Category: News

Dr. Yan Wan, Professor, Electrical Engineering, has been elected to American Institute of Aeronautics and Astronautics Associate (AIAA) Fellow Class of 2023. AIAA Associate Fellows are “individuals of distinction who have made notable and valuable contributions to the arts, sciences, or technology of aeronautics or astronautics.” Per AIAA, Dr. Wan has distinguished herself by her notable contributions and accomplishments to the aerospace community, and thus have earned this esteemed level of membership.

Each year, only one for every 150 voting members are selected and approved.  The selection process is highly competitive, and only approximately 17% of the AIAA membership are associate fellows.

With nearly 30,000 individual members from 91 countries, and 95 corporate members, AIAA is the world’s largest technical society dedicated to the global aerospace profession.

Dr. Xin Liu, Assistant Professor of Industrial, Manufacturing, and Systems Engineering, has been awarded a Phase 2 STTR subcontract by AnalySwift for a NASA project.

Affordable space exploration beyond the lower Earth orbit will require innovative lightweight structural concepts. Tailorable composites are an innovative lightweight material that have the potential applications to exploration vehicles, space habitats, and other space hardware. The Smart Multiscale Mechanics Lab (SMML), led by Dr. Xin Liu, within UTARI’s Institute for Predictive Performance Methodologies (IPPM) has been awarded the subcontract from a NASA Phase II STTR grant by AnalySwift LLC. The project is to develop integrated, efficient computational framework and design tool for advanced tailorable composites.

It is computationally infeasible to perform design optimization of realistic aerospace structures using tailorable composites with highly customizable fiber paths. Dr. Liu’s team will develop ultra-efficient deep learning models to reduce the computational cost and facilitate the design optimization of realistic aerospace structures. The machine learning models will be integrated into a unified design framework and a new efficient high-fidelity Design tool for Advanced Tailorable Composites (DATC). Dr. Liu and his team was subcontracted on the Phase I by AnalySwift in June 2021.

Dr. Nick Gans, Principal Research Scientist and Head of the Automation and Intelligent Systems Division was issued a patent by the United States Patent and Trademark Office for printing on curved surfaces (Patent #11400317). “Line width control and trajectory planning for robot guided inkjet deposition” was in collaboration with Dr. Bashir Jafari of the University of Texas at Dallas.

Inkjet printing whereby liquids (e.g., ink) are deposited onto substrates (e.g., paper, human tissues, vehicle bodies) is a flexible technology that has been used for a variety of commercial applications including printing of antennas, transistors, displays, biomaterials, tissues, and carbon nanotubes. Robot-assisted inkjet printing is a developing technology that allows manufacturers to take advantage of cost efficiencies realized through use of automation in production line applications for printing on complex 3D surfaces. Use of robotic-assisted print technology is increasing in a variety of industries including airplane and vehicle surface painting/coating applications. One of the primary challenges that needs to be addressed for more efficient use of robotic-based inkjet print applications is the accurate mapping of print trajectories onto complex, curved surfaces, particularly when such trajectories are defined by specific points and/or geometric boundaries.

A dynamic line width model has been developed based on the duty cycle of the printer actuation (e.g., motor speed, valve opening/closing), nozzle velocity, ink contact angle, ink characteristics, and the nature of the surface being printed on. Based on this data, unknown or hard to measure print parameters are estimated by the model. During printing, the computer determines the actual/measured print line width, which is compared with the desired/specified line width required for the task. If the measured line width is not within specification of the desired line width, the printer duty cycle is adjusted based on the parameters estimated/determined by the model to more closely match the desired and measured line widths to realize more accurate and cost-effective inkjet print operations.

For licensing, please contact Arul Thirumaran, Licensing Associate, Innovation & Commercialization:
thirumaran@uta.edu
innovation@uta.edu
P: 817-272-6269

Dr. Haleh Aghajani, Research Scientist at Sensor Systems Division, through the collaboration with Dr. Yue Liao (UTA Kinesiology) and other internal and external interdisciplinary collaborators, co-authored four conference papers in 2022. In these projects, she has been leading the algorithm development and signal processing of the data from wearable sensors.

• Liao, Y., Cho, P., Baum, M., Aghajani, H., Pan, Z., Beg, M., Rethorst, C., Schembre, S. M., & Basen-Engquist, K. M., “The use of glucose-based biofeedback to motivate physical activity in cancer survivors: A pilot intervention study,” Presentation at the 43rd Annual Meeting & Scientific Sessions of the Society of Behavioral Medicine, Baltimore, MD, (2022, April).  
• Liao, Y., Pandya, M., Aghajani, H., Beg, M., Schembre, S. M., & Basen-Engquist, K. M. . “The use of continuous glucose monitoring as a biobehavioral strategy in physical activity intervention for cancer survivors: Results from a pilot study, ” Presentation at the Society for Ambulatory Assessment Conference (SAA), Virtual Meeting, (2022, June). 
• Liao, Y., Aghajani, H., Schembre, S. M., & Basen-Engquist, K. M., “Daily physical activity levels and glucose pattern in cancer survivors from a pilot intervention study, ” Presentation at the German Society for Behavioral Medicine (DGVM) Congress, Salzburg, Austria, (2022, September).
• Brannon, G. E., Mitchell, S., Affleck, H. A., Aghajani, H., Nguyen, V. P., Brown, K. K., & Liao, Y. (2022, November). “Lessons learned regarding physical activity feedback message personalization, design, timing, and characteristics: A qualitative study examining perspectives of Black and Hispanic women.” Presentation at the American Public Health Association Annual Meeting & Expo (APHA), Boston, MA (Nov. 2022).

The abstract “Lessons learned regarding physical activity feedback message personalization, design, timing, and characteristics: A qualitative study examining perspectives of Black and Hispanic women”, presents some of the results from the IRP (Interdisciplinary Research Program) project, a funded research project by UTA. The IRP is intended to advance interdisciplinary research at UTA in alignment with the guiding themes of the Strategic Plan such as Health and the Human Condition.

Yi Hong, Venu Varanasi, and UTARI’s Muthu Wijesundara, UTA patent recipients, contributed to the University of Texas System’s overall ranking of No. 3 in the list of Top 100 Worldwide Universities Granted U.S. Utility Patents in 2021.

Inventors from The University of Texas at Arlington received 17 patents in 2021, contributing to the University of Texas System’s overall ranking of No. 3 in the list of Top 100 Worldwide Universities Granted U.S. Utility Patents in 2021. UT institutions have earned one of the top five spots in this ranking for four consecutive years. Entire story here.

UTARI’s Automation and Intelligent Systems Division, led by Dr. Nick Gans, has been awarded the subcontract for an Army Phase 2 STTR grant by Novateur Research Solutions. The project is to develop a real-time pavement imaging system that measures deflection depth, trailing and leading, due to a moving wheel load on pavement surfaces.

It will produce a novel system to gather data of the effects of vehicle/pavement interaction. This will aid in adapting and validating complex finite element models in the development of next generation combat vehicles and assessment of aging and contingency infrastructure. Gans and his team was subcontracted on the Phase 1 by Novateur in September 2020.

Army AL&T magazine featured Dr. Wijesundara’s ReHeal Glove, a bioengineered glove designed to promote faster healing in surgically-repaired hands. In partnership with Dr. Chris Allen, M.D. and researcher at the University of Washington, the glove is now being tested by the U.S. Army Medical Research and Development Command’s (USAMRDC) Congressionally Directed Medical Research Programs. You can access the entire article here.

Affordable space exploration beyond the lower Earth orbit will require innovative lightweight structural concepts. Advanced tailorable composites or hybrid material systems can be a means of lightweight exploration vehicles, space habitats, and other space hardware or to enable challenging performance characteristics. However, no commercially available design tools exist to produce advanced highly tailorable designs with optimized load paths or minimized effective coefficient of thermal expansion.

Dr. Liu’s group is working with AnalySwift and Purdue University under a 2022 NASA STTR grant to develop a design tool for tailorable composites and hybrid material systems. The tool will be developed based on the commercial finite element software as “plug-ins”, which provides an integrated computational design framework to enable engineers to leverage the power of commercially available tools for realistic composite structures. Such a tool will reduce the cost of the design optimization associated with tailorable composites and hybrid material systems, accelerating affordable space exploration by NASA and the private sectors.

UTARI’s Automation & Intelligent Systems Division was subcontracted by the University of Georgia. Funded by Army DEVCOM Data & Analysis Center (DAC) via Northeastern University and Georgia, the project is for the “Development of Testing & Evaluation for Soldier-Device Teaming Compatibility, Vulnerability, and Durability in Emergent Situations AI Baseline of Lay Error in Targeting.”

For the last fifty years, the Army has been using the same models for human accuracy in aiming. DAC interest is in updating those models, but in such a way that they can be compared to the old models.   The project will also focus on being able to compare human performance to autonomous system performance in aiming.  As of now, the project is for two years to design the simulation system, run human subject studies and build the new accuracy models. Dr. Nick Gans serves as the UTARI principal investigator for the project.

DAC grant funding originated with Northeastern University where the University of Georgia was subcontracted. DAC serves as the Army’s authoritative source of integrated analytical solutions for the Soldier and Future Force Modernization Enterprise to ensure the Army decisively defeats any adversary, anytime, anywhere. The center provides agile, timely and integrated analytical products for item/system level performance and effectiveness, vulnerability/lethality, and human systems integration, enabling Army Futures Command to conduct streamlined decision processes that are underpinned by sound evidence-based analysis.

UTA’s Upward Bound visited UTARI to learn more about the Institute for Predictive Performance Methodologies and the Automation and Intelligent Systems Division. Students met with researchers and toured UTARI labs.

Upward Bound (UB) is a federally funded program founded in 1965 by the U.S. Department of Education. Located at several institutions throughout the country, the Upward Bound Program at UT Arlington has been providing services to area high school students since 1982. UB looks to serve students who would be the first in their families to attend college, come from economically disadvantaged families, or who have demonstrated they are academically at risk.

UB provides students with tutoring, college readiness workshops, college tours, career development, networking opportunities, scholarship opportunities, and college credit.