Examine assumptions, governing mechanisms, equations, reproducibility, validation boundaries and open scientific questions.
Scientific methods · Modelling hierarchy · Reproducible resources
Research Methods, Modelling and Reproducible Engineering Tools
Selected methods, computational environments and public technical resources connecting applied physical chemistry, chemical kinetics, reactor modelling, CFD, thermochemical conversion, process development, experimental validation, pilot systems and industrial decision support.
How to use this page
One technical foundation serving different levels of decision
The same scientific resource can have different value for a researcher, engineer, manager or student. The purpose is therefore to present methods with enough technical depth for specialists while keeping their assumptions, maturity and practical relevance understandable to broader audiences.
Connect chemistry and transport phenomena to reactor behaviour, equipment performance, pilot configuration and scale-up risk.
Identify which evidence is decision-ready, which uncertainties remain and what development work is justified next.
Follow the progression from a technical question through modelling and validation to a defensible practical conclusion.
Research and engineering themes
From molecular mechanisms to process and technology decisions
The work connects physical and chemical phenomena across molecular, reactor, equipment and process scales. The objective is not maximum model complexity, but the level of scientific detail required to answer the decision reliably.
Chemical Kinetics and Reactive Systems
- Detailed and reduced reaction mechanisms
- Ignition, oxidation and fuel-conversion chemistry
- Reaction-rate, flux and pathway analysis
- Sensitivity and kinetic-control analysis
- Mechanism reduction and adaptive chemistry
- Combustion emissions and nanoparticle inception
Reactor, Flow and Multiscale Modelling
- Zero- to three-dimensional modelling
- Homogeneous and heterogeneous reactors
- Reactive-flow computational fluid dynamics
- Turbulence–chemistry interaction
- Heat, mass and species transport
- Residence-time and mixing effects
Thermochemical and Sustainable Processes
- Pyrolysis and gasification
- Reforming and syngas production
- Biomass, residues and alternative feedstocks
- Biochar and carbon-management screening
- Waste-to-X and chemical recycling
- Energy and resource integration
Process Development, Validation and Scale-Up
- Technical feasibility and claims assessment
- Experimental and pilot-programme planning
- Reaction–transport regime diagnosis
- Process intensification
- Operability, control and scale-up risk
- Technology and R&D decision support
Fit-for-purpose modelling
The appropriate model depends on the decision, not on complexity alone
A reliable development programme often moves through several modelling levels. Increasing detail is justified only when it resolves a material uncertainty, changes a decision or provides evidence that cannot be obtained more simply.
Balances and screening calculations
Establish orders of magnitude, thermodynamic limits, material and energy balances, plausible operating windows and immediate feasibility constraints.
Kinetic and mechanistic models
Resolve reaction pathways, controlling species, time scales, sensitivities, competing chemistry and intrinsic conversion behaviour.
Reactor and CFD models
Couple chemistry with residence time, mixing, transport, heat transfer, phase behaviour and equipment-scale flow structures.
Pilot and scale-up interpretation
Test representative operation, validate model assumptions and address operability, control, materials, safety, reliability and industrial transfer.
Methods and computational environments
Complementary tools selected according to the technical problem
Commercial software, open-source platforms and custom scientific programs are selected according to the required chemistry, physics, modelling resolution, uncertainty and available validation evidence.
CFD and Reactive Flow
- ANSYS Fluent
- OpenFOAM
- Combustion and reactive-flow modelling
- Species and energy transport
- Heat transfer
- Multiphase systems
Chemical Kinetics
- CHEMKIN
- Cantera
- Detailed and reduced mechanisms
- Reactor networks
- Sensitivity and pathway analysis
- Mechanism reduction
Scientific Computing
- Python
- Fortran
- MATLAB
- C/C++
- Jupyter Notebook
- Data analysis and visualization
Engineering Analysis
- Thermodynamics
- Reaction engineering
- Heat and mass transfer
- Process calculations
- Validation and optimization
- Scale-up and technology assessment
Public technical repositories
Reproducible resources with explicit maturity boundaries
The repositories below serve different purposes. Implemented screening calculations, engineering diagnostic frameworks, reconstructed research models and scientific hypotheses are not presented as equivalent forms of evidence.
Desulfurization Reaction–Transport Regimes
A structured framework for distinguishing kinetic, mass-transfer, diffusion, adsorption, hydrodynamic and downstream-separation limitations in sulfur-removal processes.
AOP Kinetic Process Framework
Matrix-aware Python calculations for hydroxyl-radical scavenging, radical utilization, apparent kinetics, treatment time and selected process indicators.
Biomass Process Modeling Framework
Cantera-based screening calculations, curated sensitivity cases and model-consistency documentation for biomass conversion, biochar, syngas and heat production.
NDMS Persistence–Stabilization Closure
An executable conceptual closure investigating the competition between reversible precursor association, dissociation, non-stabilizing loss and particle stabilization.
Technology development · Validation · Scale-up
An evidence-gated path from scientific understanding to industrial implementation
The methodology connects problem definition, governing-mechanism analysis, fit-for-purpose modelling, representative validation, pilot development and scale-up. Progress to the next development stage is justified by the evidence required for the decision rather than by model complexity or an assumed technology pathway.
Clarify the engineering problem, target value, system boundaries, constraints, uncertainties and decision that must be made.
Identify and rank the governing chemistry, transport, thermodynamics, hydrodynamics and system-level bottlenecks.
Select the simplest defensible model and generate the laboratory, computational or analytical evidence needed to test the governing assumptions.
Test representative operation and reassess mixing, residence time, heat and mass transfer, materials, control, reliability and other scale-dependent risks.
Integrate technical performance with operability, safety, economics and environmental constraints, then capture validated learning for reuse in future developments.
Evidence boundary: This is a structured methodology for technology development and engineering decision support. Application to a specific technology still requires representative data, domain-specific engineering, appropriate safety and regulatory review, and project-specific validation.
Controlled research-development programme
Kinetic Intelligence
Historical work on reaction rates, sensitivity, chemical reaction networks and mechanism reduction has been extended into a causal adaptive-chemistry study implemented and tested with Python and Cantera.
The published computational validation uses GRI-Mech 3.0 and USC Mech II to separate three questions: when the chemistry-refresh schedule should change, whether the reduced chemistry remains accurate, and whether the resulting implementation is computationally faster. The study includes a complete reproducibility supplement with code, computational-validation evidence, diagnostics and runtime analysis.
Published computational-validation milestone:
the adaptive method passed the defined accuracy gates for the
tested methane/air cases and demonstrated transfer to a second
detailed mechanism using a mechanism-specific candidate domain.
Static USC reduction achieved 4.56–4.99× speed-up on the tested
computer, while the present adaptive Python/Cantera prototype
was slower because controller and mechanism-management
operations dominated runtime. Accuracy and computational
acceleration are therefore reported as separate results.
Technical modules and evidence chain
- Mechanism audit and provenance
- Scenario and reactor-case management
- Reaction-rate and flux analysis
- Sensitivity and kinetic-control diagnostics
- Chemical reaction-network analysis
- Static and causal adaptive mechanism reduction
- Conservative state projection
- Computational validation, transfer and runtime attribution
Evidence, software and provenance policy
Public release follows technical and rights review
Archived materials are not uploaded automatically. Scientific value, software integrity, ownership, confidentiality and legal suitability are reviewed before public use.
Technical integrity
Equations, assumptions, units, balances, numerical methods and evidence or validation status are reviewed before results are described as reproducible, predictive or suitable for engineering use.
Authorship and licensing
Historical codes, mechanisms, figures and documents are screened for authorship, ownership, licence conditions and third-party reuse restrictions.
Confidentiality
Employer, client and project information is excluded unless it is already public, non-confidential, rights-cleared and appropriate for professional reuse.
This page presents scientific methods, modelling environments and public technical evidence. It supports the wider professional profile without converting unfinished research into marketing claims.
The Consulting page translates selected, rights-cleared and sufficiently supported capabilities into defined services, practical deliverables, working methods and engagement boundaries without duplicating the technical resources published here.
Public repositories and research prototypes support technical credibility, but they are not presented automatically as validated commercial products or as substitutes for system-specific assessment, representative data and appropriate validation.