Computational & Simulation Research Manuscripts

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.

1. 01Enquiry and requirement assessment
2. 02Technical scoping and proposal
3. 03Execution
4. 04Quality review and delivery, with an agreed round of revisions

Read the full project workflow.

In depth: how the work is done

1. Presenting the model and its assumptions

   A computational paper should state the governing equations or algorithm, the assumptions and the domain of validity before describing results. Assumptions should be justified or acknowledged as simplifications. Where established software is used, the version and settings are given, and where custom code is used, the approach to verification and availability is described. We help authors write this section so that a reader can see exactly what was solved.

2. Verification, validation and convergence

   Verification asks whether the equations are solved correctly, shown through mesh and time-step convergence and comparison with analytical solutions. Validation asks whether the model represents reality, shown through comparison with experiments or independent data. We check that the manuscript presents both, with quantitative measures, and that where validation data do not exist the limitation is stated without implying validation.

3. Sensitivity and uncertainty reporting

   Results depend on inputs that are uncertain. Papers that show how conclusions change with parameter variation are more credible than those reporting a single run. We help present sensitivity studies in a compact way, using tornado charts or tables, and ensure that the discussion distinguishes robust findings from those that depend on specific assumptions.

4. Reproducibility and code or data availability

   Journals increasingly expect data-availability statements, and many encourage code sharing. We help authors prepare clear statements, document input files and parameters, and consider repositories with persistent identifiers. Where data cannot be shared, the manuscript explains why and what is provided instead, such as detailed parameter tables.

5. Choosing figures for simulation results

   Contour plots, streamlines and time histories are visually attractive but can mislead without scales and context. We recommend consistent colour maps, colour-blind-safe palettes, quantitative line plots for comparisons and clear marking of the regions of interest. Fields shown should connect to the claims in the text.

6. Positioning the novelty

   Computational novelty may lie in a new method, a new application or new insight from a known method. Each requires a different framing and a different comparison with prior work. We help authors position the paper accordingly and avoid presenting routine application of standard software as methodological innovation.

Common pitfalls this service helps avoid

• No convergence evidence. Readers cannot tell whether results are numerical artefacts.
• Validation implied but not shown. Agreement with a different case does not validate the present one.
• Single-run conclusions. Without sensitivity analysis, robustness is unknown.
• Unreported solver settings. Missing details make the study irreproducible.

What good reporting looks like

Support for a computational manuscript is documented through a checklist covering model description, verification, validation, sensitivity, reproducibility statements and figure quality, with each item marked as provided by the authors, requested or not applicable. The deliverable is an author-approved manuscript. We do not run simulations to add results, invent validation data or promise acceptance.

An illustrative scenario

Hypothetical example written for explanation. It is not a client case, a result or a testimonial.

Suppose a researcher submits a CFD study of heat transfer in a new geometry. The draft shows impressive contours but no mesh study. After being asked, the researcher supplies results from three meshes, which are summarised in a table with a convergence index. The validation section is limited to a related geometry, so the paper says so and describes the new geometry's results as predictions awaiting experimental confirmation. The revised manuscript is clearer and more defensible.

Questions to settle before you begin

• What evidence shows my solution is converged?
• What independent data validate the model?
• How do my conclusions change with uncertain inputs?
• Can others reproduce the study from my description?
• Is my novelty a method, an application or an insight?

Key terms

Verification

Checking that equations are solved correctly.

Validation

Checking that the model represents reality.

Grid convergence index

A measure of discretisation uncertainty.

Sensitivity analysis

Study of how outputs vary with inputs.

Data availability statement

A declaration of where data and code can be accessed.

Working together on Original Research Manuscripts projects

Manuscript engagements begin with an assessment of what you have: results, methods, figures, a draft and the target journals. We ask for the underlying data or analysis outputs, because every statement in the manuscript must trace to them. Drafting and editing proceed in stages, with queries to you whenever a claim, number or reference cannot be verified from the material supplied. Authors review and approve every version. We never invent data, results, citations or contributions, and we do not promise acceptance, which is decided by editors and reviewers.

Few projects need a single service in isolation. These are the services most often combined with this one.

• Original Research Article Writing

  Structured writing and editing support for original engineering research articles built on your genuine data, methods and findings: organising the scientific narrative, tightening the argument and preparing the manuscript to the conventions of the target journal.

• CFD Simulation Services

  Computational fluid dynamics studies of internal and external flows, thermal effects and mixing, built on an explicit statement of physics, boundary conditions, turbulence treatment and validation basis.

• Finite Element Analysis (FEA)

  Finite element modelling of structures and components for stress, deformation, thermal and dynamic behaviour, with attention to meshing, element choice, boundary conditions and verification against hand calculations or tests.

• Statistical & Methodological Reporting Review

  Independent review of statistical methods and reporting in a manuscript to catch errors, omissions and unsupported inferences before reviewers do.

• Software Papers

  Support for software papers that describe research software, its functionality, design, usage and validation, in the format specific journals expect.