MethaNor evolves a 2026 Marine Engineering thesis into an auditable screening model: offshore wind → hydrogen → captured CO₂ → e-methanol → construction → operations → project finance.
Site screening combines wind, bathymetry, metocean severity, port logistics and spatial-planning readiness. Only the thesis point is an academic baseline; comparison candidates are explicitly illustrative until GIS-refresh.
Weighted comparison only: wind 35%, bathymetry 20%, metocean 15%, port logistics 15%, spatial-planning readiness 15%. It is a prioritisation device, not an engineering acceptance criterion.
The screening engine integrates a transparent IEA 15 MW reference-turbine curve against a Weibull distribution, then closes H₂/CO₂/e-methanol material and energy balances. Equations ↘
A 15 MW source has an absolute annual electricity ceiling of 131.4 GWh. Hydrogen stoichiometry alone therefore imposes a hard upper bound on methanol production; adding DAC, synthesis, water and balance-of-plant lowers it further.
Compare public manufacturer data for electrolysis, methanol synthesis, DAC and water treatment. The ranking is a transparent portfolio-fit score, not a universal “best vendor” list. Use a candidate to update only the scenario inputs that are actually supported.
The same weights are applied to every candidate. This is a concept-fit score, not a procurement recommendation, bankability rating or vendor guarantee.
Use the A/B/C buttons in a candidate detail card. Empty or unpublished fields stay visibly blank — MethaNor does not infer vendor data.
Public industrial-equipment prices are usually not published. MethaNor therefore shows “vendor quote required” and keeps category-level literature/target cost context separate from any named manufacturer.
The geometry remains conceptual. Hydrostatic values inherited from the thesis are labelled as academic baselines; component placement below is a portfolio-level arrangement, not class-approved general arrangement.
No RAO/CFD, global finite-element model, fatigue assessment, class approval, detailed scantlings, mooring dynamics or hazardous-area design. Those are explicit gates before FEED/classification.
The baseline below is reconstructed from the thesis mass and vertical-moment register. It is an academic weight model, not a class-approved lightweight/deadweight estimate. Any vendor selection can change mass, footprint and VCG.
Work breakdown, staffing and campaign assumptions are author-defined portfolio inputs. They are deliberately separated from sourced engineering data and are editable in future releases.
Salary assumptions are portfolio inputs, not market quotations. Marine logistics, spares and contractor O&M sit outside this staffing subtotal.
This is a concept-level risk register — not a HAZOP. Probability and impact are screening judgments used to prioritize the next engineering work package.
Change physical and financial drivers. Every KPI recomputes in-browser using the same equation set mirrored in the Python reference engine. Values are screening outputs, not bankable estimates.
The cashflow view is COD-normalized for screening: net CAPEX is placed at year 0; annual production degrades by 0.5%; terminal decommissioning is 3% of gross CAPEX.
Every block below states what is calculated, the equation used, the evidence class and the assumptions that still need upgrading before engineering use.
The thesis mean wind 8.63 m/s at hub height and shape factor k = 2.2 are preserved as an academic baseline. The production version should ingest hourly ERA5 time series and quantify interannual variability.
The browser numerically integrates a transparent piecewise screening power curve between the IEA turbine cut-in, rated and cut-out speeds. It is intentionally not presented as OpenFAST or aeroelastic simulation.
Molar masses imply approximately 188.75 kg H₂/t MeOH and 1.374 t CO₂/t MeOH. The software derives these ratios rather than hard-coding a production yield.
PEM intensity is editable and benchmarked to DOE targets. DAC, synthesis, water treatment and balance-of-plant are screening assumptions with higher uncertainty.
This single equation is the critical scientific correction. It prevents the digital twin from claiming a methanol output that exceeds the electrical energy physically available.
CAPEX, OPEX, price, grant and WACC are explicit scenario controls. Production degrades 0.5%/y and a 3% gross-CAPEX decommissioning allowance is charged in the terminal year.
Robust bisection solves the methanol price, maximum CAPEX, minimum grant, minimum wind resource and maximum WACC required to make the current scenario reach NPV = 0. This is more decision-useful than a single headline IRR.
Each key claim is linked to a technical, government, agency or academic source. Where the evidence does not support a number, MethaNor labels it as a scenario assumption rather than inventing precision.
Primary / officialNREL, DOE, ERA5, EMODnet, MITECO, Puertos del Estado, IEA, IRENA
Academic baselineOriginal thesis values, re-audited before reuse
Scenario assumptionEditable commercial / project-planning input
MethaNor does not replace or rewrite the academic thesis. It treats the thesis as the concept origin, preserves traceable design baselines, exposes what was uncertain and corrects what fails a physical audit.
BSc Marine Engineering · Universidad de Cantabria · Aarón Expósito Monar
15 MW floating wind + PEM + DAC + e-methanol on a semisubmersible platform.
Energy conservation, stoichiometry, source provenance and financial logic checked explicitly.
The 51,058 t/y headline is separated from a single 15 MW unit and moved to a multi-unit hub architecture.
Inputs become editable, results reproducible, evidence tagged and break-even conditions solvable.
Even at 100% capacity factor and zero downtime, the original headline exceeds the electricity available once hydrogen demand is respected. MethaNor fixes the architecture rather than hiding the inconsistency.