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SIMCenter's research is a collaboration between Ohio State students, faculty, SIMCenter staff, and industry sponsors. SIMCenter uses techniques that meet or exceed standards.
Most projects begin with digital modeling using SIMCenter's vast software library. Our researchers have experience using LS-DYNA, SOLIDWORKS, ABAQUS, HyperMesh, MATLAB and more. After digitally modeling the product or component, it is subjected to the required simulations.
Once the data from the simulations is analyzed, tweaks to the design are applied, and then physical experiments can be performed at SIMCenter or at any of its Ohio State University partners including the Center for Automotive Research, the Aerospace Research Center, or the Center for Design and Manufacturing Excellence.
SIMCenter Focus Areas
Research is focused broadly on mobility, energy and consumer products. SIMCenter has six main focus areas:
Computational Solid and Structural Mechanics
Our research team employs state-of-the-art software for the modeling of complex geometries and joining techniques under linear and non-linear deformation. These techniques are critical for developing strong, safe and lightweight structures in a variety of industries.
Computational Fluid Dynamics
Researchers can accurately predict the performance of steady-state and time-dependent external and internal flows, and acoustics, allowing optimization of varied applications such as the drag forces on vehicles and large-scale air flow in manufacturing systems, like paint rooms.
Systems Modeling, Integration, and Control
The world is full of complex products comprised of hundreds or thousands of components organized into systems and subsystems. Researchers working in this area focus on using system-level plant and control models to simulate interconnected systems, accelerating the development process without sacrificing quality.
Optimization and CAE Automation
SIMCenter employs optimization techniques to automate and enhance the use of CAE tools. These numerical techniques are employed across the areas listed above, and they allow engineers to deliver the best possible designs resulting in improved performance in areas like weight, efficiency and manufacturability.
Non-Physics, Data-Driven Models
These data-driven models, which analyze the data about a specific system rather than the physical behavior, can be applied to various topics such as materials testing and autonomous vehicle technologies.
Our research team uses physical models across multiple disciplines to capture interactions between physical domains, which accelerates development of complex systems such as land vehicles and aerospace systems, while ensuring they are safe and reliable.