I build process models for companies, SMEs, and research consortia developing decarbonisation technologies — from early-concept simulation through to design support for pilot and demonstrator scale. The output is a working model you can interrogate, plus the engineering insight that comes from building it.
Most clients come to me when they have a process at TRL 2 to 6 that is showing experimental results, and they need to understand how it will behave at larger scale, integrated with other unit operations, or under conditions they cannot test in the lab. Process modelling sits at the intersection of chemical engineering analysis and decision support.
If you already know you need process modelling work, book a scoping call at the bottom of this page. If you are still working out whether you need one, the rest of this page is written for you.
When you need a process model
A process model is the right next step in four common situations.
- Before a scale-up decision. You have lab data at a kilogram-per-hour scale and need to predict behaviour at ten or a hundred times that capacity, including utility demands, heat integration, and equipment sizing.
- Before a techno-economic or life cycle assessment. A TEA or LCA needs a mass-energy balance to populate it. The process model is the foundation that the cost and environmental analyses are built on.
- Before choosing between process configurations. Single-stage versus two-stage absorption. Heat integration with the host site or standalone. The process model lets you compare configurations on the same basis without building each one.
- Before pilot or demonstrator commissioning. Sanity-check expected behaviour, identify operating envelopes, design control philosophy, anticipate scale-up risks.
What a process model answers
Every process modelling engagement is built around the specific questions you need answered. Typical examples:
- What is the steady-state mass and energy balance for this process at the operating conditions of interest?
- What is the utility demand — steam, electricity, cooling water, refrigeration, fuel — per unit of product?
- What equipment is needed, at what duty and what size?
- How does the answer change under sensitivity scenarios — feed composition, operating temperature, pressure, flow rate?
- Where is energy lost, and where does heat integration have most value? (Pinch analysis where relevant.)
- Where does the process risk going off-spec, and what is the operating envelope?
You get a working model you can interrogate, a documented set of assumptions, and the engineering interpretation of what the results mean for your project.
How I run a process modelling engagement
The methodology adapts to the question — there is no single rigid template — but most engagements move through these four stages.
1. Model scoping and tool selection
We agree what the model has to predict, what level of fidelity is needed, and which tool fits. The default is Aspen Plus for conventional process simulation, custom Python for novel operations not well represented in commercial packages, and a hybrid where parts of the flowsheet sit in Aspen and parts in Python (linked via the Aspen Excel interface or custom unit operations). Tool choice matters: over-engineering a simple balance in Aspen costs as much as under-engineering a complex reactor in a spreadsheet.
2. Flowsheet construction
Unit operations, streams, thermodynamic package, and convergence are set up. For early-stage technologies I use literature-based kinetics, equilibrium correlations, or first-principles models depending on what data is available. Assumptions are documented as the flowsheet is built — what data is firm, what is engineering estimate, what is conservative placeholder.
3. Validation and sensitivity
Where experimental or pilot data exists, the model is validated against it and the gaps are characterised. Sensitivity studies show which inputs the answer is most exposed to. Operating envelope studies show where the process is robust and where it breaks down.
4. Engineering interpretation
The model is the input to a decision, not the output. The final step is translating numerical results into engineering recommendations — where to focus development effort, what operating point to design for, what data needs to be collected next, what scale-up risks to plan for.
What you receive
The standard deliverable set has three components.
- The model itself. Aspen Plus file, Python source, or hybrid — fully documented, with input data sources tagged and assumptions explicit. You own the model and can extend it after the engagement.
- Technical report. Methodology, assumptions, validation, results across the scenarios run, sensitivity analysis, and engineering interpretation. Written so a technical reviewer can audit the work line by line.
- Presentation deck. Twenty to thirty slides distilling the technical findings for your internal stakeholders — engineering leadership, project sponsors, investment committee. Pitched at decision-makers who need the implications.
Where process modelling sits alongside TEA, LCA, and feasibility work
A process model is the engineering foundation that other assessments are built on. A TEA needs a mass-energy balance. An LCA needs an inventory of flows. A feasibility study needs all of these plus market and commercial analysis.
| Service | What it answers |
|---|---|
| Techno-economic assessment | Is this project economically viable, and under what assumptions? |
| Life cycle assessment | What is the cradle-to-grave environmental impact, including embodied emissions? |
| Feasibility studies | Should we do this at all — technically, economically, environmentally, commercially? |
| Process modelling and design | Does the process work on paper, and what are the design choices? |
Many clients commission process modelling as a standalone engagement first — to understand the process — and then add a TEA, LCA, or feasibility study on top. Others commission everything together. The scoping call sorts what fits your decision.
Sectors and technologies I cover
I have built process models across a wide span of decarbonisation technologies. The strongest published track record is in:
- Carbon capture, utilisation and storage (CCUS) — post-combustion solvent capture, calcium looping, chemical looping, oxyfuel, novel sorbents
- Direct air capture (DAC) — solid sorbent and liquid solvent routes, including energy integration with low-grade heat
- Hydrogen production — steam methane reforming with capture, electrolysis (PEM, alkaline, SOEC), pyrolysis
- Waste-to-energy with CCUS — including biogenic CO2 recovery for negative emissions
- Power-to-X — synfuel, ammonia, methanol from renewable electricity
- Heat integration and pinch analysis across industrial sites
If your process is not on this list, ask anyway. The modelling methodology is the same across most processes; the unit operations, thermodynamics, and kinetics are the parts that change.
How we work together
Every engagement follows the same five-step shape, scaled to the size of the project.
Step 1. Scoping call
A free 30-minute call. We agree what you need, who the audience is, what decision the work is feeding, and roughly how big the engagement is. I will tell you honestly if a a process model is the wrong tool for your question.
Step 2. Outline proposal
A short written proposal: three to five key questions, numbered tasks, deliverables, hours per task, day rates, total cost, and timeline. Payment is usually structured as 50% on commissioning and 50% on delivery, though terms can be adjusted for institutional clients with longer procurement cycles.
Step 3. Engagement
Work proceeds through the agreed tasks with fortnightly check-ins for engagements over four weeks. Larger projects use a Gantt schedule. I flag risks early — particularly when an assumption I had to make at the start turns out to be wrong.
Step 4. Deliverables
Final report, deck, and calculation files. A presentation session with your team to walk through findings and answer questions.
Step 5. Follow-up
A 30-day window for follow-up questions on the work, included in the engagement. Many clients then commission a follow-on scope.
Common questions
What is process modelling?
Process modelling is the use of simulation software and first-principles engineering to predict how a chemical or physical process behaves under defined conditions. The model predicts mass and energy flows, equipment requirements, utility demands, and operating performance, without having to build the process first. It is the engineering foundation that techno-economic, life-cycle, and feasibility assessments are built on.
What is the difference between process modelling and process design?
Process modelling predicts how a process behaves. Process design specifies how to build it. The two are linked — design uses modelling results to size equipment, set operating points, and define control philosophy — but they sit at different stages of project development. The modelling work I do supports early design choices but does not extend to detailed engineering design (FEED, EPC scope).
Do you use Aspen Plus, Aspen HYSYS, or other software?
Primarily Aspen Plus for steady-state simulation of chemical processes, Aspen HYSYS for oil-and-gas-style processes where pressure-volume-temperature behaviour dominates, and custom Python for novel processes not well represented in commercial packages. For early-stage technologies where the physics is not yet well-characterised, custom Python often outperforms commercial software because you can encode exactly what is known and flag what is not.
How long does a process modelling engagement take?
A focused steady-state model with literature-based inputs usually takes four to eight weeks. A model with experimental validation, sensitivity studies, and multiple configurations compared can take three to six months. The biggest variable is data availability — if you already have experimental data ready to feed in, the work moves much faster.
What does a process modelling engagement cost?
Engagements range from roughly £8,000 for a focused single-configuration steady-state model with literature inputs, up to £80,000 or more for a multi-configuration model with experimental validation, sensitivity, and engineering interpretation. The proposal stage gives you a transparent breakdown of hours and day rates.
Can you model dynamic and transient behaviour as well as steady state?
Yes, when the question requires it. Most decarbonisation questions are answerable with steady-state modelling at the feasibility stage. Dynamic modelling is added when start-up, shut-down, control philosophy, or load-following behaviour is the dominant uncertainty — for example, for CCS plants integrated with variable renewable power.
Do I get the model files, or just a report?
You get the model files. The Aspen file, the Python source, or the hybrid — fully documented and yours to use. Several clients have continued developing the models internally after the engagement, which is exactly the point. The deliverable is knowledge transfer, not a black box.
Get started
If you have a decarbonisation project that needs process modelling, the next step is a 30-minute scoping call. No fee, no obligation, and I will tell you honestly if process modelling is the wrong shape of work for your question.
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