Service overview
Fluid flow, heat transfer, multiphase, aerodynamic and turbulence simulation. This service is part of that division and is scoped individually around what you need to learn, decide or publish.
Single-phase flow in pipes, ducts and around bodies is the workhorse of fluid engineering. Many questions can be answered with analytical estimates and established correlations before any simulation is run: the pressure drop in a straight pipe, the head loss of a fitting, the flow split between parallel branches. Starting from these estimates provides a sanity check for later numerical work and sometimes makes the simulation unnecessary.
When geometry or flow becomes complicated, such as manifolds with non-uniform distribution, rotating machinery passages or bluff bodies with separation, detailed CFD adds information that correlations cannot. This service combines the two levels: analytical and network models for quick, transparent answers, and numerical simulation where detail is needed, always cross-checked against each other and against measurements.
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
- Pressure losses and flow distribution that are hard to predict
- Uncertain flow regime (laminar, transitional or turbulent)
- Discrepancy between simple correlations and measurements
Methods and analytical approaches
- Dimensional analysis and correlation-based estimates
- Internal-flow network and detailed CFD modelling
- Pressure-loss and distribution analysis
- Comparison with measured flow data
Applications
- Piping and duct design checks
- Pump and fan passage studies
- Flow-distribution manifolds
Relevant engineering disciplines
Scope, inputs and deliverables
Scope of work
- Definition of the physics, geometry and quantities of interest
- Model set-up with verification and, where data allow, validation
- Parametric or sensitivity studies agreed at scoping
- Results and documentation suitable for reports or publication
- Feasibility check on: geometry and fluid properties
Typical inputs required from you
- Geometry and fluid properties
- Flow rate or pressure conditions
- Measured values for comparison
Deliverables
- Flow analysis report
- Pressure and velocity distributions
- Design observations and limitations
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
Dimensional analysis and correlation-based estimates
Dimensionless groups such as Reynolds number, Euler number and friction factor organise experimental knowledge and allow results to be transferred between scales and fluids. Established correlations for friction in pipes, losses in bends, valves and expansions, and drag on simple shapes give quick estimates with known ranges of validity. We select correlations appropriate to the flow regime and roughness and document their uncertainty. The estimate also provides a first-order target against which numerical results can be tested.
Network models for systems of pipes and ducts
For systems of connected components, one-dimensional network models balance pressure and flow through branches, junctions, pumps and valves. They solve quickly, allow many scenarios to be explored and reveal how a change in one branch affects the whole system. Their weakness is that local effects, such as non-uniform inlet profiles or interactions between close fittings, are represented only through loss coefficients. We therefore identify where network assumptions are reasonable and where a detailed model is justified.
Detailed numerical modelling of flow passages
Where flow distribution, secondary flow, separation or local velocity matter, CFD of the passage resolves the structure that one-dimensional models cannot. Examples include manifolds, diffusers, elbows in close succession and fan or pump inlets. The numerical set-up follows good practice for meshing, turbulence modelling and boundary conditions, and the results are used both to answer the question directly and to derive improved loss coefficients for network models.
Pressure-loss and distribution analysis
Engineering decisions usually depend on pressure loss, flow uniformity or velocity at a point. We compute these quantities with consistent definitions, such as total versus static pressure, and report sensitivity to inlet conditions and roughness. For distribution problems, such as headers feeding parallel channels, uniformity indices summarise performance and show which design changes improve it. The effect of manufacturing tolerances and fouling can be explored with parametric variations.
Comparison with measurements
Measured pressure drops, flow rates and velocity profiles provide the benchmark against which models are judged. We assess measurement uncertainty, instrument placement and flow development upstream of the measurement location, and compare like with like. Discrepancies are investigated: they may reveal a model deficiency, an unrepresentative inlet or a measurement problem. The resulting understanding of agreement and disagreement forms the basis for the confidence statement in the report.
Quality control and good practice
Quality-control approach
- Verification: mesh, time-step and solver sensitivity are examined before results are reported.
- Validation: results are compared with measurements or reference solutions where these exist, and the absence of such data is stated.
- Boundary conditions and material or fluid properties are recorded with their sources.
- Sensitivity to the least certain inputs is shown or explained.
Common pitfalls this service helps avoid
- Using correlations outside their range. Friction and loss correlations are valid for particular regimes and geometries; extrapolating them introduces unknown error.
- Ignoring upstream flow development. Fittings placed close together interact, so summing individual loss coefficients can mislead.
- Mixing static and total pressure. Inconsistent definitions are a common source of apparent disagreement between models and measurements.
- Neglecting roughness and fouling. Surface condition can change friction substantially and drifts over the life of a system.
What good reporting looks like
A flow analysis report describes the system, fluid properties and operating conditions, the dimensionless groups and regime, the analytical or network model with its equations and loss coefficients, any CFD model with verification, the predicted pressure losses and distribution, the comparison with measurements and the uncertainties. It states clearly which results are estimates from correlations and which are from detailed simulation, so that the reader understands the level of confidence of each.
An illustrative scenario
Hypothetical example written for explanation. It is not a client case, a result or a testimonial.
Imagine a header feeding eight parallel channels in a cooling plate. A network model shows that the first and last channels receive noticeably different flows, and a CFD model of the header confirms the cause: a jet from the inlet pipe that over-feeds the far end. A modified inlet diffuser is simulated and the flow uniformity index improves. The analyst notes that the result depends on the inlet profile and recommends measuring that profile before finalising the design.
Questions to settle before you begin
- Can an analytical or network model answer the question first?
- Which fittings are close enough to interact?
- What fluid properties and temperatures apply?
- What measurements exist to check the predictions?
- Which quantity decides the design: loss, uniformity or local velocity?
Key terms
- Friction factor
- A dimensionless measure of wall shear used to compute pressure loss in pipes.
- Loss coefficient
- A dimensionless number describing the pressure loss of a fitting.
- Head
- Energy per unit weight of fluid, often expressed as a height.
- System curve
- The relation between flow rate and pressure loss for a piping system.
- Uniformity index
- A measure of how evenly flow is distributed across channels or an area.
Working together on Computational Fluid Dynamics (CFD) projects
CFD engagements start with a flow-physics review: expected regime, quantities of interest, available geometry and the measurements that could validate results. A coarse pilot simulation can check set-up and cost before the full study. We ask for geometry in a standard exchange format or dimensioned drawings, fluid properties, boundary conditions and any test data. Reports include mesh and model sensitivity so that you can see how much the answer depends on numerical choices. Results are presented as engineering quantities with units, and limits of validity are stated explicitly.
Frequently asked questions
Do you only run CFD?
No. Where an analytical or correlation-based answer is adequate, we say so; CFD is used when its added detail is justified.
Do I always need CFD for pipe flow?
No. Many problems are well served by correlations and network models. CFD is recommended when geometry or flow complexity makes those unreliable.
Can you analyse non-Newtonian fluids?
Common non-Newtonian models can be used if rheological data are provided. Without data, assumptions will be flagged.
Can you check a pump or fan selection?
We can analyse the system curve and compare it with manufacturer data you provide, noting the uncertainty.
Do you design piping systems to code?
No. The service provides research-level analysis, not code-compliant design or certification.
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.