Parameter Optimization Analysis Research Articles

Efficiency-aware machine-learning driven design of solar harvester for renewable energy application

Although MIM structures have been studied for solar thermal applications for decades, the multilayer MI-MIM structure is the subject of this study's investigation for batter absorption. In order to identify an effective solar absorber, two configurations Gold-MgF2-Gold (GMGSA) and Gold-MgF2-Gold-MgF2-Gold (GMGMGSA) are examined in this work. By using machine learning approaches, this research was able to get an MSE of 2.8091 × 10−5 and an R2 value of 0.998836. The optical response and parameter optimization analysis have been examined in this work in the wavelength range of 0.4 μm–1.6 μm. When exposed to AM 1.5 spectrum radiation, the GMGMGSA absorbs 93.10 % of the radiation, compared to 88.30 % for the single-layer GMGSA. Furthermore, both structures show steady absorption that is independent of polarization up to a 70° incidence angle. The aforementioned discoveries render the structure a plausible contender for solar thermal uses, including battery-integrated photovoltaic (BIPV), commercial solar power (CSP), and solar water heating. This might lead to a future where energy is more sustainably produced.

Research on the impact mechanism and parameter optimization of RTP structure layer fusion process

Fiber-reinforced thermoplastic composite pipes (RTP) possess a complex multilayer structure. Apart from the melting process of the reinforced layer, the melting process between the inner and outer layers and the reinforced layer is equally crucial. Factors such as heating time, heating temperature, and pipe diameter significantly influence the degree of tight bonding between these layers. The purpose of this study is to investigate the influence mechanism of the fusion process between the three main layers of RTP and to perform parameter optimization analysis. First, Box-Behnken response surface method and finite element analysis were used to obtain the softened layer thickness under different parameters and to couple the influence mechanism of process parameters on the softened layer thickness. Then, single parameter sensitivity analysis was used to reveal the influence mechanism of each parameter change on the softened layer thickness of the pipe, and then the coupling analysis of the process parameters was carried out. The analysis results show that the softened layer thickness is most sensitive to the change of heating temperature, followed by heating time and pipe diameter. Finally, the optimal parameter combination was obtained through the expected function method, and experiments were conducted on finished pipes.

A Comparative Analysis of Single and Multi-objective Process Parameter Optimization of Dissimilar Metal Friction Welds

A Comparative Analysis of Single and Multi-objective Process Parameter Optimization of Dissimilar Metal Friction Welds

Energy and parametric optimization analysis of a novel double serpentine runner air-cooled PV/T assisted variable capacity air source heat pump system

Through different technologies, the solar energy and air source energy have been effectively used as renewable energies to address the heating problem in the cold area of Northwest China. However, there are very few researches on the comprehensive performance of heat transfer enhancement and airflow pressure drop in the solar collector, as well the dynamic matching performance between the air source heat pump system and energy load of building. To address the mentioned problems, we propose a novel double serpentine runner air-cooled photovoltaic/thermal collector assisted variable capacity air source heat pump (DSPV/TSAC-VCASHP) system. The summary of experimental and numerical results of the heat transfer characteristics of the double serpentine runner was used in the simulation model of the novel collector. The collector and air source heat pump system are connected in parallel with building room for space heating. The dynamic simulation model of the system was established and simulated using TRNSYS to study and analyze the power consumption, effect of key parameters, as well seasonal performance of the novel system. The simulated results show that the system could reach around 88 % power consumption lower than that of single air source heat pump system during the heating season.

Parametric optimization and energy loss analysis of a solar thermophotonic energy converter

In the present work, the model of a solar thermophotonic energy converter (STEC) is established, of which the energy balance constraint equations at both the hot and cold sides are numerically solved to uncover the dependencies of the operating temperatures of the light emitting diode (LED) and photovoltaic (PV) cell on thermal, electrical, and structural parameters. For a given band-gap 0.36 eV of the semiconductor and a concentrated factor 20 of the concentrator, the LED’s bias voltage and the PV cell’s output voltage are optimized to achieve a local maximum efficiency 13% of the STEC. Furthermore, the conditions are optimized to attain an overall maximum efficiency of 15.94%. The distributions of energy losses are presented to reveal the underlying loss mechanisms. The results obtained in this work can provide theoretical guidance for the efficient utilization of solar energy.

Identification of Major Interfering Substances for Heavy Metal Determination in Northern Sea Areas of Sri Lanka

This study investigated the physicochemical characteristics of seawater from five locations along the northern Sri Lankan coast, encompassing areas with varying degrees of anthropogenic activity. The analysis revealed significant variations in several parameters, potentially influenced by human influences. The results reveal significant variations in several parameters. For instance, turbidity levels varied from 1.88 NTU in Thalaiyadi to 13.3 NTU in Pannai, with Pannai, Myliddy, and Kakkaithivu exceeding the recommended limit of 5 NTU. Total suspended solids (TSS) ranged from 3 mg/L in Thalaiyadi to 83 mg/L in Pannai, surpassing the recommended limit of 30 mg/L. Electrical conductivity (EC) ranged from 45,700 µS/cm in Nainathivu to 49,500 µS/cm in Pannai, exceeding the typical seawater range. Nitrate levels ranged from 10.4 mg/L in Thalaiyadi to 19.1 mg/L in Myliddy. Major cations such as calcium (361 mg/L to 417 mg/L), magnesium (1,222 mg/L to 1,327 mg/L), and sodium (10,140 mg/L to 10,530 mg/L) also showed significant differences across locations. These findings highlight the need for continuous monitoring and effective management strategies to mitigate the negative impacts of anthropogenic activities on these coastal ecosystems. Furthermore, the complex seawater matrix presents challenges for heavy metal determination using Graphite Furnace Atomic Absorption Spectroscopy (GFAAS) due to spectral interferences from major cations, non-specific matrix effects, and interferences from organic matter, turbidity, and suspended solids. Careful consideration of these factors through background correction techniques, matrix modifiers, sample pre-treatment, and optimization of analysis parameters is crucial for accurate heavy metal determination in these environments. This study contributes to a better understanding of the environmental conditions and emphasizes the need for further research on heavy metal contamination and the development of robust analytical methods tailored to address the challenges posed by the complex seawater matrix in northern Sri Lanka.

Deformation strengthening mechanism of laser remelted high manganese steel

In order to further improve the deformation hardening ability of high manganese steel (HMnS) under low stress or small deformation, a low speed laser remelting technology was proposed to process the HMnS surface. Through parameters optimization, microstructure characterization, wear testing, and deformation strengthening analysis, the deformation strengthening mechanism of laser remelted HMnS (LR-HMnS) was systematically studied, and excellent wear resistance properties was also achieved. Firstly, by optimizing the parameters of laser remelting, high-quality microstructures with large remelting depth and fewer porosities were obtained. Then, the sliding wear tests showed that although the surface hardness of LR-HMnS (252.83HV0.3) was only 2.56 % higher than that of continuous casting HMnS (CC-HMnS) (246.53HV0.3), its volume wear rate (1.87×10−5 mm3/N·m) was only 10 % of CC-HMnS (18.71×10−5 mm3/N·m), which exhibited excellent wear resistance properties. Finally, for quantitative evaluating its work hardening at high strain rates, Hopkinson compression test of LR-HMnS was conduced according to the operating conditions of HMnS parts. The microstructure after small compression deformation was analyzed using EBSD and TEM. It was found that the larger grain size of LR-HMnS was helpful of reducing the nucleation stress of twins, forming high-density nano-twins, high-density stacking faults, and high-density dislocations. The synergistic effect of stacking faults, dislocations, and twins which segmented the matrix and refined the grains, and achieved the dynamic Hall-Petch effect. The superior deformation strengthening and wear resistance exhibited by larger grain HMnS were called the inverse grain size effect. Additionally, the large number of C-Mn strong bond networks formed by element segregation could enhance the pinning effect of dislocations, promote deformation hardening rate and wear resistance properties under low stress or small deformation. The research results provided a new method for pre-hardening of HMnS, and will also expand the application potential of HMnS in combined conditions of high, medium, and low impact.

Green surfactant and circulating ultrasound coupling extraction of total flavonoids from Cynanchum auriculatum leaves: Parameter optimization, extraction mechanism, and HPLC-MS analysis

This study aimed to devise an integrated green surfactant and circulating ultrasound coupling extraction (GSCUE) approach for extracting the total flavonoids from Cynanchum auriculatum leaves. Single-factor optimization combined with a Box–Behnken design was used to determine the optimal technological conditions, which included an APG0814/MES amount of 5 % (w/v), extraction temperature of 46 °C, ultrasound irradiation power of 509 W, liquid–solid ratio of 30 mL/g, mixing speed of 1000 r/min, and extraction time of 50 min. Under these conditions, the extraction yield of the total flavonoids reached 7.83 mg/g. The HPLC-MS was applied to identify the flavonoid compositions in Cynanchum auriculatum leaves extract. The results showed that flavonoid composition included Gardenin B, Luteolin, Kaempferol, Quercetin, 4′-Methoxy-7-O-beta-D-glucopyranosyl-8,3′-dihydroxyflavanone, Astragalin, Spiraeoside, Rutin, and Kaempferol 3-gentiobioside. Further, to investigate the GSCUE mechanism, plant samples before and after extraction were analyzed by fourier transform infrared spectroscopy, scanning electron microscopy, and contact angle analysis. The results indicate that the functional groups, surface microstructure, and surface wettability of the plant samples all affect the yield of the target active ingredients. The hydrophilic group content on the plant sample surface after GSCUE treatment was higher compared to the case of the untreated samples. Additionally, there was evidence of surface structural collapse and shrinkage, increased surface roughness, and a decreased contact angle due to GSCUE treatment. These results highlight the greater surface wettability of the plant samples, faster solvent penetration, and an effective increase in the total flavonoid yield, indicating the synergistic effect of combining ultrasound with green surfactants for total flavonoid extraction. Overall, GSCUE technology provided a sustainable and efficient approach for extracting the total flavonoids from plant materials.

Structure Parametric Optimization and Mechanical Analysis of the MSe1 Septum Magnet

Structure Parametric Optimization and Mechanical Analysis of the MSe1 Septum Magnet

Analysis of Film Unloading Mechanism and Parameter Optimization of Air Suction-Type Cotton Plough Residual Film Recovery Machine Based on CFD—DEM Coupling

Analysis of Film Unloading Mechanism and Parameter Optimization of Air Suction-Type Cotton Plough Residual Film Recovery Machine Based on CFD—DEM Coupling

Mechanical and Sliding Wear Performance of Vacuum-Cast AA7075-Co Alloy Composites: Parametric Optimization and Ranking Analysis

Mechanical and Sliding Wear Performance of Vacuum-Cast AA7075-Co Alloy Composites: Parametric Optimization and Ranking Analysis

Parametric design optimization and thermodynamic analysis of plate fin heat exchanger for helium liquefaction system

The plate-fin heat exchanger is one of the most important components of helium liquefaction system as it recovers cold energy from helium gas in the cold box. Because of larger heat transfer surface area and compact geometrical configuration, plate-fin heat exchangers are widely used. The design of heat exchanger using helium as a cryogenic fluid needs high thermodynamic performance with minimum pressure drop which particularly requires the optimization of dimensional array and its geometrical configurations. In this regard, a parametric investigation was performed to compute the effective geometrical parameters and its effect on thermodynamic (effectiveness and log-mean temperature difference) performance has been discussed in detail. The present study aims to design optimization and thermodynamic performance evaluation of plate-fin type heat exchangers used in helium liquefaction systems. The developed helium liquefaction model has been simulated for the most critical liquefier with and without liquid nitrogen precooling, mixed mode, and refrigeration mode. Each component of the liquefaction model has been technically and thermodynamically analyzed and, in particular, four plate-fin heat exchangers have been considered and designed accurately using Aspen EDR®. Initially, the sensitivity analysis was carried out to characterize the most significant geometrical parameters (fin thickness, height, number and arrangement of layers, frequency, and fin type) and their effect on thermodynamic performance and pressure drop. After that, the artificial intelligence model was used to determine the optimal range of such geometrical variables in which the heat exchanger has maximum effectiveness and log mean temperature difference. Finally, the operating conditions obtained from cycle modeling and optimized geometrical datasets have been applied in commercial simulation software Aspen EDR® for plate-fin heat exchangers design. Finally, a comparative thermodynamic analysis has been carried out to determine the performance of all the designed heat exchangers operating at four different modes (boundary conditions).

The Design and Process Parameters for the Optimization of an Ultrasonic—Thermal Co-Sterilization System for Liquid Eggs

The sterilization of liquid eggs plays a crucial role in the production of liquid egg products. Traditional pasteurization techniques can easily cause protein denaturation, while non-thermal sterilization techniques are often constrained by processing intensity and time. Improving the effectiveness of liquid egg sterilization while preserving the stability of its functional attributes poses a significant challenge. In response to this issue, a synergistic ultrasonic mild thermal sterilization system for liquid eggs is proposed, accompanied by the optimization of its process parameters. COMSOL is employed to simulate the acoustic field distribution of the ultrasonic–thermal system in the liquid egg medium. Verification is conducted through acoustic intensity measurements, and analysis is performed to obtain the optimal arrangement of ultrasonic transducers. Based on Modbus communication, an ultrasonic–thermal synergistic sterilization system is designed. Sterilization experiments are conducted with both 20 kHz + 28 kHz and 20 kHz + 40 kHz multifrequency ultrasound, compared with traditional 20 kHz single-frequency ultrasound. The results indicate that multifrequency ultrasound improves sterilization efficiency by approximately 15% compared to traditional single-source ultrasound. Utilizing multifrequency ultrasonic–thermal synergistic sterilization experiments, a three-factor, three-level response surface test is conducted with sterilization rate and foaming properties as evaluation criteria. The results indicate a strong correlation between ultrasonic frequency, processing time, heating temperature, and sterilization performance, with the impact magnitude being sterilization temperature > processing time > ultrasound frequency. Parameter optimization analysis is performed using a genetic algorithm, yielding sterilization conditions of 55 °C, 11 min and 30 s processing time, and 20 + 40 kHz ultrasonic frequency. The liquid egg sterilization rate is 99.32%, an average decimal reduction of 3.17 log values, and foaming properties are 42.79%.Through comparative analysis, it is determined that the sterilization rate of the ultrasonic–thermal synergistic sterilization system meets national standards, and functional properties such as foaming are superior to traditional pasteurization. This validates the proposed ultrasonic–thermal synergistic liquid egg sterilization control system as effective and feasible.

Seismic control performance of multi-story structures with an enhanced particle inerter device (EPID)

An enhanced particle inerter device (EPID) is innovatively developed to mitigate the dynamic responses of multi-story structures subjected to seismic excitations. The device dissipates energy through tuning, particle-cavity collisions, and the inertia amplification effect of the inerter. Multi-story response can be mitigated when the inerter unit connect the particle device and the cross-story. In this paper, a shaking table test was conducted to investigate the working mechanism of the EPID on the dynamic response of multi-story structures. A series of parametric studies were undertaken to analyze both the individual and combined effects of the particle damping unit and inerter unit within the device. Furthermore, a parameter optimization analysis guided by a genetic algorithm was carried out, resulting in a significant enhancement of 27.92% in displacement control and 24.41% in acceleration control when compared to the traditional design. Moreover, the energy dissipated by the main structure with the optimized EPID shows a decrease of 45.4% when compared to the traditional design.

Reliability-based thermal-fluid-structural topological optimization of three-dimensional coolant channels in proton exchange membrane fuel cells

In order to minimize the flow resistance in designing the cooling multi-channels of proton exchange membrane fuel cells (PEMFCs) under the double constraints of target thermal reliability index and target structural performance, this work proposes a three-dimensional (3D) thermal-fluid-structural reliability-based topology optimization (RBTO) method for the first time. In the RBTO for PEMFCs’ coolant channels, the position uncertainty of the multi-heat loads on the bipolar plates caused by irregular metal foam skeleton is considered, and the multi-heat load positions are treated as the interval uncertain variables within a certain range. To solve the problem of low computational efficiency caused by the coupling of topological parameter optimization and reliability constraint analysis, the RBTO is equivalently decoupled to a sequence of cycles of deterministic topology optimization (DTO) and inverse reliability assessment, and the latter is completed by performance measure approach (PMA) based on the target reliability index. Results show that RBTO introduces more flow resistance cost than DTO, and the additional flow resistance in RBTO increases with the increase of the target reliability index. The heat concentration caused by a smaller fiber diameter of foam skeletons results in more flow resistance cost of RBTO compared to DTO. When the inlet velocity of the coolant channel varies in the region of 0.05–0.3 m/s, the flow resistance of the multi-channel obtained by RBTO is 1.29–0.96 times as that of the straight multi-channel. In addition, the uneven reactant gas concentration in PEMFC gas channels leads to the uneven distribution of heat flow, and it affects the temperature distribution on bipolar plates, which in turn affects the results of RBTO. The above method and findings can be applied to design the cooling channels of PEMFCs with irregular metal foam gas channels.

Significant duration prediction of seismic ground motions using machine learning algorithms.

This study aims to predict the significant duration (D5-75, D5-95) of seismic motion by employing machine learning algorithms. Based on three parameters (moment magnitude, fault distance, and average shear wave velocity), two additional parameters(fault top depth and epicenter mechanism parameters) were introduced in this study. The XGBoost algorithm is utilized for characteristic parameter optimization analysis to obtain the optimal combination of four parameters. We compare the prediction results of four machine learning algorithms (random forest, XGBoost, BP neural network, and SVM) and develop a new method of significant duration prediction by constructing two fusion models (stacking and weighted averaging). The fusion model demonstrates an improvement in prediction accuracy and generalization ability of the significant duration when compared to single algorithm models based on evaluation indicators and residual values. The accuracy and rationality of the fusion model are validated through comparison with existing research.

Tridiagonal Interval Matrix: Exploring New Perspectives and Application

Tridiagonal interval matrices are relevant in diverse applications, especially in dealing with parameter estimation, optimization and circuit analysis uncertainties. This research paper aims to improve the computational efficiency of obtaining the inverse of a general tridiagonal interval matrix. This matrix is pivotal in electric circuit analysis. We achieve this by employing interval arithmetic operations in the LU decomposition process, enabling effective handling of circuit parameter uncertainties. This approach generates an inverse interval matrix that addresses uncertainties in circuit analyses.

Design and test of tangential and longitudinal-axial threshing and separating unit for wheat

To achieve low loss and efficient wheat harvest in the Huanghuaihai region of China, this paper designed a tangential and longitudinal-axial threshing and separating unit (TLTSU). Key components such as the tangential threshing rotor (TTR), longitudinal-axial threshing rotor (LTR), and tangential concave were designed. Dynamic balance simulation of the threshing rotors was done to obtain the reaction forces at supporting ends of the threshing rotors and the amount of unbalance, and the amount of unbalance of the LTR was corrected to meet the standard requirement. Response surface optimization experiments of wheat threshing were conducted using throughput, TTR speed, and LTR speed as influencing factors and entrainment loss rate and impurity rate as test indicators. The regression models for the threshing device's entrainment loss rate and impurity rates were established. Through multi-objective parameter optimization analysis, the optimal threshing parameter combination for TLTSU was determined to be throughput of 8 kg s−1, TTR speed of 557 r·min−1, and LTR speed of 900 r·min−1. A validation experiment was conducted on this parameter combination, and the results showed that the entrainment loss rate was 0.27 % and the impurity rate was 28.23 %. The relative errors between the evaluation indicators and the predicted values of their regression models were 3.85 % and 1.4 %, respectively, which were less than 5 %, which proved the correctness of the regression model and provided a reference for the design of threshing and separating unit of wheat combine harvester.

Design, Installation, and Performance Monitoring of a 105 kWp Rooftop Solar PV System

Rooftop Solar PV systems are gaining growing attention on the path toward carbon neutrality. Hence, a great effort must be exerted to ensure smooth and efficient penetration of such systems into the existing utility grids. In the current work, a 105 kWp rooftop solar system is designed and installed to fulfil part of the electric demand of the faculty of Engineering, Zagazig University, Egypt. The performance parameters of this grid-connected solar PV system are optimized for the least-cost of electricity supply through using industry-standard software NREL SAM. For the current rooftop system, fixed orientation of an optimized tilt angle of 23 degrees is preferred over sun-tracking systems due to the reduced operating and maintenance costs. The annual energy production of the system is 175,700 kWh with a capacity factor of 19.1%. Through using parametric optimization and inter-connected financial analysis algorithms, it was possible to define the least cost for the electricity supplied to the grid to be 0.55 EGP/kWh, which achieves grid parity in Egypt. The project is finically profitable without any subsidy, with a discounted payback period of 7.9 years, and IRR (on equity) of 20.1 % and saves 1882-ton CO2 over its lifetime. Sensitivity analysis showed that the electricity escalation rate greatly enhances the project finances. In the first year of operation, the system performed fairly well compared with the theoretical design, provided that the system is frequently cleaned (at least once a week) and continuously connected.

Parameter Optimization and Solution Performance Analysis of Multi-Modal Butterfly Optimization Algorithm

Parameter Optimization and Solution Performance Analysis of Multi-Modal Butterfly Optimization Algorithm