Evidence map›Paper›PMID 38857211›Full record

ArticlePloS one2024

Performance optimization for an optimal operating condition for a shell and heat exchanger using a multi-objective genetic algorithm approach.

B Venkatesh, Ajmeera Kiran, Mudassir Khan, Mohammad Khalid Imam Rahmani, Laxmi Upadhyay, J Chinna Babu, T Lakshmi Narayana

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

B VenkateshDepartment of Mechanical Engineering, Annamacharya Institute of Technology and Sciences, Rajampet, Andhra Pradesh, India.
Ajmeera KiranDepartment of Computer Science and Engineering, MLR Institute of Technology, Hyderabad, Telangana, India.
Mudassir KhanDepartment of Computer Science, College of Computer Science, King Khalid University, Abha, Saudi Arabia.ORCID 0000-0002-1117-7819
Mohammad Khalid Imam RahmaniCollege of Computing and Informatics, Saudi Electronic University, Riyadh, Saudi Arabia.
Laxmi UpadhyayCollege of Computing and Informatics, Saudi Electronic University, Riyadh, Saudi Arabia.
J Chinna BabuDepartment of Electronics and Communication Engineering, Annamacharya Institute of Technology and Sciences, Rajampet, Andhra Pradesh, India.ORCID 0000-0001-9005-0615
T Lakshmi NarayanaKandula Lakshumma Memorial College of Engineering for women, Kadapa, Andhra Pradesh, India.ORCID 0000-0002-9020-4773

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, shell and heat exchangers are optimized using an integrated optimization framework. In this research, A structured Design of Experiments (DOE) comprising 16 trials was first conducted to systematically determine the essential parameters, including mass flow rates (mh, mc), temperatures (T1, t1, T2, t2), and heat transfer coefficients (€, TR, U). By identifying the first four principal components, PCA was able to determine 87.7% of the variance, thereby reducing the dimensionality of the problem. Performance-related aspects of the system are the focus of this approach. Key outcomes (€, TR, U) were predicted by 99% R-squared using the RSM models. Multiple factors, such as the mass flow rate and inlet temperature, were considered during the design process. The maximizing efficiency, thermal resistance, and utility were achieved by considering these factors. By using genetic algorithms, Pareto front solutions that meet the requirements of decision-makers can be found. The combination of the shell and tube heat exchangers produced better results than expected. Engineering and designers can gain practical insight into the mass flow rate, temperature, and key responses (€, TR, U) if they quantify improvements in these factors. Despite the importance of this study, it has several potential limitations, including specific experimental conditions and the need to validate it in other situations as well. Future research could investigate other factors that influence system performance. A holistic optimization framework can improve the design and engineering of heat exchangers in the future. As a result of the study, a foundation for innovative advancements in the field has been laid with tangible improvements. The study exceeded expectations by optimizing shell and heat exchanger systems using an integrated approach, thereby contributing significantly to the advancement of the field.

Indexed as

AlgorithmsHot TemperatureEquipment DesignModels, Theoretical

Identifiers

PMID38857211
PMCPMC11164377

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Registered trials

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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.