International Journal of Engineering
Volume:36 Issue: 7, Jul 2023

Novel ultrafiltration mixed matrix membranes combined by dual nanofillers Graphene Oxide + Functionalized Halloysite Nanotubes (GO/FHNTs) were prepared. In this work, we improved the performance and properties of polycarbonate-based membranes for oil/water separation applications. The morphology and other properties of the fabricated membranes were characterized by different analytical method including Field Emission Scanning Electron Microscope (FESEM), Fourier-transform infrared spectroscopy (FTIR), contact angle goniometer, and mechanical strength apparatus. The obtained results confirmed that addition of GO/FHNTs had a positive effect on hydrophilicity and tensile strength. Also, the water permeation of the optimum GO0.25-FHNT0.75 membrane was about 2.5 times more than pure polycarbonate. Overall results showed that all membranes reached 100% oil separation efficiency at various ultrafiltration times. Furthermore, the optimum membrane showed a flux recovery ratio of more than 90% where the permeate fluxes of feed solutions with 100 ppm and 200 ppm olive oil concentrations were reduced to only about 5.5% and 6% after three regeneration cycles, respectively.

The seismic performance of non-structural components (NSCs) has been the focus of intensive study during the last few decades. Modern building codes define design forces on components using too simple relationships. The component accelerates faster than the floor acceleration to which it is connected. Therefore, component dynamic amplification factors (CDAFs) are calculated in this work to quantify the amplification in the acceleration of NSCs for the various damping ratios and tuning ratios of the NSC, and the primary structural periods. From the analysis results, it was observed that CDAF peaks are either underestimated or overestimated by the code-based formulae. A prediction model to ascertain the CDAFs was also developed using artificial neural networks (ANNs). Following that, the suggested model is contrasted with the established relationships from the past research. The ANN model's coefficient of correlation ( ) was 0.97. Hence, using an ANN algorithm reduces the necessity of laborious and complex analysis.

Fusing textual information, as type of information fusion, has been of great significance to those interested in making informative texts out of the existing ones. The main idea behind text fusion, like any other type of information fusion, is to merge the partial texts from different sources in such a way that the outcome can hold a reasonably high relevance with regard to certain objectives. In this paper, a fuzzy framework is proposed for text generation, according to which a range of relevant texts are merged to yield producing a new text that can help the users fulfill a certain functionality in plausible manner. The focal point in our approach with regard to fusion is the distance between the class prototype of a text on the one side and the feature vectors belonging to different subsets of the existing texts on the other side. Results of experiments, show that the suggested framework can be a suitable alternatives for performing fusion in the cases that the identity of the existing texts from the viewpoint of the texts considered is unclear. This would turn into an effective utilization of the existing texts for the purpose of generating new texts.

Load shedding is generally regarded as the final option to evade voltage collapse and blackout following major overloads. The traditional method of load shedding curtails random loads regardless of their importance until the system’s voltage is improved. Shedding random loads without considering their priority will lead to power interruption in vital infrastructures. Hence, to improve the existing power system protection scheme, development of a more effective and efficient load shedding method is necessary. In this paper, an optimal under voltage load shedding (UVLS) method is proposed for optimum prediction of amount of load shed and the best location for load curtailment. Moreover, the proposed method is designed to maintain the vital loads in the system during the load shedding process. In this work, the stability index (SI) and feed-forward backpropagation neural network (FFBPNN) were adopted to avoid voltage collapse and blackout by mitigating voltage instability following overloads in distribution system. The performance of the proposed method to several overload scenarios is investigated. Case studies performed on the IEEE 33-bus system exposed significant robustness and performance of the recommended technique. Compared to other approaches, the proposed approach is efficient in counteracting under-shedding occurrence, enhancing the voltage profile, and improving the stability of the system, whilst maintaining vital loads in the system during load shedding.

Due to the strong electromechanical coupling, small size and high sensitivity, piezoelectric nanomaterials have been widely used in generators, sensors and other fields. In this paper, the characteristics of energy collector in IIoT power supply system based on piezoelectric nano-materials are analyzed. PVDF piezoelectric nanofibers are prepared by electrospinning technology. The material and control chips are integrated into a bimodal piezoelectric energy collector. The effectiveness is analyzed experimentally. The experimental results show that the resonant frequency of energy collection varies with the length of the cantilever arm. When the length of the cantilever arm is 12mm, the installation error of 1.0mm length leads to 3.5% of the resonant frequency error. The optimal load of piezoelectric vibration collectors with different cantilever arms is 400K. The output power of CUB, BRG and BTG are 50.7 μ W 55.6 μ W and 51.8 μ W, respectively. At the same time, the working frequency band of energy collectors with various cantilever structures is 12Hz to 18Hz. The optimal excitation frequency is 16Hz. In summary, the energy collector of power system constructed by piezoelectric nano-materials proposed by many researchers has high efficiency, which can provide a quick solution for IIOT in Industry 4.0 and enhance the power generation mechanism. It is of great significance to the development of IIOT in practice.

Bi-directional power converters are utilized for effective management of available electrical energy associated with renewable energy systems with the use of an energy storage system. Improved hybrid three quasi z source converter (IHTQZSC) is proposed in this paper which has been providing a higher voltage gain without any switched capacitor or charge pump cells. IHTQZSC has been intended for bi-directional power transfer and control applications in this paper. The converter ensures a widespread voltage gain in a single stage DC↔AC power conversion system with lesser shoot-through time instants. The competence of the converter is acclaimed with voltage stress, current stress, peak switching device power and power losses compared with the other high voltage gain converters. Impact of voltage gain and power drawn by the converter on the efficiency has been explained. The four-quadrant power control is achieved with the constant switching frequency predictive controller. The DC-link voltage of the converter is controlled with a PI controller, and a predictive controller is used for the grid current tracking. The bi-directional working of the converter is illustrated with MATLAB/Simulink software

Caverns are massive underground openings excavated for purposes like defense installations and nuclear waste disposal which becomes challenging for weak strata consisting of fractured rock masses and may result in future calamities. This study is dedicated to ascertain stability of a horseshoe cavern in different types of granitic rock masses as well as fractured rocks. Two different types of granitic formations are accounted and displacements obtained along cavern periphery have been illustrated in the preliminary part of this study. An increment in vertical displacement at the crown of 260% and lateral displacement of almost 170% for both walls were observed for moderately weathered rock. Further, implications due to orientation and frequency of joint sets on the displacements incurred has also been explored. This study acquires its novelty by considering combinations of joint sets with varying spacings for investigating their implications on cavern walls. Presence of discontinuities depicted that horizontal joint spaced closely increased the deformation magnitude which reduced with decrement in joint frequency. Subsequently, along with horizontal joints at 4m interval, vertical and oblique joints sets were also incorporated at different frequencies. Consideration of vertical joints at 2m spacing with horizontal joints resulted in 313.2% increase in vertical displacement at cavern crown as well as 340% and 363% increase in lateral deformation at the left and right wall, respectively in comparison to intact rock. In case of oblique joints spaced at 2m with horizontal joints, increment in vertical deformation at the crown proliferated to 329% in comparison to intact rock.

The impact of aluminium nitride (AlN) Spacer, Gallium Nitride (GaN) Cap Layer, Front Pi Gate (FG) and Back Pi Gate(BG), Dual Floating material  High K dielectric material such as Hafnium dioxide (HfO2), Aluminium Oxide (Al2O3), Silicon nitride  (Si3N4) on Aluminium  Galium Nitride/ Gallium Nitride (AlGaN/GaN), Heterojunction High Electron Mobility Transistor (HEMT) of 6nm technology is simulated and extracted the results using the Silvaco Atlas Technology Computer-Aided Design (TCAD) tool.The importance of High K dielectric materials like Al2O3 and Si3N4 were studied for the proposal of GaN HEMT. AlN, GaN Cap Layers, and High K Dielectric material are layered one on another to overcome the conventional transistor draw backs  like surface defects, scattering of the electron, and less mobility of electron. Hot electron effect is overcome by Pi type gate.Triple tooth floating material is placed in the buffer layer to improve breakdown voltage. Therefore, by optimizing the HEMT structure the inabilities for certain devices are converted to abilities. The dependency on DC characteristics and RF characteristics due to GaN Cap Layers, Multi gate (FG &BG), and High K Dielectric material, Dual triple tooth material in buffer layer  with recessd gate  is established. Further Compared Single Gate (SG)  Passivated HEMT, Double Gate (DG) Passivated HEMT, Double Gate Triple (DGT) Tooth Passivated HEMT, High K Dielectric Front Pi Gate (FG) and Back Pi Gate  (BG), Asymmetric High K Dielectric Front Pi Gate (FG) and Back Pi Gate (BG) with recessed gate Nanowire HEMT. It was observed that the proposed resulted with increased Drain Current (Ion) of 7.5 (A/mm), low Leakage current (Ioff) 3E-15 (A), Transconductance (Gm) of 4.8 (S/mm), Drain Conductance (Gd) of 2.5 (S/mm), Maximum Oscillation frequency (Fmax) 745 GHz, Minimum Threshold Voltage (Vth) of -4.5V, On Resistance (Ron) of 0.12(Ohms) at Vgs =0V.

In computer vision, contour/edge detection is a crucial phenomenon. Edge detection is an important step in contour detection, which is helpful in the identification of important data. The accuracy of the edge detection process is heavily dependent on edge localization and orientation. In recent years, due to their versatility, soft computing approaches have been considered effective edge detection strategies. Broadly, edge detection accuracy is deeply affected by weak and dull edges. In recent works, edge detection based on fuzzy logic (FL) was proposed, and image edges were improved using guided filtering. However, guided image filtering (GIF) does not take into account the local features of an image. To include local features of an image for edge detection, an improved version, i.e., an offset enable sharpening-guided filter is used in this paper, and FL is used for edge detection. The figure of merit (FoM) and F-score are used to evaluate the method's accuracy. Using visual representations and performance metrics, the results are compared with those from cutting-edge techniques.

This paper demonstrates the effect of adding basalt fibers into a concrete matrix and altering tie spacing on the behavior of short concrete columns since short columns are more robust than long ones and are primarily used in structures. Also, the impact of changing the reinforcement ratio on column behavior is numerically discovered. Three volume fractions of basalt fiber and three-tie spacing are adopted. The results illustrate that no-fiber columns sustain more than 50 % of the failure load before cracking, while this percentage raised to 75 % upon adding basalt fiber to concrete. 0.3 % of basalt fiber increases the compressive strength, cracking and ultimate column loads better than 0.6 %. Likewise, the impact of basalt fiber on the crack load is more pronounced than on the maximum load of the column. Basalt fiber columns exhibit lower longitudinal displacement than no-fiber ones at the cracking state. The shortening increases with increasing tie spacing, whereas decreasing tie spacing barely increases the ultimate load of the column. The numerical analysis provides close results to the experimental ones and shows that increasing the reinforcement ratio raises the column's load capacity. For the same tie spacing, increasing the reinforcement ratio raises the loading capacity of columns, and the longitudinal displacement barely increases upon increasing spacing. Generally, basalt fibers delay cracking and improve the column loading capacity.

A compound of a modified incinerator system with an organic Rankine cycle (ORC) was analyzed and optimized regarding exergy and energy. This paper provides an overview of system performance considering thermal aspects in a conceptual design to understand the technical effects of the system on future energy systems; it also provides a way to increase efficiency up to an amount that did not exist before in practice by using optimization. The conceptual design uses multiple flue gas regeneration units, and R124 is used as ORC working fluid. The power plant is modeled and optimized for its thermal performance. An innovative cycle is designed to reuse the wasted heat, which makes the evaporator more efficient and increases the overall exergy efficiency of the power plant. Then, the exergy destructions and systems efficiency are observed. The results indicate that 3.19 MW output power could be generated from municipal wastes with capacity of 400 tons/day. The highest destruction of exergy for the incinerator unit and boiler were approximately 8 kW and 6.4 kW, respectively. For the primary cycle the  power output capacity was almost 2.8 MW. Also, this research increased their exergy efficiency by using heating flow streams. The ORC cycle could not produce high power but generally improve the exergy and energy efficiency. The proposed combined cycle with flue gas reheating units and optimization increases the system output power from 3.02 to 3.19 MW. Furthermore, energy and exergy efficiency increased by 10% and 9%, respectively.

Cloud manufacturing (CMfg) is a new advanced manucatring model developed with the help of enterprise information technologies under the support of cloud computing, Internet of Things and service-based technologies. CMfg compose multiple manufacturing resources to provide efficient and valuable services. CMfg has a highly dynamic environment. In this environment, many disruptions or events may occur that lead the system to unplanned situations. In CMfg, a series of service providers are scheduled for production. During the production operation, some of them may be damaged, stopped, and out of service. Therefore, rescheduling is necessary for the continuation of the production process according to the concluded contracts and initial schedule. When any disruptions or other events occurred, the rescheduling techniques used to updating the inital schedule. In this paper, the dynamic rescheduling problem in CMfg is analyzed. Then the multi-objective rescheduling in CMfg is modeled and defined as a multi-objective optimization problem. Defining this problem as a multi-objective optimization problem provides the possibility of applying, checking and comparing different algorithms. For solving this problem, previous optimization methods have improved and a multi-objective and elitist algorithm based on the Jaya algorithm, called advanced multi-objective elitist Jaya algorithm (AMEJ) is proposed. Several experiments have been conducted to verify the performance of the proposed algorithm. Computational results showed that the proposed algorithm performs better compared to other multi-objective optimization algorithms.

Future wireless networks will use Universal Filtered Multicarrier (UFMC) as a new waveform modulation technique. The UFMC waveform sensibly considers the sub-band filter specifications such as filter order, and shape to combine the key benefits of the present generation modulation waveforms while averting their disadvantages. Therefore, in UFMC-based systems, it is important to pay attention to how the sub-band filter is made. In this paper, the sub-band filter configuration is adapted according to the sub-band size such that the UFMC symbol generates the minimum level of interference with minimum frequency selectivity. Also, the total interference caused by inter-carrier interference (ICI) and inter-sub-band interference (ISBI) was studied by finding the closed form of its change in the UFMC signal with sub-band size and filter length. From this analysis, we determined the ICI increases and ISBI decreases with filter length.  Therefore, the proposed method optimizes the filter length in terms of sub-band size and interference. By this approach, the filter length is shorter than the conventional method and hence improves the symbol utilization. With the proposed method, the overall signal-to-interference ratio (SIR) improved by 1 to 3 dB.

In the current research, a novel vertical axis wind turbine producing both power and ventilation is presented. The idea is similar to an ancient wind catchers. The wind capacity of the Manjil city in Iran has been studied and a typical home-scale wind turbine has been assessed. To modify the geometry, a 3D semi-analytical code has been developed based on Double Multiple Stream Tube (DMST) theory. The validation analysis has been accomplished by the reference turbine. Using this code, the turbine performance including power coefficient and flow diversion index was studied. Particularly the effect of blade cone angle on the power deficiency and ventilation ratio was investigated. The results of the parameter study would reveal that for the optimal range of tip speed ratio, 2.9-3.2 based on the power curve, it is feasible to produce up to 400 m3/h ventilation flow and 50-200 W shaft power. It would be obtained by 20-degree blade inclination and is equivalent to 2.5% of the total flow entering the rotor. The power deficiency due to this change is 30% which is compromised by the ventilation capability. The results also revealed the optimal range of tip speed ratio is 2.9-3.2. . It is depicted that, power attenuation could be minimum when the suitable TSR and the appropriate geometry are selected. Finally, some generalized trends of the objective functions also have been drawn. The methodology is versatile for the ongoing problems in the field of vertical axis wind turbines.

Today, the number of cyber-attacks has increased and become more complex with an increase in the size of high-dimensional data, which includes noisy and irrelevant features. In such cases, the removal of irrelevant and noisy features, by Feature Selection (FS) and Dimensions Reduction (DR) methods, can be very effective in increasing the performance of intrusion detection systems (IDS). This paper compares some FS and DR methods for detecting cyber-attacks with the best accuracy using implementation on KDDCUP99 dataset. A Deep Neural Network (DNN) is used for training and simulating them. The results show the filter methods are faster than wrapper methods but less accurate. Whereas the Wrapper methods have more accuracy but are computationally costlier. Embedded methods have the best output and maximum values, which is 99% for all the metrics, comparing to it the DR methods have shown a good performance and speed, among them Linear Discriminant Analysis (LDA) method even better than embedded method.

This paper presents a new symmetrical switched-capacitor (SC) multilevel inverter topology which can convert the input DC voltage to a step-up multilevel AC waveform on the load. This proposed multilevel inverter consists of one T-type and several cross-capacitor modules. The structure of the generalized multilevel inverter is such that the peak inverse voltage (PIV) remains constant as the number of cross-capacitor modules increases which leads to reduce the total standing voltage (TSV) of the switches and cost function compared to other traditional topologies. The introduced structure can inherently generate the positive, negative, and zero voltage levels on the output without the back-end H-bridge section. The capacitor’s voltages in the T-type and cross modules are inherently balanced, simplifying the control system under the nearest level control (NLC) switching strategy. To verify the performance of the proposed topology, several simulations and experimental results for a type 13-level inverter are provided by MATLAB and TMS320F28379D DSP, respectively.

The aim of this research is to introduce a semi-analytical approach for the analysis of the free and forced nonlinear vibrations of a bending shape memory alloy (SMA) beam; while, considering the effect of its pseudo-elastic behavior. In order to create a primary deflection, an appropriate pre-strain is applied to the SMA beam using a compression spring. A new material model was utilized to simulate the nonlinear hysteric behavior of the SMA beam, while the differential equations of motion of the beam were derived based on Euler–Bernoulli beam theory and Hamilton principle. The extracted nonlinear partial differential equations of motion are semi-analytically solved by utilizing the Galerkin method. The pseudo-elastic behavior and energy dissipation of the SMA beam were studied in the free and forced nonlinear vibration regimes. Finally, the influences of the system parameters such as the spring constant, amplitude, and frequency of the excitation force on the absorber efficiency were investigated, and its stability was studied. The numerical results depict that the SMA beam exhibits a highly nonlinear dynamical behavior, and can be used as an actuator for energy dissipation.

Today, concrete is the most widely used building material. Cement production releases about 7% of carbon dioxide gas into the atmosphere and increases greenhouse gases, so it seems necessary to use an alternative to Portland cement. In recent years, geopolymers (mineral polymers) have been proposed as a new environmentally friendly cement. Metakaolin, bentonite, zeolite, iron blast furnace slag and fly ash can be mentioned as aluminosilicate sources. In the field of geopolymer concrete construction, few articles have been working on the composition and effect of replacing aluminosilicate sources. In this experimental study, the effect of replacing slag aluminosilicate sources, class F fly ash and bentonite with proportions of 5-45% with metakaolin on the mechanical properties and durability of geopolymer concrete based on metakaolin was investigated. After making the samples, compressive, bending, tensile and carbonation tests were performed on the geopolymer concrete samples to obtain the optimal strength and carbonation depth of the samples. Also, to determine the validity of the tests, machine learning estimation analysis was performed on the samples. The findings showed that bentonite leads to a decrease in strength, while fly ash and slag lead to an increase in strength. The predicted R2 values showed the highest matching of the correlation matrix (more than 93%) for the pressure samples. In addition, the results of the tests showed that the metakaolin-based geopolymer concrete sample replaced with fly ash (35%) had a lower penetration depth (carbonation) and higher mechanical properties than other samples.