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TODO

Simulation

vr.wm-vrt-003 · wm-vrt-003-simulation

Runs of a computational model that imitate a system under stated conditions.

World Models Information and virtual systems INF.VRT.SIM
Bundle → Layer → Finding → QuestionsClassifiersWhat it isWhy it existsDistinguishing featuresWhat robots and AI may and may not doMoral aspectsOwnersLinks to other meta-modelsIdentity and identifiersDirect propertiesRecognitionCapabilities and actionsHazards and failure modesStandards and interfacesContext of useSources

Bundle → Layer → Finding → Questions Filled

3 bundles · 3 layers · 5 findings · 10 questions

Setup What was simulated and how.

Model and inputs

The model version, parameters and initial conditions.

Model version

The model and software version used.

  1. Which model and which software version ran the simulation?
  2. Which assumptions and simplifications does that model make?

Inputs and scenario

Parameters, initial conditions and the scenario applied.

  1. Which parameters, initial conditions and scenario were used?
  2. Where do the input data come from, and how current are they?
Execution How the run was performed.

Run record

Time step, random seeds and computing environment.

Reproducibility

Seeds, time step and environment needed to reproduce the run.

  1. Which random seeds, time step and computing environment were used?
  2. Can the run be reproduced with the recorded setup?
Credibility Whether results can be trusted for the intended use.

Verification and validation

Evidence that the model is solved correctly and fits reality.

Validation evidence

Comparison of results with reference data.

  1. Against which reference data was the model validated, and with what error?
  2. Is the intended use within the validated range?

Uncertainty

Stated uncertainty and sensitivity of results.

  1. What uncertainty ranges are stated for the results?
  2. Which inputs are the results most sensitive to?

Classifiers Filled

Family
World Models
Category
Information and virtual systems
Entry kind
standalone-mm
Navigation path
NAV.INF.VRT.SIM
Domain
INF.VRT.SIM
Industry
Cross-industry
Tags
simulationinf.vrt.sim

What it is Filled

A simulation is the execution of a computational model over time to imitate the behaviour of a real or hypothetical system under stated conditions, producing results that are used for analysis, training, design or decisions. The mathematical model itself, a reusable scenario definition and a live digital twin synchronized with a real asset are separate subjects.

Why it exists Filled

Runs of a computational model that imitate a system under stated conditions.

Distinguishing features Filled

  • An execution of a model, so the same model can yield many simulations with different inputs.
  • Its results are only as credible as its verification, validation and stated uncertainty.
  • Not synchronized with a live asset, which separates it from a digital twin.
  • Distinct from a scenario, which is the reusable definition of conditions a simulation may run.

What robots and AI may and may not do Filled

Must not

  • Present simulated results as observed measurements.
  • Use a model outside its validated range for safety decisions without saying so.
  • Tune inputs to reach a predetermined answer without disclosing it.
  • Discard runs that contradict a preferred outcome.

Only with a human decision

  • Accepting simulation results as the basis for safety, certification or policy decisions.
  • Approving a model as validated for a given use.

May

  • Run simulations with recorded model versions, inputs and seeds.
  • Report results together with their assumptions and uncertainty.
  • Compare results across scenarios and flag sensitivity.
  • Check whether a requested use lies within the validated range.

Moral aspects Filled

  • Simulations inform decisions on safety, public policy and investment, and hidden assumptions can mislead.
  • Overconfidence in precise-looking results can shift responsibility away from human judgement.
  • Simulations of people or populations can encode bias from their inputs.

Who is affected

  • People affected by decisions based on results
  • Engineers and analysts running simulations
  • Regulators and certifying bodies

Owners Filled

Steward

The analyst or engineering team that runs the simulation and answers for its setup and reporting.

Master systems

  • Simulation data management system
  • Model repository
  • Experiment tracking system

Links to other meta-models Filled

requires

  • wm-knw-019-mathematical-computational-model - A simulation executes a computational model.

references

  • wm-vrt-012-simulation-scenario - A simulation runs one scenario definition.

neighbor

  • wm-vrt-001-digital-twin - A digital twin is synchronized with a live asset, while a simulation need not be.

What else AI and robots need to interact with it Filled

Identity and identifiers required Filled

  • Identified by a run identifier in the simulation data management or experiment tracking system.
  • Linked to the model version, scenario and input dataset identifiers it used.

Direct properties not applicable Not applicable

Not applicable

A simulation is a computational run; the quantities it reports are model outputs, not physical measurements of the simulation.

Recognition optional Filled

  • Recognized by a model, inputs, a run configuration and results labelled as simulated.
  • Often confused with the model, with measured data or with a digital twin.

Capabilities and actions required Filled

  • Can explore conditions that are dangerous, costly or impossible to test in reality.
  • Can be repeated with varied inputs for sensitivity and uncertainty analysis.
  • Can train people and systems in virtual conditions.

Hazards and failure modes required Filled

  • Wrong decisions from unvalidated models or unstated assumptions.
  • Results taken out of the validated range.
  • Irreproducible results when setup is not recorded.

Standards and interfaces required Filled

  • Functional Mock-up Interface (FMI) for model exchange and co-simulation.
  • IEEE 1516 High Level Architecture for distributed simulation.
  • ASME V&V standards for verification and validation.

Context of use required Filled

  • Used in engineering, climate and earth science, health economics, defence training and planning.
  • Certification bodies may accept simulation evidence only under validated processes.

Sources Filled

  1. Functional Mock-up Interface (FMI) standard, Modelica Association
  2. IEEE 1516 Standard for Modeling and Simulation High Level Architecture, IEEE
  3. ASME V&V 10 Standard for Verification and Validation in Computational Solid Mechanics, ASME

Open questions

  • Planned model: boundary questions, research and every section remain to be written.

Machine files

Card as JSON Specification AGENTS.md Card backlog vercy.card/1

Provenance

planned (registry candidate) · todo

Built from: models/runtime-index.json, ver-cy/world-models/card-supplements/wm-vrt-003-simulation.json

Planned entry, hidden from the catalogue until researched.