Performance In-Live of Marine Engines: A Tool for Its Evaluation
Clicks: 205
ID: 114780
2020
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
30.0
/100
205 views
33 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #133 of 187 articles by views in applied sciences
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 187 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Currently, most ships use internal combustion engines (ICEs) either as propulsion engines or generator sets. The growing concern in environmental protection along with the consequent international rule framework motivated shipowners and designers to replace conventional power systems in order to mitigate pollutant emissions. Therefore, manufacturers have made available on the market many technological solutions to use alternative fuels (Liquefied Natural Gas or LNG, methanol, etc.). However, the main energy source is still fossil fuel, so almost all the ICEs are made up of turbocharged diesel engines (TDEs). TDEs have still the potential to improve their efficiency and reduce fuel consumption and pollutant emissions. In particular, the interpretation of Industry 4.0 given by manufacturers enabled the installation of a robust network of sensors on TDEs, which is able to allow reliable power management systems and make ships much more efficient regarding operating costs (fuel consumption and maintenance) and environmental footprint. In this paper, a software tool that is capable of processing the in-live performance of TDEs is described. The great novelty consists in the ability to process all the information detected by the sensor network in-live and dynamically optimize TDEs’ operation, whereas the common practice involves the collection of performance data and their off-line processing.
| Reference Key |
dodero2020appliedperformance
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Matteo Dodero;Serena Bertagna;Alberto Marino’;Vittorio Bucci;Dodero, Matteo;Bertagna, Serena;Marino’, Alberto;Bucci, Vittorio; |
| Journal | applied sciences |
| Year | 2020 |
| DOI |
10.3390/app10165707
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.