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JournalISSN: 0025-5300

MP MATERIALPRUEFUNG - MP MATERIALS TESTING 

De Gruyter
About: MP MATERIALPRUEFUNG - MP MATERIALS TESTING is an academic journal published by De Gruyter. The journal publishes majorly in the area(s): Materials science & Metallurgy. It has an ISSN identifier of 0025-5300. Over the lifetime, 287 publications have been published receiving 323 citations. The journal is also known as: Matériaux, essais et recherches & Materials testing.

Papers published on a yearly basis

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Journal ArticleDOI
TL;DR: In this article , the mechanical properties of composite materials produced from woven jute type were investigated and it was observed that the tensile and bending failure loads of the composite materials obtained by using the particle reinforced adhesive increased.
Abstract: Abstract In this investigation, mechanical properties of composite materials produced from woven jute type were investigated. These composites were produced in the form of epoxy adhesive layers by using hand lay-up method in which aluminum, mica and ceramic particles were added into epoxy as a structural adhesive by 2, 4 and 6 wt%. Samples produced according to ASTM D procedures were subjected to tensile and three point bending loads to examine the effect of the particles. Experimental results were presented in tables and graphs. As a result, it was observed that the tensile and bending failure loads of the composite materials obtained by using the particle reinforced adhesive increased. Also, the biggest rise in tensile strength was achieved with 4 wt% aluminum and the biggest increase in bending strength was observed for 2 wt% aluminum particles.

25 citations

Journal ArticleDOI
TL;DR: A hunger game search algorithm is applied to optimize the automobile suspension arm (SA) by reduction of mass vis-à-vis volume and it was found that the HGS algorithm is able to pursue the best optimized solution subjecting to critical constraints.
Abstract: Abstract The modernization in automobile industries has been booming in recent times, which has led to the development of lightweight and fuel-efficient design of different automobile components. Furthermore, metaheuristic algorithms play a significant role in obtaining superior optimized designs for different vehicle components. Hence, a hunger game search (HGS) algorithm is applied to optimize the automobile suspension arm (SA) by reduction of mass vis-à-vis volume. The performance of the HGS algorithm was accomplished by comparing the achieved results with the well-established metaheuristics (MHs), such as salp swarm optimizer, equilibrium optimizer, Harris Hawks optimizer (HHO), chaotic HHO, slime mould optimizer, marine predator optimizer, artificial bee colony optimizer, ant lion optimizer, and it was found that the HGS algorithm is able to pursue the best optimized solution subjecting to critical constraints. Moreover, the HGS algorithm can realize the least weight of the SA subjected to maximum stress values. Hence, the adopted algorithm can be found robust in terms of obtaining the best global optimum solution.

18 citations

Journal ArticleDOI
TL;DR: This research uses both the hybrid Taguchi salp swarm algorithm-Nelder–Mead (HTSSA-NM) and the manta ray foraging optimization algorithm (MRFO) to optimize the structure and shape of the automobile brake pedal.
Abstract: Abstract The adaptability of metaheuristics is proliferating rapidly for optimizing engineering designs and structures. The imperative need for the fuel-efficient design of vehicles with lightweight structures is also a soaring demand raised by the different industries. This research contributes to both areas by using both the hybrid Taguchi salp swarm algorithm-Nelder–Mead (HTSSA-NM) and the manta ray foraging optimization (MRFO) algorithm to optimize the structure and shape of the automobile brake pedal. The results of HTSSA-NM and MRFO are compared with some well-established metaheuristics such as horse herd optimization algorithm, black widow optimization algorithm, squirrel search algorithm, and Harris Hawks optimization algorithm to verify its performance. It is observed that HTSSA-NM is robust and superior in terms of optimizing shape with the least mass of the engineering structures. Also, HTSSA-NM realize the best value for the present problem compared to the rest of the optimizer.

13 citations

Journal ArticleDOI
TL;DR: In this article , a steel cylindrical component was analyzed at two regions (bottom and top region) along the building direction and the results showed that the microstructure of the part differed from the bottom to the top region, resulting in a hardness difference between 169 and 181 (Hv 0.5), and impact toughness varied from 72 to 80 J.
Abstract: Abstract Wire arc additive manufacturing (WAAM) offers high-quality technology for producing large complex geometry structures in close proximity to near-net form, using cost-effective manufacturing resources, such as welding and wiring materials. In this study, the cold-metal-transfer-based WAAM system was utilized to manufacture the steel cylindrical component. The mechanical properties and microstructure analysis of the component were analyzed at two regions (bottom and top region) along the building direction. The results showed that the microstructure of the part differed from the bottom to the top region, resulting in a hardness difference between 169 and 181 (Hv0.5), and impact toughness varied from 72 to 80 J. There were also anisotropic features in the tensile properties: the yield strength and the ultimate tensile strength ranging from 401 to 457 MPa and between 492 and 543 MPa, respectively.

11 citations

Journal ArticleDOI
TL;DR: In this article , a hybrid metaheuristic algorithm (HAHA-SA) based on the artificial hummingbird algorithm (AHA) and simulated annealing problem is proposed to improve the performance of the AHA.
Abstract: Abstract Nature-inspired algorithms known as metaheuristics have been significantly adopted by large-scale organizations and the engineering research domain due their several advantages over the classical optimization techniques. In the present article, a novel hybrid metaheuristic algorithm (HAHA-SA) based on the artificial hummingbird algorithm (AHA) and simulated annealing problem is proposed to improve the performance of the AHA. To check the performance of the HAHA-SA, it was applied to solve three constrained engineering design problems. For comparative analysis, the results of all considered cases are compared to the well-known optimizers. The statistical results demonstrate the dominance of the HAHA-SA in solving complex multi-constrained design optimization problems efficiently. Overall study shows the robustness of the adopted algorithm and develops future opportunities to optimize critical engineering problems using the HAHA-SA.

9 citations

Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
2023117
2022149
201113
20104
20096
20084