Performance Analysis Optimization Research Articles

Performance Optimization and Numerical Analysis of Boiler at Husk Fuel Based Thermal Power Plant

The increasing cost of fuel oil forced the industry to search for alternate fuels, and biomass. In general, rice husks were considered an appropriate substitute for producing energy. Because, the use of rice husk offered lot of benefits such as reduction in emission of sulfur and other pollutants connected with the use of other fossil fuel, cheaper than coal (approx. 36%), and carbon neutral. Hence, in this paper, water, Fuel and Steam generation data of husk-based Boiler has been measured, numerically analyzed and plotted graphically. The results revealed that husk based thermal power plant has huge potential. Further, it is supposed that exploiting the renewable energy potential and utilizing agricultural waste will be useful to the country’s energy portfolio while adding numerous environmental and social benefits (reducing CO2emissions, improving air quality, and diminishing the unemployment rate).

Performance Analysis of Optimization Based FOC and DTC Methods for Three Phase Induction Motor

Three-phase induction motors are becoming increasingly utilized in industrial field due to their better efficiency and simple manufacture. The speed control of an induction motor is essential in a variety of applications, but it is difficult to control. This research analyses the three-phase induction motor’s performance using field-oriented control (FOC) and direct torque control (DTC) techniques. The major aim of this work is to provide a critical evaluation of developing a simple speed controller for induction motors with improving the performance of Induction Motor (IM). For controlling a motor, different optimization approaches are accessible; in this research, a Fuzzy Logic Controller (FLC) with Fractional Order Darwinian Particle Swarm Optimization (FODPSO) algorithm is presented to control the induction motor. The FOC and DTC are controlled using FODPSO, and their performance is compared to the traditional FOC and DTC technique. Each scheme had its own simulation model, and the results were compared using hardware experimental and MATLAB-Simulink. In terms of time domain specifications and torque improvement, the proposed technique surpasses the existing method.

The method of navigation performance optimization analysis for high speed monohull ships

This paper is based on the drag resistance test data of the high-speed monohull model, a mathematical model for comprehensive optimization of the navigation performance of a high-speed monohull taking into account the rapidity, maneuverability, seakeeping and static performance of the ship is constructed. The optimization calculation software based on particle swarm, standard genetic algorithm and growth mechanism genetic algorithm is designed and written. Taking a high-speed monolithic sea-going ship with a displacement of 1500 tons and a large inclination-measuring single propeller as the object of discussion, the comparison of optimization methods, the comprehensive navigation performance of different ship types and the sensitivity analysis of design variables are carried out respectively. It provides a practical approach and an effective and practical scientific method for analysis and evaluation of how to maintain the comprehensive optimal navigation performance of high-speed monohull ships. At the same time, it provides a way to quickly evaluate the comprehensive performance of similar high-speed monolithic ships in the preliminary design stage, and can also obtain the model diagram with the best comprehensive performance through this software or method, which is useful for shortening the preliminary design cycle of the ship and improving the design quality of the ship. It has important reference value.

Optimal design and development of renewable based multi‐energy system for village sustainability: A case study simulation

AbstractThe primary objective of this article is the design and development of the optimal hybrid renewable energy (HRE) system for rural communities through village‐owned resources. The optimal performance and economic analysis is carried out with a suitable multi‐energy generation configuration model simulation. Based on the simulation outcomes the feasibility report of the proposed HRE system is to be considered for the investor's decision‐making process. The complete analysis has been planned with three important phases such as pre assessment stage, simulation and optimization stage, and evaluation stages. This real conducted case study has expressed many interesting facts about the integration of renewable resources toward meeting the rural energy requirements with economical and smooth manners. The proposed configuration is capable to generate net annual energy of 89,822 kWh/year with CoE (cost of energy) of Rs. 8.102. In addition, the proposed HRE system is reducing the CO2 impact on the environment by nearly 3.5% with an excess energy capacity of 6688 kWh/year.

Structural optimization and hydraulic performance analysis of bionic pit flow channels based on a genetic algorithm

Orthogonal experiments have mostly been used in the structural optimization of drip irrigation emitter flow channels. To further improve the efficiency of the optimal design, this study used a genetic algorithm to optimize the structure of the bionic pit flow channel. Based on the structural similarity and performance optimization of the torus-margo bordered pit structure, the constitutive equation of the flow channel unit was constructed. The selection, crossover and mutation operators were set by the genetic algorithm, and the objective function value was calculated. The design variables and known variables that met the requirements were put into the computational domain model, and the pit flow channel structure was simulated and optimized. The results showed that there were large low-velocity regions at the junctions and corners of the pit flow channel units at a working pressure of 50 kPa, and no complete low-velocity vortices were observed, indicating that the flow channels had good anti-clogging performance. The distribution of flow velocity on the same cross-section was quite different, which made the flow layers collide and mix, which intensified the loss of energy, indicating that it had a good energy dissipation effect. The multivariate linear regression analysis showed that the four variables of tooth stagger value (j), flow channel angle (θ), tooth spacing (l) and inner and outer boundary spacing (h) had a decreasing degree of influence on the flow index (x). The flow index (x) was negatively correlated with the tooth stagger value (j), flow channel angle (θ) and tooth spacing (l), and positively correlated with the inner and outer boundary spacing (h). The test results of physical samples showed that the average error between the simulation results and the real values was 3.4%, indicating that the accuracy was high, which can provide a basis for the structural optimization design of related pit drip irrigation emitters.

A Boosted Communicational Salp Swarm Algorithm: Performance Optimization and Comprehensive Analysis

A Boosted Communicational Salp Swarm Algorithm: Performance Optimization and Comprehensive Analysis

Experimental study of a hemispherical solar distillation system with and without rock salt balls as low-cost sensible storage: Performance optimization and comparative analysis

The significant heat losses from the solar distillers are the essential bottlenecksfor their deprived performance. Minimization of the heat losses of the solar distillers by utilizing sensible storage materials has been proposed as a promising strategy. In this study, the potential ofusing rock salt balls as a low-cost sensible storage medium for augmenting the freshwater product of hemispheric solar still (HSS) is investigated. The influences of rock salt balls with a size diameter of 20 mm at different gap spacing of (3, 4, 5, and 6 cm) are investigated and compared to the conventional hemispheric solar still (CHSS) to determine the optimal arrangement of the rock salt balls that maximizes the freshwater production. The experimental results showed the utilization of rock salt balls with a spacing gap of 4.0 cm represents the optimal arrangement that maximizes the energic-economic performance of distillers. The accumulative freshwater reached 6.50, 7.0, 6.0, and 5.35 kg/day.m2 for rock salt balls with gap spacing of 3.0, 4.0, 5.0, and 6.0 cm, respectively, compared to 4.70 kg/day.m2 yielded by the CHSS. The improvement in freshwater for the utilization of rock salt balls reached 38.3 %, 49.0, 27.65 %, and 13.84, respectively. Furthermore, under these conditions, the enhancement in daily energy efficiency for using the rock salt balls is obtained as 55.92 %, 60.10, 51.46 %, and 45.98 %, respectively, compared to CHSS. The proposed hemispheric distillers using the rock salt balls show a 25.23 %, 31.0 %, 19.84 %, and 10.77 %, reduction in the cost per 1.0 L of freshwater than CHSS, respectively.

Starting up anammox system with high efficiency nitrogen removal at low temperatures: Performance optimization, sludge characterization and microbial community analysis

Anaerobic ammonia oxidation (anammox) has potential advantages for nitrogen removal when operating at medium temperatures, but the increased operation costs of heating limit its application. It would be advantageous to start and operate anammox at low temperatures, the feasibility of which was studied here on a lab scale. Two identical expanded granular sludge bed (EGSB) reactors were inoculated at 35 ± 1 °C (Amed) and 15 ± 3 °C (Alow). Results showed that anammox was successful after 138 d for Alow, only 7 d longer than Amed. Stable operation to 194 d in Alow, the nitrogen loading rate (NLR) increased to 1.01 kg m−3·d−1, giving a high nitrogen removal efficiency (NRE) of 85%, which was only slightly lower than that of Amed (90%). More extracellular polymeric substance (EPS) was produced by the microbes of Alow compared to Amed, which prevented anaerobic ammonia oxidizing bacteria (AnAOB) against low temperature stress. Microbial community revealed presence of Candidatus Jettenia in Amed with relative abundance 7.4%, while the “cold-tolerant” Candidatus Kuenenia with 4% was the dominant anammox bacteria in Alow. The anammox granules adapted well to low temperatures and demonstrated high efficiency in anammox process without heating. Therefore, constructing an energy-saving and cost-effective anammox system in high latitudes or high altitudes can be considered.

Optimal Design and Dynamic Performance Analysis of Vehicle Suspension Employing an Eccentric Inerter

This paper concerns the dynamic performance analysis of the vehicle ISD (inerter-spring-damper) suspension employing an eccentric inerter. Firstly, the quarter car model of the two basic vehicle suspension layouts involving an eccentric inerter, namely, the series-connected layout and the parallel-connected layout, is established. Then, by considering the overall performance such as the vehicle body acceleration, the suspension working space, and the dynamic tire load, the key parameters of the two suspensions are optimized by using the genetic algorithm. Simulation analysis results indicate that the series-connected vehicle ISD suspension is superior to the parallel-connected one, and all of the RMS values of the body acceleration, the suspension working space, and the dynamic tire load are decreased significantly by comparing to the conventional suspension, while the improvement of the parallel-connected vehicle ISD suspension is relatively poor. At last, the impact of the flywheel eccentricity and the screw pitch on the dynamic performance indices of the two suspensions is discussed, and the trade-offs among the three performances are analyzed, which will provide a guide method for the suspension design when considering the eccentric factor.

Optimal design and dynamic performance analysis of a fractional-order electrical network-based vehicle mechatronic ISD suspension

To further explore the beneficial effects of the vibration isolation performance of a new vehicle ISD (inerter-spring-damper) suspension using a mechatronic inerter, this paper proposes a novel optimal design methodology for a vehicle mechatronic ISD suspension system based on a fractional-order electrical network is proposed. In view of difficulties in the engineering implementation of fractional-order mechanical network elements, this paper first studies the correspondingrelationship and analytical expression of fractional-order mechanical and electrical network elements respectively. Under the instruction of fractional calculus, the fractional-order electrical network elements are used to realize equivalent fractional-order mechanical network elements by adopting a ball-screw mechatronic inerter. Then, a quarter car dynamic model of vehicle mechatronic ISD suspension is constructed, and the parameters of the fractional-order electrical network and the integer-order electrical network are obtained by means of particle swarm optimization algorithm. The performance advantages of vehicle mechatronic ISD suspension using a fractional-order electrical network are verified by numerical simulations and experiments. The results show that, compared with the application of an integer-order electrical network, the vibration suppression performance of a vehicle mechatronic ISD suspension can be further enhanced by using a fractional-order electrical network.

Intelligent Network Service Optimization in the Context of 5G/NFV

Our contemporary society has never been more connected and aware of vital information in real time, through the use of innovative technologies. A considerable number of applications have transitioned into the cyber-physical domain, automating and optimizing their routines and processes via the dense network of sensing devices and the immense volumes of data they collect and instantly share. In this paper, we propose an innovative architecture based on the monitoring, analysis, planning, and execution (MAPE) paradigm for network and service performance optimization. Our study confirms distinct evidence that the utilization of learning algorithms, consuming datasets enriched with the users’ empirical opinions as input during the analysis and planning phases, contributes greatly to the optimization of video streaming quality, especially by handling different packet loss rates, paving the way for the achievable provision of a resilient communications platform for calamity assessment and management.

A Robust, Compact and Efficient AMC-Enabled Dual-Band Antenna for Wearable Healthcare

This paper details an antenna design with a minuscule lateral footprint of [Formula: see text][Formula: see text]mm3. The antenna operates for the two bands of WiMAX 3.5[Formula: see text]GHz (for wireless communication standard) and industrial, scientific and medical radio (ISM) 5.8[Formula: see text]GHz (for healthcare applications). Optimization and computer-aided performance analysis of the proposed design are carried out using Computer Simulation Technology (CST) Microwave Studio. Required electromagnetic performance in close proximity to the human body is achieved by backing the primary CPW-fed antenna with a fabric-based dual-band AMC surface. Several prototypes of the formulated design are characterized experimentally to validate the computationally obtained performance parameters. The proposed AMC-integrated dual-band design readily meets directional radiation characteristics desired for off-body communication with 7.53-dB and 8.58-dB gains in the lower and upper resonance frequencies, respectively. Moreover, the antenna’s top layer consists of a semi-flexible laminate, while textile constitutes the bottom layer to maximize user comfort. Further analysis reveals a significant reduction in SAR by 16.7[Formula: see text]W/kg at the lower band and by 13.5[Formula: see text]W/kg at the upper band. The precedence of the reported structure demonstrated in the results endorses its application in robust wearable devices.

Analysis of performance optimization of high‐temperature solid oxide electrolytic cell based on the coupling of flow, heat, and mass transfer and electrochemistry

AbstractA three‐dimensional (3D) model simulating the flow, heat, and mass transfer characteristics of a high‐temperature solid oxide electrolytic cell (SOEC) is developed based on the coupling of gas flow in channels, the electrochemical reaction in the triple‐phase boundary of electrodes and component diffusion in the porous media in electrodes. The model comprises several equations such as mass equation, momentum equation, energy equation, mass transport equation, and electrochemical reaction equation. The computational fluid dynamics method is adopted to simulate the operating performance (current density distribution, temperature distribution, and gas component distribution) of the 3D electrolytic cell model under different operating conditions (electrolytic voltage, gas temperature at the inlet, flow rate and flow pattern). The simulation results show that gas temperature at the inlet obviously influences electrolytic hydrogen production by SOEC. In the case of lower voltage, a higher temperature can be selected to effectively increase the current density. When the current density is high enough, the supply flow of water vapor needs to be increased to prevent the inhibition reaction of low‐concentration reactants, but this may lead to the reduction of water vapor conversion. In practical operation, a lower voltage and higher gas temperature should be selected, and the flow rate of water vapor appropriately increased to ensure hydrogen production and improve operating efficiency.

Parameter Optimization and Bending Performance Analysis of a Corrugated Steel Plate-UHPC Composite Bridge Deck with PZ Shear Connectors

Composite bridge decks consisting of steel plates and concrete are used to minimize fatigue cracking and damage of asphalt pavement of orthotropic steel bridge decks subjected to wheel loads. This paper presents a methodology to optimize the parameters and mechanical performance of a corrugated steel plate-ultrahigh-performance concrete (UHPC) composite bridge deck with panel zone (PZ) shear connectors using the improved non-dominated sorting genetic algorithm (NSGA-II). A 3-D finite element model is established in ANSYS Workbench software to conduct numerical parameter analysis, and ABAQUS software is used to analyze the optimized model’s mechanical performance. The results show a significant improvement in the mechanical performance of the optimized composite bridge deck, with a 27.66% decrease in the maximum stress in the UHPC layer. The vertical displacement of the optimized composite bridge deck increases sharply when the load reaches 90% of the ultimate load, and a significant change in the strain is caused by the sliding displacement between the UHPC layer and steel plate. The bottom part of the corrugation yields first in the middle span, followed by failures of the ribs. In addition, as the tensile stress increases, damage occurs first in the UHPC layer near the PZ shear connectors in the shear bending area and the bottom in the bending area, expanding significantly to the entire bending and loading areas. The results indicate that the parameter optimization of the corrugated steel plate-UHPC composite bridge deck using NSGA-II improves the structure’s bending performance.

Optimization Design and Performance Analysis of Improved IEEE802.11p MAC Mechanism Based on High Mobility of Vehicle

The high-speed movement of vehicles is the core factor affecting the rapid development of vehicular ad hoc network (VANET), especially the impact of vehicle mobility on data access and transmission performance. However, the classic IEEE802.11p data access and transmission protocol are still used in the multi-hop VANET under the highway system, which is adopted in the low-speed environment. Therefore, the impact of vehicle movement on the performance of the existing network is analyzed theoretically, and it is found that the network performance will be greatly reduced with the increase of vehicle speed. In order to improve the network performance in high-speed environment, an improved network access transmission protocol is proposed. Through Markov modeling, the analytic expressions of system delay, throughput, and packet loss rate are obtained. Finally, the effectiveness of the improved mechanism is verified by comparing the simulation results of two mechanisms.

Optimal Design and Performance Analysis of Three-phase Distribution Transformer with Variable Loading

Electrical power passes through several transformers after generation through consumption. The final stage of any power system consists of many small-rating distribution transformers. Since the loads connected to these transformers vary with time, their effective design and operation with variable loading conditions are crucial for the system to operate efficiently and reliably. In most previous works, loads connected to these transformers are treated as constant power and stray losses of the transformers are neglected in the calculations. Neglecting the load variation and stray losses reduces the transformer life span noticeably and impairs grid quality and reliability. In this work, a small-rating distribution transformer is designed and analyzed analytically and numerically. Detailed procedures on the conventional design are presented with the general design issues. The effect of variable loading on the transformer’s power losses, efficiency, temperature rise, voltage regulation, and output voltage variation is analytically and numerically investigated. Results show that the rating and power factor of the load significantly influence the performance characteristics of the transformer.

Porous interbody fusion cage design via topology optimization and biomechanical performance analysis

The porous interbody fusion cage could provide space and stable mechanical conditions for postoperative intervertebral bone ingrowth. It is considered to be an important implant in anterior cervical discectomy and internal fixation. In this study, two types of unit cells were designed using topology optimization method and introduced to the interbody fusion cage to improve the biomechanical performances of the cage. Topology optimization under two typically loading conditions was first conducted to obtain two unit cells (O-unit cell and D-unit cell) with the same volume fraction. Porous structures were developed by stacking the obtained unit cells in space, respectively. Then, porous interbody fusion cages were obtained by the Boolean intersection between the global structural layout and the porous structures. Finite element models of cervical spine were created that C5-C6 segment was fused by the designed porous cages. The range of motion (ROM) of the cervical spine, the maximum stress on the cage and the bone graft, and the stress and displacement distributions of the cage were analyzed. The results showed the ROMs of C5-C6 segment in D-unit cell and O-unit cell models were range from 0.14° to 0.25° under different loading conditions; the cage composed of the D-unit cells had a more uniform stress distribution, smaller displacement on cage, a more reasonable internal stress transfer mode (transmission along struts of the unit cell), and higher stress on the internal bone graft (0.617 MPa). In conclusion, the optimized porous cage is a promising candidate for fusion surgery, which would avoid the cage subsidence, and promote the fusion of adjacent endplates.

Optimal design and performance analysis of magnetorheological damper based on multiphysics coupling model

Magnetorheological (MR) fluid is a kind of intelligent magnetic material, and MR damper is widely used in various fields based on its rheological properties. Therefore, aiming at the problems of low optimization accuracy and efficiency in the optimization design process MR damper using single physical field analysis method, a multi-objective optimization design method for MR damper based on multiphysics coupling model was proposed. The magnetic circuit of the MR damper was calculated, and the mechanical model, electromagnetic field model, flow field model and stress field model of MR damper were established, respectively. A multiphysics coupling model of the MR damper was established in the COMSOL software. The multi-platform joint optimization model was setup, and a multi-objective optimization design method of DOE combined with the surrogate model was proposed. A test system was built up and the initial and optimal MR dampers were fabricated. The results show that the simulation and experimental error of the damping force and dynamic range of the optimal MR damper are only 4.9% and 8.8% at the applied current of 1.4 A, respectively. Also, the damping force and dynamic range of the optimal MR damper are increased by 21.9% and 11.9% compared with the initial MR damper, respectively, which verifies the accuracy of the multiphysics coupling model and effectiveness of optimal design.

Design and evaluation of coconut fiber bionic‐stripping device based on Lucanidae palate frictional characteristics

AbstractManual stripping of coconut fiber has low processing efficiency coupled with difficulty in operation. To overcome these problems, a coconut fiber bionic‐stripping device based on Lucanidae palate frictional characteristics was designed. The device relied on the torsion spring edge hook and brush working principle to strip the coconut fiber. The coconut shell was not damaged during the stripping operation owing to the elasticity and toughness of the bionic torsional spring. The test parameter optimization was carried out using the coconut fiber bionic‐stripping device and analyzed using Design‐Expert.V8.0.6 Software. The results showed that the planting distance between torsion springs had significant effect on stripping coconut fiber (p < .001), but the diameter of torsion spring had the least effect on stripping coconut fiber. Regression analysis of the test data showed that the device had higher processing efficiency at coconut rotation speed of 1200 rad/min, coupled with bionic torsion springs diameter and planting distance of 2.0 and 17 mm, respectively. Under optimal combination of parameters, coconut fiber removal thickness was found to be R△ = 30.9 mm. The data obtained showed high repeatability, thereby indicating that the coconut fiber bionic‐stripping device can meet the technological requirements for coconut fiber removal.Practical ApplicationsThis study focuses on coconut characteristics as well as the process requirements for coconut fiber removal. A mechanism to strip the fiber using bionic torsion springs was proposed, which was designed based on the characteristics of the Lucanidae palate. Including a device for peeling coconut fiber using bionic torsion springs. Furthermore, the structural stress analysis of the device was carried out so as to explore the feasibility of using the bionic torsion spring group to peel coconut fiber. Parameter optimization test, performance analysis, and comparative performance analysis were carried out using the device to analyze the influence of different bionic torsion spring group parameters on the thickness of stripped coconut fiber. This can provide a theoretical and experimental basis for the study of coconut fiber stripping mechanism, and can broaden the existing research methods of coconut fiber stripping.

A Comprehensive Performance Analysis of Transfer Learning Optimization in Visual Field Defect Classification

Numerous research have demonstrated that Convolutional Neural Network (CNN) models are capable of classifying visual field (VF) defects with great accuracy. In this study, we evaluated the performance of different pre-trained models (VGG-Net, MobileNet, ResNet, and DenseNet) in classifying VF defects and produced a comprehensive comparative analysis to compare the performance of different CNN models before and after hyperparameter tuning and fine-tuning. Using 32 batch sizes, 50 epochs, and ADAM as the optimizer to optimize weight, bias, and learning rate, VGG-16 obtained the highest accuracy of 97.63 percent, according to experimental findings. Subsequently, Bayesian optimization was utilized to execute automated hyperparameter tuning and automated fine-tuning layers of the pre-trained models to determine the optimal hyperparameter and fine-tuning layer for classifying many VF defect with the highest accuracy. We found that the combination of different hyperparameters and fine-tuning of the pre-trained models significantly impact the performance of deep learning models for this classification task. In addition, we also discovered that the automated selection of optimal hyperparameters and fine-tuning by Bayesian has significantly enhanced the performance of the pre-trained models. The results observed the best performance for the DenseNet-121 model with a validation accuracy of 98.46% and a test accuracy of 99.57% for the tested datasets.