International Journal of Engineering
Volume:34 Issue: 7, Jul 2021

Providing a new cheap medium in terms of biomass and pigment production from Arthrospira maxima is an important issue. In order to determine the effect of nitrogen starvation versus its excess, urea was used as a cheap nitrogen source in two different modes (alternative and additive) at four different concentrations (0, 1.25, 2.5, 5 gL-1). It was indicated that an alternative method is better than additive method due to accelerate the ammonia synthesis (NH3) and pH changes in the period of the growth that is directly related to biomass and pigments production. Moreover, the intensive production of biomass concentration, PC, APC, Ca, and C(X+C) content were 1.403, 0.074, 0.093,10.72, and 3.17 mgL-1 with nitrogen starvation medium. Urea considered being one of the inhibition sources of biomass growth due to the formation of NH3. Analyzing final results by general factorial design concluded that omitting nitrogen sources had the potential possibility for growing A. maxima in order to reduce the production costs in large-scale cultivation,which yields better performance than cost-effective Zarrouk’s medium.

A large amount of sludge is produced by the geothermal brine at the Dieng Geothermal power plant, exceeding 165 tons per month. This sludge is generally not utilized, except for use in landfills. The precipitate (sludge) is primarily composed of silica. The aim of this research is to synthesis mesoporous silica (SiO2) xerogel from geothermal sludge (GS) and to investigate the effects of pH as an effort to elevate the economic value of sludge through alkaline extraction followed by acidification. SiO2 xerogel was prepared by extracting the GS to become sodium silicate (Na2SiO3) assisted by a base NaOH and precipitated using H2SO4 as a gelation agent. The FTIR analysis of the SiO2 xerogel showed a group of silanol (Si-OH) and siloxane (Si-O-Si). The XRD analysis indicated that SiO2 xerogel was amorphous. Furthermore, it was observed from nitrogen absorption-desorption using BET (Breneur-Emmet-Teller) method test that decreased pH tends to the specific surface area increase, and the pore size becomes decrease. The largest specific surface area observed at SiO2 xerogel prepared at pH of 5.5 reached 400.10 m2/g with a pore size of 4.5 nm. The pore sized for all cases was in the range of 4 ~12 nm, indicating that the SiO2 xerogels were mesoporous. Pore size of the as-prepared silica affected the thermal stability property of the sample.

In this work, determination of naproxen concentration by chitosan capped silver nanoparticles were investigated. A new, simple and inexpensive spectrophotometric method for the first time was developed. The characteristics of chitosan capped silver nanoparticles were determined by ultraviolet spectroscopy (UV), Fourier transform infrared spectroscopy (FT-IR), atomic force microscopy (AFM), dynamic light scattering (DLS) and zeta potential (ZP) under optimal conditions. It worth to be mentioned that, synthesized chitosan (CS) -Ag nanoparticles were approximately 100 nm and PDI 0.385 with strong anionic (-24.8mV) zeta potential in acidic condition. It was found that chitosan as a chiral selector was able to detect naproxen at optimal experimental conditions. Validation of this method, including limit of detection and limit of quantification were accurately confirmed according to ICH instructions. Based on this method, the limit of detection (LOD) and the limit of quantification (LOQ) of naproxen were calculated 0.022 and 0.066 mol. L-1, respectively. Analysis of statistical data, the reproducibility and accuracy of this method demonstrated that the use of this novel method is valuable and practical for determination of naproxen in pharmaceutical formulations

The prediction of responses of the reinforced concrete shear walls subject to strong ground motions is critical in designing, assessing, and deciding the recovery strategies. This study evaluates the ability of regression models and a hybrid technique (ANN-SA model), the artificial neural network (ANN), and Simulated Annealing (SA), to predict responses of the reinforced concrete shear walls subject to strong ground motions. To this end, four buildings (15, 20, 25, and 30-story) with concrete shear walls were analyzed in OpenSees.150 seismic records are used to generate a comprehensive database of input (characteristics of records) and output (responses). The maximum acceleration, maximum velocity, and earthquake characteristics are used as predictors. Different machine learning models are used, and the accuracy of the models in identifying the responses of the shear walls is compared. The sensitivity of input variables to the seismic demand model is investigated. It has been seen from the results that the ANN-SA model has reasonable accuracy in the prediction.

Al-Najaf, one of Iraq's most important cities, is expected to grow in the coming years. Many buildings located on the slopes of Al-Najaf, which is near the shrine of Imam Ali, possess important economic and tourism values. This paper examines the stability of the city's slope under a variety of conditions, including slope geometry, neighbor structure loading, and earthquake magnitude. A computer-aided 2D Finite Element Method is adopted in the analysis. A set of soil classification and identification tests were carried out in addition to the available required soil parameters in the constitutive modeling. The Mohr-Coulomb model is applied to define the failure state that began in the slope. The results show that the slope is stable due to its weight and geometry, with a minimum factor of safety of 2.6. While under footing loading, this factor of safety decreases to less than 1.8. The most hazardous condition is when the slope has been subjected to seismic loading and the factor of safety is less than unity, for all investigated cases and characteristics, where the slopes would collapse.

In this study, the seismic performance of a 20-storey steel structure with a mat foundation located on layered soil is investigated under an array of strong ground excitations, which includes 6 far-fault and 6 near-fault earthquakes. Eight different modes for soil layering have been considered in the numerical simulation. FLAC 2D nonlinear platform has been used to model the near-realistic behavior. To this end, hundred lines of codes and sub-routines have been developed in this platform to perform the analysis. The results of the analyzes include the absolute displacement of the floors, the ratio of the relative displacement of the floors, the shear force, the axial force, and the bending moment of the columns. It was concluded that for a 20-story structure on a mat foundation under both far-field and near-field earthquakes, the most reliable type of soil is the dense sandy soil and the most critical case is the soft clay soil. It was also observed that the near-field strong ground motions have imposed more critical structural responses compared to far-field records.

Discovery of alternative to the pozzolanic materials generated from industrial wastes was needed because of its unavailability when the industries was shutdown permanently. This paper deals the optimization of calcined bentonite clay utilization in cement mortar using response surface methodology (RSM). The variables were taken as three levels of calcination temperature (room temperature, 7000C and 8000C) and seven levels of calcined bentonite (0%, 5%, 10%, 15%, 20%, 25% and 30%). The compressive strength, workability, strength activity index and sorpitivity were taken as responses. The fresh and hardened properties of all determined for all mixes. Design Expert 11.0 version was utilized to carried out  modelling and optimization using RSM. Workability was decreased upon increasing the calcination temperature and bentonite content in cement mortar. This attributed to high water absorption capacity of bentonite. The peak compressive strength was displayed by 20% replaced bentonite calcined at 8000C cement mortar after 28 days curing. Strength activity was improved upon increasing the percentage of bentonite calcined at 8000C. The sorpitivity of cement mortar was improved by incorporation of bentonite calcined at 8000C. The generated models from RSM were significance in all the factors considered. Optimum performance of the responses was observed at 15.25 % bentonite substitution calcined at 8000C

The performance of simultaneous application of steel cantilever damper and Shape Memory Alloy (SMA) rods in the reinforced concrete (RC) shear wall was investigated. In this regard, the critical numerical validation of three full-scale experimental models were distinctly performed and the results were analyzed. Various aspects of numerical modelling, including material modelling assumptions, behavioural models, elements, and solution methods were compared with experimental results. Specimens considering SMA rods as well as steel cantilever damper were numerically investigated. The results illustrated that with increasing the SMA rod angle, the maximum force was decreased, and the residual displacement and dissipated energy was improved. Also, comparing the specimen results without the SMA rods and the specimen with the SMA rods showed that despite the positive effect of the SMA rods, which leads to an increase in maximum force and reduction of residual displacement, the dissipated energy was decreased

With the growth of population, shortage of water, and severe lack of water resources, optimization of reservoirs operation is a principal step in water resource planning and management. Therefore, in the present study, water was optimally allocated for a period from 2010 to 2020 using two simulation-optimization models based on Grey Wolf Optimization algorithm (GWO) and Genetic Algorithm (GA) and WEAP model. System operational indices including volumetric reliability, temporal reliability, vulnerability, and sustainability were used to evaluated the perforemance of optimization algorithms as well as WEAP model. The objective function of resources allocation problem was minimizing sum of the squared relative deficiencies for each month and maximizing reliability over the entire 11-year period. The results showed that optimal allocation solution found by the GWO algorithm with volumetric reliability, vulnerability, and sustainability indices which were 86.93, 0.29, and 21.48%, respectively was better and more suitable than the optimal allocation solution found by GA algorithm (which were 87.12, 0.41, and 21.34%, respectively). Finally, given an increase in the water demands , it is possible to obviate the needs of beneficiaries to an acceptable level and prevent severe draught in dry months through optimizing the use of available resources. According to the calculated indices for the WEAP model, in which volumetric reliability, vulnerability, and sustainability were equal to 87.46, 0.92, and 1.03%, respectively. It can be concluded that the use of optimization algorithm in optimal operation of the dam is more reliable than WEAP model.

The paper industry burns or buries a significant amount of waste paper sludge. This issue is not suitable from environmental and economic aspects. In this study, the mechanical and durability properties of high-strength concrete containing waste paper sludge ash (WPSA) were evaluated. The variables were WPSA (0, 5, 10, and 15% by weight of cement), silica nanoparticles (0 and 2.5 by weight of cement), and aluminum oxide nanoparticles (0 and 2.5 by weight of cement). Compressive strength, splitting tensile strength, flexural strength, and ultrasonic pulse velocity testswere conducted to evaluate the mechanical properties. The durability properties were also investigated using water penetration depth, water absorption, and electrical resistivity tests. The microstructure of the specimens was analyzed by preparing electron microscopic images. The combined effect of WPSA and nanoparticles on improving the mechanical and durability properties of high-strength concrete are better than using each of them alone. WPSA and nanoparticles react with calcium hydroxide formed due to cement's hydration, and silica produces hydrated calcium, which is the hard material that makes concrete strength. Consumption of calcium hydroxide and production of more hydrated calcium silicate in the presence of nanoparticles and WPSA are among the reasons for water absorption reduction, increased electrical resistance, and water penetration depth reduction in concrete specimens. By replacing part of the cement with WPSA, silica nanoparticles, and aluminum oxide nanoparticles, the transition zone between the aggregates strengthens, and the tensile and flexural strengths increased

With the modern invention of high-quality sensors and smart chips with high computational power, smart devices like smartphones and smart wearable devices are becoming primary computing sources for routine life. These devices, collectively, might possess an enormous amount of valuable data but due to privacy concerns and privacy laws like General Data Protection Regulation (GDPR), this enormous amount of very valuable data is not available to train models for more accurate and efficient AI applications. Federated Learning (FL) has emerged as a very prominent collaborative learning technique to learn from such decentralized private data while reasonably satisfying the privacy constraints. To learn from such decentralized and massively distributed data, federated learning needs to overcome some unique challenges like system heterogeneity, statistical heterogeneity, communication, model heterogeneity, privacy, and security. In this article, to begin with, we explain some fundamentals of federated learning along with the definition and applications of FL. Subsequently, we further explain the unique challenges of FL while critically covering recently proposed approaches to handle them. Furthermore, this paper also discusses some relatively novel challenges for federated learning. To conclude, we discuss some future research directions in the domain of federated learning.

Finger-Knuckle-Print (FKP) is an accurate and reliable biometric in compare to other hand-based biometrics like fingerprint because of the finger's dorsal region is not exposed to surfaces. In this paper, a simple end-to-end method based on Convolutional Neural Network (CNN) is proposed for FKP recognition. The proposed model is composed only of three convolutional layers and two fully connected layers. The number of trainable parameters hereby has significantly reduced. Additionally, a straightforward method is utilized for data augmentation in this paper. The performance of the proposed network is evaluated on Poly-U FKP dataset based on 10-fold cross-validation. The best recognition accuracy, mean accuracy and standard deviation are 99.83%, 99.18%, and 0.76, respectively. Experimental results show that the proposed method outperforms the state-of-the-arts in terms of recognition accuracy and the number of trainable parameters. Also, in compare to four fine-tuned CNN models including AlexNet, VGG16, ResNet34, and GoogleNet, the proposed simple method achieved higher performance in terms of recognition accuracy and the numbers of trainable parameters and training time.

In this paper, the load frequency control problem of microgrids in islanded operation mode is tackled using Fuzzy Feedforward PI (FFPI) controller. To this end, a feedforward loop is considered in the control structure of the microgrid in addition to the classical feedback controller wherein a proportional integrator controller is used. The disturbance signal, which can be load variations or renewable energy resources uncertainties, is estimated using a disturbance observer. The understudy microgrid includes wind turbine and solar cells as renewable sources, and a diesel generator and loads. A fuzzy controller is also used for pitch angle control of the wind turbine, which may smooth out the generated power and improve the frequency control of microgrid. To show the capability of the proposed strategy, two different scenarios are considered and the obtained simulation results easily approve the efficiency of the proposed structure for load frequency control of microgrid in islanded operation mode.

Disabled people find their movements extremely difficult with their current gadgets. Although there are numerous devices and instruments accessible to empower their mobility, they require fine and precise control, which may be impractical in instances of higher disability. The haptic innovations are very beneficial, but demands a user friendly environment too. Strategies, designs and frameworks in this field are more in number, which depends on Joystick. But this can prove to be a big-budget. Therefore, the aim of this paper is to control a wheelchair through a utility that is budget-sensitive and practical to use. A flex sensor based wheelchair is presented in this paper, which is user friendly within a low budget. The proposed system is also accompanied by a movement monitoring system that can help the user’s kin to observe his/her movement. The aim is to provide such features which is affordable to the society and can be used with ease.

The process of reducing dimensions in CMOS technology and also making digital devices more portable, faces serious challenges such as increasing frequency and reducing power consumption. For this reason, scientists are looking for a solution such as replacing CMOS technology with other technologies including Quantum-dot Cellular Automata (QCA) technology and many researches have designed digital circuits by using QCA technology. Flip-flops are one of the main blocks in most digital circuits. In this paper, a D-type flip-flop (D-FF) is presented in QCA technology that a majority gate has been used in its feedback path to reset. The D-FF is designed by the proposed D Latch which is based on Nand-Nor-Inverter (NNI) and a new inverter gate that the proposed D latch has 24 cells and 0.5 clock cycle latency and 0.02 〖μm〗^2 area. The new inverter gate of the D-FF has output signal with high polarization level and lower area than previous inverters and the NNI gate of the D-FF is a universal gate. One of the applications of D-FFs with reset pin is the use in Phase-frequency detector (PFD). In the proposed scheme, a reset feature has been added to D-FF since the PFD structure can be designed. All of the proposed schemes are evaluated by the QCADesigner software and energy consumption simulations are estimated using QCAPro software for all proposed circuits.

This paper presents a one-dimensional analytical model for calculating gate capacitance in Gate-All-Around Carbon Nanotube Field Effect Transistor (GAA-CNFET) using electrostatic approach. The proposed model is inspired by the fact that quantum capacitance appears for the Carbon Nanotube (CNT) which has a low density of states. The gate capacitance is a series combination of dielectric capacitance and quantum capacitance. The model so obtained depends on the density of states (DOS), surface potential of CNT, gate voltage and diameter of CNT. The quantum capacitance obtained using developed analytical model is 2.84 pF/cm for (19, 0) CNT, which is very close to the reported value 2.54 pF/cm. While, the gate capacitance comes out to be 24.3×10-2 pF/cm. Further, the effects of dielectric thickness and diameter of CNT on the gate capacitance are also analysed. It was found that as we reduce the thickness of dielectric layer, the gate capacitance increases very marginally which provides better gate control upon the channel. The close match between the calculated and simulated results confirms the validity of the proposed model.

This paper proposes a novel distributed adaptive secondary controller for microgrids (MGs) in islanded operation. To enhance the dynamic behaviour of a microgrid considering uncertainties and disturbances, the proposed controller uses a consensus-based adaptive control structure. A novel consensus protocol is proposed to restore the frequency and voltage (f &V) of a microgrid to their rated values. A Lyapunov function is presented to assure the asymptotic stability of the controller and the ultimate boundedness of the global neighborhood consensus error. The nonlinear nature of MGs has been also considered in the algorithm. Unlike other methods in this field that require complete information of distributed generators (DGs), the proposed controller requires only power droop coefficients and is independent of DGs parameters. Different simulations are conducted in MATLAB/SimPower Toolbox on a typical microgrid and under various disturbances to judge the performance of the adaptive controller. The simulation results show the effect of the proposed controller on increasing the resilience of an MG.

Identification of drug-target protein interaction plays an important role in the drug discovery process. Given the fact that prediction experiments are time-consuming, tedious, and very costly, the computational prediction could be a proper solution for decreasing search space for evaluation of the interaction between drug and target. In this paper, a novel approach based on the known drug-target interactions based on similarity graphs is proposed. It was shown that use of this method was a low-ranking issue and WNNM (weighted nuclear norm minimization) method was applied to detect the drug-target interactions. In the proposed method, the interaction between the drug and the target is encoded by graphs. Also known drug-target interaction, drug-drug similarity, target-target and combination of similarities were used as input. The proposed method was performed on four benchmark datasets, including enzymes (Es), ion channels (IC), G protein-coupled receptors (GPCRs), and nuclear receptors (NRs) based on the AUC and AUPR criteria. Finally, the results showed the improved performance of the proposed method.

This work proposes an objective function to optimize an ultra wideband antenna for adjusting the bandwidth and coupling with other elements, based on the performance comparison of several objective functions from the literature. The optimal dimensions of a printed rectangular monopole antenna were obtained with the Particle Swarm Optimization method to compare such functions. In the results of the comparison, the linear functions had a mean value of S11 magnitude near the threshold, but they presented a smaller standard deviation than the rest of the functions. The logarithmic and cubic functions showed a mean value of S11 magnitude higher than the double of the threshold, but they had superior standard deviation values, which did not happen with the quadratic function. Hence, the proposed function is the mean of a logarithmic expression with the quadratic argument. With this function, a bandwidth adjustment of 130%, a mean S11 magnitude of -22.1 dB and a standard deviation equal to 6.7 dB were obtained on the resonant band for the designed antenna. In this way, the proposed function can be used to avoid interference with other wireless systems and to obtain a uniform coupling of the antenna.

This study aims to introduce a new structure based on a nonlinear controller for controlling and analyzing the stability of the microgrids. In the proposed model, AC and DC resources and loads are located on two different sides. In addition, an AC/DC bidirectional interface converter is applied to supply loads by AC/DC sources. There are AC/DC products on both sides of the converter and each side can supply the load of the other side via a bidirectional interface converter and its load. Alternatively, an energy storage system is used for the system stability on the DC side. The nonlinear microgrid controller is designed to adjust the AC bus side frequency and the DC bus side voltage properly. In this structure, the coordinated optimal power exchange and precise regulation of control signals lead to constant improvement. Thus, system performance is improved. The results show that the proposed model is efficient for both reduction of the fluctuations and improvement of the system stability

This paper develops a bi-objective optimization model for the integrated production-distribution planning of perishable goods under uncertainty. The first objective seeks to maximize the profit in a specific supply chain with three levels: plants, distribution centers, and in the last level, customers. Since transportation is one of the major pollution sources in a distribution problem, the second objective is to minimize their emission. In the considered problem, the decisions of production, location, inventory, and transportation are made in an integrated structure. In developing the demand function, the effect of the product freshness and the price is formulated. Besides, to encourage customers, three strategies, including perished product return, discount, and credit policies, are proposed. Also, robust optimization is utilized to cope with the operational uncertainty of some cost parameters. To prove the applicability of this research and the feasibility of the environmental aspect, a case study is conducted. Finally, the numerical computations on the case study provide a trade-off between the environmental and economic goals and indicate a 37.5 percent increase in the profit using the developed model.

The article proposes to consider the problem of comprehensive assessment of project risks as applied to the energy industry. The authors of the research focused on the description of the applied solution. A real investment project on replacement of a bark boiler at Mondi Syktyvkar enterprise was chosen as an object for testing the results. We proposed to divide the risks accompanying the project into 2 categories: risks for which there is necessary and statistical information for their quantitative assessment and risks for which this information is absent. As a technique of a quantitative assessment of risks from the first category it is expedient to apply a method of Simulation modeling of Monte Carlo. In this case, the authors of the article conducted a significant analysis of existing methods for assessing project risks and the choice of the Monte Carlo methodology is due to the practical orientation of the study. In practice, the real enterprise is quite problematic to use more complex methods of assessment, such as methods of Real Options or methods of fuzzy logic, neural networks, etc. As a method of qualitative risk assessment (from the second category) the method of expert evaluation with subsequent calculation of risk premium in the discount rate was chosen. This method is common in practice and easy enough to implement. According to the results of the analysis (statistical and expert) the most dangerous risks of energy projects were identified: Production and technological risks (the risk of choosing the wrong technological scheme, the risk of reducing the quality of internal controls, the risk of incorrect calculation of the design capacity of energy production, the risk of industrial safety), security risks (the risk of hacking attacks on information systems of energy enterprises), as well as country risks. Among the most influential risks (based on the analysis of their impact on the main technical and economic indicators of the project) are: the risk of rising prices for purchased gas (fuel), the risk of high volatility of the dollar exchange rate. The results of the study were used in a real project and the risk assessment methodology was implemented in the project activities of Mondi Syktyvkar enterprise.

Heaters are one of the central parts of natural gas reduction stations using turboexpanders to prevent the formation of hydrate and corrosion failure. This study intends to design a fired heater by applying a combustion sub-model to derive an optimal model for this kind of application. This model is developed to accurately consider all subsections of the fired heater namely radiation, convection, and shield sections, as well as flue gas composition, and its volume. Within this context, a multi-objective optimization is employed to identify the optimal design of the gas-fired heater in the natural gas reduction station for the Ramin power plant case study. The total economic and environmental costs, together with modified exergy efficiency, are selected as objective functions. Multi-criteria-decision-making-method is employed on Pareto frontiers optimal curve to suggest the optimal solution. Results show that the developed model can outperform previous models in thermal efficiency with relatively similar costs. Besides, the optimal point in Pareto suggested by the decision-making-method accounts for a higher modified exergy efficiency (1.3%) than the counterpart, which thermal efficiency is regarded as an objective function. At the same time, its total cost remained almost constant. The effects of changes in each of the design parameters on the objective functions are also evaluated.

The longitudinal friction coefficient is a very important parameter to calculate vehicle dynamics. The theoretically longitudinal friction coefficient is often used to investigate the vehicle dynamics. However, the longitudinal friction coefficient depends on many factors and changes when the vehicle moves on the actual road. This paper presents the experimental method to determine the longitudinal friction coefficient function when braking the tractor semi-trailer on the road. The results of this study can be used as an input to dynamic survey model for the tractor semi-trailer and to verify the theoretical model. The experimental results showed that when braking the tractor semi-trailer on the dry asphalt, the maximum longitudinal friction coefficient is jxmax=0.89 and the minimum longitudinal friction coefficient is jxmin=0.72. Matlab-Simulink software was used to investigate and compare the longitudinal friction coefficient determined by experiment and the theoretically longitudinal friction coefficient according to Ammon tire model. The survey results showed that the average error between experiment and theory was about 17%.

This paper analyses the possibility of increasing the efficiency of loading the destroyed rock mass into the face scraper conveyor by the lagging screw actuator of the shearer in the process of coal mining in the complex mechanized treatment faces of coal mines. It was taken into account that the most significant influence on the loading efficiency of coal is exerted by the dimensions of the cross-sectional area of the loading window, the distance between the screw and conveyor and the height of the bottom of the conveyor. Non-traditional technical solutions are proposed that reduce the negative impact of the gap between the screw and the conveyor on the efficiency of coal loading by the lagging screw actuator of shearers and increase the degree of filling of the conveyor groove. Technical solutions contribute to the formation of a rational section of the cargo flow in the trough of the downhole conveyor and, therefore, increase its productivity. The results of modeling the process of loading coal onto the face conveyor by an auger actuator with an additional loading device are presented. Evaluation of the effectiveness of the proposed constructive technical solutions for the interface unit in the loading area confirmed an increase of 2.94 times the maximum capacity of the screw executive body for loading coal onto the face conveyor while 2.7 times less specific energy consumption during loading.