Service overview
Single and multi-objective, metaheuristic, Bayesian and topology optimisation; decision models. This service is part of that division and is scoped individually around what you need to learn, decide or publish.
Topology optimisation asks where material should be placed within a design space to carry loads efficiently. Starting from a block of possible material with specified loads and supports, the algorithm removes material that contributes little and keeps what carries load, producing organic-looking shapes that can be remarkably efficient. It has become important with additive manufacturing, which can build complex geometries that conventional processes cannot.
The results of a topology optimisation are concepts, not finished designs. They depend on the load cases, constraints and the filtering that controls feature size, and they must be interpreted, smoothed and verified before manufacture. Good practice treats topology optimisation as an early-stage idea generator whose output is refined by shape and size optimisation and checked with detailed analysis.
If you plan to publish the outcome, see manuscript & publication support, for example computational & simulation manuscripts or original research article writing.
What this service covers
Problems this service can address
- Concept stage lacking a good starting layout
- Optimised layouts that are impractical to manufacture
- Multiple load cases and constraints
Methods and analytical approaches
- Density-based topology optimisation
- Filtering and minimum-feature-sise control
- Multiple load case and stress/frequency constraint handling
- Post-processing for manufacturability
Applications
- Lightweight structural concepts
- Additive-manufacturing-oriented designs
- Heat-sink and flow-path layout concepts
Relevant engineering disciplines
Scope, inputs and deliverables
Scope of work
- Data audit and definition of the prediction or decision task
- Model development with structure-aware validation and baselines
- Evaluation, error analysis and uncertainty reporting
- Documentation sufficient for others to reproduce the work
- Feasibility check on: design space, loads and supports
Typical inputs required from you
- Design space, loads and supports
- Objectives and constraints
- Manufacturing process assumptions
Deliverables
- Topology-optimised concept geometries
- Performance verification with refined analysis
- Notes on manufacturability
Highly specialised requests are first checked for feasibility from this information. Please do not send confidential data through the public form; describe it first and agree secure transfer afterwards.
Project workflow and method
- 01Enquiry and requirement assessment
- 02Technical scoping and proposal
- 03Execution
- 04Quality review and delivery, with an agreed round of revisions
Read the full project workflow.
In depth: how the work is done
Density-based formulations
In the common density-based approach, each element has a pseudo-density between zero and one, with intermediate values penalised so the solution tends towards solid or void. The objective is typically to minimise compliance (maximise stiffness) subject to a volume constraint, or to minimise mass subject to stiffness or stress limits. Sensitivity analysis provides gradients efficiently, and gradient-based optimisers update the design. Convergence behaviour depends on penalisation and move limits.
Filtering and minimum feature size
Without regularisation, topology optimisation produces mesh-dependent designs with checkerboard patterns and extremely fine features. Density or sensitivity filters and projection methods impose a minimum length scale, which links to manufacturing limits. The choice of filter radius changes the topology significantly, so we examine its influence and relate it to the capabilities of the intended process.
Load cases and additional constraints
A single load case can give a design that is fragile to any other load. Multiple load cases are combined in the objective or as constraints. Stress constraints are harder than compliance because they are local and singular, but they matter for strength-critical parts. Frequency constraints address vibration, and thermal or fluid objectives allow heat-sink and flow-path concepts. Each addition increases problem difficulty and solution time.
Interpretation and post-processing
The raw optimised density field is converted into a geometry by thresholding and smoothing, then often reconstructed as a CAD model. This step changes the performance, so the interpreted geometry is reanalysed. We discuss how to simplify the result, add fillets, treat supports and handle regions that are fragile in practice, noting that final design decisions belong to the engineers responsible for the part.
Manufacturability, especially for additive processes
Additive manufacturing relaxes many constraints but introduces others: overhang angles, support structures, minimum wall thickness, residual stress and anisotropy of properties. Overhang-aware and self-supporting formulations reduce the need for supports. Conventional processes impose casting or machining limits, which can also be encoded as constraints. We examine which manufacturing rules are essential and how they affect the result.
Quality control and good practice
Quality-control approach
- Data are audited for quality, leakage and drift before modelling.
- Validation respects data structure (by specimen, machine or time) and includes simple baselines.
- Performance is reported with uncertainty and failure cases, not only headline scores.
- Model limits and the conditions under which it should not be trusted are documented.
Common pitfalls this service helps avoid
- Treating the output as final design. Raw topology results need interpretation, smoothing and verification.
- Single load case. Designs may perform poorly under loads not considered.
- Ignoring feature size and manufacturing limits. Mathematically valid features may be impossible to produce.
- Comparing with a weak baseline. Reported savings depend on the quality of the reference design.
What good reporting looks like
A topology optimisation report states the design space, loads and supports, objectives and constraints, the formulation and filter settings, the optimised layouts for the cases studied, the interpreted geometry, a verification analysis of the interpreted design with a refined model and any additional load cases, a comparison with a reference design, manufacturing considerations and limitations. It presents the results as concepts and does not claim that the design is ready for production or certified.
An illustrative scenario
Hypothetical example written for explanation. It is not a client case, a result or a testimonial.
Suppose a researcher develops a lightweight bracket concept for a defined set of loads. A density-based optimisation with a volume limit and a minimum feature size produces a branching structure. After smoothing, a refined finite element analysis shows higher stress near a junction, which is addressed by adding fillets. The final concept is compared with a conventional machined bracket on stiffness per unit mass, and the report notes that fatigue life has not been assessed.
Questions to settle before you begin
- Which load cases and supports are known?
- What is the minimum feature size the process can make?
- Which constraints beyond stiffness matter: stress, frequency or others?
- What reference design will I compare against?
- How will I verify the interpreted geometry?
Key terms
- Compliance
- A measure of flexibility, equal to the work done by the loads; minimising it maximises stiffness.
- SIMP
- A density-based penalisation approach for topology optimisation.
- Filter radius
- The length scale controlling minimum feature size.
- Checkerboarding
- A numerical instability producing alternating solid and void elements.
- Overhang
- A surface that needs support during additive manufacturing.
Working together on Engineering Optimisation & Decision Science projects
Optimisation engagements begin with formulation: objectives, decision variables, constraints and the model or experiment used to evaluate designs. Much of the value is created at this stage, because poorly posed problems give unusable optima. We ask for the evaluation model or data, bounds on variables, constraints and any manufacturing or operational limits. Algorithms are chosen to suit evaluation cost and problem structure, and results are checked against independent evaluations and robustness tests. Reports present trade-offs rather than a single answer where objectives conflict, and they state assumptions behind the model that an optimiser could exploit.
Frequently asked questions
Is a topology-optimised result a finished design?
No. It is a concept requiring interpretation, detailed design, verification and testing.
Can you provide a CAD model of the result?
An interpreted geometry can be described or supplied in a suitable format. Final CAD and detailed design remain the responsibility of your design team.
Do you handle stress-constrained problems?
Yes, though they are more demanding and may need more time and care.
Can you optimise for additive manufacturing?
Yes, by including overhang and feature-sise considerations. Process-specific effects such as residual stress need separate analysis.
Is this the same as the structural optimisation service?
Related, but topology optimisation changes material layout, whereas structural optimisation typically adjusts sizes and shapes of a given layout.
How is this service scoped and priced?
After your enquiry we review what you need, ask for missing information and send a written scope and quotation. Price depends on complexity, deliverables and timeline. See the project workflow.