Three engineering faculty receive NSF CAREER awards
Assistant Professors Marcello Canova, Maryam Ghazisaeidi and Wei Zhang recently received the Faculty Early Career Development (CAREER) award—the National Science Foundation’s top award given to support the work of the nation’s most promising junior faculty.
The award recognizes junior faculty who exemplify the role of teacher-scholars through outstanding research, excellent education and the integration of both.
Automotive propulsion technologies have become considerably complex as manufacturers strive to improve fuel economy, emissions, safety and the driver experience, requiring the adoption of advanced control and estimation algorithms. Canova will build the first-ever framework that systematically transfers the accuracy and fidelity of physics-based models into low-order models suitable for control design.
State-of-the-art model-based control design relies almost exclusively on low-fidelity models based on empirical approaches and on approximations of the physical system. The proposed research introduces a transformative framework that analytically generates control-oriented models from the conservation laws for thermal, fluid and chemical systems in nonlinear Partial Differential Equations (PDEs) form. This research will lead to developing a new set of tools for control engineers who need to employ high-fidelity, physics-based models for estimation and control design. It will be directly applied to the estimation of thermal imbalances in Li-ion battery packs for high-performance electric vehicles and to the estimation and control of surge dynamics in downsized boosted engines, two key technologies for current and future automotive powertrains.
Ford Motor Company and General Motors Corporation will participate in the research, providing oversight and facilitating technology transfer. Research, education and outreach will be integrated through The Ohio State University’s Buckeye Current electric motorcycle team, inspired by e-mobility, e-racing and sustainable transportation. Integration will also be pursued through the enrichment of existing courses, creation of web-based teaching tools and student internship programs, and by collaborating with the Teaching Engineering to K-8 (TEK8) programs to attract young talent from underrepresented groups.
Using state-of-the-art computational methods, Ghazisaeidi's work will create a computational framework for predictive and quantitative models of the mechanical behavior of metal alloys to accelerate the design of materials with tailored properties. Mechanical properties, such as strength and fracture resistance, of metal alloys are governed by crystal defects, including dislocations, grain boundaries and solutes. Designing new metal alloys, with enhanced properties, requires detailed knowledge of the properties of these defects.
Ghazisaeidi’s project will provide a new understanding of the structural defects and plasticity in high entropy alloys, a new class of multicomponent alloys with desirable and nonconventional properties. Her work stimulates the study of complex, multi-component alloy compositions that have never been considered before, creating a great potential for discovery of new materials to address the ever-increasing technological needs of the twenty-first century such as energy and efficient transportation. In addition, novel properties of high entropy alloys encourages new ways of viewing fundamental aspects of physical metallurgy, yielding new insights that are applicable to a wide range of metallic alloys.
Ghazisaeidi and her team will also create and disseminate short videos on atomic-scale deformation mechanisms as course enrichment modules to enhance teaching/learning of materials science and provide mentorship. Research opportunities and hands-on activities for K-12 students from the Columbus School for Girls (CSG) will also be provided to encourage and mentor young women towards career paths in science and engineering fields. Ghazisaeidi's research group will host a CSG student for a summer internship each year, during which the student will learn basic coding skills in the context of simple atomic models.
Over the next five years, Zhang will establish new control and game theoretic foundations, along with numerical algorithms, to enable formal and scalable design of hierarchical control systems for large-scale cyber-physical systems.
Many complex engineering systems—such as electricity demand response programs, communication networks, ground and air transportation systems, and robotic networks—involve interactions among a large number of agents with coupled dynamics and decisions due to their shared environment and resources. Such systems are often operated using a hierarchical architecture, where a coordinator determines some macroscopic control signal to steer the population to achieve a desired group objective while respecting local preferences and constraints for individual agents.
Zhang’s research aims to significantly advance the understanding of complex engineering systems that involve coordination of a large population of dynamic agents. One key application is coordinating the vast amount of distributed energy resources to achieve efficient and reliable operations of the future power grid. In collaboration with researchers at national labs and industries, the project is also expected to yield new design principles and practical algorithms for the modernization of the power grid.