Centrifugal blood pumps have provided a powerful artificial support system for patients with vascular diseases. In the design process, geometrical optimization is usually needed to acquire a more biocompatible model for clinical uses. In the current paper, we propose a method for multi-objective optimization concerning both the hydraulic and the hemolytic performances of the pump based on the near-orthogonal array in which the traditional hemolysis index (HI) is replaced with the maximum scalar shear stress criteria to reduce the computation load. The method is demonstrated with the optimization of an extracorporeal centrifugal blood pump with an unshrouded impeller. CFD studies on the original and nine modified pump models are carried out. The calculated hydraulic performances of the optimized model are also compared against the experiments for validation of the numeric method, with an error of 3.6% at the original design point. The resulting blood pump with low maximum scalar shear s... [more]

Dividing-wall columns (DWCs) are intensified processes that have attracted industrial and academic attention due to the reduction in operating and installation costs compared to traditional distillation systems. Several methodologies are available for the design of DWCs. Most of them consist of three parts: an analysis of operating variables; an analysis of the structural design (topology); and an optimization of the resulting preliminary design. This paper aims to study three widely used design methodologies reported in the literature for DWCs, i.e., Triantafyllou and Smith (T&S), minimum vapor (Vmin), and Sotudeh and Shahraki (S&S) methods, along with their implementation on process simulators. A proposed modification to the S&S methodology is also presented. A comparison of the methods is carried out and rated against designs with minimum total annual costs. The analysis considers the effect of different structural design variables to initialize the design procedure with each method... [more]

The main purposes of this project are to assess and to optimize the solubility of carbon dioxide (CO2) in an aqueous 30 wt% monoethanolamine-tetrabutylphosphonium methanesulfonate (MEA-[TBP][MeSO3]) new hybrid solvent. In this study, the viscosity and density of aqueous MEA-[TBP][MeSO3] hybrid solvents containing different amounts of [TBP][MeSO4] were determined. Meanwhile, Fourier Transform-Infrared (FT-IR) Spectroscopy was used to determine the presence of carbamate in aqueous MEA-[TBP][MeSO3] to prove that CO2 was absorbed by aqueous MEA-[TBP][MeSO3]. Response Surface Methodology (RSM) based on central composite design (CCD) was used to design the experiments and explore the effects of three independent parameters on the solubility of CO2 in aqueous MEA-[TBP][MeSO3]. The three independent parameters are concentration of [TBP][MeSO3] (2−20 wt.%), temperature (30−60 °C) and pressure of CO2 (2−30 bar). The experimental data was found to fit a quadratic equation using multiple regressio... [more]

The prediction accuracy of support vector regression (SVR) is highly influenced by a kernel function. However, its performance suffers on large datasets, and this could be attributed to the computational limitations of kernel learning. To tackle this problem, this paper combines SVR with the emerging Harris hawks optimization (HHO) and particle swarm optimization (PSO) algorithms to form two hybrid SVR algorithms, SVR-HHO and SVR-PSO. Both the two proposed algorithms and traditional SVR were applied to load forecasting in four different states of Nigeria. The correlation coefficient (R), coefficient of determination (R2), mean square error (MSE), root mean square error (RMSE), and mean absolute percentage error (MAPE) were used as indicators to evaluate the prediction accuracy of the algorithms. The results reveal that there is an increase in performance for both SVR-HHO and SVR-PSO over traditional SVR. SVR-HHO has the highest R2 values of 0.9951, 0.8963, 0.9951, and 0.9313, the lowes... [more]

Preload optimization is very important for ultrasonic motors’ design and application. In this paper, a novel method for a traveling-wave rotary ultrasonic motor is proposed. Firstly, based on linear regression and the analytic hierarchy process (AHP), the mapping between the drive characteristics, mechanical characteristics, speed stability, and preload of the traveling-wave-type rotary ultrasonic motor was established. Then, the characteristic curves of stalling torque, no-load speed, maximum efficiency, and speed stability with the change of preload method were measured with a new test platform. Finally, three traveling-wave rotary ultrasonic motors with optimized preload were used in a cooperative manipulator for validation. The experimental results showed that when the preload was optimized from 200 N to 310 N, the stalling torque of the motor increased by 20.7%, the maximum efficiency increased by 15.3%, the standard deviation of the speed decreased by 53.8%, and the no-load speed... [more]

One of the most crucial aspects of image segmentation is multilevel thresholding. However, multilevel thresholding becomes increasingly more computationally complex as the number of thresholds grows. In order to address this defect, this paper proposes a new multilevel thresholding approach based on the Evolutionary Arithmetic Optimization Algorithm (AOA). The arithmetic operators in science were the inspiration for AOA. DAOA is the proposed approach, which employs the Differential Evolution technique to enhance the AOA local research. The proposed algorithm is applied to the multilevel thresholding problem, using Kapur’s measure between class variance functions. The suggested DAOA is used to evaluate images, using eight standard test images from two different groups: nature and CT COVID-19 images. Peak signal-to-noise ratio (PSNR) and structural similarity index test (SSIM) are standard evaluation measures used to determine the accuracy of segmented images. The proposed DAOA method’s... [more]

The “Drying-redissolution” method is promising for the industrial production of high-concentration well-dispersed graphene oxide slurry (GOS). As the potential key step in this method, the spray drying process requires a statistical investigation which guides the large-scale preparation of graphene oxide powder (GOP). This work systematically studies the effects of operating parameters, including nozzle airflow rate (439−895 L·h−1), atomization pressure (0.5−0.7 MPa), and liquid feed rate (3.0−9.0 mL·min−1), by using the response surface methodology integrated Box−Behnken design (RSM−BBD), aiming to produce GOP with high yield and easy re-dispersion. The optimized spray drying condition is predicted to be 439 L·h−1, 0.59 MPa, and 9.0 mL·min−1, at which a powder yield of 70.45% can be achieved. The experimentally obtained GOP has an average particle size of 11.65 μm and the low crumpling degree of the particle morphology results in the good re-dispersibility (97.95%) and excellent adsor... [more]

Wind power generation is a widely used power generation technology. Among these, the wind turbine blade is an important part of a wind turbine. If the wind turbine blade is damaged, it will cause serious consequences. The traditional methods of defect detection for wind turbine blades are mainly manual detection and acoustic nondestructive detection, which are unsafe and time-consuming, and have low accuracy. In order to detect the defects on wind turbine blades more safely, conveniently, and accurately, this paper studied a defect detection method for wind turbine blades based on digital image processing. Because the log-Gabor filter used needed to extract features through multiple filter templates, the number of output images was large. Firstly, this paper used the Lévy flight strategy to improve the PSO algorithm to create the LPSO algorithm. The improved LPSO algorithm could successfully solve the PSO algorithm’s problem of falling into the local optimal solution. Then, the LPSO al... [more]

In order to optimize the process parameters of Cd removal in the ZnSO4 production process and study the mechanism of Cd removal reaction, the response surface methodology was used to arrange Cd removal experiments and analyze the optimal production conditions, and the mechanism of Cd removal was studied using kinetics. The results show that the optimal process conditions for Cd removal are as follows: reaction temperature 55 °C, reaction time 13.43 min, and the zinc powder dosage should be 2.14 times that of Cd; the main effects of the three variables from large to small are zinc powder dosage, reaction temperature and reaction time; Cd removal is a second-order reaction, and the activation energy of the reaction is 29.6986 kJ/mol, so the reaction conforms to the diffusion control mechanism.

The sintered zinc oxide (ZnO) electro-ceramics are a brittle class of hard-to-cut materials such that shaping them with the post-finishing operations necessitates careful handling and precision machining. The conventional machining approach using the grinding and lapping processes represents limited productivity, an inability to produce the required geometries and frequent uncontrolled chipping of the edges of the final products. This study thus investigates the turning performance of dense sintered ZnO varistors and chip formations to obtain the parametric range (cutting mechanism) which causes the chipping or the trans-granular/sudden failure in these brittle materials. With the analysis of the cutting tool vibration in relation to the machining parameters (f and VC), the vibration-induced chipping correlations are made and interlinked with the occurrence of grain pull-out during the turning operation. The results show that the reflected vibratory motion of the tools is directly corr... [more]

Optimization of the continuous fermentation process is important for increasing efficiency and decreasing cost, especially for complicated biochemical processes described by substrate and product inhibition. The optimum design (minimum volume) of CSTRs in series assuming substrate and product inhibition was determined in this study. The effect of operating parameters on the optimum design was investigated. The optimum substrate concentration in the feed to the first reactor was determined for N reactors in series. The nonlinear, constrained optimization problem was solved using the MATLAB function “fmincon”. It was found that the optimum design is more beneficial at high substrate conversion and at a medium level of feed substrate concentration. The best number of reactors is two to three for optimum arrangements and two for equal-size arrangements. The presence of biomass in the feed to the first reactor reduces the reactor volume, while the presence of product in the feed slightly in... [more]

For proton exchange membrane fuel cells (PEMFCs), the parameter extraction issue is among the most widely studied problems in the field of energy storage systems, since the precise identification of such parameters plays an important role in increasing the PEMFC performance and life span. The optimization process is intended to adjust the performance of PEMFCs by appraising the optimal parameters that produce a good estimation of the current−voltage (I−V) curve. In order to build an accurate equivalent circuit model for PEMFCs, a reliable and effective parameter extraction algorithm, termed a supply−demand-based optimization (SDO) algorithm, is proposed in this paper. Nine parameters (ξ1, ξ2, ξ3, ξ4, Rc, β, λ, l, and Jmax) are evaluated, to minimize the sum squared deviation (SSE) between the experimental and simulated I−V curves. To validate the feasibility and effectiveness of the SDO algorithm, four sets of experimental data with diverse... [more]

To improve the transport performance of a rotodynamic multiphase pump for a gas−liquid mixture, we took the head and efficiency index at rated flow rate with 15% inlet gas volume fraction as the indices, and used the orthogonal test design method and CFD technology to optimize. We selected the blade shroud angles at the leading edge and trailing edge, and axial length of the impeller, as well as the inlet incidence angle and blade number of the diffuser, and a total of five factors were used for the orthogonal test. The weight function was used to determine the final trial protocol. The results showed that the blade shroud angle at the trailing edge had the greatest influence on the head and efficiency indices. Under the rated flow rate with a 15% inlet gas volume fraction, the head and efficiency of the optimized pump were increased by 2.81 m and 5.6%, respectively, in comparison to the base pump. After the optimization, the partial fast-speed regions at the inlet of the impeller pass... [more]

The development and utilization of low-carbon energy systems has become a hot topic of energy research in the international community. The construction of a multi-energy complementary distributed energy system (MCDES) is researched in this paper. Based on the multi-objective optimization theory, the planning optimization of an MCDES is studied, and a three-dimensional objective-optimization model is constructed by considering the constraints of the objective function and decision variables. Aiming at the optimization problem of building terminals for the MCDES studied in the paper, two genetic optimization algorithms—Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and Non-Dominated Sorting Genetic Algorithm III (NSGA-III)—are used for calculation based on an example analysis. The constraint conditions of practical problems were added to the existing algorithms. Combined with the comparison of the solution quality and the optimal compromise solution of the two algorithms, a multi-d... [more]

The traditional pig manure wastewater treatment in Taiwan has been low in methane production efficiency due to unstable influent concentration, wastewater volume, and quality. Two-stage anaerobic systems, in contrast, have the advantage of buffering the organic loading rate in the first stage (hydrolysis-acidogenesis phase), allowing a more constant feeding rate to the second stage (methanogenesis phase). Response surface methodology was applied to optimize the operational period (0.5−2.0 d) and initial operational pH (4−10) for hydrolysis and acidogenesis of the swine manure (total solid 5.3%) at 35 °C in batch operation mode. A methanogenesis verification experiment with the optimal condition of operational period 1.5 d and pH 6.5 using batch operation resulted in peak volatile acid production 7 g COD/L, methane production rate (MPR) 0.3 L-CH4/L-d, and methane yield (MY) 92 mL-CH4/g-CODre (chemical oxygen demand removed). Moreover, a two-stage system including a hydrolysis-acidogenes... [more]

Optimal power flow (OPF), a mathematical programming problem extending power flow relationships, is one of the essential tools in the operation and control of power grids. To name but a few, the primary goals of OPF are to meet system demand at minimum production cost, minimum emission, and minimum voltage deviation. Being at the heart of power system problems for half a century, the OPF can be split into two significant categories, namely optimal active power flow (OAPF) and optimal reactive power flow (ORPF). The OPF is spontaneously a complicated non-linear and non-convex problem; however, it becomes more complex by considering different constraints and restrictions having to do with real power grids. Furthermore, power system operators in the modern-day power networks implement new limitations to the problem. Consequently, the OPF problem becomes more and more complex which can exacerbate the situation from mathematical and computational standpoints. Thus, it is crucially important... [more]

Due to the target of carbon neutrality, energy saving has become more important than ever. At the same time, the widespread use of distributed energy systems and the regional utilization of industrial waste heat leads to the existence of multiple heat sources in an area. Therefore, how to design an economical and reliable pipeline network to meet energy-saving demand under multiple heat source conditions becomes a problem. In this work, an optimization method is established to determine the optimal pipeline network topology with minimum total annual cost. In this optimization method, Star tree algorithm, Kruskal algorithm and GeoSteiner algorithm are combined with a linear programming model to establish a distributed energy pipeline network for multiple heat sources. The model incorporates Euclidean Steiner Minimum Tree and Rectilinear Steiner Minimum Tree in the consideration of the topology optimization of Distributed Energy System pipeline networks. Four pipeline network topologies,... [more]

This paper presents a framework for the use of variable pricing to control electricity imported/exported to/from both fixed and unfixed residential distributed energy resource (DER) network designs. The framework shows that networks utilizing much of their own energy, and importing little from the national grid, are barely affected by dynamic import pricing, but are encouraged to sell more by dynamic export pricing. An increase in CO2 emissions per kWh of energy produced is observed for dynamic import and export, against a baseline configuration utilizing constant pricing. This is due to feed-in tariffs (FITs) that encourage CHP generation over lower-carbon technologies. Furthermore, batteries are shown to be expensive in systems receiving income from FITs and grid exports, but for the cases when they sell to/buy from the grid using dynamic pricing, their use in the networks becomes more economical.

Cascade cooling systems containing different cooling methods (e.g., air cooling, water cooling, refrigerating) are used to satisfy the cooling process of hot streams with large temperature spans. An effective cooling system can significantly save energy and costs. In a cascade cooling system, the heat load distribution between different cooling methods has great impacts on the capital cost and operation cost of the system, but the relative optimization method is not well established. In this work, a cascade cooling system containing waste heat recovery, air cooling, water cooling, absorption refrigeration, and compression refrigeration is proposed. The objective is to find the optimal heat load distribution between different cooling methods with the minimum total annual cost. Aspen Plus and MATLAB were combined to solve the established mathematical optimization model, and the genetic algorithm (GA) in MATLAB was adopted to solve the model. A case study in a polysilicon enterprise was u... [more]

As the object detection dataset scale is smaller than the image recognition dataset ImageNet scale, transfer learning has become a basic training method for deep learning object detection models, which pre-trains the backbone network of the object detection model on an ImageNet dataset to extract features for detection tasks. However, the classification task of detection focuses on the salient region features of an object, while the location task of detection focuses on the edge features, so there is a certain deviation between the features extracted by a pretrained backbone network and those needed by a localization task. To solve this problem, a decoupled self-attention (DSA) module is proposed for one-stage object-detection models in this paper. A DSA includes two decoupled self-attention branches, so it can extract appropriate features for different tasks. It is located between the Feature Pyramid Networks (FPN) and head networks of subtasks, and used to independently extract globa... [more]

The main application of electrical discharge machining in ceramic processing is limited to conductive ceramics. However, the most commonly used non-conductive potteries in modern industry, such as aluminum oxide (Al2O3), also reveal the limitations of choosing a suitable process. In this study, Taguchi based TOPSIS coupled with AHP weight method to optimize the machining parameters of EDM on Al2O3 leads to better multi-performance. The results showed that the technique is suitable for tackling multi-performance machining parameter optimization. The adhesive foil had a significant impact on material removal rate, electrode wear rate, and surface roughness, according to the findings. In addition, the response graph of relative closeness is used to determine the optimal combination levels of machining parameters. A confirmation test revealed a good agreement between predicted and experimental preference values at an optimum combination of the input parameters. The suggested experimental a... [more]

Compounds 2,4,6-trichloroanisole (TCA), 2,3,4,6-tetrachloroanisole (TeCA), 2,4,6-tribromoanisole (TBA) and pentachloroanisole (PCA), 2-methylisoborneol (2MIB) and geosmin (GSM) have been reported as being responsible for cork and wine taint. A sustainable method based on thermal desorption-gas chromatography−mass spectrometry (TD-GC/MS) has been developed and optimized, taking into account desorption parameters and chromatographic and mass spectrometric conditions. The combination of parameters that jointly maximized the compound detection was as follows: desorption temperature at 300 °C, desorption time at 30 min, cryo-temperature at 20 °C and trap high temperature at 305 °C. The proposed methodology showed a good linearity (R ≤ 0.994) within the tested range (from 0.1 to 2 ng) for all target compounds. The precision expressed as repeatability and reproducibility was RSD < 10% in both. The limits of quantification ranged from 0.05 to 0.1 ng. The developed methodology and the sampli... [more]

Process-based numerical models developed to perform hydraulic/hydrologic/water quality analysis of watersheds and rivers have become highly sophisticated, with a corresponding increase in their computation time. However, for incidents such as water pollution, rapid analysis and decision-making are critical. This paper proposes an optimized parallelization scheme to reduce the computation time of the Environmental Fluid Dynamics Code-National Institute of Environmental Research (EFDC-NIER) model, which has been continuously developed for water pollution or algal bloom prediction in rivers. An existing source code and a parallel computational code with open multi-processing (OpenMP) and a message passing interface (MPI) were optimized, and their computation times compared. Subsequently, the simulation results for the existing EFDC model and the model with the parallel computation code were compared. Furthermore, the optimal parallel combination for hybrid parallel computation was evaluat... [more]

The friction rotary welding (FRW) of magnesium alloy to aluminum alloy was presented in a paper due to significant interest in the manufacturing industry. A genetic algorithm (GA) method for optimizing FRW process parameters of dissimilar light alloys was presented. After obtaining the welding parameters by GA method, it was possible to determine the best tensile strength of the friction joint. The obtained joints were subjected to tensile strength. The highest tensile strength TS = 178 MPa was found using a genetic algorithm for the following friction welding parameters: friction force FF = 16 kN, friction time FT = 4 s, and upsetting force UF = 44 kN. The optimized values were compared with the experimental results. The application of the genetic algorithm method allowed increasing the tensile strength joint from 88 to 180 MPa. The maximum tensile strength of the friction welded magnesium alloy-aluminum alloy joints was 73% of the base AZ31B metal. The relationship between welding pa... [more]

In this paper, subdivided kriging multi-objective optimization (SKMOO) is proposed for the optimal design of interior permanent magnet synchronous motor (IPMSM). The SKMOO with surrogate kriging model can obtain a uniform and accurate pareto front set with a reduced computation cost compared to conventional algorithms which directly adds the solution in the objective function area. In other words, the proposed algorithm uses a kriging surrogate model, so it is possible to know which design variables have the value of the objective function on the blank space. Therefore, the solution can be added directly in the objective function area. In the SKMOO algorithm, a non-dominated sorting method is used to find the pareto front set and the fill blank method is applied to prevent premature convergence. In addition, the subdivided kriging grid is proposed to make a well-distributed and more precise pareto front set. Superior performance of the SKMOO is confirmed by compared conventional multi... [more]