METAMORPH INC — Department of Defense SBIR Phase I: SB142-003

Description

This project will demonstrate the feasibility of extending the probabilistic design verification capabilities of the OpenMETA tool suite with probabilistic programming methods. These extensions will enable correct-by-construction design methodologies in the presence of component, system, environment, and epistemic uncertainties.The OpenMETA model- and component-based design tool suite for the manufacturing-aware design of complex Cyber-Physical Systems (CPS) uses a deterministic model for dynamic simulations, using a causal component model connections, with lumped parameter models represented in Modelica.The current, limited PCC approach allows stochastic modulation of parameters in a Monte Carlo simulation. Thisproject will design and test mechanisms for introducing Probabilistic Dynamics Modeling directly in Modelica, a significant capability enhancement of the Modelica . These extensions will add probabilistic variablesparameters, signals, input/outputs to the model that could vary within a simulation run, and could be used to accurately incorporate the uncertainty in the dynamics models.The current PCC is insufficient for capturingtime-dependent, non-invariant signals. The proposal will add a probabilistic dynamics model to Modelica to address these limitations. Furthermore, the project will investigate mechanisms for addressing Inverse Problems, using inferencing techniques (Bayesian, MCMC), and sampling reduction approaches