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1. GreenEVT: Greensboro Electric Vehicle Testbed

   https://doi.org/10.1109/JSYST.2023.3343692  

   Nilsson, Gustav; Aquino, Alejandro_D Owen; Coogan, Samuel; Molzahn, Daniel K (March 2024, IEEE Systems Journal)

   The ongoing electrification of the transportation fleet will increase the load on the electric power grid. Since both the transportation network and the power grid already experience periods of significant stress, joint analyses of both infrastructures will most likely be necessary to ensure acceptable operation in the future. To enable such analyses, this article presents an open-source testbed that jointly simulates high-fidelity models of both the electric distribution system and the transportation network. The testbed utilizes two open-source simulators, OpenDSS to simulate the electric distribution system and the microscopic traffic simulator SUMO to simulate the traffic dynamics. Electric vehicle charging links the electric distribution system and the transportation network models at vehicle locations determined using publicly available parcel data. Leveraging high-fidelity synthetic electric distribution system data from the SMART-DS project and transportation system data from OpenStreetMap, this testbed models the city of Greensboro, NC down to the household level. Moreover, the methodology and the supporting scripts released with the testbed allow adaption to other areas where high-fidelity geolocated OpenDSS datasets are available. After describing the components and usage of the testbed, we exemplify applications enabled by the testbed via two scenarios modeling the extreme stresses encountered during evacuations. 

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2. GreenEVT: Greensboro electric vehicle testbed

   G. Nilsson; A. Aquino; S. Coogan; D. Molzahn (May 2024, IEEE systems journal)

   The ongoing electrification of the transportation fleet will increase the load on the electric power grid. Since both the transportation network and the power grid already experience periods of significant stress, joint analyses of both infrastructures will most likely be necessary to ensure acceptable operation in the future. To enable such analyses, this paper presents an open- source testbed that jointly simulates high-fidelity models of both the electric distribution system and the transportation network. The testbed utilizes two open-source simulators, OpenDSS to simulate the electric distribution system and the microscopic traffic simulator SUMO to simulate the traffic dynamics. Electric vehicle charging links the electric distribution system and the transportation network models at vehicle locations determined using publicly available parcel data. Leveraging high-fidelity synthetic electric distribution system data from the SMART-DS project and transportation system data from OpenStreetMap, this testbed models the city of Greensboro, NC down to the household level. Moreover, the methodology and the supporting scripts released with the testbed allow adaption to other areas where high-fidelity geolocated OpenDSS datasets are available. After describing the components and usage of the testbed, we exemplify applications enabled by the testbed via two scenarios modeling the extreme stresses encountered during evacuations. 

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3. A Cutaneous Haptic Cue Characterization Testbed

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   Fleck, Joshua J.; Zook, Zane A.; Tjandra, Tiffani W.; O'Malley, Marcia K. (July 2019, 2019 IEEE World Haptics Conference (WHC))
4. A Framework of an IoT Testbed

   https://doi.org/10.1109/SoutheastCon48659.2022.9763934  

   Workman, Chad; Tomlinson, Gavin; Di, Jia; Du, Xiaojiang; Zeng, Qiang (March 2022, IEEE SoutheastCon 2022)

   As Internet of Things (IoT) technology becomes more widespread and commonplace in homes, the efficiency of these devices using available bandwidth is becoming more of a concern, as the number of connected devices in a home increase drastically. If each device is controlled using a separate Application Programming Interface (API), the strain on a network will be much worse than it would if all these devices are controlled from a single point. This single point could handle all commands to and from the devices, thereby decreasing the network load. The framework of a testbed presented in this paper will allow developers to build an API around the devices included in the testbed. Then test their algorithms and other research methods from a remote location. 

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5. A Hypergravity Testbed to Advance Biogeotechnics

   https://doi.org/10.1061/geosek.0000491  

   Wilson, Daniel W.; DeJong, Jason T.; Boulanger, Ross W. (August 2023, GEOSTRATA Magazine)

   Biogeotechnics, specifically bio-mediated and bio-inspired geotechnical engineering, has matured rapidly over the past two decades, becoming one of the fastest growing subdisciplines within geotechnical engineering. As typical in most science and engineering fields, biogeotechnics relies on data from physical experiments and field observations to advance technology. Obtaining field data to drive advancement can pose unique challenges, and in many cases may be cost or logistically prohibitive. Physical experiments or models are often preferable and may offer the sole feasible pathway for technology development and upscaling. Hypergravity scaled modeling using centrifuges has been instrumental in biogeotechnics development to support the building of basic science knowledge, the validation of computational and theoretical models, and the advancement of emerging technologies towards field implementation. 

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