Physics Based Modelling
Physics Based Modelling for coupled engineering behaviour, system studies and reduced order analysis.
Part of CX24 Engineering. Complementary to conventional CAE.
Engineering disciplines
Select the physics and model fidelity around the problem. Suitability is assessed against the available inputs, operating conditions and intended use.
Understand how a rotating assembly responds across its operating speed range.
Represent shafts, bearings, stiffness and damping to investigate critical speeds, imbalance response and sensitivity to design changes.
Speed range · Bearing properties · Response limitsAssess how temperature changes shape, stress and mechanical performance.
Connect temperature fields or thermal networks to structural response, making material behaviour, interfaces and coupling assumptions explicit.
Thermal loads · Expansion · Interface conditionsLocate the mechanisms behind unwanted vibration and transmitted noise.
Use modal and dynamic response models to study excitation, transfer paths and sensitivity. Correlate against suitable measured evidence where available.
Excitation · Modes · Transfer pathsUnderstand interactions that a component model alone cannot explain.
Connect mechanical, thermal, electrical or control behaviour at the level of detail the engineering question needs. Check units, interfaces and time scales.
Coupled physics · Controls · InterfacesExplore repeated scenarios when a detailed model is too costly to run for every decision.
Build a compact representation from appropriate physics, simulation or test evidence. Measure error and runtime together within a defined operating envelope.
Reference model · Error limits · RuntimeCompare architectures and operating strategies before committing to detailed implementation.
Represent subsystem behaviour, energy flows and operating constraints. Identify which interfaces and parameters drive the whole system response.
Architecture · Operating cycles · Trade studiesOur engagement approach
Verification checks whether the model is implemented as intended. Validation assesses how well it represents the relevant physical behaviour. Both matter.
Name the decision, operating conditions, constraints and quantities that matter.
Set fidelity, inputs, outputs, assumptions, acceptance criteria and intended use.
Implement the governing relationships. Check equations, units, numerical behaviour and reference cases.
Use an identified calibration dataset to estimate uncertain parameters. Record the fitting process and parameter bounds.
Evaluate against evidence not used for calibration where available. Report errors, uncertainty and the limits of the comparison.
Measure accuracy and computational cost on a documented baseline, workload and hardware configuration.
Release for the agreed use only when acceptance criteria are met. Document operation, interfaces, limitations and change control.
The modelling approach
CX24 develops and applies models around a defined engineering problem, then evaluates them against agreed evidence and acceptance criteria. The objective is a model whose purpose, behaviour and limits are understood.
Mechanical ↔ Thermal ↔ System dynamics
Engineering proof
A transparent evidence record, separate from a customer case study.
This space is reserved for an internally developed reference demonstrator. No validated results, performance figures or demonstrator screenshots are currently published here.
It must not be read as evidence of a customer deployment or an industry qualification.
Discuss the validation approachCX24 reference problems, with their development and validation status stated.
Explanations of an approach. Not evidence of client delivery or measured performance.
Actual commissioned work, published only with permission and a defined scope.
Customer outcomes supported by a baseline, method, measurements and publication approval.
Aerospace & Automotive
Industry context changes the operating conditions, constraints, data and acceptance requirements. The problem leads the model, not the industry label.
Defence & Aerospace
Candidate applications include shaft and bearing dynamics, thermally loaded structures, actuator response and reduced models for repeated subsystem studies.
Explore Aerospace ApplicationsAutomotive
Candidate applications include drive unit NVH, battery and power electronics thermal behaviour, suspension response and system duty cycle studies.
Explore Automotive ApplicationsApplication areas describe engineering relevance. They do not assert completed industry deployments or validated customer outcomes.
One engineering capability
Physics Based Modelling complements conventional CAE. The right mix depends on the decision, required fidelity and available evidence.
Detailed engineering
Resolve local behaviour in components and assemblies: stress, deformation, temperature, flow and dynamic response.
Shared physics
Shared evidence
Agreed interfaces
Connected behaviour
Represent the relationships that govern system behaviour, coupled effects and repeated operating scenarios.
A reduced or system model does not automatically replace detailed CAE or physical testing. Its intended use and limitations remain part of the engineering decision.
What an engagement can deliver
Deliverables are agreed for the scope and development stage. A pilot may conclude that more data, a different model or physical testing is needed.
Decision, fidelity, interfaces, assumptions, operating envelope and acceptance criteria.
Versioned model, authorised parameter data, dependencies and reproducible run instructions.
Implementation checks, reference cases and numerical behaviour appropriate to the model.
Comparison evidence, error measures, uncertainty, gaps and stated applicability limits.
Documented workload, baseline, model size, runtime and compute environment where relevant.
Interpretation, acceptance status and the decision to refine, extend or apply the model.
Start with a focused engagement
Start with a focused engineering problem and scale based on the outcome. Agree the scope, inputs, acceptance criteria and review points before committing to a larger programme.
There is no universal pilot duration. A delivery schedule is proposed after the model complexity, data readiness and validation requirements are reviewed. No pricing or performance guarantee is implied.
A technical conversation first
Bring the problem, operating context and available evidence. We will help shape a focused scope and the criteria for deciding what comes next.