Simulationspecific

Simulation-specific refers to practices, data structures, interfaces, and workflows that are tailored to the needs of simulation work rather than general software development. The term is used to describe abstraction layers and components designed to model time, events, stochastic behavior, and system state in a repeatable and scalable way.

Scope includes discrete-event simulations, agent-based models, physical solvers integrated with simulation drivers, and calibration workflows. It encompasses time management, random number stream control, scenario management, result logging, and reproducibility.

Key characteristics include deterministic replay with controlled randomness, modular separation between model and platform, solver-agnostic interfaces, and performance considerations such as parallel execution and load balancing. It often requires specialized data models and ontologies to describe entities, events, and interactions.

Common techniques include event scheduling queues, time-stepping engines, multi-method support, and simulation-logging metadata. Tools and practices emphasize validation against analytical benchmarks, sensitivity analysis, and reproducible workflows with versioned scenarios.

Applications span engineering, logistics, epidemiology, and virtual prototyping, where accurate timing, repeatability, and scalable experiment design are essential.

Challenges include portability across solvers, numerical stability, nondeterminism in parallel simulations, and maintaining reproducibility across platforms and architectures.

See also: simulation, modeling, discrete-event simulation, agent-based modeling, numerical simulation.