Assessing the reliability of a ship energy performance simulation tool through on-board data
Bibliographic record
Abstract
• A holistic approach is suggested for assessing the ship envelope, weather conditions, and energy system. • Errors below 4% can be obtained by replicating the actual operation of the ship. • Detailed information can be obtained to enhance the development of digital twins. • Different operating conditions can be investigated by stakeholders. To mitigate the environmental impact of shipping on climate change, it is nowadays urgent to explore energy efficiency and cost-effective measures by means of reliable digital tools. These are becoming essential for assisting the design of new ships and the refurbishment of the existing ones, as well as for assessing and optimizing the energy performance of a ship during its entire life-cycle. This paper focuses on the verification of the reliability of a novel ship energy dynamic simulation tool, developed for the calculation of the energy, economic, and environmental performance of large ships, the design and optimization of energy system layouts and operational logics, as well as the definition of design and management guidelines for ships. The reliability of the developed model was verified through the use of data measured onboard an existing sample cruise ship. The verification procedure is conducted for assessing the reliability and for exploiting the potentiality of dynamic analysis for a more precise evaluation of ships energy loads, temperature levels, and necessary sizes of possible saving technologies. The validated tool will enable reaching two different goals: i) to evaluate different energy system layouts and to define the optimal one for achieving the present imposed targets and constraints, ii) to obtain a large amount of data for allowing the implementation of the digital twin approach in the maritime sector. The model validation was successfully achieved and very low or negligible deviations, lower than 4%, of numerical data vs. measurements were observed. Through the validated simulation tool approximately 23.4 GWh of primary energy from polluting fuels over two weeks is computed. In addition, the model provided insights into the flow rate, temperature levels, and energy flows of the ship energy system, necessary for identifying the amount of thermal energy to be recovered as well as potential solutions to enhance the energy efficiency of the entire system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".