Evidence map›Paper›PMID 41917027›Full record

ArticleScientific reports2026

Crashworthiness and technoeconomic assessment of bioinspired GFRP PP tubes using experiments numerical modeling and artificial neural networks.

Yucai Tian, Ping Zhou, Fatma Ahmed Hassan, Omar Al-Khatib, Fuhaid Alshammari, Naser Mazraoui

Abstract read
In one paragraph

Article in Scientific reports, 2026. 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
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0citing papers in PubMed
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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

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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

6 authors.

Yucai TianCollege of Intelligent Engineering, Chongqing College of Mobile Communication, Chongqing, 401520, China.
Ping ZhouCollege of Intelligent Engineering, Chongqing College of Mobile Communication, Chongqing, 401520, China. pingzhouxq873110@163.com.
Fatma Ahmed HassanDepartment of Economics, College of Business Administration, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia.
Omar Al-KhatibArchitectural Engineering Department, College of Engineering, UAE University, Al Ain, United Arab Emirates. Omar.Alkhatib@uaeu.ac.ae.
Fuhaid AlshammariMechanical Engineering Department, Engineering College, University of Ha'il, 2440, Ha'il, Saudi Arabia.
Naser MazraouiMechanical Engineering Faculty of Technology, University of Ibadan, Ibadan, Nigeria.

Funding

Princess Nourah Bint Abdulrahman University PNURSP2026R869
6 · The paper itself

Abstract

This study presents a comprehensive experimental and computational investigation of the quasi-static axial compression behavior of glass fiber-reinforced polymer/ polypropylene (GFRP/PP) sandwich tubes inspired by bamboo and horsetail structures, designed for crashworthiness applications. The combination of these materials, due to their high strength-to-weight ratio, offers excellent energy absorption capabilities. To this end, firstly, single-hollow tubes were investigated numerically and experimentally. After ensuring the accuracy of the numerical results, many numerical sandwich tubes were simulated to investigate the effect of geometric parameters. Then, the numerical results such as peak crushing force (PCF) and specific energy absorption (SEA) were used as input data for learning of multi layers perceptron (MLP) algorithm network. Finally, using genetic algorithm showed the optimal specimen with t = 1.2 mm, h = 80 mm, and 3 GFRP sub-core tubes has the optimal crashworthiness performance. This specimen exhibits the optimal PCF (18.24 kN) and SEA (7.8 J/g) values compared with the other samples. In addition, a techno-economic assessment was conducted using the Net Present Value (NPV) method to determine the long-term financial viability of replacing traditional materials with GFRP/PP. This approach is an essential step in bridging the gap between technical performance and industrial applicability. The results revealed that while GFRP/PP crash tubes offer superior weight-specific energy absorption, their economic competitiveness varies by reference material. Specifically, replacing steel and aluminum crash boxes with GFRP/PP results in positive net present values of $322.49 and $240.27 per vehicle, respectively, highlighting clear financial and environmental benefits.

Indexed as

Genetic algorithmGFRPMachine learningPolypropyleneSandwich tubeTechno-Economic Analysis

Identifiers

PMID41917027
PMCPMC13186985

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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.