Engineering simulation services: CFD, FEA and multiphysics

Geometry, material or fluid properties, loads or boundary conditions, the outputs you need and any validation data. Unknowns can be bounded with documented assumptions and a sensitivity study. See the full guide.

Use CFD for fluid flow and heat transfer; use FEA for structural response. Many problems need both, coupled one-way or two-way. Read the comparison.

Simulation covers a family of methods: finite element analysis for structures and heat transfer, computational fluid dynamics for flow, multibody dynamics for mechanisms, circuit and system-level simulation for electronics, discrete-event simulation for operations, Monte Carlo and agent-based simulation for stochastic systems. The best choice depends on the physics, the question and the data available. Using a method beyond its assumptions produces numbers without meaning, so we begin by defining what decision or claim the simulation must support.

A simple analytic or one-dimensional model is sometimes enough and is easier to validate. Full three-dimensional multiphysics models are justified only when simpler models cannot represent the essential behaviour.

Verification checks that the equations are solved correctly: mesh and time-step convergence, comparison with analytical solutions, conservation and code checks. Validation checks that the right equations are used: comparison with experimental or field data, with uncertainty. A simulation that has not been verified and validated is a hypothesis, not evidence.

We structure projects so that each of these steps is planned, executed and reported, and we say plainly when validation data do not exist and what that implies for confidence.

Simulation output is conditional on inputs. Report the uncertainty from numerical error (for example, a grid convergence index), from input parameters (through sensitivity or Monte Carlo analysis) and from model form (by comparing alternative models where feasible). Show results as ranges, and describe which uncertainty dominates.

Decision makers can then judge whether a difference between two designs is larger than the uncertainty and avoid false precision.

Common pitfalls include using default material or turbulence settings without justification, inadequate mesh in regions of high gradients, ignoring contact or friction effects, neglecting boundary-condition sensitivity, reporting a single run without uncertainty, and comparing with experiments without accounting for measurement error. Another is overfitting model parameters to match data and then claiming predictive power.

A good practice is to separate calibration data from validation data and to report the fit quality on the latter.

Reviewers expect enough detail to reproduce a simulation: software and version, solver settings, mesh description and convergence, boundary conditions, material data and validation. Simulation papers are stronger when they compare with experiments or benchmarks, discuss the limitations of the model and provide data or inputs.

Our manuscript services help present simulation work clearly and completely.

We work with the tool categories used in research and industry, including open-source and commercial packages. Method matters more than tool: results should not depend on a specific interface. Where the client has a licensed tool, we can work within it or prepare input for the client to run. Mentioning a tool on this site does not imply partnership or endorsement.

We encourage open formats for geometry, meshes and results to support long-term reproducibility.