Hydrogen-Carrier Safety Comparison: Ammonia, Methanol and Liquid Organic Hydrogen Carriers
A chemical engineering comparison of ammonia, methanol, methylcyclohexane and dibenzyltoluene across safety, conversion, storage, logistics, materials, lifecycle boundaries and uncertainty.
Project definition
Problem statement
Hydrogen carriers are often compared using one attractive property such as hydrogen content, storage pressure or existing infrastructure. A real pathway couples synthesis, storage, transport, release, purification, safety controls and the final use case.
The engineering problem is to compare these coupled choices without turning literature positions into plant measurements or presenting one carrier as universally superior.
Project objectives
- Compare ammonia, methanol, methylcyclohexane and dibenzyltoluene carrier pathways.
- Evaluate hydrogen density, storage, conversion, toxicity, fire, spill, materials, infrastructure and lifecycle positions.
- Study port import, road delivery, long-duration storage and fuel-cell endpoint contexts.
- Test balanced, safety, efficiency and infrastructure priority scenarios.
- Propagate evidence uncertainty with a fixed random seed.
- Retain hard gates, FMEA cells and assurance requirements alongside weighted scores.
Project structure
Project components
Carrier register
Declares physical, chemical, safety, conversion, logistics and evidence positions for four carrier archetypes.
Context model
Applies port, road, storage and fuel-cell endpoint conditions without hiding non-applicable assumptions.
Decision model
Compares balanced, safety, efficiency and infrastructure priorities with visible dimension weights.
Uncertainty model
Runs 25,000 fixed-seed samples per carrier and retains score intervals and threshold probabilities.
Safety evidence model
Retains workflow FMEA cells, validation criteria, hard gates and assurance requirements.
Methodology
Project workflow
- 01Define the boundary
Carrier production, transport, release, purification, return logistics and endpoint conditions are declared.
- 02Build the comparison matrix
Four carriers are evaluated across eight tradeoff drivers, four contexts and four evidence cases.
- 03Apply decision priorities
The same retained positions are scored under four transparent weighting scenarios.
- 04Propagate uncertainty
Fixed-seed sampling tests whether score order persists when evidence positions vary.
- 05Review safety gates
FMEA, validation and assurance tables expose issues that a weighted total cannot cancel.
Demonstration scenario
Under equal dimension weights, the DBT pathway has the highest retained screening position at 69.44, followed by methanol, MCH and ammonia. Methanol leads the efficiency and infrastructure priority scenarios, while DBT leads the safety priority scenario. The changing order is the main result: carrier choice depends on context, boundary and engineering priorities.
Engineering
Tools and method
- Tools
- The project uses Python 3.12, NumPy, Pandas, Matplotlib for subject analysis, simulation, and results.
- Engineering model
- Python and NumPy implement the declared carrier, context, evidence and uncertainty calculations.
- Data analysis
- Pandas retains case matrices, summaries, scenarios, FMEA, assurance and sensitivity results.
- Figures
- Matplotlib generates twelve labelled comparison, uncertainty and safety-boundary figures.
- Reproducibility
- A fixed seed, retained configuration, automated tests and Docker reproduce the study.
- Documentation
- The report covers carrier chemistry, process safety, materials, logistics, lifecycle boundaries, methodology, results and further work.
Testing
Evaluation
Evaluation measures
- Hydrogen density, storage simplicity and conversion efficiency
- Toxicity, fire, spill and material compatibility positions
- Infrastructure, supply-chain and carbon-boundary evidence
- Balanced, safety, efficiency and infrastructure rankings
- Uncertainty intervals and sensitivity to dimension weights
- Workflow FMEA, hard gates and assurance completeness
- Automated tests, accessibility audits, repository validation and container reproduction
Project boundaries
- Inputs are literature-informed screening positions and sensitivity cases, not measurements from one operating plant.
- Scores are not failure probabilities, quantitative risk assessments, equipment designs or approval decisions.
- Carrier purity, production route, heat source, loss rate, return logistics, regulation and endpoint requirements can change the comparison.
- A site decision requires process simulation, dispersion and fire analysis, materials review, HAZOP, cost data and professional safety assessment.
Included
- 01Complete reproducible Python source code
- 02Four hydrogen-carrier archetypes and twelve evidence dimensions
- 03512 deterministic context and evidence cases
- 04Four decision scenarios with 25,000 uncertainty samples per carrier
- 05180 workflow FMEA cells and sixty assurance crosswalk cells
- 06Complete CSV, JSON and analytical figure outputs
- 0793-page project documentation in PDF and editable Word formats
- 0816-page setup and usage guide in PDF and editable Word formats
- 0957 annotated references and one sourced literature figure
- 10Automated tests, accessibility audits, repository validation and Docker verification
Project record
No information is collected on this page.
- Permanent project ID
- GP-CH-0TMDVFS
- Catalogued
- 21 Aug 2026
- Completed
- 03 Sept 2026
- Verified
- 03 Sept 2026
- Demonstration
- Included in repository
Handover
After purchase
- 01Payment is confirmed
The project is marked unavailable and cannot be purchased again.
- 02Repository access is granted
The buyer's submitted GitHub account receives access to the private repository.
- 03The purchase record is delivered
The certification sheet is prepared from the reviewed buyer details and sent privately by email.