Maryland Shared Open Access Repository
MD-SOAR is a shared digital repository platform for twelve colleges and universities in Maryland. It is currently funded by the University System of Maryland and Affiliated Institutions (USMAI) Library Consortium (usmai.org) and other participating partner institutions. MD-SOAR is jointly governed by all participating libraries, who have agreed to share policies and practices that are necessary and appropriate for the shared platform. Within this broad framework, each library provides customized repository services and collections that meet local institutional needs. Please follow the links below to learn more about each library's repository services and collections.
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Recent Submissions
Analyzing and Comparing Mineral Identification Methods and their Applications
(2024-12-18) Nooney, Bridget; Department of Geography; GEOG482 and GEOG 483
Mineral identification is a fundamental aspect of mineralogy. Traditional identification methods involved analyzing physical and observable properties, but more advanced methods, such as petrographic microscopy and X-ray fluorescence spectroscopy, can be used to measure optical and geochemical characteristics. Thirteen hand samples from Ward’s Laboratory Rock and Mineral Set were observed for physical characteristics (hardness, streak, crystal habit, luster, color, cleavage, and fracture) and scanned in an XRF spectrometer to generate graphs of their elemental composition. Seven thin sections were observed with a petrographic microscope and photographed using a digital camera. The results for each method were combined into a comprehensive dataset of each mineral. Each method provided a distinctive analysis of mineral characteristics and should be used to supplement each other for a more well-rounded dataset. Implementing a combination of these methods into educational settings, such as undergraduate laboratory exercises, would allow students to gain more understanding and experience with optical mineralogy and geochemistry.
Developing and Testing an Advanced Hybrid Electric Vehicle Co-Cooperative Adaptive Cruise Control System at Multiple Signalized Intersections
(2020-10) Chen, Hao; Rakha, Hesham; Jeihani, Mansoureh; Urban Mobility & Equity Center
This research develops an advanced Eco-Cooperative Adaptive Cruise Control System (Eco-CACC) for hybrid electric vehicles (HEVs) to pass signalized intersections with energy-optimized speed profiles, with the consideration of impacts by multiple signalized intersections. The research extends the Eco-CACC at signalized intersections (Eco-CACC-I) system previously developed by the research team for conventional internal combustion engine (ICE) vehicles to HEVs. In the proposed system, a simple HEV energy model is used to compute the instantaneous energy consumption level for HEVs. In addition, a vehicle dynamics model is used to capture the relationship between speed, acceleration level, and tractive/resistance forces on vehicles. The constraints of energy model and vehicle dynamics are used to develop two HEV Eco-CACC-I controllers for single-intersection and multiple-intersection, respectively. The developed HEV Eco-CACC-I controllers include two modes: automated and manual, for vehicles with or without an automated control system. The automated mode was implemented into the microscopic traffic simulation software so that connected and automated vehicles (CAVs) can directly follow the energy-optimized speed profile. Simulation tests using the INTEGRATION software validated the performances of the proposed controllers under the impact of signal timing, speed limit, and road grade. The simulation tests also demonstrated the improved benefits of using the proposed HEV Eco-CACC-I controllers in a traffic network with multiple intersections. Lastly, the manual model of the proposed HEV Eco-CACC controller was implemented in a driving simulator at Morgan State University so that drivers in connected vehicles (non-automated driving) can follow the recommended speed advisories. The data collected by the driving simulator with 48 participants demonstrated that the speed advisories calculated by the proposed controller can help drivers drive smoothly and save fuel while passing signalized intersections.
Developing and Testing an Advanced Hybrid Electric Vehicle Eco-Cooperative Adaptive Cruise Control System at Multiple Signalized Intersections
(2020-10) Chen, Hao; Rakha, Hesham; Jeihani, Mansoureh; Ahangari, Samira; Urban Mobi
This research develops an advanced Eco-Cooperative Adaptive Cruise Control System (Eco-CACC) for hybrid electric vehicles (HEVs) to pass signalized intersections with energy-optimized speed profiles, with the consideration of impacts by multiple signalized intersections. The research extends the Eco-CACC at signalized intersections (Eco-CACC-I) system previously developed by the research team for conventional internal combustion engine (ICE) vehicles to HEVs. In the proposed system, a simple HEV energy model is used to compute the instantaneous energy consumption level for HEVs. In addition, a vehicle dynamics model is used to capture the relationship between speed, acceleration level, and tractive/resistance forces on vehicles. The constraints of energy model and vehicle dynamics are used to develop two HEV Eco-CACC-I controllers for single-intersection and multiple-intersection, respectively. The developed HEV Eco-CACC-I controllers include two modes: automated and manual, for vehicles with or without an automated control system. The automated mode was implemented into the microscopic traffic simulation software so that connected and automated vehicles (CAVs) can directly follow the energy-optimized speed profile. Simulation tests using the INTEGRATION software validated the performances of the proposed controllers under the impact of signal timing, speed limit, and road grade. The simulation tests also demonstrated the improved benefits of using the proposed HEV Eco-CACC-I controllers in a traffic network with multiple intersections. Lastly, the manual model of the proposed HEV Eco-CACC controller was implemented in a driving simulator at Morgan State University so that drivers in connected vehicles (non-automated driving) can follow the recommended speed advisories. The data collected by the driving simulator with 48 participants demonstrated that the speed advisories calculated by the proposed controller can help drivers drive smoothly and save fuel while passing signalized intersections.
Optimized Development of Urban Transportation Networks 2.0
(2020-12) Schonfeld, Paul; Urban Mobility & Equity Center
This report presents as series of eight papers on methods for planning, designing, and scheduling the implementation of improvements in urban transportation systems. Five of the papers (1 - 4 and 6) focus on methods for evaluating, sequencing and scheduling interrelated improvements in transportation networks while the others present methods for designing flexible route services (5 - 7) and improving the reliability of rail transit networks (8). Due to the complexity of the relevant functions for evaluating interrelated network improvements, which cannot be optimized with classical calculus techniques, the proposed methods rely on customized genetic algorithms for optimizing the selection, sequencing and scheduling of the interrelated alternatives. Applications to urban transportation networks are presented in papers for journals, which are included in appendices. The papers demonstrate the applicability of the developed methods to urban road networks, intersections in urban road networks, urban rail transit networks and flexible-route transportation systems.
Equity in Transportation Policy Interviews, Transcriptions, and Keyword Coding
(The SMARTER Center, 2024-12-18) Philip Barnes; Andrea Pierce; Calaia Jackson; The National Transportation Center; University Transportation Centers Program
Equitable outcomes is an increasingly important principle for expenditures by state Departments of Transportation, yet little is known about the methods and procedures used to incorporate equity into financial decision-making. This applied research project will employ semi-structured interviews with key personnel in the Delaware Department of Transportation (DelDOT) to illuminate their conceptualization of equity and how the concept influences capital expenditures. The interview data will be compared to the state of the art of equity in transportation and infrastructure spending, which will be gleaned through a literature review. The resulting analysis will highlight gaps and innovative practices at DelDOT, which will lead to recommendations for closing gaps and accentuating positive practices and outcomes. Research findings will be communicated to DelDOT leadership and local government officials.