Simulation-driven experimental design | Measurement uncertainty | Model validation
The Computer-Aided Validation Laboratory (CAVL) is a research laboratory developing open-source software for simulation-driven experimental design, measurement analysis, uncertainty quantification and engineering model validation.
Our goal is to help researchers and engineers design better experiments, understand measurement uncertainty and make evidence-based engineering decisions by connecting physics simulations with experimental measurements.
Our research and software development are led by a team at the UK Atomic Energy Authority (UKAEA), working with academic and industrial collaborators.
PyVale is our flagship Python platform for simulation-driven experimental design. It connects physics simulations, sensor simulation, measurement inference and information exploitation to support the design and analysis of engineering experiments.
GitHub Repository | Documentation & Examples | Python Package
Riley is a high-performance software rasteriser written in Zig for synthesising realistic images from finite element simulations. It supports scientific camera simulation and digital image correlation uncertainty quantification, and is integrated into PyVale's rendering framework.
GitHub Repository | Python Package
Our tools are open-source and intended for researchers, experimental engineers and software developers across academia and industry.
Explore our repositories, documentation and examples to get started.
