Evidence map›Paper›PMID 36936311›Full record

ArticleACS omega2023

Experimental Investigation for Determining an Ideal Algal Biodiesel-Diesel Blend to Improve the Performance and Mitigate Emissions Using a Response Surface Methodology.

Elumalai Ramachandran, Ravi Krishnaiah, Elumalai Perumal Venkatesan, Manickam Murugan, Sreenivasa Reddy Medapati, Prabhakar Sekar

Abstract read
In one paragraph

Article in ACS omega, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Elumalai RamachandranSchool of Mechanical Engineering, VIT University, Vellore 632014, India.ORCID https://orcid.org/0000-0002-4970-8777
Ravi KrishnaiahSchool of Mechanical Engineering, VIT University, Vellore 632014, India.ORCID https://orcid.org/0000-0001-7911-0437
Elumalai Perumal VenkatesanDepartment of Mechanical Engineering, Aditya Engineering College, Surampalem 533437, India.ORCID https://orcid.org/0000-0002-7536-8200
Manickam MuruganDepartment of Mechanical Engineering, Aditya College of Engineering and Technology, Surampalem 533291, India.
Sreenivasa Reddy MedapatiDepartment of Mechanical Engineering, Aditya Engineering College, Surampalem 533437, India.
Prabhakar SekarAutomotive Engineering, Wollo University, Dessie 208, Ethiopia.ORCID https://orcid.org/0000-0002-7595-1770

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ongoing depletion of the world's fossil fuel sources and environmental damage has compelled the quest for alternative energy. Excellent characteristics of biodiesel include its renewable nature, safety, absence of sulfur, environmental advantages, and biodegradability, which can eradicate the above problems. In this study, algal oil was characterized to obtain the fatty acid profile, and the free fatty acid value of algal oil suggested a two-step process of esterification and transesterification for efficient biodiesel production. The performance and emission results of biodiesel and its blends (B10, B20, and B30) were investigated in a constant speed, single-cylinder, 4-stroke, 3.5 kW compression ignition engine at different loads for arriving at an appropriate fuel blend ratio. The response surface methodology technique is used to predict the ideal composition of microalgae-diesel using the experimental data with due weightage for the optimization criterion. The predicted blend ratio of B25 was tested on the engine and authenticated. The findings recorded an improvement in brake thermal efficiency to 31.42% and reduction in brake specific energy consumption to 9.82 MJ/kW h, unburned hydrocarbon to 85 ppm, carbon monoxide to 0.164% v/v, carbon dioxide to 4.115% v/v, nitrogen oxides to 691 ppm, and smoke opacity to 16.93%.

Identifiers

PMID36936311
PMCPMC10018500

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.