open-deck railway bridges require expensive and customized timber sleepers. When these sleepers are due for replacement, a manual process for geometry measurement is necessary which can be time consuming, inaccurate, and expensive. In addition, significant downtime is required for the safety of the inspectors that measure and assess the conditions... |
Sep 6, 2022 - CAIT-UTC-REG46: Driving behavioral learning leveraging sensing information from Innovation Hub
Di, Sharon; Jin, Peter; Huang, Yufei; Mo, Zhaobin, 2022, "Data for "CAIT-UTC-REG46: Driving behavioral learning leveraging sensing information from Innovation Hub"", https://doi.org/10.7910/DVN/XIHFDG, Harvard Dataverse, V1, UNF:6:9+I2xW5bGdSdMEwDY4kRjA== [fileUNF]
With the accelerated deployment of connected and automated vehicle (CAV) technologies, public agencies have urgent needs on how to utilize these rich data sources of CAVs to improve traffic mobility, safety, and environmental and energy impact. This research will tackle one of the big data challenges, which is mining driving behavior patterns using... |
Aug 30, 2022 - CAIT-UTC-REG26: Passenger Flow Modeling and Simulation in Transit Stations
Liu, Xiang; Zhu, Yadi, 2022, "Data for "CAIT-UTC-REG26: Passenger Flow Modeling and Simulation in Transit Stations"", https://doi.org/10.7910/DVN/SYBV9V, Harvard Dataverse, V1
Crowd analysis and management is key area of study for transit agencies to maximize operational efficiency and minimize risk. Passenger flow volume, crowd density and walking speed are key features of crowd analytics. This study proposes a generalized Artificial Intelligence (AI)-based crowd analytics model framework for rail transit stations, by a... |
Aug 29, 2022 - CAIT-UTC-REG23: The Development of a Smart Intersection Mobility Testbed (SIMT)
Jin, Peter; Jafari, Mohsen; Zhang, Tianya; Huang, Yufei; Wang, Yizhou; Ge, Yi, 2022, "Data for "CAIT-UTC-REG23: The Development of a Smart Intersection Mobility Testbed (SIMT)"", https://doi.org/10.7910/DVN/UFS7IC, Harvard Dataverse, V1, UNF:6:c9nsl12Uffc/FZfy07elDw== [fileUNF]
This project developed the key modules and models for building a prototype smart mobility intersection testbed. The project proposed the key system design, developed the computer-vision based sensing module, created 3D infrastructure model, and explored a risk-based intersection traffic conflict analysis application as an application of the develop... |
