Research Project (Studienarbeit) · Institut für Maritime Logistik (MLS), TU Hamburg · Grade: 1.7 · May–November 2024
A data-driven research project evaluating 13 alternative marine fuels across 11 weighted parameters to identify the most viable decarbonization pathway for the maritime industry. Conducted at Fraunhofer CML / TU Hamburg under Prof. Dr.-Ing. Carlos Jahn and supervised by Shubhangi Gupta.
Core finding: LNG, Biodiesel (FAME), and LNG + Electric Battery were identified as the most commercially viable bridging fuels. Green hydrogen and green ammonia remain promising long-term candidates but lack infrastructure readiness today.
- Defined scope, objectives, and timeline across 6 months
- Managed all tasks and milestones using Jira (Kanban board)
- Led literature review on fuel overview (13 fuel types)
- Authored the conclusion and final documentation
- Coordinated 9 supervisor meetings and 11 internal team meetings
The project followed an iterative, milestone-based workflow using agile principles adapted for academic research:
Sprint structure: Work was organized in roughly 2-week cycles aligned with internal and supervisor meetings. Each cycle had a clear focus — from initial brainstorming (May) through literature division, parameter definition, scoring, drafting, and revision (Oct).
Task management: All tasks were tracked on a Jira Kanban board with columns for To-Do, In Progress, Review, and Done. Task ownership was clearly assigned per team member and topic area, ensuring accountability and parallel workstreams.
Collaboration tools:
| Tool | Purpose |
|---|---|
| Jira | Task tracking, Kanban board, milestone management |
| Monday.com | Gantt chart — project timeline and dependencies |
| Miro | Mind mapping and brainstorming |
| Zotero | Reference management (100+ academic sources) |
| Zoom | Bi-weekly supervisor check-ins and team standups |
| LaTeX | Standardized report formatting |
| Power BI | Data visualization and dashboard reporting |
Deliverables were iterative — a first draft was completed mid-September, reviewed by the supervisor, revised through two feedback cycles, and finalized by November 1.
Project Gantt chart — 6-month timeline from kickoff to submission
Parameters were grouped into 4 importance tiers based on peer-reviewed literature on maritime fuel adoption:
Tier 1 — weight 0.20 (critical): Carbon emissions (WtW CO₂eq/MJ) · Cost (USD/mmBTU)
Tier 2 — weight 0.16 (major): Port availability worldwide
Tier 3 — weight 0.08 (significant): Safety · Technology readiness (TRL-based) · Volumetric energy density
Tier 4 — weight 0.04 (moderate): Infrastructure needs · Existing subsidies · Regulation · Political environment · Supply chain challenges
Each fuel was scored 1–10 per parameter using quantitative thresholds (e.g., specific CO₂eq/MJ ranges, USD/mmBTU price bands) derived from DNV's Alternative Fuels Insight platform, IRENA, IEA, and IMO reports. Scores were multiplied by weights and summed to produce a final composite score.
Parameter weight distribution — Tier 1 parameters (carbon emissions, cost) carry the highest weight at 20% each
Final composite scores (max 10.0). LNG (7.92), Biodiesel (7.28), and LNG + Battery (7.08) rank highest overall.
Each cell shows the raw score (1–10) for that fuel × parameter combination. Light green = low score (1), dark green = high score (10).
Bridging fuels are not the final destination — they are a necessary stepping stone. The risk is carbon lock-in: over-investment in LNG infrastructure may delay the transition to fully zero-emission fuels. Regulatory frameworks must balance short-term practicality with long-term emission targets.
Team of 3 M.Sc. MEM students — responsibilities divided as follows:
| Role | Responsibilities |
|---|---|
| Project Leader (Swarit) | Scope definition · Jira management · Fuel overview · Conclusion · Final documentation |
| Team Member 2 | Evaluation parameters · Implementation · Scoring methodology |
| Team Member 3 | Hybrid fuels · Electrification of ports · Introduction |
All members contributed equally to literature research, brainstorming, and bridging fuel analysis.
├── README.md
├── images/
│ ├── weighted_score_ranking.png
│ ├── scoring_heatmap.png
│ ├── parameter_weights.png
│ └── gantt_chart.png
This project was completed as part of the Research Project (Studienarbeit) module at the Institut für Maritime Logistik (MLS), Technische Universität Hamburg-Harburg, WS 2023/24. All findings are based on literature available up to October 2024. This is an academic research project and does not constitute professional engineering or policy advice.