International Journal of Engineering
Volume:37 Issue: 2, Feb 2024

Nickel (Ni)-rich single-phase nickel-copper (Ni-Cu) alloy coatings were produced on aluminum (Al) substrates by electrodeposition in stabilized citrate baths. Electrodeposition experiments were performed at four different current densities. Increasing the current density resulted in the metal deposition rate increasing faster than the hydrogen evolution rate; thus, the cathodic current efficiency increased. The crystal systems of the Ni-Cu alloys were face center cubic (fcc), with the (111) plane as the preferred crystal plane. Scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDS) measurements showed that the Ni content in the coating increased with increasing current density. The Ni-Cu 40 sample had the most Ni content and showed a homogeneous and compact morphology. It was found that the higher the concentration of Ni in the solution, the smaller the grain size. Measurements recorded with a vibrating sample magnetometer (VSM) showed that the Ni-Cu 40 sample provided magnetic saturation, with the highest value being 0.108 emu/g. The microhardness method produced 404 HV on the Ni-Cu 40 sample. In conclusion, higher current densities were associated with a higher Ni composition and increased thickness, which were responsible for the increases in the magnetic properties and hardness.

In modern megacities, every day, people are faced with the problem of finding a place to park the cars, this problem is especially acute in the city center. The number of existing parking spaces is sorely lacking in view of the rapid growth in the number of cars. Therefore, the optimal solution for the construction and reconstruction of buildings in large metropolitan areas is the rational use of underground space, namely the construction of underground parking lots. The present work is an analysis on construction of underground and multi-story car parks in large cities through a case on the city of St. Petersburg, Russia. It considers optimal solutions for construction of underground car parks in complex geotechnical conditions using Plaxis 2D program. The purpose of the study is to develop technological solutions for the construction of underground parking lots in complex engineering and geological conditions of large megacities with the use of sheet pile fencing. Input data were collected from available engineering and geological surveys datasets obtained from construction sites. The methodology used was 2D design diagrams and a nonlinear Mohr–Coulomb model was used, which made it possible to assess as accurately as possible the geotechnical conditions in the construction area by analyzing horizontal and vertical displacements of the sheet pile wall, soil settlement at the bottom of the excavation, and the maximum settlement of a building located near the excavation. As a result, professional recommendations were developed for construction of underground and multi-storey car parks in complex geotechnical conditions: it is necessary to carry out complex geotechnical support of construction; when constructing a pit in difficult engineering and geological conditions, construct a pit with metal spacer systems (open pit); when constructing a pit near existing buildings and structures, it is very important to take into account the relative position of the base of the foundation and the pit being constructed; accurately and reliably perform calculations in the design and implementation of the construction of underground parking as part of new construction or reconstruction of previously constructed buildings in difficult engineering and geological conditions. The authors of the article have developed new technological solutions that are of great scientific and practical significance to improve the reliability and safety of preserved architectural monuments during the construction of underground parking lots, as well as the safety of neighboring buildings that may be affected by construction or reconstruction.

Heart valve replacement is a major health burden and is required by millions of people worldwide, which invites the continuous need to discover and manufacture more effective and permanent artificial replacements. In the present work, unique models of eight artificial heart valves were designed and examined using seven synthetic and nanocomposite materials. The designed valves were examined to determine the best designs and materials in terms of durability, flexibility, and energy consumption, and to improve the biomechanical performance by using the Response Surface Methodology (RSM) and the Design Expert System 13. The highest values of the equivalent stress due to the applied blood pressure on the moving parts on each type of manufactured heart valve occur in valves with three dimensions moving parts, reached in the mitral tri-leaflet valve 14.13 MPa, followed by the tricuspid aortic valve. The equivalent stresses for other types of valves produced with simple surface action were lower than 2 MPa. The strain energy that is expended during the process of diastole and systole was found to be directly proportional to the strength and flexibility of the materials used. The energy consumption rates decrease when using highly elastic materials such as TPE and PSN4. The values of this energy also increase with an increase in the area of the moving parts of the valve, especially when faced with the process of closing blood flow, as with the use of the tricuspid aortic valve (TAV). The highest total deformation resulted in the valve body when using TPU, followed by TPE, nylon, PETG, and PLA, while the lowest deformation rates were observed when using PSN4, which ranged from 5x105 to 0.1 mm, followed by SIBSTAR103 nanostructured rubber. The obtained values of stress safety factors were decreased with the complexity of the movement for the moving parts of the valve. The highest rates were recorded when using the tricuspid mitral valve, reaching 2.45 when using the high-strength and flexible PSN4 nanomaterial. It can be concluded that the best materials for manufacturing these four types of valves are the PSN4, followed by SIBSTAR103T, TPU, and TPE. The use of PETG, PLA, and nylon materials is not recommended for the manufacture of any prosthetic heart valves, due to their lack of strength, flexibility, and high brittleness, especially for PETG and PLA materials. It was also noted here that PSN4 is the only material suitable for the manufacture of mitral tri-leaflet and tricuspid mitral valve artificial valves. For other types of valves manufactured with a single leaflet, high safety stress factors were obtained because their movement is simple, flat, and in one direction, where the highest values were observed when testing a single hemispherical leaflet type valve, then the conical caged ball and the caged ball type, respectively.

Grid-connected inverters are considered vital elements for effectively connecting renewable energy sources and distributed generation system applications. Ripple-induced current harmonics in DC link and high switching frequency are the disadvantages of grid-connected inverters that are reduced by LCL filters. However, the intrinsic resonance in the LCL filter leads to instability of the power transmission system. As a result, suitable damping is essential for removing resonance in the LCL filters. The contribution of this paper is to improve the quality of injectable power of LCL filter-based grid-connected photovoltaic array. For this contribution, the stability of the grid-connected inverter has been investigated using active damping method, and maximum power point tracking (MPPT) for the PV array has been performed. The capacitor voltage feedforward active damping method considering computational delay is presented in this paper. By using the inverter-side current feedback beside this method, the proposed control maintains the system's low-frequency specifications independent of the grid impedance changes. It provides high harmonic rejection capability without additional compensators. Also, the number of sensors is decreased due to the alternative measurement of the capacitor voltage instead of the grid voltage for the phase lock loop (PLL). Meanwhile, maximum power point tracking is implemented using the incremental conductance (IC) technique in the boost converter. In addition, a simple and suitable computational method for designing LCL filter parameters is presented, and the system’s sensitivity is analyzed. Finally, the simulation has been implemented in MATLAB software that indicates the accurate performance of the control system in injecting the maximum power of the photovoltaic array into the grid and the highly desirable quality of the injectable current to the grid.

Ensuring seismic resilience in earthquake-prone regions is imperative for structural safety. Fiber-Reinforced Concrete (FRC) columns hold promise for enhancing structural performance under seismic conditions. This study seeks to comprehensively evaluate their seismic behavior. The primary objective of this research is to assess and compare the seismic performance of various FRC column types, including polypropylene fibers (PFRC), steel fibers (SFRC), and hybrid combinations (HyFRC), in contrast to conventional reinforced concrete (RC) columns. To achieve this, the study employs eXtended Finite Element Method combined with Concrete Damage Plasticity (XFEM-CDP) in Abaqus to scrutinize static and dynamic responses. The nonlinear static pushover analysis unveiled a notable improvement in seismic resistance across all FRC types when compared to RC columns. Incremental dynamic analyses (IDA) are conducted using the selected suite of 10 near fault as-recorded ground motions to evaluate the inelastic seismic responses of different FRC bridge columns. XFEM-CDP simulations in Abaqus captured multiple aspects of FRC columns, such as concrete cracking, loss of stiffness and plastic behavior. Seismic fragility analysis of these FRC columns is conducted considering four damage states: a) longitudinal steel yielding, b) core concrete crushing, c) steel bar buckling, and d) longitudinal steel bar fracture. The results indicated that HyFRC columns exhibit the lowest damage vulnerability compared to PFRC and SFRC variants.

In linear Fresnel reflectors, field arrangement has a significant effect on optical efficiency. Three constant, optimal, and variable distance layouts are proposed for Fresdemo solar power plant. The study was carried out by simulation and experiment. The small-scale Fresnel concentrator was designed and built with the capability to implement these three arrangements. The optical efficiency of the solar power plant with optimal variable and constant gap between mirrors were compared, considering fixed conditions for all layouts, including overall dimensions of the plant, width, and number of mirrors and dimensions of the receiver. It was observed that the arrangement with the optimal variable, and fixed distance had the highest to the lowest energy efficiency. Besides, the mirrors farther from the center entail more losses due to the sharper tilt angles, hence more spaces between these mirrors is required to reduce the losses. Meanwhile, the last mirrors in fixed distance arrangement have severe losses of shading and blocking while, they produce almost the same energy as central mirrors in the optimal and variable distance arrangement. The experimental results of the developed prototype showed that the thermal efficiency for the optimal distance was the highest, while it was followed closely by variable distance arrangement. The fixed distance arrangement had the lowest thermal efficiency. In addition, the variable and optimal distance arrangements exhibited an efficiency of 54% and 55%, respectively.

The wide area measurement system (WAMS) consists of two different measuring and communication infrastructures, which is respectively responsible for measuring power girds’ data in the wide area and sending and processing them in the control centers. The design of WAMS can include the design of each of its infrastructures or target both infrastructures at the same time, the latter has been known as the WAMS comprehensive design. The WAMS comprehensive design means the simultaneous placement of measurement components and its required communication, which is known as minimum connected dominating set (MCDS) problem in graph theory and is formulated in the form of an optimization problem. Solving such a complex optimization problem is often done with evolutionary algorithms (e.g. genetic algorithm and ant colony), and the speed and efficiency of finding the solution has always been a challenge. This research proposes an adaptive genetic algorithm known as the Adam and Eve algorithm, which has the ability to solve the MCDS problem that arises from the WAMS comprehensive design. Through simulation results for IEEE 1354 bus network, we demonstrate that proposed algorithm is well-tuned to solved MCDS related to the power graphs. It is 30% faster than simple genetic algorithm, handles large-scale problems effectively, and outperforms both simple genetic algorithm and ant colony algorithm within a given timeframe.

Timely access to healthcare is crucial in order to maintain a high standard of living. However, obtaining medical consultations can be difficult, especially for those living in remote areas or during a pandemic when face-to-face consultations are not always possible. The ability to accurately diagnose diseases is essential for effective treatment, and recent technological advancements offer a potential solution. Machine learning (ML) and Natural language processing (NLP) enables computer programs to understand human language and extract desired features from responses, allowing for human-like interaction with users. By leveraging these technologies, healthcare professionals can potentially provide more accessible and efficient medical consultations to individuals, regardless of their location. The concept is to establish an online platform where users can ask medical-related queries and receive responses from both medical professionals and fellow users. The platform would feature a Medical Chatbot, which employs advanced ML techniques to analyze user-provided symptoms and provide initial disease diagnosis and related information prior to consulting with a doctor. This disease prediction chatbot interacts dynamically with the users to enter the symptoms of the diseases and based on syntactic and semantic similarity response is given. In this work the threshold of similarity score is kept of 0.7. K-Nearest neighbors, Random forest, Support vector machine, Naive bayes and Logistic regression algorithms are used for prediction of disease based on symptoms which are faced by users. The syntactic similarity, fuzzy string matching and semantic similarity using all-MiniLM-L6-v2 model is used to improve the efficiency of the result.

Resilience of the innovation ecosystem as a driving force of knowledge-based economies, provides relative stability against environmental disruptions. Currently, finding a comprehensive framework of factors influencing innovation ecosystem resilience is a major concern of policymakers to effectively select policies of resilience improvement. This research analyzes and presents a comprehensive framework of factors influencing innovation ecosystem resilience by using meta-synthesis approach, confirmatory factor analysis and structural equation modelling. These factors include Adaptability, Innovation Management, Recovery Capability, Culture, Resource, Robustness, Strategic Planning, and Vulnerability. In this paper, Iranian Power Innovation Ecosystem is considered as a case study. The computational results indicate that vulnerability and adaptability are the most influential factors on innovation ecosystem resilience, while recovery capacity and resiliency culture are less impactful factors. The innovative aspects of this study include the use of meta-Synthesis method for systematic review, content analysis, and categorization of influential factors, as well as the presentation of a comprehensive framework based on factor analysis and structural modelling. The findings of this research assist innovation ecosystem policymakers in evaluating various factors and planning accordingly to achieve their desired goals based on the aforementioned framework.

Due to the widespread adoption of DC source-based distributed energy resources (DERs) and loads, alongside advancements in power electronics technology, DC microgrids (DC MGs) have recently gained significant attention. To effectively implement DC MGs, it is crucial to employ a suitable control strategy that maintains the bus voltage at the desired level and ensures appropriate power sharing among the integrated DERs. To address these objectives, a two-layer control scheme is proposed in this paper. In the primary layer, a customized droop control scheme is introduced, which applies lower voltage drop in comparison to the conventional droop strategies. Simultaneously, in the secondary layer, a modified voltage controller  which is supplemented by a term to enhance power sharing in a distributed manner is employed,. The proposed control strategies are characterized by their simplicity and low communication infrastructure requirements. To assess the efficacy of the proposed control architecture, several case studies, including plug and play integration, load variations, and communication challenges, including link disconnection and noise effects, are conducted. Additionally, the performance of the proposed strategies is benchmarked against an architecture featuring conventional primary droop control and cooperative distributed secondary control approaches. The simulation studies conducted in MATLAB/SIMULINK software demonstrate that the proposed control methods outperform the alternative approaches, confirming their effectiveness in maintaining voltage regulation and power sharing objectives.

This research presents a rigorous and innovative approach, the Homotopy Perturbation Method-Laplace Transform Method (HPM-LTM), implemented in Python, for the efficient solution of linear and nonlinear partial differential equations (PDEs). By combining the Homotopy Perturbation technique (HPM) with the Laplace Transform Method (LTM), our method successfully addresses the significant challenges posed by equations with nonlinear components. Through the utilization of He's polynomials, the HPM-LTM approach effectively handles nonlinear terms, resulting in accurate and reliable solutions. To demonstrate the efficacy of our method, we extensively apply it to five representative PDE scenarios, including heat and wave equations. Our comprehensive results substantiate the remarkable accuracy and reliability of the HPM-LTM approach, highlighting its superiority in comparison to conventional approaches that require restrictive assumptions or discretization, which can introduce round-off errors. Furthermore, our method overcomes the limitations imposed by numerical errors inherent in traditional HPM techniques. The robustness, effectiveness, and adaptability of our proposed approach are further validated by its successful application to a wide range of PDE problems across various fields. This research presents a significant contribution to the development of a powerful computational tool for resolving diverse PDE problems, with particular relevance to the engineering discipline.

The main goal of this research is to use zeolite TiO2 nanocomposite membranes in order to remove moisture from gas. For this reason, a certain TiZ-V membrane was selected and manufactured as a standard membrane, which was the result of the initial assessment of a suitable membrane for gas dehumidification, and this membrane was used as a standard to measure the effect of manufacturing parameters. The findings showed that increasing the concentration of SiO2 had greatest effect on increasing the water flux of the membrane due to the effect of increasing the reaction time of the vapor phase carrier and reducing the selectivity drop at higher pressures. Also, the experiments of changing the relative humidity of the feed have shown the improving efficiency of the membrane in relative humidities lower than 80%, so that under the conditions of lower relative humidity, the selectivity of the membrane has increased. Another positive point found is a slight change in the selectivity efficiency of the membrane with respect to different relative humidities. This case showed the stability of membrane performance under the different conditions of humidity of the feed gas. Next, in order to increase the performance of membrane as much as possible, the sweeper gas was added from the inside of membrane. Increase in the sweeper gas, which increases the water concentration gradient and decreases the gas concentration gradient on the sides of membrane wall, increases the selectivity of membrane to the highest level of 543.

Glucomannan carboxymethylation is conducted to increase its hydrophobic properties and expand its interaction with hydrophobic compounds. However, glucomannan has high molecular weight and long polysaccharide chain which prevented the modification of its amphiphilic properties. This study aimed to examine the effect of molecular weight, deacetylation, and carboxymethylation on glucomannan properties. Performance of the modified glucomannan to stabilize oil in water (o/w) emulsion was also studied. Ultrasonication was applied to glucomannan at 40 kHz for 15-45 min to obtain various molecular weights. Sodium carbonate (Na2CO3) and sodium monochloroacetate were used as deacetylation and carboxymethylation agents, respectively. The results show that decrease molecular weight supported the deacetylation and the carboxymethylation process on attaching the hydrophobic groups to the glucomannan chain, hence, lowering the hydrophilic properties and swelling degree of glucomannan. Structural and morphological changes of glucomannan after modifications were confirmed from the IR spectra and SEM images. Excellent performance of the amphiphilic glucomannan on stabilizing o/w emulsion was observed as only ~5% phase separation occurred after 300 h of storage in ambient conditions. Hence, ultrasonication is proposed as a suitable preliminary treatment for amphiphilic glucomannan production.

This study focuses on utilizing image data for statistical process control and improving quality monitoring in manufacturing and service systems. The effectiveness of individual and combined feature extraction methods is evaluated, with the Wavelet-Fourier approach identified as the most suitable. The proposed method not only identifies image processing issues but also provides valuable information for estimating change points, fault locations, and fault sizes. This enables the resolution and prediction of faults, leading to cost and time savings in production. To perform evaluation of the proposed method, an image from a tile production line is subjected to Wavelet transform, followed by Fourier transform on the obtained coefficients. The results demonstrate the superiority of the Wavelet-Fourier method over individual methods such as Fourier transform and Wavelet transform. The proposed method exhibits comparable or improved performance in fault detection and localization compared to similar research. This study highlights the potential of utilizing image data for statistical process control and quality monitoring, offering a comprehensive solution for fault detection and analysis. The findings contribute to advancements in image processing techniques and have practical implications for enhancing quality monitoring in various industries. By leveraging image data, manufacturers can make informed decisions, enhance process performance, and improve overall product quality.

This study has been conducted aiming at improvement of a multi-agent model whose task is planning and energy management of a power distribution system based on electric vehicles and their aggregators. In this work, the wear of automobile batteries is considered as an inhibitor agent for electric vehicle owners which affects other agents. Therefore, the aggregator agent should consider the cost as encouragement for the owners of electric vehicles. The agents used in this paper are: 1) Technical agent distribution system operator 2) Distribution System Operator market agents 3) Electric vehicle aggregator agents. This paper proposes a strategy for the aggregation agent of electric vehicles in a competitive electricity market, taking into account market reservations. This model provides a way to reimburse vehicle owners for battery burnout over the consumption cycle and it helps to increase the desire of electric vehicles to charge and sell electricity to the market and increase the profits of vehicle agents and owners.

Admixture is a common phenomenon in human populations, resulting from the mating of individuals from two or more previously isolated populations. This can lead to the formation of mosaic DNA segments, with each segment originating from a different ancestral population. Local ancestry inference methods are used to identify the ancestry of each segment, which can provide insights into the history of admixture in a population. Many local ancestry inference (LAI) methods require the determination of various parameters that may be difficult to obtain, which can hamper using LAI methods. In this paper, we present a novel method for identifying approximate boundaries of ancestry change (IABAC) in admixed haplotypes and then determining the ancestry between boundaries. Unlike many LAI methods, our method does not rely on many statistical or biological parameters, therefore more robust to variations in admixture patterns. We evaluate our method on human data, and show that it is more accurate than existing methods for ancestry detection. Our results suggest that IABAC is a promising new method for identifying ancestry boundaries in admixed haplotypes. This method could be used to study the history of admixture in human populations, and to identify genetic variants that are associated with different ancestral populations.

Vertical geometric irregular reinforced concrete (RC) buildings are widely used in structural engineering due to their aesthetic appearance and functional characteristics. Indeed, improving their reliability and seismic performance is of crucial interest and has even become a necessity. This research study underlines the importance of using shear walls (SW) as a fundamental means of reinforcement for this type of structure. Twenty models, including ten with SW and ten without SW, of mid-rise buildings with setback irregularity were considered for this purpose, and fragility analyses were carried out, using a non-linear procedure, to highlight the potential usefulness of shear walls for irregular structures. The results of this work clearly indicate that the dynamic behavior and response of buildings have been improved by the use of shear walls. The fragility study reveals that for some cases the damage probability is reduced, with the difference exceeding 13% for the majority of models, and for some cases the differences are highly significant, ranging from 30% to 60%. This shows the benefits of incorporating shear walls into the design phase of irregular buildings.

The scientometrics has become the most important tool to evaluate and analyze the performance of scientists, cooperation between universities, the impact of public funding of science on the results of national research and development, the effectiveness of education, and others. Therefore, professionals and scientists need a range of theoretical and practical tools to measure experimental data. The purpose of this article is to provide an up-to-date overview of the various tools available for scientometric analysis, including data sources, performance analysis and visualization tools. In this study performed a scientometric analysis based on 21,180 publications from the Scopus database was conducted with only published articles in mining industry between 1960 and 2023. It also revealed that 77% of the articles were published in journals and only 2.6% corresponded to review studies. Using network analysis in VOSviewer, the publications were grouped by keywords into 5 clusters with Strength. Cartographic analysis confirmed the descriptive findings and visualized the co-authorship of authors. Using bibliographic linkage analysis, the semantic relationship between authors and their associated institutions and countries was investigated (consist of 38 clusters with 404 link). Average number of citations per keyword (3.2) will allowed the most cited area is devoted to health risks. Recent studies have focused on dust and lung diseases which can pose a serious threat to the life and health of mine workers, therefore risk of coal dust explosions, which  in result poses a direct risk of injury or even loss of life.