Simcenter Studio is an application in the Simcenter portfolio for generating and evaluating system architectures during the early concept phase. The software includes patented technology for engineers and data scientists to create novel and topologically different system architectures. Simcenter Studio also combines system simulation, optimal control methods, and reinforcement learning on top of a state-of-the-art machine learning and scientific computing stack to automatically simulate and evaluate of hundreds of these architectures. This allows engineers and data scientists to create user defined procedures in computational notebooks for generative engineering.
Simcenter Studio
Generative engineering in the early concept phase
Simcenter Studio
Simcenter Studio is an application in the Simcenter portfolio for generating and evaluating system architectures during the early concept phase. The software includes patented technology for engineers and data scientists to create novel and topologically different system architectures. Simcenter Studio also combines system simulation, optimal control methods, and reinforcement learning on top of a state-of-the-art machine learning and scientific computing stack to automatically simulate and evaluate of hundreds of these architectures. This allows engineers and data scientists to create user defined procedures in computational notebooks for generative engineering.
AI-based generation of system architectures
Generate system architectures by expressing what is needed and let the software help you discover novel designs. Driven by a patented AI technology, Simcenter Studio generates a wide range of system architectures from an engineering-friendly formal model description. This avoids the problem of design fixation using a systematic and reproducible approach which also captures essential knowledge in the early design phase.
Computational notebooks for system simulation
Evaluate generated or imported system architectures by system simulation from inside of computational notebooks. Computational notebooks combine narrative text, mathematical equations, code, models, and visualization so that workflows, user-defined procedures, executable models, and documentation are included in the same place. Accelerate your evaluation runs by automatically spawning and pooling system simulations via an advanced scriptable interface using Python. Gather all results into a single HDF5 file to ease post-processing. This way computational notebooks enable design decisions to be reproducible and documented.
Controller generation for realistic trade-studies
Automate controller generation to create the most accurate and realistic trade studies possible in the early design stages. Use either a model-free approach via reinforcement learning or a model-based approach via optimal control. Execute the closed-loop evaluation of hundreds or thousands of variants to gain a competitive edge.
Guided selection of the best system architecture
Bring all relevant stakeholders together to do multi-attribute balancing with an intuitive web-based application. Use AI to generate compliant architectures and leverage an interactive tool for cross-filtering and ranking of thousands of designs. A recommender system can suggest potentially overlooked alternatives from the vast design space. Set up your own workflows to generate use-case specific reports in computational notebooks to enable targeted discussions on individual designs.
