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24. Insights on the bearing response of glass fiber‐reinforced stainless steel laminates: Investigating the influence of natural fiber and specimen geometry.

Author

Vasumathi, M., Begum, S. Rashia, Gokul Nath, P., Kavimani, V., Romanovski, Valentin, and Salah, Bashir

Abstract

This study delves into the bearing response of two types of Fiber Metal Epoxy Laminates (FMLs): Glass Fiber/Stainless Steel laminates and Glass Fiber/Jute/Stainless Steel laminates, where a portion of glass fiber is replaced with jute. The primary focus is to assess the impact of introducing natural fiber (jute) into FML on its pin‐type bearing performance, considering various edge‐to‐hole ratios (e/D), width‐to‐hole ratios (W/D), and stacking orders. The study aims to understand how these parameters influence the bearing load and failure modes of the laminates. Observations reveal that variations in e/D and W/D ratios, along with the stacking arrangement of materials in the FMLs, exert a significant influence on the ultimate load‐bearing capacity of the pinned joint. It is observed from the study that, for the two stacking sequences considered, the load bearing capacity of the FMLs with W/D ratio 6 is greater than those with W/D ratio of 4 by a maximum of 23.06%. Moreover, if the weight fraction of the glass fiber content in the FML is reduced, the ultimate load bearing capacity of the FML also gets curtailed to a maximum extent of 44%. The experimental findings suggest that the prepared fiber metal laminate, characterized by lower weight, cost‐effectiveness, and enhanced environmental friendliness, exhibits a substantial capacity to withstand bearing loads. Consequently, it emerges as a promising candidate for the construction of structures such as storage silos, offering a balanced combination of structural performance and sustainability. Highlights: FML bearing performance: Glass/Stainless versus Glass/Jute/Stainless.Influence of e/D and W/D ratios on pin‐type bearing.Stacking order impact on load‐bearing capacity.Lightweight, cost‐effective, and eco‐friendly FMLs.Promising for silo construction: structural and sustainable. [ABSTRACT FROM AUTHOR]

Published
2024
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42. Analytical analysis of silver-water, silver-blood base nanofluid flow over fluctuating disk with the influence of viscous dissipation over fluctuating disk.

Author

Rehman, Ali, Inc, Mustafa, Salah, Bashir, and Hussain, Shah

Subjects
NANOFLUIDICS, NUSSELT number, SIMILARITY transformations, TEMPERATURE distribution, HEAT transfer, INDUSTRIAL engineering
Abstract

This work considers the analytical analysis of silver-water, silver-blood base nanofluid flow over fluctuating disk with the influence of viscous dissipation over fluctuating disk. The primary goal of this study is an effort to improve the heat transfer ratio, which is a core part of the engineering and industrial sectors. Following a continuity check, the problem is modeled using the conservation rules of momentum and energy. Nonlinear PDEs are produced through modeling, which are then transformed into ODEs using a similarity transformation and thermophysical characteristics. The resultant ODEs are resolved using the Optimal Homotopy Asymptotic Method (HAM). The outcomes of this method are compared to authenticate the outcomes of the obtained results. The Mathematica software is used to run HAM methods, and graphical interpretations are given to highlight the influence of dissimilar contributing factors on the velocity profile and temperature distribution. Nusselt's number, and the skin friction are examined through graphical representation. Convergence of the problem is checked with the help of graphs and tables by using dual solution of the problem. [ABSTRACT FROM AUTHOR]

Published
2023
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45. Optimal Scheduling of Rainwater Collection Vehicles: Mixed Integer Programming and Genetic Algorithms

Author

Alnahhal, Mohammed, Gjeldum, Nikola, and Salah, Bashir

Subjects
water tankers, water treatment plant, flood, parallel machines scheduling, mixed integer programming, genetic algorithm
Abstract

Due to climate change, some areas in the world witnessed higher levels of heavy rain than the capacity of the wastewater system of the streets. Therefore, water tankers are used for the dewatering process to take the extra rainwater from the streets to keep a smooth flow of vehicles and to use the water in agriculture and industry. Water is taken to a water treatment plant. Performing the dewatering process as fast as possible, especially in crowded streets, was ignored by researchers. In this study, at first, the problem was solved using two mixed integer programming (MIP) models. A new variant of identical parallel machine scheduling with job splitting is proposed for the first time, where one or at most two tankers can work at the same flood location at the same time. This is performed in the second model. However, the first model considers dividing the dewatering processes into two phases, where the first one, which is more urgent, is to reduce the amount of floodwater. The second one is for dewatering the rest of the water. Then two genetic algorithms (GAs) were used to solve faster the two MIP models, which are NP-hard problems. At first, the MIP and GA models were applied to small-sized problems. Then GA was used for large practical data sets. Results showed that for small problems, MIP and GA gave optimal solutions in a reasonable number of iterations, while for larger problems, good solutions were obtained in a reasonable number of iterations.

Published
2023

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