International Journal of Engineering
Volume:36 Issue: 5, May 2023

Since power systems are susceptible to damages induced by disastrous incidents, the assessment and improvement of system resilience are unavoidable as a new goal of planning and operation. On the other hand, the expansion of generation and transmission grids constitute an essential part of power system planning as it needs a huge budget. So, a primary concern of researchers has always been the optimal planning of power systems. This paper studies the emerging concept of resilience, its criteria, and indicators, how to enhance it, and the identification of its strengths and weaknesses. It also reviews the strategies recommended in the literature to improve power system resilience. The paper briefly reports the models for expansion plan analysis and the generation and transmission expansion planning (GTEP) tools with or without the target of resilience enhancement, which can be instrumental in future research and can be used to estimate the effectiveness of different tools. Furthermore, the paper discusses the planning problems, thereby opening the way for further work in future studies. Finally, the study presents the most eminent challenges of GTEP to accomplish better, resilient, and innovative plans to escalate power system resilience.

Network Real-Time Congestion (RTC) is a bottleneck that limits energy transfer from the generation units or up-grid to the loads. Some factors, such as intermittent generation of renewable resources and forced outages of generating units and load forecasting errors, can lead to Real-Time Congestion Management (RTCM) in a smart grid network. RTCM is a set of methods to eliminate congestion in real-time. To implement RTCM, some approaches can be employed, including network reconfiguration by Remote Control Switches (RCS), load shedding generation and up-grid power rescheduling. In this paper, a two-stage programming model is proposed to find the optimal solution for RTCM using the integration of reconfiguration and market-based approaches. Therefore, following the occurrence of congestion, at the first stage, microgrid central controller (MGCC) or central energy manager implements reconfiguration as the lowest-cost approach to mitigating RTC. The Soccer League (SL) algorithm is employed at the first stage to find the optimal network topology. Subsequently, based on the results obtained from the first stage, a programming model is applied at the second stage to completely eliminate the RTC. The proposed model minimizes a weighted objective function that includes the generation and up-grid rescheduling cost, load shedding cost, switching cost, and congestion clearing time. In order to model switching costs, a new index is defined to prevent risky switching and the depreciation caused by frequent switching. This index is determined based on the critical locations in the network and the age of RCSs. The numerical results demonstrate the efficacy of the proposed model.

The literature and previous research revealed that reducing the variation order by selecting the favorite material visually by the project's owner in the design stage is not available recently. As a problem, the cost estimates in real-time from walk-through interactions selecting multi-alternative building components are a potential threat to projects' success unless there is a visualization system helping to decide the costs of different building items and the items’ suitability. This research is a powerful tool that allows the project's owner to reduce the variation order by visually selecting his favorite material in the design stage. It expresses the application of Building Information Modeling (BIM) with Virtual Reality (VR) to improve Cost Estimation (CE) and the material selection process. The authors utilize BIM and virtual reality technology to enhance the visualization and processing of project cost estimation in the construction industry. In this study, the primary goal is to develop a BIM-VR-CE system that helps construction stakeholders to visualize and quickly to decide the costs of different building items and the items’ suitability. Accordingly, the authors developed a BIM-VR-CE system that integrates BIM and virtual reality technology using Unity 3D. Navigating building environments in real-time with the ability to select the cost and items suitable for elements of projects is now available to construction stakeholders through the BIM-VR prototype developed in this paper. To evaluate the effectiveness of the proposed preliminary model, a questionnaire was created, and 85 evaluations were collected. The findings of this paper show significant potential to utilize the proposed model in construction projects to deal with cost, reduce the variation orders, and select the favorite elements.

In patients with refractive errors or impaired vision, light rays received by the pupil do not fall directly onto the retina. This can be corrected by wearing monocled glasses. The focal point of the eyeglass lens needs to be adjusted to the center of the user's pupil. This can be known through the measured pupil distance (PD) value information. The measurement of the PD is very important to determine the center distance of the pupils in both eyes. where the eye does not experience the prism effect. This study aims to apply the radial symmetry transformation (RST) method combined with self-quotient (SQI) imagery to detect the pupillary center and measure PD. This algorithm combines to get more optimal results in detecting the center of the pupil in dark conditions or those exposed to shadow illumination. The program created using the MATLAB software simulates PD measurements for pupillary center detection in bright and dark images conditions. The test was carried out ten times, and the results showed that the system was able to measure PD on low-resolution images of 300 x 300 pixels at 72 dpi in bright image conditions; with measurement uncertainty values in each image of 0.60 mm. As for testing on dark images, the uncertainty values are 0.80 mm. In this case, the standard deviation value is obtained from the effect of the different dimensions of the face object on the tested image.

Coffee is a crucial agricultural commodity in developing nations like Indonesia; so it is important to implement a trustworthy traceability system for the product. However, there are no established guidelines for developing a blockchain-based traceability system that the coffee industry can adopt. Therefore, this study aims to present a Digital Business Ecosystem (DBE) framework and a blockchain-based traceability system prototype for Indonesian coffee. The study process involved a literature review, field observations, and the creation of the proposed frameworks and prototypes using an integrated rapid prototyping method. The proposed DBE framework has three layers: business, digital, and infrastructure, while the prototype has use case diagrams and a model of functional, technological, and transaction flows. The system was validated through deployment tests such as recording-tracking coffee data using Ethereum smart contracts and interplanetary file system. The interconnectivity was verified through a mobile-based user interface design that includes registration and login pages, a main page, a transaction confirmation page, and a traceability page. It was discovered that the proposed framework and prototype have a high potential for real-world implementation due to their ability to effectively address the challenges and promote a positive business community culture while being supported by the mapped DBE layers. Further study is recommended to test and enhance the proposed framework and prototypes and examine the relationship between system development and technology adoption. Moreover, managerial insights were provided to the coffee business community, policymakers, and developers for the successful development of Indonesian coffee DBE with the blockchain-based traceability system.

Babbitt-Ilmenite composite prepared via stir casting method with controllable parameters which include percentage weight of Ilmenite, stirring speed and aging time was investigated for its sliding wear characteristics and coefficient of friction (COF) with varying applied load, sliding velocity and sliding distance. Morphological tests were conducted for characterization of the composite and to ascertain the wear mechanism under mild and severe conditions. Taguchi philosophy with analysis of variance (ANOVA) statistical technique was used for multi-objective optimization of the tribological characteristics of the composite. The entropy based grey relation analysis (EGRA) performed for weighted multi-performance optimization of tribological aspects of the composite and hybrid Taguchi grey relation technique (TGRA) confirmed that the percentage weight of Ilmenite, applied load, sliding distance and stirring speed were the significant parameters with regard to multi - criteria optimization with contributions of 44.46%, 23.82%, 11.33%, and 5.66%, respectively. There is an overall improvement in wear resistance and COF at optimal TGRA conditions. Babbitt-Ilmenite composite can be used in steel slide bearing bushings for power, automobile and aerospace.

The utilization of fibers in the concrete reduces cracks, increases the energy absorption and concrete strength. The use of fine recycled aggregate (FRA) in concrete overcomes the scarcity of natural aggregates, however its deprived quality affects the concrete properties through development of cracks. This study investigates the effect of glass fiber (GF) utilization in reducing crack propagation using fine recycled aggregate (FRA) in the concreteThe coarse natural aggregate (CNA) was replaced with 10, 30, 50, 70, 90 and 100% of FRA and GF was added 0, 0.25, 0.5, 0.75, 1 and 1.5% by weight. The concrete mixtures with the optimal percentage of FRA and different percentages of GF were prepared by two-stage mixing approach (TSMA) and normal mixing approach (NMA) and tested for their fresh and hardened properties. The optimized mix was observed with 30% of FRA and 1% of GF prepared by TSMA, with a strength improvement of 11.3% compared to the control mix at 28 days. The study further investigated the practical suitability as a paver block for non-traffic and medium volume traffic applications as per IS 15658: 2006 and observed that minimum strength requirement of 40 MPa was achieved under both conditions with the optimized mix with an improvement of 17.4% compared to conventional paver block.

Surface roughness significantly affects the scattering of load-displacement curves and the measurement of mechanical properties by the macro-scale indentation. Many mechanical properties such as modulus of elasticity, yield stress, strain hardening exponent, and hardness can be determined using the indentation results, which are the information obtained from the load-displacement curve. Reliable parameters of the load-displacement (P-h) curve are employed to estimate the mechanical properties. The inaccurate P-h curve leads to a misestimation of material properties. Ignoring the surface roughness might be a source of error in the indentation results. In this paper, the effects of surface roughness on the P-h curve of macro spherical indentation and Brinell hardness number (BHN) were studied. The range of roughness with minimal effect on indentation results was obtained. The surface roughness of 2 and 12 microns was created on the experimental samples using the electrical discharge machining (EDM) process. The finite element simulations were performed with different surface roughnesses. The results showed that roughness affected both the P-h curve and hardness values in different indentation depths and various indenter sizes. It was observed that with increasing the Rq roughness, the P-h curve level and hardness value decreased and that with increasing the indentation depth, the effect of roughness on hardness decreased as well. The neumerical results showed a good agreement with the results of experiments.

In the healthcare system and hospital environment, the data security and the data connectivity are the major factors to consider for patient data management system. For that, there are several techniques are used to preserve and arrange the patient data with enhanced security system. In that, Blockchain structure of data management improves the secure data storage and transmission process. In the data security system, the quality measure can be validate by means of the size of key that are used for the encryption process. Combined with the blockchain, the encryption model is to be improved for the solve the problem in data security system. This also needs to focus on the size reduction of data storage due to the large key size of encrypted data. In the proposed work, Intuitionistic Derivative Symmetrical Encryption (IDSE) Algorithm based security algorithm along with blockchain function was integrated to form the authorized data storage and transmission process. For the key pattern generation, Differential Hashing Pattern (DHP) based key pattern extraction model was used for high speed data transmission and to reduce the size of data that are encrypted. The features that are considered for the appropriate security system are the data transmission pattern with respect to the time and the hashing model of key generation. In the result analysis, the performance of the IDSE-DHP are validated with the parameters of data transmission and loss rate in the Blockchain and with the throughput related features.

Copper anode slime, a valuable by-product generated during the electrorefining process, is an important secondary resource for the recovery of metals, such as gold, silver, selenium, tellurium, PGMs and copper. A full characterization of the anode slime is an essential part of the efficient recovery of these valuable metals. In this research, the refinery slimes of the Sarcheshmeh and Khatoon-Abad copper complexes, were fully characterized and compared using inductively coupled plasma (ICP), X-ray diffraction (XRD), X-ray fluorescence (XRF), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), thermogravimetric analysis (TGA), differential thermal analysis (DTA), and particle size analysis. Besides the bottom cell slime characterization, properties of the Sarcheshmeh’s adherent slime was also analyzed and correlated. Sarcheshmeh copper slime particle size was found much smaller than the Khatoon-Abad slime. For both slimes though, the major part the gold and tellurium are located in larger than 38-micron particles. The main difference in thermal analysis of the two slime samples was originated from their selenium content difference. This has caused the higher concentration of non-selenide copper compounds at Khatoon-Abad slime, resulted in its easier copper recovery. Decopperization of both bottom-cell slimes were investigated and a significant difference in copper dissolution behaviors of the two slimes were observed due to their characteristic difference including the copper-selenide phases and capsulated copper in the barium sulfate agglomerates. Copper dissolution from Khatoon-Abad slime was observed to reach 90% comparing to 40% for Sarcheshmeh slime using atmospheric leaching.

The identification of structural systems with unknown vibration signature response is still a challenging issue which has been addressed by many reviewers. The current sensor technology states that the sensor position should be very close to the damaged element in order to identify and localize the damage. The primary goal of this research is to present a baseline-free method using the roving mode shape response based, multiple damage localization in a cantilever beam. Consequently, the damage location indicator is based on the roving mode shape approach (DLRA). The theoretical development is carried out on a cantilever beam, a finite element model. The different cases for multiple damages i.e. 2 elements damage, 3 elements damage and 5 elements to be damage, at a time, have been modelled on the structural member. The system response, for the healthy and damaged structural systems, has been determined using the roving mode shape approach. Further, the algorithm has been developed for multiple damage identification and localization using MATLAB software. The combined mass and stiffness damage, as well as only the mass change damage, both cases were considered. From the results, it was found that the proposed method can reliably identify the damage and its position. The method will also be helpful while keeping the sensor’s position very close to the damage. The novelty of this method is that it uses the response which is basically a field output and no prior assumptions have been made at the damaged element's location.

In this research, the engineering characteristics of self-compacting lightweight concrete (SCLWC) containing carbon nanotubes and steel micro-fiber were evaluated. The variables included the amount of carbon nanotubes (0, 0.02, 0.04, and 0.06% by weight of cement) and steel micro-fiber (0, 0.5, and 1% by volume). Lightweight expanded clay aggregate was used as lightweight aggregates. The experimental tests were self-compacting tests, compressive, splitting tensile, and flexural strengths, ultrasonic pulse velocity, electrical resistivity, water penetration depth, and scanning electron microscope. Adding 0.02 to 0.06 percent of carbon nanotubes to SCLWC reinforced with steel micro-fiber increases the compressive strength by about 33 to 64 percent. The use of 0.06% carbon nanotubes and 1% steel micro-fiber increased the splitting tensile strength by 36%. The use of carbon nanotubes and steel micro-fiber has the effect of influencing the filling of empty spaces and reducing concrete porosity. This can be attributed to the growing process of cement paste hydration and the filling of pores and capillary pores with the products of cement reactions, resulting in concrete compaction. Adding 0.02% carbon nanotubes to SCLWC samples containing 0.5% and 1% steel micro fibers increased the 28-day compressive strength by 36%, 34% and 33%, respectively.

The battery electric vehicle (BEV) adaptation is at an accelerated pace due to its zero tail-pipe emissions and estimated environmental benefits. However, when considering an electric vehicle's entire life cycle, the environmental benefit could be a deception. It should be reckoned whether electric vehicles are really environmentally friendly and if they are, then under which conditions? According to the literature, the carbon footprint of electric mobility varies by geographic location as well as by the regional energy mix and the environmental impacts might exacerbate by introducing a plethora of electric vehicle. Since very less research has been carried out in the Indian context; this paper contemplates the environmental impacts of BEV and compares it with conventional vehicles performing a life cycle assessment.The paramount purpose of the study is to unveil weather BEVs are low carbon transport mode in India and where do they stand compared globaly. The results reveal that out of 18 impact categories considered under mid-point analysis, BEV outperformed IC Engine vehicles for 10 categories. The green house gases emissions from a BEV is 242 g CO2eq/km at mid-point level and the single score at end-point level is 0.58 kpt compared to that of ICEV which has 2.1 kpt. Further, separate impacts from the production and the use-to-end life phase were derived to pinpoint the major emission contribution phase. At the ReCePi end-point analysis BEV favors being more environmentally friendly, however, switching to cleaner energy will further alleviate the environmental impacts.

Extensive research have been conducted to optimize the water distribution networks, but none has simultaneously considered the economic-mechanical and hydraulic properties of the networks. Moreover, the entropy difference in the various networks has not been exactly calculated. Therefore, the present study suggests a modified entropy function for computing the information entropy of the water distribution networks to calculate the demand nods and entropy difference amongst the various networks considering the mechanical and hydraulic properties of the network. This modification is carried out by defining a coefficient in entropy function as the output amount in every node by the exponent of all the power wasted in the network. Furthermore, the most optimum diameter and the most economic state are obtained simultaneously using the ant colony algorithm (ACO). Thus, considering all the three mechanical, hydraulic, and economic properties of the network while keeping simplicity, a more realistic method will be offered using these two metaheuristic methods. The efficiency of the proposed method was evaluated in some of the sample water networks using the modified function

The predictive accuracy of the finite element (FE) based packages are broadly based on the compatibility of adopted non-linear numerical procedures and incorporated material models. However, the routine way to define concrete material is not applicable to the concretes containing substitute materials in place of conventional concrete ingredients. Therefore, in this work, appropriate definition of materials in terms of stress-strain relations have been utilized to simulate the experimental work of RC beams containing coarser fractions of recycled concrete aggregates (RCA). The entire work has been carried out into two phases; an experimental work and the simulation of experimental work using FEA package, ABAQUS. In the experimental part, three number of full-scaled beam specimens were tested to failure through four-point monotonous loading. The replacement level of natural coarse aggregates was taken as 0.0, 50 and 100% by direct substitution. In the simulation phase, in addition to laboratory evaluated properties like compressive stress, tensile stress and elastic modulus, the measured stress-strain relationship for reinforcing steel and constitutive relationship for recycled aggregate concrete (RAC) reported in the literature have been considered as an input. The stress-strain relationships of RAC selected from the literature has been treated as user defined model. Besides the strength, serviceability in terms of deflections, crack patterns and load deformation characteristics of simulated beams have been investigated and compared with those of laboratory tested beam specimens.

Earthquakes cause a lot of damage to structures. A quantitative estimate of the amount of damage to the structure always seems quite necessary after an earthquake. For this purpose, seismic damage indices have been introduced as dimensionless quantities that can report the extent of damage using various criteria. This quantitative assessment can help make decisions about the process of improving, repairing, and strengthening structures. This paper presented a new stiffness-based damage index with simple formulation by performing pushover analysis on existing concrete models and applying the results. Using the capacity curve obtained from the pushover analysis output, this index can provide a quantitative estimate of the amount of damage to the entire structure. To validate the results, damage estimation was also performed using several reliable models such as the Park-Ang model and then compared with the proposed index results. Then, a series of theoretical suggestions were presented to address the existing weaknesses, which were implemented, and new results were obtained. Finally, the implemented reform proposals led to an improvement in the performance of the proposed index, resulting in excellent accuracy due to the simple computational process compared to the complex implementation of the Park & Ang index.

This study developed unified theory of acceptance and use technology (UTAUT) to examine the predictive factors of mobile marketing adoption. Variables such as personal innovativeness, hedonic motivations, performance expectancy, mobility, and social influence were studied for mobile marketing acceptance. The predicted artificial neural networks (ANN) approach was applied to evaluate the data, and the results of the data were used for comparison with path analysis. The ANN model was derailed by the linear statistical model and was able to show the importance of all predictors that could not be identified by the path analysis model. The results show that personal innovativeness is the most effective factor in mobile marketing acceptance. Subsequently, the hedonic motivations, performance expectancy, mobility, social influence, trust, and facilitating conditions play a vital role. Furthermore, the results illustrate that price value, perceived risk, and effort expectancy were not effective.

This article is about mixed-mode multiphase sinusoidal oscillators that are made up of differential voltage current conveyor transconductance amplifier (DVCCTA) and use all the grounded passive components. The proposed multiphase sinusoidal oscillators provide a single DVCCTA, a single grounded resistor and a capacitor for each phase which is suitable for integrated circuit implementation. In addition, the sinusoidal outputs generate currents and voltages simultaneously. The current signals from the outputs have high impedances, which make it easier to connect them directly to the next circuit or stage. The proposed circuits can generate multiphase sinusoidal signals that are both equally phased and in amplitude. The oscillation can be adjusted simultaneously of the frequency of oscillation by the electronic method. A simulation with the PSPICE program and an experiment with commercially available ICs (AD830, AD844, and LM13700N) demonstrated. The results show the efficiency of the circuit is completely consistent with the theory.