ArticleHeliyon2024
Using CRITIC-TOPSIS and python to examine the effect of 1-Hepatnol on the performance and emission characteristics of CRDI CI engine with split injection.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recently, biofuels with higher alcohol content have become a promising alternative to diesel fuel. These fuels are appealing because they are sustainable, renewable, and possess attractive fuel properties. This study uses a split injection strategy to analyze the performance and emissions of a CRDI diesel engine fueled by 1-heptanol. The work involved testing different fuel blends, ranging from 10 % to 30 %, while maintaining a constant engine speed of 1500 rpm and varying the operating load between 0 kg and 12 kg in 4 kg increments. During the second stage, the CRITIC-TOPSIS method determines the objective weights and rankings of various criteria and alternatives. A Python approach based on machine learning was used to ensure the CRITIC-TOPSIS results were accurate. Seven criteria were evaluated to maximize BTE while minimizing BSFC, NOx, smoke opacity, HC, CO, and CO
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.