Discrete Stochastic and 0D/1D Modeling and Simulation Platform
New:
Graphical Interface for Integrating PyCATSHOO Models and Compliance with the FMI 3.04 Standard
Hybrid systems combine two types of behavior:
1. Discrete and stochastic behavior, generally arising from failures and repairs of the system’s components.
2. Continuous and deterministic physical phenomena, which evolve within the system.
Conventional approaches to probabilistic safety assessment are unable to account for both types of behavior simultaneously.
As a result, conservative assumptions are introduced to compensate for the lack of physical phenomenon modeling, which often leads to the loss of valuable safety margins.
PyCATSHOO addresses this limitation.
PyCATSHOO is based on the theoretical framework of Piecewise Deterministic Markov Processes (PDMPs). This framework is implemented through Distributed Hybrid Stochastic Automata (DHSA).
Such an approach minimizes the additional complexity introduced by the hybrid behavior of systems.
PyCATSHOO is written in C++. It can be used on Windows, Linux, and macOS, and it takes advantage of multicore architectures through the use of MPI (Message Passing Interface), which must be installed on the target machine.
Both Python and C++ APIs are available. These APIs can be used either to model specific systems or for generic modeling, such as the creation of libraries of component models.