Parameter Optimization Analysis Research Articles

Chemical Looping Enhanced Oil Shale-to-Liquid Fuels Process: Modeling, Parameter Optimization, and Performance Analysis

The solid heat carrier moving bed with internals is an advanced oil shale retorting technology. However, the retorting gas produced by pyrolysis is generally used as fuel gas. The content of CO, H2, and CH4 in the retorting gas is high, and direct combustion leads to resource waste and environmental pollution. In addition, heteroatomic sulfur and nitrogen, as well as unsaturated hydrocarbons, reduce the quality of shale oil. To solve these problems, this paper proposed a chemical looping enhanced oil shale-to-liquid fuels (CLeSTL) process. The chemical looping hydrogen production technology is applied to convert retorting gas to hydrogen, and the hydrogen produced is used for shale oil hydrogenation to improve the oil quality. In this paper, the new process is modeled and simulated; then technoeconomic analysis is carried out. Technical analysis shows that shale oil yield is increased from 65% to 95.7% and the yield of light fraction is increased from 20% to 64%–83%. Economic analysis shows that the CLeSTL process with ligh fraction hydrogenation has the highest investment profit rate and large profit space. In addition, when the oil price is lower than 50 USD/bbl, the investment profit is 5%, which shows strong anti-risk ability.

Efficient large-scale mechanism-based computation of skin permeability

A drug’s skin permeability is a key quantity within dermatological risk assessment as it quantifies the maximal rate of dermal absorption, under steady state conditions, per unit concentration difference across the skin of a topically applied drug. Given descriptors of the permeant, the vehicle, and skin conditions, this paper adopts a systematic approach to efficiently calculate estimates of a topically applied chemical’s skin permeability based on mechanistic knowledge of permeability across the elements of a fine spatial discretization of the dermal strata. The permeability estimates are obtained by solving a system of linear equations constructed using an electrical resistor network analogy. Being mechanism based, these estimates can account for skin conditions, heterogenous dermal penetration pathways, and the chemical-dependence and spatial dependence of partitioning and diffusivity.The contribution of this work can be viewed as a mechanistic, numerical, extension of the Potts-Guy relation that augments an open-source dermal PBPK model. Moreover, rather than requiring model simulations of steady state conditions, the approach centers on a direct calculation of permeability based on the mechanistic descriptors of the permeation scenario. The calculation method may therefore be directly integrated into parameter identification, optimization, and sensitivity analysis algorithms. We demonstrate the validity of the method by comparing its permeability predictions with previously reported in silico estimates and in vitro measurements. We additionally illustrate the utility of the method towards the analysis of dermal PBPK models using a minimal example that relates overall skin permeability to the interaction between multiple permeation pathways.

Parametric Optimization and Numerical Analysis of GaAs Inspired Highly Efficient I-Shaped Metamaterial Solar Absorber Design for Visible and Infrared Regions

Renewable energy demand is increasing as fossil fuels are limited and pollute the environment. The solar absorber is an efficient renewable energy source that converts solar radiation into heat energy. We have proposed a gallium arsenide-backed solar absorber design made with a metamaterial resonator and SiO2 substrate. The metamaterial resonator is investigated with thin wire metamaterial and I-shaped metamaterial designs. The I-shape metamaterial design outperforms the thin wire metamaterial design and gives 96% average absorption with a peak absorption of 99.95%. Structure optimization is applied in this research paper using parametric optimization. Nonlinear parametric optimization is used because of the nonlinear system results. The optimization method is used to optimize the design and improve the efficiency of the solar absorber. The gallium arsenide and silicon dioxide thicknesses are modified to see how they affect the absorption response of the solar absorber design. The optimized parameter values for SiO2 and GaAs thicknesses are 2500 nm and 1000 nm, respectively. The effect of the change in angles is also investigated in this research. The absorption is high for such a wide angle of incidence. The angle of 30° only shows a lower absorption of about 30–50%. The effect of the change in angles is also investigated in this research. The design results are verified by presenting the E-field results for different wavelengths. The optimized solar absorber design applies to renewable energy applications.

Coordinated DC Interruption Method Based on Magnetic Coupling Current-Limiting and Dissipation

A flexible dc grid is important for supporting large-scale new energy integrations. To ensure the stable operation of the dc grid, a dc circuit breaker (DCCB) is needed for fault isolation. At present, the cost of DCCBs is high, and the breaking capacity is limited. This limitation can be effectively solved through the coordination of fault current limiters (FCLs) and DCCBs. In this article, a coordinated interruption topology of an magnetic coupling FCL (MCFCL) and hybrid DCCB is proposed. A coordinated interruption strategy based on magnetic coupling current-limiting and energy dissipation is proposed to improve the dynamic performance of the FCL and reduce the energy dissipation and breaking time of the DCCB. A two-stage mathematical model of coordinated interruption is established, and its control principle is analyzed. Furthermore, the influence of the inductance and resistance of the MCFCL secondary side, coupling coefficient and rated voltage of the arrester on the coordinated interrupting process is researched. On this basis, parameter optimization and economic analysis are carried out. Finally, a scaled test for the coordinated interruption of the DCCB and MCFCL was carried out, which verifies the feasibility of the coordinated interruption strategy based on magnetic coupling current-limiting and energy dissipation.

Parametric optimization and wear analysis of AISI D2 steel components

AISI D2 steel is widely used for forming die or cold stamping, chipper knives, shear blade, trimming cutter threading dies, punches and stamping tools etc. Hence, the current investigation aim is to determine the effects of sliding parameters on the wear performance of AISI D2 steel. The experiments were conducted on AISI D2 steel pin and disk of mild steel using the pin-on-disk apparatus. After that, relationships for forecasting weight loss of pins due to rubbing action have been developed using the design of experiment (DOE), which is based on response surface methodology (RSM) and has three independent parameters (slide duration, normal load, and sliding speed). ANOVA was used to perform the model adequacy tests, and the results of various parameters were computed and displayed in 3D surface graphs and contour plots. To reduce the weight loss, numerical optimization has been done while keeping all of the input parameters within range (wear volume). The manufacturing sector that uses AISI D2 steel for deforming dies would benefit from the study's findings.

Rheological Test of Flowability and Diffusion Behavior of Carbon Fibre Reinforced Polyamide

Various materials have been produced to be used as feeder material in 3D printing application to obtain the level of mechanical properties and physical properties of a product. Before to its usage as a 3D printing feed material, polyamide-reinforced carbon fibre composites were investigated for flowability and diffusion behaviour. Using a heated nozzle to transform polymer filament into a semi-liquid that is extruded to create a structure layer-by-layer, the primary issue to prevent is delamination. For the success of this study, there are 2 main methods, namely to study the physical properties of carbon fibre reinforced polyamide composites against the composition of 20 wt.% carbon fibre and to study the temperature and rheological load on the rheological properties. Rheological test analysis found that the material flowability of 20 wt.% CF/PA at temperature parameters 210 °C, 230 °C and 250 °C against rheological loads (40, 60, 80) N recorded a range of viscosity values between 48.80 Pa.s to 97.88 Pa.s and shear rate value range between 19700 s<sup>-1</sup> to 20270 s<sup>-1</sup>. Parameter optimization analysis using Taguchi method found that the largest factor contributing to the viscosity of CF/PA composite feed material was the addition of load applied. Moreover, the microstructural results of CF/PA composites show that smoother surfaces and good polymer structural bonding occur at an extrusion temperature of 250 °C. As a result, the rheology-derived flow rate may be used to tackle the problem of delamination and layer separation in 3D printing.

A unified method for parameter optimization and dynamic characteristics analysis of tuned mass damper inerter

To enhance the performance of the tuned mass damper (TMD), an inerter has recently been incorporated into a conventional TMD system to constitute a new type of an inerter-based passive control system, namely, tuned mass damper inerter (TMDI). The present study proposes a unified design idea for the TMDI based on the Kramers–Kronig relations in the complex effective mass. The TMDI is equivalent to a combination of a static mass and a conventional TMD, and the theoretical links between the TMDI and conventional TMD have been established. Based on the proposed method, the performance of the TMDI is investigated combined with the existing dynamic characteristics of the conventional TMD. It is concluded that the proposed design idea is feasible, and the previously reported dynamic characteristics of the TMDI can be well demonstrated. Moreover, the mass ratio of the equivalent TMD can be used to compare the control performance of the TMDI and TMD, and when it is larger than the physical mass ratio, the inerter enhances the control performance of the TMD.

Taguchi Parametric Optimization and Cost Analysis of Hexavalent Chromium Sequestration From Aqueous Solution by NaOH-Modified Garcinia kola Hull Particles.

The presence of chromium in industrial wastewater is unavoidable due to its large usage as part of chemical constituents used in many industries. Its removal from wastewater is imperative because it's toxic in nature. This study investigated the application of NaOH-modified Garcinia kola hull particles (cMGK-HP) for Cr(VI) sequestration from aqueous solution. The optimization of process parameters was executed using Taguchi of Design Expert software for optimum point prediction, analysis of variance, parameters interaction and mathematical model development. A proposed model was used for the adsorption cost analysis. The predicted and experimental percentage of Cr(VI) sequestration were recorded at optimum point to be 99.02% and 98.76% with pH, adsorbent dose, contact time, initial concentration, and temperature of 2, 8 g/L, 20 minutes, 10 mg/L, and 20°C respectively. A correlation coefficient of .9937 between experimental and predicted values of percentage Cr(VI) sequestration affirmed high efficacy of the developed model. ANOVA showed the order of parameter contribution to be pH > adsorbent dose > initial concentration > contact time > temperature. A maximum adsorption capacity of 217.39 mg g-1 was obtained for cMGK-HP. Cost analysis revealed using cMGK-HP to be cost effective for Cr(VI) sequestration with a total operational cost of 0.824 $/mole Cr(VI) ions when compared with commercial activated carbon. Adsorbent characterization revealed the presence of active functional groups enhancing the sequestration process. It could be deduced that cMGK-HP is effective to remove Cr(VI) from solution.

Retracted: Parameter Optimization and Performance Analysis of Composite Substance That Can Prevent Burning Based on Machine Learning

Retracted: Parameter Optimization and Performance Analysis of Composite Substance That Can Prevent Burning Based on Machine Learning

Retracted] Parameter Optimization and Performance Analysis of Composite Substance That Can Prevent Burning Based on Machine Learning

In the past 30 years, a substance that can prevent burning has played an important role in reducing the loss of life and property caused by fire. At present, the total amount of antibaking agent is second only to plasticizer and various plastic additives in the world. With an average annual growth rate of 0.5% from 2019 to 2021. The fire protection industry is a regulatory industry and a globally competitive industry. Therefore, the entry into force and gradual improvement of relevant laws and regulations at home and abroad will affect the pattern of the whole fire protection industry. China’s “Twelfth Five‐Year Plan” will bring a substance that can prevent burning into key development industries and form a strategic alliance for technological innovation of green substance that can prevent burning industries. It provides a policy platform for the development of a substance that can prevent burning in industry. Firstly, we introduce several common a substance that can prevent burnings, then we use machine learning method to establish prediction model and to analyze the performance of composite combustibles. And draw the conclusion: composite material is better than the other two composites; among the six machine learning algorithms, the gradient boosting regression (GBR) model has the best prediction ability, followed by the extra tree regressor (ETR) model and the random forest regressor (RFR) model. Compared with the above three integrated algorithms, Ridge, Ada Boost regressor (ABR), and Lasso regression algorithms have relatively poor prediction results.

Parametric optimization and structural feature analysis of humic acid extraction from lignite

Humic acid (HA) is a complex organic compound made up of small molecules. A variety of raw materials are used to manufacture HA, due to which the structure and composition of HA vary widely. In this study, nitric acid oxidation of two coal samples from Lakhra (Pakistan) was followed by HA extraction using 2.5, 3.0 and 3.5% KOH solutions. The impact of different operating parameters such as; the effect of KOH concentrations, KOH-coal proportion, extraction time and pH range influencing the HA extraction efficiency was optimally investigated. Commercial HA applications possess numerous challenges, including valuable applications and sub-optimal extraction techniques. A significant limitation of conventional experimental methods is that they can only investigate one component at a time. It is necessary to improve the current processing conditions, this can only be achieved by modelling and optimization of the process conditions to meet market demands. A comprehensive evaluation and prediction of HA extraction using Response Surface Methodology (RSM) are also being reported for the first time in this study. The maximum HA extraction efficiency of 89.32% and 87.04% for coal samples 1 and 2 respectively was achieved with the lowest possible pH of 1.09 (coal sample 1) and 1(coal sample 2), which is remarkably lower as compared to those reported in the literature for conventional alkaline extraction process. The model was evaluated for two coal samples through the coefficient of determination (R2), Root Means Square Error (RMSE), and Mean Average Error (MEE). The results of RSM for coal sample 1 (R2 = 0.9795, RMSE = 4.784) and coal sample 2 (R2 = 0.9758, RMSE = 4.907) showed that the model is well suited for HA extraction efficiency predictions. The derived humic acid from lignite coal was analyzed using elemental analysis, UV–Visible spectrophotometry and Fourier-transformed infrared (FTIR) spectroscopy techniques. Scanning Electron Microscopy (SEM) was applied to analyze the morphological modifications of the extracted HA after treatment with 3.5% KOH solution. For agricultural objectives, such as soil enrichment, enhancing plant growth conditions, and creating green energy solutions, this acquired HA can be made bioactive. This study not only establishes a basis for research into the optimized extraction of HA from lignite coal, but it also creates a new avenue for the efficient and clean use of lignite.

Drying characteristics, quality changes, parameters optimization and flavor analysis for microwave vacuum drying of garlic (Allium sativum L.) slices

The influence factors such as microwave power, vacuum degree and temperature were investigated using the color L*, thiosulfinate content, rehydration ratio and comprehensive score of garlic slices as responses. The microwave vacuum drying (MVD) parameters of garlic slices were optimized by response surface methodology. The electronic nose was used to compare the flavor differences between fresh garlic and dried garlic slices. The results showed that the drying curve and rate curve of MVD garlics accorded with the drying characteristics of foods, the optimum MVD conditions of garlic slices were microwave power 260 W, vacuum degree 81 kPa, and temperature 49.5 °C. Under these conditions, the color L*, the thiosulfinate content, the rehydration ratio and the comprehensive score of garlic slices were 82.26, 3.0378 mg/100 g, 2.796 and 0.9265, respectively. The principal component analysis results of electronic nose demonstrated that there was no difference in the composition between the dried garlic slices and fresh garlic, while the linear discriminant analysis of electronic nose could distinguish them. There was no significant difference in the volatile components of dried garlic slices under different drying conditions. Therefore, MVD process could be an effective drying method and quite suitable for garlic.

Parameter optimization and simulation analysis of floating root cutting mechanism for garlic harvester

Root cutting is an essential step in the mechanized harvesting of garlic. A floating root cutting mechanism was developed to improve the root clearance rate and bulb damage rate for garlic harvesting. Mechanical models of bulb collision and root cutting were presented to theoretically analyze the forces on the bulb and root. Mathematical models of the root clearance rate and bulb damage rate were established to optimize the parameters of the floating root cutting mechanism. A rigid–flexible coupling simulation model of the garlic floating root cutting mechanism was built to clarify the dynamic characteristics of the floating root cutting process. An experimental system was developed to verify the performance of the floating root cutting mechanism. Analysis and experiment results showed that high-speed cutting was beneficial to an upright and efficient root cutting for unsupported roots; the collision damage of the bulb could be reduced by optimizing the conveying speed of garlic and the boundary dimension of the contact region of the root cutting mechanism; the optimal parameter combination was a conveying speed of clamping chain of 0.8 m/s, rotational speed of cutter group of 1450 rpm, cutter plane angle of 30°, and protective grid pitch of 35 mm; an unsupported root cutting of garlic could be realized at a rotational speed of cutter group of 1450 rpm, with a minimum distance between fracture point of root and root disc of 3 mm, and maximum deviation distance of root mass center of 48.48 mm, meeting the requirements of garlic root cutting quality. This study provides a theoretical and simulation model reference for the design, analysis and optimization of the floating root cutting mechanism for garlic harvester.

Parameter optimization and quality analysis of pulsed laser joining of 316L stainless steel and polylactic acid

To realize the joining of dissimilar material 316L stainless steel with polylactic acid (PLA), the laser-assisted metal-plastic direct joining (LAMP) method was applied, and the process parameters were optimized based on the method of orthogonal experiment, and the quality of the joint was studied. The influence law of each influencing factor of the joining process on the joint quality and joint morphology was obtained through orthogonal experiments, to find out the maximum influencing factor and obtain the optimal process combination. By a universal tensile testing machine to find out the influence of the process parameters on the joint failure modes. The results showed that the laser power, pulse duty ratio, and laser speed had a major influence on the shear force, elongation at break and joint width. The maximum shear force achieved by the optimized method was 1694.379 N, reaching 88.73 % of the tensile force of the PLA base material, and the elongation at break was 5.47 %, reaching 76.91 % of the base material, obtained a more satisfactory joint effect. The correspondence between five joint morphologies and four failure modes is established, and different process parameters can be selected according to different applications of 316L stainless steel-PLA composite materials, to optimize industrial manufacturing.

Print parameter optimization and mechanical deformation analysis of alumina-nanoparticle doped photocurable nanocomposites fabricated using vat-photopolymerization based additive technology

As the recent trend of fabricating high-strength polymer has been gaining more attention in the market, researchers are exploring the possibility of using a 3D printing technique for the same. Vat-photopolymerization additive technology has good process capability and produces high-quality photopolymer parts with greater geometrical complexity. This paper proposes the vat-photopolymerization process to fabricate high-strength acrylate-based photopolymer composite with improved mechanical strength. The composite structures contain 1.0, 2.0, and 3.0 wt percentages of 13 nm average-sized alumina (Al2O3) nanoparticle (NP) as the reinforcement and acrylate photopolymer as matrix material. The viscosities of all the prepared suspensions were measured to determine the printing properties of the prepared nanocomposites, and these values are within the feasible printing limit. Furthermore, the depth of cure and time of exposure to UV light were optimized to achieve the desired level of printing performance. The thermogravimetric analysis (TGA) of the alumina nanocomposites reveals that the addition of alumina NP has minimal influence on the thermal stability of the photopolymer matrix. To ascertain the mechanical strength of the 3D printed products, tensile tests are performed, and it was witnessed that 1.0% weight fraction of alumina-NP loaded specimen experienced the highest tensile strength amongst all the weight fractions of alumina-NP considered, and its value increased by ∼48% when compared against the pure acrylate polymer sample. The increase in strength values for the alumina-NP loaded specimen was explained using dynamic mechanical analysis and optical and scanning electron micrographs. A constitutive elastic-viscoplastic isothermal non-linear time-dependent material model is also developed to predict the post-yield strain-softening behavior of these nanocomposites. The weight fraction and optimal weight fraction of alumina nanoparticles are correlated using semi-empirical equations of various model parameters.

Entropy analysis and parametric optimization on the Nano fluid flow and heat transfer of a pin-fin heatsink with the splitter using the two-phase mixture model

The nanofluid (NF) flow rate and concentration (φ) in a pin-fin heat sink with the splitter (WS) were numerically investigated and the optimum Re and φ values were determined by applying a parametric optimization analysis on the thermal and frictional entropy generation rates (S˙th and S˙fr). To this end, the discretization of the governing equation was done by the second-order upwind scheme, the finite volume method. The results were compared with those obtained for the pin-fin heatsink without the splitter (WOS). Based on the findings, the intensification of Re and φ reduces S˙th by almost 43-45% and 10-13%, respectively, for both WS and WOS heatsinks. An insignificant difference between S˙th of two configurations was obtained (0.37-2.93%). Although S˙fr diminishes by 12% as φ intensifies from 0 to 1%, the escalation of Re from 500 to 2000 intensifies S˙fr by 2312% and 4618% in WS and WOS heatsinks, respectively. In addition, S˙fr of WS heatsink is nearly 43-48% lower than that WOS heatsink due to using splitters. The absence of the splitter in the WOS heatsink leads to a delay in flow separation from the pin-fin bodies and deteriorates the heat dissipation, thereby increasing the CPU temperature and S˙fr intensification.

Bench Test and Analysis of Cleaning Parameter Optimization of 4 L-2.5 Wheat Combine Harvester

Inaccurate and untimely adjustments of cleaning parameters during the operation of wheat combine harvesters lead to high cleaning losses and impurity rates. For this reason, a self-made 4 L-2.5 threshing and cleaning experiment table was employed for cleaning parameter optimization experiments for wheat combine harvesters in this paper. The influence of the cleaning parameters on the cleaning loss and impurity rates was analyzed, and the optimum combination of cleaning parameters was predicted and verified. The contribution hierarchy of cleaning parameters to cleaning loss rate is as follows: crank speed of shale shaker > opening of chaffer > operation speed > fan speed > throttle opening. Meanwhile, the contribution hierarchy of cleaning parameters to impurity rate is as follows: operation speed > fan speed > throttle opening > crank speed of shale shaker > opening of chaffer. The predicted optimum combination of cleaning parameters, i.e., when the cleaning loss and impurity rates are both at a minimum and the feed quantity is at the maximum, is as follows: operating speed—2.2 m/s; opening of chaffer—26 mm, throttle opening—20°; fan speed—1100 r/min; and Crank speed of shale shaker—350 r/min. With these settings, the cleaning loss rate was 1.5% and the impurity rate was 1.9%. In the validation experiment, the average cleaning loss rate was found to be 1.47%, the average impurity rate was 1.96%, and the relative error of the predicted values was 0.03% and 0.06%, respectively. Compared with the cleaning index of combine harvesters with commonly used parameters, the cleaning loss rate was reduced by 0.12% and the impurity rate was reduced by 0.19%.

A new scheme for ammonia and fertilizer generation by coal direct chemical looping hydrogen process: Concept design, parameter optimization, and performance analysis

Ammonia is a very important chemical industry product. It has a wide range of applications in refrigeration, energy, and fertilizers , and 80% of ammonia is used as a nitrogen fertilizer. China mainly produces ammonia and urea from coal gasification , which leads to difficult CO 2 capture and high energy consumption. This study proposed a new process for the production of ammonia and urea by coal direct chemical looping hydrogen production process (CDCLTU). The coal direct chemical looping hydrogen production replaces the air separation unit and water gas conversion unit of the traditional coal-to-urea process (CTU), which effectively separates and captures CO 2 and significantly reduces the energy consumption. A model of the CDCLTU was established using Aspen Plus. Parameter optimization, technoeconomic, and environmental analysis were conducted through simulations. The results showed that CDCLTU could completely replace the air separation system that the CTU relies on. Compared with the traditional process, the utilization rate of C increased from 53.46% to 67.95% in the new process. The energy consumption of CO 2 separation and capture was reduced by 97.04%. The CDCLH had a 79.7% energy efficiency in the hydrogen production process and 99% capture rate of CO 2 . The total capital investment was dropped by 41%, unit urea production cost dropped by 12.1%, and the payback period dropped from 7.5 to 3.5 years. This paper provides a new direction for clean and efficient utilization of coal resources. • Proposed a novel coal-to-urea process by chemical looping technology. • Conducted main parameters optimization and performance analysis for the new process. • The new process reduced 97.04% energy consumption of CO 2 separation and capture. • Production cost of the new process is 12.1% lower than that of the conventional process. • The new process achieved 67.95% C utilization rate and 1.39 t/t lower CO 2 emission.

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.

Simulation Analysis of Multi-Physical Field Coupling and Parameter Optimization of ECM Miniature Bearing Outer Ring Based on the Gas-Liquid Two-Phase Turbulent Flow Model.

Electrochemical machining (ECM) is an essential method for machining miniature bearing outer rings on the high-temperature-resistant nickel-based alloy GH4169. However, the influence of electrolyte temperature distribution and bubble rate distribution on electrolyte conductivity in the ECM area could not be fully considered, resulting in the simulation model not being able to accurately predict the machining accuracy of the outer ring of the miniature bearing, making it challenging to model and predict the optimal process parameters. In this paper, a multiphysics field coupled simulation model of electric, flow, and temperature fields during the ECM of the miniature bearing outer ring is established based on the gas–liquid two-phase turbulent flow model. The simulation analyzed the distribution of electrolyte temperature, bubble rate, flow rate, and current density in the machining area, and the profile change of the outer ring of the miniature bearing during the machining process. The analysis of variance and significance of machining voltage, electrolyte concentration, electrolyte inlet flow rate, and interaction on the mean error of the ECM miniature bearing outer rings was derived from the central composite design. The regression equation between the average error and the process parameters was established, and the optimal combination of process parameters for the average error was predicted, i.e., the minimum value of 0.014 mm could be achieved under the conditions of a machining voltage of 16.20 V, an electrolyte concentration of 9.29%, and an electrolyte inlet flow rate of 11.84 m/s. This is important to improve the machining accuracy of the outer ring of the ECM miniature bearing.