Computational Science and Engineering Laboratory
The Computational Science and Engineering Laboratory (CSE Lab) is dedicated to the development, advancement, and utilization of high-performance, multidisciplinary engineering design tools. The CSE Lab is designed to augment the ongoing internal research and development (IR&D) and research programs of industrial and government sponsors, providing their researchers with unprecedented control in specifying and prioritizing application code features, research objectives, and functional capabilities. Member organizations receive source code and training, as well as installation, user, and application support. Our mission is to:
- develop state-of-the-art multidisciplinary computational kernels;
- enable simultaneous, multidisciplinary design and optimization;
- provide physics-based, system-of-systems discrete event simulation;
- provide a robust, supported codebase to which proprietary and niche capabilities can be added;
- significantly lower recurring, development, and support costs;
- advance research in computational algorithms and high-performance computing methods; and
- transition existing and emerging research capabilities into high-performance production-ready tools.
CSE Lab expertise spans the full range of technical subject-matter areas needed to develop, utilize, and support multidiscipline design and analysis, including:
- Design optimization methods
- Discrete event simulation techniques
- Development of advanced software frameworks
- Visualization of scientific and engineering data
- Graphical user interface design
- High-performance computing
- Technical training and support
The CSE Lab combines contractual investments from multiple government and industry organizations to develop software products and provide support services. These organizations define functional and software requirements, which are then implemented within a modular and flexible software framework. The end result is a validated and robust codebase that supports vastly different computational algorithms and engineering disciplines and computationally-intensive high-performance computing.
A component-based software architecture that supports design optimization and discrete event simulation is used to integrate multiple engineering disciplines and computational codes. This architecture supports multiple programming languages and hardware platforms, and it maximizes code reuse of infrastructural components, e.g., data formats, graphical user interfaces, and job submission and monitoring. Industry standard libraries and toolkits such as OpenMDAO, Python, Qt, and VTK are extensively leveraged throughout the CSE Lab codebase.
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