Surface Method Research Articles

Abrasive Flow Material Removal Mechanism Under Multifield Coupling and the Polishing Method for Complex Titanium Alloy Surfaces

This study addresses the challenge of uneven surface quality on the concave and convex regions during the precision machining of titanium alloy thin-walled complex curved components. An electrostatic field-controlled liquid metal-abrasive flow polishing method is proposed, which is examined through both numerical simulations and experimental investigations. Initially, a material removal model for the liquid metal-abrasive flow under electrostatic field control is developed, with computational fluid dynamics (CFD) and discrete phase models employed for the numerical simulations. Subsequently, the motion characteristics of liquid metal droplets under varying amplitudes of alternating electric fields are experimentally observed within the processing channel. This serves to validate the effectiveness of the proposed method in enhancing surface quality uniformity across the concave and convex regions of titanium alloy thin-walled complex curved components. Our results demonstrate that by controlling the distribution of the electric field in regions with varying flow strengths, the roughness differences between the concave and convex surfaces of the workpiece are reduced to varying degrees. Specifically, in the experimental group subjected to a 24 V alternating electric field, the roughness difference is minimized to 58 nm, representing a 44% reduction compared to conventional abrasive flow polishing. These findings indicate that the proposed electrostatic field-controlled liquid metal-abrasive flow polishing method significantly enhances the uniformity of surface polishing on concave and convex areas of titanium alloy thin-walled complex curved components.

Response Surface Method (RSM) Process Optimization of Sulfides Oxidation in the Presence of Orange Peel Extract Immobilized Magnetic Hybrid Nanocomposite Catalyst

ABSTRACTThe oxidative transformation of sulfides to sulfoxides over magnetic green catalysts is one of the most important applications in pharmaceuticals. In this report, we demonstrate the step‐by‐step fabrication and synthesis of CoFe2O4, CuFe2O4, and Fe3O4 nanocomposite modified with orange peel extract complexes as advanced high‐performance magnetic nanocomposite materials. One of the goals of this project was to use phenolic acid phytochemicals in the catalytic process. The newly synthesized nanocomposites were characterized by several advanced analytical methods. Utilizing the Box–Behnken experimental design and the response surface methodology (RSM), reaction parameters such the amount of catalyst, hydrogen peroxide, and duration were improved. Furthermore, without experiencing a discernible loss of reactivity in the sulfide oxidation reaction, the catalysts were effortlessly magnetically retrieved and may be employed repeatedly.

Reliability assessment of steel slag and construction waste backfill for reinforced earth structures using response surface method

Reliability assessment of steel slag and construction waste backfill for reinforced earth structures using response surface method

Enhancing overall performances of large constructed wetlands using an integrated approach of numerical simulation and response surface method--Taking Bagong hybrid CWs as an example.

Constructed wetlands (CWs) with low carbon properties represented an effective approach for treating low-polluted water and improving water quality. Here, a research scheme was proposed to achieve maximum operation benefits of the large-scale CWs through parameter identification, operation simulation, evaluation, and analysis of the water quality process. Based on the two-dimensional water hydrodynamic model coupling with the Eco-Lab water quality module (with nutrients), simulation for Bagong hybrid CWs was successfully conducted. Variables were estimated using response surface design (RSD), and the values of model parameters were calibrated in accordance with central combination design (CCD) experiments. Ten key parameters in the water quality process affecting the overall pollutant removal of CWs were identified, and the water quality model of the CWs could be replicated well with the actual situation within the 95% confidence interval. The water purification effect of the CWs under five different influent flow conditions was simulated, and the maximum hydraulic loading (0.036m3·(m-2·h-1)) of the CWs was determined with the effluent water quality to meet the design requirements. The integrated method could effectively enhance the efficiency of parameter calibration and significantly reduce the simulation workload. The results of pollutants migration and transformation under different influent conditions could provide a universally applicable and valid method in engineering applications, and process a promising application prospect.

Experimental study of the combined effect of benzene exposure and physical load in rats

Introduction. The working process in many industries is often associated not only with chemical exposures but also with heavy physical workload, which can be potent of toxic effects of the former differently. The purpose of the study was to establish body responses to effects of benzene exposure combined with exercise in an experiment on rats. Materials and methods. The study was conducted on mature male Wistar rats, ten animals in each of the following groups: “Control”, “Running”, “Benzene exposure”, and “Benzene exposure + running”. Subchronic toxicity was modelled by intragastric administration of benzene thrice a week for 4 weeks in a cumulative dose of 100 mg/kg body weight. Exercise was modelled by means of 10-minute forced running sessions at a speed of 25 m/min 5 times a week for 4 weeks. We then measured post-exposure biochemical and hematological indices and the proportion of different types of cells in imprint smears of rat internal organs. Statistical data analysis was carried out using the Student’s t-test with p<0.05. For mathematical modelling of the combined effect of factors, we applied a Response Surface Method (RSM) with the construction of Loewe isobols on its basis. Results. Almost no statistically significant changes were registered in the rodents who exercised while statistical ones were sporadic and diagnostically insignificant in most cases. Benzene exposure induced changes in blood indices indicating blood clotting disorders, typical of chronic exposure to benzene, and in the antioxidant system. The impact of running on health effects of benzene exposure was ambiguous but isobolographic analysis showed possible additivity and even synergy, both detrimental to health, in 15.6 % of cases. Limitations. Extrapolation of the study results to human should be done with caution, since the combined effect has been examined only for subchronic exposure using a single species and sex of laboratory animals. Conclusion. Additivity proven by a number of indices of toxic effect gives important information for understanding and predicting health effects of exposure to organic pollutants combined with physical activity.

Optimizing ultrasonic extraction of polysaccharides from Spirulina platensis and evaluating their antioxidant and antibacterial activities in acidic environments.

In this study, the response surface method was used to optimize the ultrasonic extraction of polysaccharide from Spirulina platensis. The optimal extraction conditions were ultrasonic time 50 min, solid-liquid ratio 1: 40, ultrasonic power 265 w, and the predicted extraction rate was 6.861 ± 0.116 %. The FT-IR and NMR confirmed that polysaccharide from S. platensis would protonate to form β-glucoside bond in acidic environment, and the original carbonyl group would be converted to carboxyl group and then esterified to form acyl group donor. In the acidic pH range (7.0, 6.0, 5.0 and 4.0), the antioxidant, nitrite scavenging and bacteriostatic activities of the extracted polysaccharide from S. platensis were measured in vitro. The results showed that polysaccharide of S. platensis had better antioxidant activity in acidic environment and better performance in low pH condition. In addition, it has the best inhibitory effect on Salmonella enteritidis (14.3-17.15 mm) in acidic environment, and the inhibitory effect on Staphylococcus aureus (11.95-12.87 mm) is stronger than that in neutral environment (10.48-12.08 mm). To sum up, the structure of polysaccharide from S. platensis will change in acidic environment, and it has good antioxidant and antibacterial properties.

A Novel Seat Cushion Cell Structure for Vibration Isolation

Vehicle seat vibrations significantly affect driver and passenger comfort. This study proposes a 3D-printed seat cushion incorporating a double-diamond cell structure designed for low-frequency vibration isolation. Characterized by quasi-zero stiffness (QZS), this structure was analyzed through analytical and simulation approaches to determine its vibration transmissibility. A machine learning-based response surface method enabled performance prediction and sensitivity analysis of key design parameters, revealing that link element length and spring stiffness most influence peak transmissibility. Unlike previous seat suspension designs focusing on X-shaped suspension supports, this approach provides an efficient means of optimizing the seat cushion’s vibration isolation performance without extensive simulations or complex analytical solutions.

Comparative Analysis of pK a Predictions for Arsonic Acids Using Density Functional Theory-Based and Machine Learning Approaches.

Arsonic acids (RAsO(OH)2), prevalent in contaminated food, water, air, and soil, pose significant environmental and health risks due to their variable ionization states, which influence key properties such as lipophilicity, solubility, and membrane permeability. Accurate pK a prediction for these compounds is critical yet challenging, as existing models often exhibit limitations across diverse chemical spaces. This study presents a comparative analysis of pK a predictions for arsonic acids using a support vector machine-based machine learning (ML) approach and three density functional theory (DFT)-based models. The DFT models evaluated include correlations to the maximum surface electrostatic potential (V S,max), atomic charges derived from a solvation model (solvation model based on density), and a scaled solvent-accessible surface method. Results indicate that the scaled solvent-accessible surface approach yielded high mean unsigned errors, rendering it less effective. In contrast, the atomic charge-based method on the conjugated arsonate base provided the most accurate predictions. The ML-based approach demonstrated strong predictive performance, suggesting its potential utility in broader chemical spaces. The obtained values for pK a from V S,max show a weak prediction level, because the way of predicting pK a is related only to the electrostatic character of the molecule. However, pK a is influenced by many factors, including the molecular structure, solvation, resonance, inductive effects, and local atomic environments. V S,max cannot fully capture these different interactions, as it gives a simplistic view of the overall molecular potential field.

Estimating Cotton Yield Response Surface to Planting and Harvest Dates in Arkansas

Knowledge of anticipated long-run yield penalties over a range of planting and harvest time periods is necessary to formulate whole-farm planning models. Until now, gaps existed for several cotton (Gossypium hirsutum L.) planting-by-harvest-date combinations. Publicly available data from the Arkansas Cotton Research Verification and Sustainability Program deemed suitable for this research included 169 fields from 19 years and 22 counties. Given several relevant plant and harvest weeks had no observations, a response surface was estimated. Results indicated that planting during weeks 18 to 20 minimized yield penalties, but only when harvested in corresponding best weeks. Likewise, yield penalties can be avoided if harvested during weeks 40 to 43, but only when planted in respective best weeks. Ten planting-by-harvest-week combinations were associated with at least 98% attainable yield. Fields planted and harvested outside these 10 weeks were susceptible to yield penalties. Penalties during weeks adjacent to optimal combinations tended to be minor, usually less than 5% deviations, but more severe further from the top of the response surface. Fields planted during week 22 and harvested in week 42 expected 21% yield penalty. Current Extension recommendations based on heuristics were validated from these estimates. Results are of interest to equipment manufacturers, agricultural engineers developing machinery, agricultural lenders assessing the risk of equipment loans, farmers considering optimal equipment capacity for acreage, and farm management economists estimating whole-farm profitability. Response surface methods are useful to estimate yield penalties for planting and harvest date combinations via field-scale observations.

Implementation of ANN and response surface method for dual-fuel CI engine optimization and prediction using water infusion and biofuel

Implementation of ANN and response surface method for dual-fuel CI engine optimization and prediction using water infusion and biofuel

Research on bioaugmented slurry remediation of PAHs in actual contaminated soil: Screening microbial agents and optimizing key parameters.

Bioaugmented slurry technology is a sustainable remediation technology for PAHs-contaminated soil. However, the lack of experimental data on the remediation of complex, actual contaminated soils has hindered the practical application of this technology. This study explored the bioaugmented degradation of PAHs using actual soil slurry with and without the addition of microbial agents in the microscopic world. NS4 has the highest degradation efficiency. The response surface method was used to determine the effects of water-soil ratio, temperature, aeration rate and their interaction on the degradation of PAHs. Temperature significantly affects the degradation of phenanthrene, and the aeration rate significantly affects the degradation of pyrene. The influence of each factor follows the order: aeration rate>temperature>water-soil ratio. The highest degradation rates of phenanthrene and pyrene are observed at a water-soil ratio of 3:1, a temperature of 30°C, and an aeration rate of 2L/min. Under the optimal conditions, the addition of either peptone or Tween-80 increased the degradation rate. Peptone and Tween-80 can effectively enhance the growth rate of microorganisms and the release of PAHs in actual contaminated soil. In conclusion, by screening microbial agents suitable for real contaminated soils and maintaining the dynamic stability of the bioaugmented slurry system by optimizing key influencing factors, efficient, green, and low-energy remediation of PAHs-contaminated sites can be achieved.

Drop Dynamics during Condensation on Superhydrophobic Surfaces in Vapor Shear Flow.

Accurate models for predicting drop dynamics, such as maximum drop departure sizes, are crucial for estimating heat transfer rates during condensation on superhydrophobic (SH) surfaces. Previous studies have focused on examining the heat transfer rates for SH surfaces under the influence of gravity or vapor flowing over the surface. This study investigates the impact of surface solid fraction and texture scale on drop mobility in a condensing environment with a humid air flow. Experiments recorded condensation with varying surface feature sizes from micro- to nano scale under different flow rates. Video analysis detected the drop-size distribution and maximum drop departure sizes. Particle image velocimetry (PIV) provided accurate shear force representations. Results showed that the maximum drop departure sizes decreased with lower surface solid fractions and higher flow rates. A force balance analysis revealed that coalescence-induced drop jumping aids drop departure. Different drop behaviors due to coalescence were linked to surface characteristics. The study quantified drop jump distances under shear force during condensation on SH surfaces, and found that jump distances increased when coalescing drop sizes were similar. Based on these findings, a method for tuning SH surfaces to control drop size at coalescence and departure was suggested. Drop mobility was measured in terms of Bond and Capillary numbers, showing a dependence on surface solid fraction and pitch size. By combining these into surface slip length, it was shown that drop mobility increases with increasing slip length.

Computational-Fluid-Dynamics-Based Optimization of Wavy-Slit Fin Geometry in Indoor Units of Air Conditioners Using Low-Global-Warming-Potential Refrigerants

This study explores the optimization of wavy-slit fins in the indoor units of air conditioners that use low-global-warming-potential refrigerants, with a focus on the interactions between slit length, width, and height. A response surface method was employed to analyze the trade-offs between thermal performance and pressure loss, and numerical optimization was performed using two objective functions: pumping power and volume goodness factor (Gv). The results demonstrated that optimizing the slits’ geometry significantly enhanced overall performance. For pumping power, a minimum point was observed near the design boundaries, which underscores the critical role of geometric interactions. The flow and temperature field analysis under fixed heat-duty conditions revealed substantial flow separation caused by the slits, enhanced mixing between the upper and lower surfaces, and a reduction of up to 2.05% in pumping power. In contrast, the Gv optimization model exhibited a more uniform flow, reducing flow separation beyond the pipe and improving the Gv by 1.85%, although it led to an increase in pumping power. These findings highlight the potential that tailored slit fin designs have to achieve a balanced enhancement in heat transfer and aerodynamic performance, offering valuable insights for the development of efficient, low-environmental-impact air conditioning systems.

Optimization of fermentation conditions to increase the production of antifungal metabolites from Streptomyces sp. KN37

The bacterium Streptomyces sp. KN37 was isolated from the soil of Kanas, Xinjiang. The broth dilution of strain KN37 has a strong inhibitory effect against a variety of crop pathogenic fungi. However, in practical applications, its effective biological activity is limited by medium formulations and fermentation conditions. In this study, we used the response surface method to optimize the fermentation medium and conditions of the strain KN37, for investigating the reasons for the enhanced biological activity at both the metabolic and transcriptomic levels. The results of the Plackett-Burman design showed that millet, yeast extract, and K2HPO4 were the key factors influencing its antifungal activity. Subsequently, optimization by the response surface methodology yielded the final fermentation conditions as: millet 20 g/L, yeast extract 1 g/L, K2HPO4 0.5 g/L, rotation speed 150 r/min, temperature 25 °C, initial pH 8, fermentation time 9 d, inoculation amount 4%, liquid volume 100 mL. The antifungal effect of the optimized strain fermentation dilution was significantly enhanced, and the antifungal rate of R. solani increased from 27.33 to 59.53%, closely aligning with the predicted value of 53.03%. The results of HPLC-MS/MS and transcriptomic analysis revealed that the content of some secondary metabolic active substances in the fermentation broth of KN37 was significantly different from that of the original fermentation broth. Notably, the content of 4- (diethylamino) salicylaldehyde (DSA) was significantly increased by 16.28-fold while the yield of N- (2,4-dimethylphenyl) formamide (NDMPF) was increased by 6.35 times. Transcriptomic analysis further elucidated molecular mechanisms behind these changes with the expression of salicylic acid dehydrogenase (SALD) was significantly down-regulated, which was only 0.48 times compared to that before optimization. This research successfully optimized the fermentation process of strain KN37 providing a strong foundation for the actual production and application of strain KN37 in agriculture.

Simultaneous Optimization of Hydrogen Network with Pressure Swing Absorption Based on Evolutionary Response Surface Method

The simultaneous optimization of complex process units and hydrogen networks is a significant challenge in refinery hydrogen network integration. To address this, an evolutionary response surface-based collaborative optimization method is proposed, enabling the concurrent optimization of pressure swing adsorption (PSA) and the hydrogen network. This method develops a mechanistic model for PSA and alternates between random sampling and evolutionary response surface-based hydrogen network optimization to obtain diverse sampling points and potential optimal solutions. The PSA mechanistic model is then used to compute the accurate output parameters for the sampled points, and these parameters are incorporated into the hydrogen network optimization to obtain precise objective function values. An efficient optimization framework is presented to streamline the process. The proposed method is applied to a refinery hydrogen network integration case study, comprehensively considering both PSA costs and hydrogen utility costs. The results demonstrate that the method is computationally efficient and effectively reduces the refinery’s total annual costs. The accuracy of the optimization results is significantly improved compared to traditional methods, providing an effective solution for the collaborative optimization of the refinery hydrogen network and PSA.

Tracing magnetic switchbacks to their source: An assessment of solar coronal jets as switchback precursors

The origin of large-amplitude magnetic field deflections in the solar wind, known as magnetic switchbacks, is still under debate. These structures, which are ubiquitous in the in situ observations made by Parker Solar Probe (PSP), likely have their seed in the lower solar corona, where small-scale energetic events driven by magnetic reconnection could provide conditions ripe for either direct or indirect generation. We investigated potential links between in situ measurements of switchbacks and eruptions originating from the clusters of small-scale solar coronal loops known as coronal bright points to establish whether these eruptions act as precursors to switchbacks. We traced solar wind switchbacks from PSP back to their source regions using the ballistic back-mapping and potential field source surface methods, and analyzed the influence of the source surface height and solar wind propagation velocity on magnetic connectivity. Using extreme ultraviolet images, we combined automated and visual approaches to identify small-scale eruptions (e.g., jets) in the source regions. The jet occurrence rate was then compared with the rate of switchbacks captured by PSP. We find that the source region connected to the spacecraft varies significantly depending on the source surface height, which exceeds the expected dependence on the solar cycle and cannot be detected via polarity checks. For two corotation periods that are straightforwardly connected, we find a matching level of activity (jets and switchbacks), which is characterized by the hourly rate of events and depends on the size of the region connected to PSP. However, no correlation is found between the two time series of hourly event rates. Modeling constraints and the event selection may be the main limitations in the investigation of a possible correlation. Evolutionary phenomena occurring during the solar wind propagation may also influence our results. These results do not allow us to conclude that the jets are the main switchback precursors, nor do they rule out this hypothesis. They may also indicate that a wider range of dynamical phenomena are the precursors of switchbacks.

Chemometric tools to comprehend a recovery process for the bioactive ingredients from purple basil (Ocimum basilicum L.): Box-Behnken design-based optimization and principal component analysis.

Medicinal and aromatic plants are alternative products to synthetics because of their antioxidant, antimicrobial, anti-inflammatory and antidiabetic effects. The objective of this study is to investigate the automated solvent extraction (ASE) process parameters for the extraction of bioactive-rich substances from purple basil (Ocimum basilicum L.). Process optimization in relation to total phenolic content (TPC), total flavonoid content (TFC), and total anthocyanin content (TAC) was performed through a chemometric approach. The ASE system was designed, modelled and optimized by 3-factor and 3-level Box-Behnken design of Response Surface method (RSM). Antioxidant activity of the samples were measured by 2 different free radical scavenging activity assays (ABTS and DPPH). By using principal component analysis (PCA) to the dataset, the impact of interactions between the parameters was also evaluated according to their antioxidant activity, TPC, TFC and TAC levels. The optimal ASE conditions (0.3 g of purple basil, 19 min of immersion time and 66 % ethanol solution) provided the highest yields of TPC (98.888 mg-GAE/g-DM), TFC (27.033 mg-CE/g-DM) and TAC (11.556 mg-C3G/g-DM), which were verified by satisfactory validation findings (the error<2 %).

Simulation of temperature field and optimisation of high-temperature parts for a giant mine tire

The temperature field of tires has a significant impact on the cracking aging and service life of tires. Therefore, the finite element simulations of the temperature field of the mining tire were carried out in this paper. The temperatures of the key parts of the tire were measured with the thermocouple under real working conditions. The deviation between the results of the simulation and the measurement is 1.3%. In addition, the function among the maximum temperature, the velocity and sinking amount of the tire was fitted using the simulating results of the temperature field under the nine types of working conditions. Further, based on the response surface method, the structure of the 1# strap layer with high temperature of the tire was optimised by taking the width of the strap layer, the distribution density of the steel wire and the angle of the steel wire arrangement as the independent variables, and the maximum temperature of the tire under steady rolling as the response value. Finally, the results show that the maximum temperature of the optimised model decreases by 3.06 °C compared to the original model.

Design and study of moving-iron torque motor for two-dimensional proportional servo valve

This paper proposes a novel moving-iron torque motor designed for two-dimensional (2D) valves. The torque motor features a strap spring in place of the traditional return spring, effectively reducing the overall number of springs. The unique design allows the torque motor to return to its circumferential neutral position through the return torque generated by the strap spring. In order to analyze the torque-displacement characteristics of the torque motor, an analytical model is established, and a simulation model is constructed based on the equivalent magnetic circuit method, which takes into account the magnetic leakage at the control coil and the working air gap. In order to select a strap spring that matches the stiffness of the magnetic spring of the torque motor, the structural parameters of the spring are optimized using the response surface method with multi-objective optimization, and finally three springs with different stiffnesses are manufactured according to the optimization results. The experimental results show that the maximum step-up time of the torque motor is 20.6 ms, the maximum step-down time is 21.6 ms, the maximum hysteresis loop is 12.5%, and the maximum linearity is 20%. In order to improve the −3dB cut-off frequency of the torque motor, this paper adopts the current closed-loop control method, and increases the maximum cut-off frequency not exceeding 25 Hz in the open-loop mode to 110 Hz.The hysteresis loop and linearity of the torque motor decrease with the increase of the spring stiffness. The amplitude frequency −3dB cutoff frequency increases with increasing spring stiffness.

Experimental study of parameters in micro-photochemical machining using maskless digital projection on flat surfaces of 100Cr6 steel

Photochemical machining (PCM) is a chemical etching process, in which a photoresist agent is used to cover parts of the workpiece that need to be protected from etching. In this study, the main goal is to create a groove on the flat surface of a workpiece made of 100Cr6 steel using the PCM process and to investigate different variables on the dimensional and geometrical accuracy of the groove. The experiments were designed using the response surface method with a central composite methodology, involving 20 experiments and three repetitions. In this study, the effects of different variables such as time of etching, the concentration of ferric chloride (FeCl3) in the etchant solution, and the weight ratio of hydrochloric acid (HCl) to FeCl3 in the etchant solution were investigated on dimensional accuracy such as length and width error and also geometrical accuracy such as out of parallelism, out of squareness, and out of straightness. Results indicate that as the etching duration increases, the length, width, out of straightness, out of parallelism, and out of squareness also increase. This error becomes substantial with longer durations. Also, with an increase in FeCl3 concentration in etchant solution, errors in length and width, out of straightness, out of parallelism, and out of squareness reduce. The optimal variables resulting in the least possible errors were an etching duration of 10.72 minutes (10 minutes and 43 seconds), FeCl3 solution concentration of 599.64 g/L, and a weight ratio of HCl to FeCl3 in the etchant solution of 0.1. The following results on the flat surface were obtained: groove length: 3,056 µm, groove width: 625 µm, groove depth: 48 µm, and surface roughness (Ra): 1.285 µm.