Search results for: optimization of steel

Authors: Nabaa M. Abdul Rahim, Mohammed A.Kadhim, Fadhil K. Fuliful

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A biocompatible layer is prepared from calcium phosphate, which plays a role in building damaged bones and is used in many applications. In this research, calcium phosphate is coated on stainless steel substrates (SS 316) by using the flame coating. FE-SEM images show that the behavior of the sample surfaces varies with distance, at 3cm, appeared with nanostructures of bumps shaped of diameter about 317 nm. The contents of the elements are analyzed by energy-dispersive X-ray spectroscopy (EDX). The chemical elements C, Ca, Fe, Ni, Cr, Mn and O corresponding to calcium phosphate and the alloy are revealed by EDX analysis of the coating layer. XRD patterns for the calcium phosphate layers indicate the formation of the Hap layer on the deposited layers. The samples are immersed in a solution of simulated body fluids (SBF) for 21 days to examine the biocompatibility, as the tests show that the calcium phosphate ratio of 1.65 is the appropriate and biocompatible ratio in the human body. The assays show antibacterial activity using the diffusion disk procedure. On the surface of the agar, observed infested E.coli bacteria and incubated for 24 hours at 37°C. Bacteria grow on the entire agar rather than in some areas around some samples at a distance of 3 cm from the flame hole.

Keywords: biomaterial, flame coating, antibacterial activity, stainless steel

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Authors: Tahseen Saad, Halim Ceylan, Jonathan Weaver, Osman Nuri Çelik, Onur Gungor Sahin

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A new concept of uniform delay offset dependent mathematical optimization problem is derived as the main objective for this study using a differential evolution algorithm. To control the coordination problem, which depends on offset selection and to estimate uniform delay based on the offset choice in a traffic signal network. The assumption is the periodic sinusoidal function for arrival and departure patterns. The cycle time is optimized at the entry links and the optimized value is used in the non-entry links as a common cycle time. The offset optimization algorithm is used to calculate the uniform delay at each link. The results are illustrated by using a case study and are compared with the canonical uniform delay model derived by Webster and the highway capacity manual’s model. The findings show new model minimizes the total uniform delay to almost half compared to conventional models. The mathematical objective function is robust. The algorithm convergence time is fast.

Keywords: area traffic control, traffic flow, differential evolution, sinusoidal periodic function, uniform delay, offset variable

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Authors: Ashish Shukla, K. P. Mishra, Pushplata Tripathi

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This paper investigates the production and optimization of β-galactosidase enzyme using synthetic medium by isolated wild strains (S1, S2) mutated strains (M1, M2) through SSF and SmF. Among the different cell disintegration methods used, the highest specific activity was obtained when the cells were permeabilized using isoamyl alcohol. Wet lab experiments were performed to investigate the effects of carbon and nitrogen substrates present in Vogel’s medium on β-galactosidase enzyme activity using S1, S2, and M1, M2 strains through SSF. SmF experiments were performed for effects of carbon and nitrogen sources in YLK2Mg medium on β-galactosidase enzyme activity using S1, S2 and M1, M2 strains. Effect of pH on β-galactosidase enzyme production was also done using S1, S2, and M1, M2 strains. Results were found to be very appreciable in all the cases.

Keywords: β-galactosidase, cell disintegration, permeabilized, SSF, SmF

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Authors: Soheila Afkar

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Mentha piperita is a medicinal plant that contains a large amount of secondary metabolite that has adverse effect on RNA extraction. Since high quality of RNA is the first step to real time-PCR, in this study optimization of total RNA isolation from leaf tissues of Mentha piperita was evaluated. From this point of view, we researched two different total RNA extraction methods on leaves of Mentha piperita to find the best one that contributes the high quality. The methods tested are RNX-plus, modified RNX-plus (1-5 numbers). RNA quality was analyzed by agarose gel 1.5%. The RNA integrity was also assessed by visualization of ribosomal RNA bands on 1.5% agarose gels. In the modified RNX-plus method (number 2), the integrity of 28S and 18S rRNA was highly satisfactory when analyzed in agarose denaturing gel, so this method is suitable for RNA isolation from Mentha piperita.

Keywords: Mentha piperita, polyphenol, polysaccharide, RNA extraction

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Authors: H. Singh, H. Bhowmick

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Now-a-days, particle based lubricants have been widely used to enhance the lubrication performance. Use of tailor made micro/nanofluids can reduce the friction losses and dissipate heat in a better way. Use of Carbon Nanotubes (CNTs) has gained interests because of its structure that can endure much better in a system mechanically or thermally in comparison to any other additive in oil. On the other hand, nanoclays have been characterized mechanically and tribologically for the use of clay/polymer composite, and they have been gaining huge interest. Hence it is interesting to be investigated the effect of nanoclays as additive in oil. Thermophysical characteristics of lubricant play a predominant role in defining the friction and wear characteristics of lubricated contacts. However, very limited studies have been carried out to correlate the thermophysical properties of nanolubricants with their lubricity characteristics. Besides, most of the lubricant formulations till dates are found to be optimized for steel/steel contacts. In the present study, Multiwall Carbon Nanotube (MWCNT) and nanoclay are used as particle additives in mineral oil to develop nanofluids of various concentrations. The prepared lubricants are tested for their rheological, thermal and lubricity characteristics under aluminium-steel contacts. From the thermophysical investigation, it is observed that nanoclay particles significantly improve the viscosity of lubricant with an insignificant improvement in thermal conductivity. On the other hand, MWCNT particles moderately increase the viscosity but significantly increase the thermal conductivity of the base oil. Frictional responses of the nanofluids are characterized using a Pin-on-Disc tribometer which reveal some interesting facts. The findings from this study will greatly aid in formulating the particle based lubricants for cutting fluid in metal forming industries as well as fully developed nanolubricants for aluminium and Aluminium Metal Matrix Composite (AMMC) tribocontact for the use in the automotive and their allied industries.

Keywords: MWCNT, Multiwall Carbon Nanotube, nanoclay, nanolubricant, rheology, thermal conductivity

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Authors: N. Ourabia, M. Boubaker Ourabia

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An approach for modeling and numerical simulation of passive planar structures using the edge line concept is developed. With this method, we develop an efficient modeling technique for microstrip discontinuities. The technique obtains closed form expressions for the equivalent circuits which are used to model these discontinuities. Then, it would be easy to handle and to characterize complicated structures like T and Y junctions, truncated junctions, arbitrarily shaped junctions, cascading junctions and more generally planar multiport junctions. Another advantage of this method is that the edge line concept for arbitrary shape junctions operates with real parameters circuits. The validity of the method was further confirmed by comparing our results for various discontinuities (bend, filters) with those from HFSS as well as from other published sources.

Keywords: optimization, CAD analysis, microwave circuits, S-parameters

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Authors: Kalpana Dahiya

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This paper discusses a two-level hierarchical time minimization transportation problem, which is an important class of transportation problems arising in industries. This problem has been studied by various researchers, and a number of polynomial time iterative algorithms are available to find its solution. All the existing algorithms, though efficient, have some shortcomings. The current study proposes an alternate solution algorithm for the problem that is more efficient in terms of computational time than the existing algorithms. The results justifying the underlying theory of the proposed algorithm are given. Further, a detailed comparison of the computational behaviour of all the algorithms for randomly generated instances of this problem of different sizes validates the efficiency of the proposed algorithm.

Keywords: global optimization, hierarchical optimization, transportation problem, concave minimization

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Authors: O. Altuntaş, A. Güral

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The hardness-microstructure relationships of spherical cementite in bainitic matrix obtained by a different heat treatment cycles carried out to high carbon powder metallurgy (P/M) steel were investigated. For this purpose, 1.5 wt.% natural graphite powder admixed in atomized iron powders and the mixed powders were compacted under 700 MPa at room temperature and then sintered at 1150 °C under a protective argon gas atmosphere. The densities of the green and sintered samples were measured via the Archimedes method. A density of 7.4 g/cm³ was obtained after sintering and a density of 94% was achieved. The sintered specimens having primary cementite plus lamellar pearlitic structures were fully quenched from 950 ^°C temperature and then over-tempered at 705 °C temperature for 60 minutes to produce spherical-fine cementite particles in the ferritic matrix. After by this treatment, these samples annealed at 735 °C temperature for 3 minutes were austempered at 300 °C salt bath for a period of 1 to 5 hours. As a result of this process, it could be able to produced spherical cementite particle in the bainitic matrix. This microstructure was designed to improve wear and toughness of P/M steels. The microstructures were characterized and analyzed by SEM and micro and macro hardness.

Keywords: powder metallurgy steel, bainite, cementite, austempering and spheroidization heat treatment

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Authors: Juan P. Novoa, Mario A. Rios

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This paper presents a transmission planning methodology that considers the conversion of HVAC transmission lines to HVDC as an alternative of expansion of power systems, as a consequence of restrictions for the construction of new lines. The transmission expansion planning problem formulates an optimization problem that minimizes the total cost that includes the investment cost to convert lines from HVAC to HVDC and possible required reinforcements of the power system prior to the conversion. The costs analysis assesses the impact of the conversion on the reliability because transmission lines are out of service during the conversion work. The presented methodology is applied to a test system considering a planning a horizon of 10 years.

Keywords: transmission expansion planning, HVDC, cost optimization, energy non-supplied

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Authors: Nasim Fallahi, Erasmo Carrera, Alfonso Pagani

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Variable angle tow describes the fibres which are curvilinearly steered in a composite lamina. Significantly, stiffness tailoring freedom of VAT composite laminate can be enlarged and enabled. Composite structures with curvilinear fibres have been shown to improve the buckling load carrying capability in contrast with the straight laminate composites. However, the optimal design and analysis of VAT are faced with high computational efforts due to the increasing number of variables. In this article, an efficient optimum solution has been used in combination with 1D Carrera’s Unified Formulation (CUF) to investigate the optimum fibre orientation angles for buckling analysis. The particular emphasis is on the LE-based CUF models, which provide a Lagrange Expansions to address a layerwise description of the problem unknowns. The first critical buckling load has been considered under simply supported boundary conditions. Special attention is lead to the sensitivity of buckling load corresponding to the fibre orientation angle in comparison with the results which obtain through the Genetic Algorithm (GA) optimization frame and then Artificial Neural Network (ANN) is applied to investigate the accuracy of the optimized model. As a result, numerical CUF approach with an optimal solution demonstrates the robustness and computational efficiency of proposed optimum methodology.

Keywords: beam structures, layerwise, optimization, variable stiffness

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Authors: Omar Al Denali, Abdelaziz Badi

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The ASTM A516 Grade 70 steel is a suitable material used for the fabrication of boiler pressure vessels working in moderate and lower temperature services, and it has good weldability and excellent notch toughness. The post-weld heat treatment (PWHT) or stress-relieving heat treatment has significant effects on avoiding the martensite transformation and resulting in high hardness, which can lead to cracking in the heat-affected zone (HAZ). An adaptive neuro-fuzzy inference system (ANFIS) was implemented to predict the material tensile strength of post-weld heat treatment (PWHT) experiments. The ANFIS models presented excellent predictions, and the comparison was carried out based on the mean absolute percentage error between the predicted values and the experimental values. The ANFIS model gave a Mean Absolute Percentage Error of 0.556 %, which confirms the high accuracy of the model.

Keywords: prediction, post-weld heat treatment, adaptive neuro-fuzzy inference system, mean absolute percentage error

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Authors: Mohammad Reza Esmaili

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One of the most important parts of the restoration process of a power network is the synchronizing of its subsystems. In this situation, the biggest concern of the system operators will be the reduction of the standing phase angle (SPA) between the endpoints of the two islands. In this regard, the system operators perform various actions and maneuvers so that the synchronization operation of the subsystems is successfully carried out and the system finally reaches acceptable stability. The most common of these actions include load control, generation control and, in some cases, changing the network topology. Although these maneuvers are simple and common, due to the weak network and extreme load changes, the restoration will be associated with low speed. One of the best ways to control the SPA is to use FACTS devices. By applying a soft control signal, these tools can reduce the SPA between two subsystems with more speed and accuracy, and the synchronization process can be done in less time. Meanwhile, the unified power controller (UPFC), a series-parallel compensator device with the change of transmission line power and proper adjustment of the phase angle, will be the proposed option in order to realize the subject of this research. Therefore, with the optimal placement of UPFC in a power system, in addition to improving the normal conditions of the system, it is expected to be effective in reducing the SPA during power system restoration. Therefore, the presented paper provides an optimal structure to coordinate the three problems of improving the division of subsystems, reducing the SPA and optimal power flow with the aim of determining the optimal location of UPFC and optimal subsystems. The proposed objective functions in this paper include maximizing the quality of the subsystems, reducing the SPA at the endpoints of the subsystems, and reducing the losses of the power system. Since there will be a possibility of creating contradictions in the simultaneous optimization of the proposed objective functions, the structure of the proposed optimization problem is introduced as a non-linear multi-objective problem, and the Pareto optimization method is used to solve it. The innovative technique proposed to implement the optimization process of the mentioned problem is an optimization algorithm called the water cycle (WCA). To evaluate the proposed method, the IEEE 39 bus power system will be used.

Keywords: UPFC, SPA, water cycle algorithm, multi-objective problem, pareto

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Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Tae-Hyeon Oh, Dae-Gyu Park

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Nonwoven fabric such as an automobile interior material becomes consists of several material layers required for the sound-absorbing function. Because several material layers, many experimental tuning is required to achieve the target of sound absorption. Therefore, a lot of time and money is spent in the development of the car interior materials. In this study, we present the method to predict the sound-absorbing performance of the various layers with physical properties of each material. and we will verify it with the measured value of a prototype. If the sound absorption can be estimated, it can be optimized without a number of tuning tests of the interiors. So, it can reduce the development cost and time during development

Keywords: automotive interior material, sound absorbing, optimization design, nonwoven fabric

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Authors: Zhiyan Meng, Dan Liu, Jintao Meng

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Dependable encrypted traffic classification is crucial for improving cybersecurity and handling the growing amount of data. Large language models have shown that learning from large datasets can be effective, making pre-trained methods for encrypted traffic classification popular. However, attention-based pre-trained methods face two main issues: their large neural parameters are not suitable for low-computation environments like mobile devices and real-time applications, and they often overfit by getting stuck in local minima. To address these issues, we developed a lightweight transformer model, which reduces the computational parameters through lightweight vocabulary construction and Squeeze-and-Excitation Block. We use sharpness-aware optimization to avoid local minima during pre-training and capture temporal features with relative positional embeddings. Our approach keeps the model's classification accuracy high for downstream tasks. We conducted experiments on four datasets -USTC-TFC2016, VPN 2016, Tor 2016, and CICIOT 2022. Even with fewer than 18 million parameters, our method achieves classification results similar to methods with ten times as many parameters.

Keywords: sharpness-aware optimization, encrypted traffic classification, squeeze-and-excitation block, pretrained model

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Authors: Ali Farzan

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Classification of data objects or patterns is a major part in most of Decision making systems. One of the popular and commonly used classification methods is Decision Tree (DT). It is a hierarchical decision making system by which a binary tree is constructed and starting from root, at each node some of the classes is rejected until reaching the leaf nods. Each leaf node is a representative of one specific class. Finding the splitting criteria in each node for constructing or training the tree is a major problem. Particle Swarm Optimization (PSO) has been adopted as a metaheuristic searching method for finding the best splitting criteria. Result of evaluating the proposed method over benchmark datasets indicates the higher accuracy of the new PSO based decision tree.

Keywords: decision tree, particle swarm optimization, splitting criteria, metaheuristic

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Authors: Firoz Alam Faroque, Ankur Neog

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Earthquake causes significant loss of lives and severe damage to infrastructure. Base isolator is one of the most suitable solutions to make a building earthquake resistant. Base isolation consists of installing an isolator along with the steel plates covered with pads of strong material like steel, rubber, etc. In our study, we have used lead rubber bearing (LRB). The basic idea of seismic isolation is based on the reduction of the earthquake-induced inertia forces by shifting the fundamental period of the structure out of dangerous resonance range, and concentration of the deformation and energy dissipation demands at the isolation and energy dissipation systems, which are designed for this purpose. In this paper, RC frame buildings have been modeled and analyzed by response spectrum method using ETABS software. The LRB used in the model is designed as per uniform building code (UBC) 97. It is found that time period for the base isolated structures are higher than that of the fixed base structure and the value of base shear significantly reduces in the case of base-isolated buildings. It has also been found that buildings with vertical irregularities give better performance as compared to building with plan irregularities using base isolators.

Keywords: base isolation, base shear, irregularities in buildings, lead rubber bearing (LRB)

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Authors: Yi Jin, Xu Tang, Cuiyang Feng

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The ‘11th five-year’ and ‘12th five-year’ plans have clearly put forward to strictly control the total amount and intensity of energy and water consumption. The synergy effect of energy and water has rarely been considered in the process of energy and water saving in China, where its contribution cannot be maximized. Energy sectors consume large amounts of energy and water when producing massive energy, which makes them both energy and water intensive. Therefore, the synergy effect in these sectors is significant. This paper assesses and optimizes the synergy effect in three energy sectors under the background of promoting energy and water saving. Results show that: From the perspective of critical path, chemical industry, mining and processing of non-metal ores and smelting and pressing of metals are coupling points in the process of energy and water flowing to energy sectors, in which the implementation of energy and water saving policies can bring significant synergy effect. Multi-objective optimization shows that increasing efforts on input restructuring can effectively improve synergy effects; relatively large synergetic energy saving and little water saving are obtained after solely reducing the energy and water intensity of coupling sectors. By optimizing the input structure of sectors, especially the coupling sectors, the synergy effect of energy and water saving can be improved in energy sectors under the premise of keeping economy running stably.

Keywords: critical path, energy sector, multi-objective optimization, synergy effect, water

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Authors: Alexandre Barbosa de Almeida, Telma Woerle de Lima Soares

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Protein structure prediction is a challenging task in the bioinformatics field. The biological function of all proteins majorly relies on the shape of their three-dimensional conformational structure, but less than 1% of all known proteins in the world have their structure solved. This work proposes a deep learning model to address this problem, attempting to predict some aspects of the protein conformations. Throughout a process of multiobjective dominance, a recurrent neural network was trained to abstract the particular bias of each individual multiobjective algorithm, generating a heuristic that could be useful to predict some of the relevant aspects of the three-dimensional conformation process formation, known as protein folding.

Keywords: Ab initio heuristic modeling, multiobjective optimization, protein structure prediction, recurrent neural network

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Authors: Jay J. Vora, Vishvesh J. Badheka

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This work attempts to investigate the effect of oxide fluxes on 6mm thick Reduced Activation ferritic/martensitic steels (RAFM) during Activated TIG (A-TIG) welding. Six different fluxes Al₂O₃, Co₃O₄, CuO, HgO, MoO₃, and NiO were mixed with methanol for conversion into paste and bead-on-plate experiments were then carried out. This study, systematically investigates the influence of oxide-based flux powder and carrier solvent composition on the weld bead shape, geometric shape of weld bead and dominant depth enhancing mechanism in tungsten inert gas (TIG) welding of reduced activation ferritic/martensitic (RAFM) steel. It was inferred from the study that flux Co₃O₄ and MoO₃ imparted full and secure (more than 6mm) penetration with methanol owing to dual mechanism of reversed Marangoni and arc construction. The use of methanol imparted good spreadabilty and coverability and ultimately higher peak temperatures were observed with its use owing to stronger depth enhancing mechanisms than use of acetone with same oxide fluxes and welding conditions.

Keywords: A-TIG, flux, oxides, penetration, RAFM, temperature, welding

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Authors: Mostafa Jafarian Abyaneh, Khashayar Jafari, Vahab Toufigh

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The cost of experiments on different types of concrete has raised the demand for prediction of their behavior with numerical analysis. In this research, an advanced numerical model has been presented to predict the complete elastic-plastic behavior of polymer concrete (PC), high-strength concrete (HSC), high performance concrete (HPC) along with different steel fiber contents under uniaxial compression. The accuracy of the numerical response was satisfactory as compared to other conventional simple models such as Mohr-Coulomb and Drucker-Prager. In order to predict the complete elastic-plastic behavior of specimens including softening behavior, disturbed state concept (DSC) was implemented by nonlinear finite element analysis (NFEA) and hierarchical single surface (HISS) failure criterion, which is a failure surface without any singularity.

Keywords: disturbed state concept (DSC), hierarchical single surface (HISS) failure criterion, high performance concrete (HPC), high-strength concrete (HSC), nonlinear finite element analysis (NFEA), polymer concrete (PC), steel fibers, uniaxial compression test

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Authors: Yunhan Zhang, Xiaopeng Li, Zhongxiao Peng

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Additive manufacturing (AM) possesses several key characteristics, including high design freedom, energy-efficient manufacturing process, reduced material waste, high resolution of finished products, and excellent performance of finished products. These advantages have garnered widespread attention and fueled rapid development in recent decades. AM has significantly broadened the spectrum of available materials in the manufacturing industry and is gradually replacing some traditionally manufactured parts. Similar to components produced via traditional methods, products manufactured through AM are susceptible to degradation caused by wear during their service life. Given the prevalence of 316L stainless steel (SS) parts and the limited research on the tribological behavior of 316L SS samples or products fabricated using AM technology, this study aims to investigate the degradation process and wear mechanisms of 316L SS disks fabricated using AM technology. The wear mechanisms and tribological performance of these AM-manufactured samples are compared with commercial 316L SS samples made using conventional methods. Additionally, methods to enhance the tribological performance of additive-manufactured SS samples are explored. Four disk samples with a diameter of 75 mm and a thickness of 10 mm are prepared. Two of them (Group A) are prepared from a purchased SS bar using a milling method. The other two disks (Group B), with the same dimensions, are made of Gas Atomized 316L Stainless Steel (size range: 15-45 µm) purchased from Carpenter Additive and produced using Laser Powder Bed Fusion (LPBF). Pin-on-disk tests are conducted on these disks, which have similar surface roughness and hardness levels. Multiple tests are carried out under various operating conditions, including varying loads and/or speeds, and the friction coefficients are measured during these tests. In addition, the evolution of the surface degradation processes is monitored by creating moulds of the wear tracks and quantitatively analyzing the surface morphologies of the mould images. This analysis involves quantifying the depth and width of the wear tracks and analyzing the wear debris generated during the wear processes. The wear mechanisms and wear performance of these two groups of SS samples are compared. The effects of load and speed on the friction coefficient and wear rate are investigated. The ultimate goal is to gain a better understanding of the surface degradation of additive-manufactured SS samples. This knowledge is crucial for enhancing their anti-wear performance and extending their service life.

Keywords: degradation process, additive manufacturing, stainless steel, surface features

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Authors: Ahmed Mohamed Nasr, Waseim Ragab Azzam, Nada Osama Ramadan

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Contaminated soil can weaken the stability of buildings and infrastructure, posing serious risks to their structural integrity. Therefore, this study aims to understand how oil contamination affects the torsion behavior of model steel piles at different soil densities. This research is crucial for evaluating the structural integrity and stability of piles in oil-contaminated environments. Clean sand samples and heavy motor oil were mixed in amounts ranging from 0 to 6% of the soil's dry weight. The mixture was thoroughly mixed to ensure uniform distribution of the oil throughout the sandy soil for simulating the field conditions. In these investigations, the relative densities (Dr), pile slenderness ratio (Lp/Dp), oil content (O.C%), and contaminated sand layer thickness (LC) were all different. Also, the paper presents an analysis of piles that are loaded both vertically and torsionally. The findings demonstrated that the pre-applied torsion load led to a decrease in the vertical bearing ability of the pile. Also, at Dr = 80%, the ultimate vertical load under combined load at constant torsional load T = (1/3Tu, 2/3Tu, and Tu) in the cases of (Lc/Lp) = 0.5 and (Lp/Dp) =13.3 was found to be reduced by (1.48, 2.78, and 4.15%) less than piles under independent vertical load, respectively so it is crucial to consider the torsion load during pile design.

Keywords: torsion-vertical load, oil-contaminated sand, twist angle, steel pile

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Authors: Tugrul Oktay, Mehmet Konar, Mustafa Soylak, Firat Sal, Murat Onay, Orhan Kizilkaya

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In this paper, autonomous performance of a small manufactured unmanned helicopter is tried to be increased. For this purpose, a small unmanned helicopter is manufactured in Erciyes University, Faculty of Aeronautics and Astronautics. It is called as ZANKA-Heli-I. For performance maximization, autopilot parameters are determined via minimizing a cost function consisting of flight performance parameters such as settling time, rise time, overshoot during trajectory tracking. For this purpose, a stochastic optimization method named as simultaneous perturbation stochastic approximation is benefited. Using this approach, considerable autonomous performance increase (around %23) is obtained.

Keywords: small helicopters, hierarchical control, stochastic optimization, autonomous performance maximization, autopilots

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Authors: Comingstarful Marthong, Shembiang Marthong

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Application of Polyethylene terephthalate (PET) fiber for enhancing the seismic performance of exterior RC beam-column connections in substitution of steel fibers is experimentally investigated. The study involves the addition of Polyethylene terephthalate (PET) fiber-reinforced concrete, i.e., PFRC at the joint region of the connection. The PET fiber of 0.5% volume fraction used in the PFRC mix is obtained by hand cutting of post-consumer PET bottles. Specimens design as per relevant codes was casted and tested to reverse cyclic loading. PFRC specimen was also casted and subjected to similar loading sequence. Test results established that addition of PET fibers in the joint region is effective in enhancing the displacement ductility and energy dissipation capacity. The improvement of damage indices and principal tensile stresses of PFRC specimens gave experimental evidence of the suitability of PET fibers as a discrete reinforcement in the substitution of steel fiber for structural use.

Keywords: beam-column connections, polyethylene terephthalate fibers reinforced concrete, joint region, ductility, seismic capacity

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Authors: Ramon Erasmo Verdin Rodriguez

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Many has been the ways that historically the managers and gurus has been trying to get closer to the perfect supply chain, but since this topic is so vast and very complex the bigger the companies are, the duty has not been certainly easy. On this research, you are going to see thru the entrails of the logistics that happens at a glass manufacturing company with the number one raw material of the process that is the silica sand. After a very quick passage thru the supply chain, this document is going to focus on the way that raw materials flow thru the system, so after that, an analysis and research can take place to improve the logistics. Thru Operations Research techniques, it will be analyzed the current scheme of distribution and inventories of raw materials at a glass company’s plants, so after a mathematical conceptualization process, the supply chain could be optimized with the purpose of reducing the uncertainty of supply and obtaining an economic benefit at the very end of this research.

Keywords: inventory management, operations research, optimization, supply chain

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Authors: Ikechukwu Ejim

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This research project addresses the optimization of biodiesel production from gossypium herbaceum (cottonseed) and moringa oleifera seeds. Soxhlet extractor method using n-hexane for gossypium herbaceum (cottonseed) and ethanol for moringa oleifera were used for solvent extraction. 1250 ml of oil was realized from both gossypium herbaceum (cottonseed) and moringa oleifera seeds before characterization. In transesterification process, a 4-factor-3-level experiment was conducted using an optimal design of Response Surface Methodology. The effects of methanol/oil molar ratio, catalyst concentration (%), temperature (°C) and time (mins), on the yield of methyl ester for both cottonseed and moringa oleifera oils were determined. The design consisted of 25 experimental runs (5 lack of fit points, five replicate points, 0 additional center points and I optimality) and provided sufficient information to fit a second-degree polynomial model. The experimental results suggested that optimum conditions were as follows; cottonseed yield (96.231%), catalyst concentration (0.972%), temperature (55oC), time (60mins) and methanol/oil molar ratios (8/1) respectively while moringa oleifera optimum values were yield (80.811%), catalyst concentration (1.0%), temperature (54.7oC), time (30mins ) and methanol/oil molar ratios (8/1) respectively. This optimized conditions were validated with the actual biodiesel yield in experimental trials and literature.

Keywords: optimization, Gossypium herbaceum, Moringa oleifera, biodiesel

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Authors: Balarabe Nkom, Adam P. R. Taylor, Craig Baguley

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Power Line Communications (PLC) is being employed in existing power systems, despite the infrastructure not being designed with PLC considerations in mind. Given that power transformers can last for decades, the distribution transformer in particular exists as a relic of un-optimized technology. To determine issues that may need to be addressed in subsequent designs of such transformers, it is essential to have a highly accurate transformer model for simulations and subsequent optimization for the PLC environment, with a view to increase data speed, throughput, and efficiency, while improving overall system stability and reliability. This paper reviews various methods currently available for creating transformer models and provides insights into the requirements of each for obtaining high accuracy. The review indicates that a combination of traditional analytical methods using a hybrid approach gives good accuracy at reasonable costs.

Keywords: distribution transformer, modelling, optimization, power line communications

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Authors: B. Dikici, I. Ozdemir, M. Topuz

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The corrosion behaviour of 316L stainless steel coatings obtained by cold spray method was investigated in this study. 316L powders were deposited onto Al5052 aluminum substrates. The coatings were produced using nitrogen (N₂) process gas. In order to further improve the corrosion and mechanical properties of the coatings, heat treatment was applied at 250 and 750 °C. The corrosion performances of the coatings were compared using the potentiodynamic scanning (PDS) technique under in-vitro conditions (in Ringer’s solution at 37 °C). In addition, the hardness and porosity tests were carried out on the coatings. Microstructural characterization of the coatings was carried out by using scanning electron microscopy attached with energy dispersive spectrometer (SEM-EDS) and X-ray diffraction (XRD) technique. It was found that clean surfaces and a good adhesion were achieved for particle/substrate bonding. The heat treatment process provided both elimination of the anisotropy in the coating and resulting in healing-up of the incomplete interfaces between the deposited particles. It was found that the corrosion potential of the annealed coatings at 750 °C was higher than that of commercially 316 L stainless steel. Moreover, the microstructural investigations after the corrosion tests revealed that corrosion preferentially starts at inter-splat boundaries.

Keywords: biomaterials, cold spray, 316L, corrosion, heat treatment

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Authors: R. Kanmaniraja, R. Freshipali, J. Abdullah, K. Niranjan, K. Balasubramani, V. R. Sanal Kumar

Abstract:

The present environmental issues have made aircraft jet noise reduction a crucial problem in aero-acoustics research. Acoustic studies reveal that addition of chevrons to the nozzle reduces the sound pressure level reasonably with acceptable reduction in performance. In this paper comprehensive numerical studies on acoustic characteristics of different types of chevron nozzles have been carried out with non-reacting flows for the shape optimization of chevrons in supersonic nozzles for aerospace applications. The numerical studies have been carried out using a validated steady 3D density based, k-ε turbulence model. In this paper chevron with sharp edge, flat edge, round edge and U-type edge are selected for the jet acoustic characterization of supersonic nozzles. We observed that compared to the base model a case with round-shaped chevron nozzle could reduce 4.13% acoustic level with 0.6% thrust loss. We concluded that the prudent selection of the chevron shape will enable an appreciable reduction of the aircraft jet noise without compromising its overall performance. It is evident from the present numerical simulations that k-ε model can predict reasonably well the acoustic level of chevron supersonic nozzles for its shape optimization.

Keywords: supersonic nozzle, Chevron, acoustic level, shape optimization of Chevron nozzles, jet noise suppression

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Authors: A. K. M. Kamrul Islam, Abdelhamid Bouchachia, Suang Cang, Hongnian Yu

Abstract:

Forecasting model has a great impact in terms of prediction and continues to do so into the future. Although many forecasting models have been studied in recent years, most researchers focus on different forecasting methods based on fuzzy time series to solve forecasting problems. The forecasted models accuracy fully depends on the two terms that are the length of the interval in the universe of discourse and the content of the forecast rules. Moreover, a hybrid forecasting method can be an effective and efficient way to improve forecasts rather than an individual forecasting model. There are different hybrids forecasting models which combined fuzzy time series with evolutionary algorithms, but the performances are not quite satisfactory. In this paper, we proposed a hybrid forecasting model which deals with the first order as well as high order fuzzy time series and particle swarm optimization to improve the forecasted accuracy. The proposed method used the historical enrollments of the University of Alabama as dataset in the forecasting process. Firstly, we considered an automatic clustering algorithm to calculate the appropriate interval for the historical enrollments. Then particle swarm optimization and fuzzy time series are combined that shows better forecasting accuracy than other existing forecasting models.

Keywords: fuzzy time series (fts), particle swarm optimization, clustering algorithm, hybrid forecasting model

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