Evidence map›Paper›PMID 35454422›Full record

ArticleMaterials (Basel, Switzerland)2022

Preference Index of Sustainable Natural Fibers in Stone Matrix Asphalt Mixture Using Waste Marble.

Sandeep Singh, Mohammad Iqbal Khairandish, Mustafa Musleh Razahi, Raman Kumar, Jasgurpreet Singh Chohan, Aditya Tiwary, Shubham Sharma, Changhe Li, R A Ilyas, M R M Asyraf and 1 more

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
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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

11 authors.

Sandeep SinghDepartment of Civil Engineering, Chandigarh University, Mohali 140413, India.
Mohammad Iqbal KhairandishDepartment of Civil Engineering, Chandigarh University, Mohali 140413, India.
Mustafa Musleh RazahiDepartment of Civil Engineering, Chandigarh University, Mohali 140413, India.
Raman KumarUniversity Centre of Research and Development, Department of Mechanical Engineering, Chandigarh University, Mohali 140413, India.ORCID 0000-0002-5040-7920
Jasgurpreet Singh ChohanUniversity Centre of Research and Development, Department of Mechanical Engineering, Chandigarh University, Mohali 140413, India.ORCID 0000-0002-3903-8589
Aditya TiwaryDepartment of Civil Engineering, Chandigarh University, Mohali 140413, India.
Shubham SharmaUniversity Centre of Research and Development, Department of Mechanical Engineering, Chandigarh University, Mohali 140413, India.ORCID 0000-0001-9446-8074
Changhe LiSchool of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, China.ORCID 0000-0003-4409-956X
R A IlyasSchool of Chemical and Energy Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia.ORCID 0000-0001-6622-2632
M R M AsyrafInstitute of Energy Infrastructure, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, Kajang 43000, Malaysia.ORCID 0000-0001-6471-0528
S Z S ZakariaResearch Centre for Environment, Economic and Social Sustainability (KASES), Institute for Environment and Development (LESTARI), Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Malaysia.

Funding

This research was funded by Universiti Kebangsaan Malaysia (UKM) for financial support through research grants, XX-2020-010 and GP-2021-K012939.M for the financial support through research grants, XX-2020-010 and GP-2021-K012939. This research was funded by Universiti Kebangsaan Malaysia (UKM) for financial support through research grants, XX-2020-010 and GP-2021-K012939.M for the financial support through research grants, XX-2020-010 and GP-2021-K012939.
6 · The paper itself

Abstract

The present study investigates the preference index of natural fibers such as sisal, coir, and rice straw fibers in stone matrix asphalt mixtures (SMA), using waste marble as filler. Waste marble was used as the filler in asphalt mixtures and was crushed by abrasion machine and sieved according to SMA filler requirements. The SEM topography and EDS analysis of sisal, coir, and rice straw fibers were also carried out. The Marshall test was conducted, which is the most acceptable, cost-effective, and widely adopted method to estimate the optimum bitumen and to examine several Marshall Measures, such as flow value, voids filled with bitumen (VFB), stability, voids in mineral aggregate (VMA), and air voids (VA). Furthermore, tests were performed on the specimen with the optimum amount of bitumen, different percentages of fibers, and waste marble as filler to calculate drain down, moister sensitivity, and Marshall Stability. Multi-criteria decision-making (MCDM) techniques were implemented to obtain subjective and objective weights, which were further used to compute the values of the preference index of natural fiber contents. The outcomes revealed favorable results for the usage of marble dust as filler in Stone Matrix Asphalt (SMA). In addition, the preference index upshots are inclined toward the usage of rice straw over coir followed by sisal fiber. It was observed that the value of the preference index in rice straw at 0.3 varied from 0.918, 0.925, and 0.931 in rice straw using equal, objective, and subjective weights, respectively. The maximum drain down value observed is 0.335 based on ASTM-D 6390 and IRC-SP-79 are against 0.3 percent natural fiber. Moreover, as per the prescribed limit of MoRTH, because of the thin film around aggregates, moisture susceptibility characteristics, i.e., better resistance to moisture, were enhanced by more than 80%.

Indexed as

coirdrain down testEDS analysismarshall stability propertiesmoisture sensitivity testrice straw fibersSEM topographysisalwaste marble

Identifiers

PMID35454422
PMCPMC9027365

What OpenQuestion holds

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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.