OPEN-SOURCE SOFTWARE LICENSING OPPORTUNITY RAVEN: Comprehensive Uncertainty Quantification and Optimization for Complex Systems

OPEN-SOURCE SOFTWARE LICENSING OPPORTUNITY RAVEN: Comprehensive Uncertainty Quantification and Optimization for Complex Systems RAVEN is a versatile framework designed for uncertainty quantification, risk assessment, and optimization of complex systems, integrating advanced statistical, data analysis, and AI techniques for enhanced system understanding and performance. Overview: Developed in 2012 under the Risk Informed Safety Margin Characterization (RISMC) pathway of the Light Water Reactor Sustainability (LWRS) program, RAVEN (Risk Analysis and Virtual ENvironment) addresses the need for modern risk evaluation in complex systems like nuclear power plants. It caters to the increasing demand for sophisticated tools to analyze systems' responses under varied conditions, especially considering the uncertainties inherent in these systems. RAVEN's design philosophy aims to be user-friendly for engineers and scientists while offering a modular structure for easy expansion by developers. This balance makes RAVEN a powerful tool for a wide range of applications in different sectors. Description: RAVEN operates by perturbing system responses using various strategies (Monte-Carlo, Latin Hypercube, etc.) and analyzing the data through classical and advanced data mining approaches. It works in tandem with other INL software (like RELAP5-3D, MAAP5, BISON) to model complex physical systems. RAVEN's strength lies in its ability to manage parallel dispatching of simulations and its use of AI algorithms to create surrogate models for complex analysis tasks. This multifaceted approach allows for thorough uncertainty quantification, reliability analysis, and parametric studies, making it a comprehensive tool for risk assessment and optimization in complex environments. Benefits: Versatile Analysis Capabilities: Supports various analysis methods, including regression, risk assessment, and data mining. Integration with Third-party Software: Enhances existing physical models with advanced analytical capabilities. Advanced AI Utilization: Employs AI for surrogate modeling and complex system analysis. Parallel Computing Support: Efficiently manages computational resources for large-scale analyses. Customizable Workflow: Offers flexibility in analysis flow construction to suit specific project needs. Applications: Risk assessment and safety margin characterization in nuclear power plants. System response analysis in multi-physics environments. Optimization and data analysis in engineering and scientific research. Uncertainty quantification in complex physical and engineering systems. Advanced modeling and simulation in various industries, including energy, manufacturing, and research. Access: https://github.com/idaholab/raven IP Status: Copyright asserted on software titled “Risk Analysis and Virtual ENvironment: RAVEN,” BEA Docket No. CW-14-01. Partner with Idaho National Laboratory (INL) for Access to Pioneering Technology and Mutual Growth Managed by Battelle Energy Alliance, LLC, INL offers unique opportunities for businesses to access and license advanced technology. Our agreements are tailored to provide flexibility and affordability, particularly supporting small businesses in their growth and innovation endeavors. By licensing our intellectual property, you not only gain access to groundbreaking technology but also contribute to economic development and public welfare. We invite you to explore our technology portfolio, designed to give your organization a competitive edge in the market. Learn more about our licensing opportunities and the support we provide at: https://inl.gov/inl-initiatives/technology-deployment . For specific discussions on how your business can benefit, please contact Andrew Rankin at [email protected] . INL’s Technology Deployment department focuses exclusively on licensing intellectual property and partnering with industry collaborators capable of commercializing our innovations. Our goal is to commercialize the technologies developed by INL researchers. We do not engage in purchasing, manufacturing, procurement decisions, or providing funding. Additionally, this is not a call for external services to assist in the development of this technology.