Optimal Parameter Combination Research Articles

In-depth research on fault diagnosis of turbine rotor utilizing NGSABO-optimized VMD and CNN-BiLSTM

Abstract To solve the problem of difficulty in extracting and identifying fault types during turbine rotor operation, a fault diagnosis method based on improved subtraction mean optimizer (NGSABO) algorithm to optimize variational mode decomposition (VMD) and CNN-BiLSTM neural network is proposed. Firstly, three improvements are made to the subtraction average optimizer algorithm. Secondly, the optimal VMD parameter combination of NGSABO adaptive selection mode decomposition number K and penalty factor is used to decompose the rotor fault signal, and the minimum sample entropy is used as the fitness function for feature extraction. Combining convolutional neural network and bidirectional long short-term memory network to identify and classify features. Compared with other methods, this method has outstanding performance in the diagnosis of single and coupled rotor faults. The accuracy of fault diagnosis reaches 98.5714%, which has good practical application value.

A novel bionic lotus leaf channel liquid cooling plate for enhanced thermal management of lithium-ion batteries

Battery Thermal Management Systems (BTMS) are pivotal in safeguarding the safety, efficiency, and lifespan of electric vehicles. In this study, we propose a bionic lotus leaf (BLL) channel liquid-cooled plate to mitigate temperature accumulation issues observed during lithium-ion battery (LIB) discharge. The primary objective is to enhance heat dissipation and achieve uniform temperature distribution within LIBs. We investigated the impact of different interior configurations and mass flow rates on individual lithium-ion battery (LIB) temperatures using single-variable analysis. Our findings indicate that higher inlet mass flow rates effectively lower the temperature increase in individual LIBs, albeit at the cost of inducing a significant pressure drop.The optimal parameter combination is determined through orthogonal analysis. Specifically, the channel angle (α) and inlet mass flow rate (M) are found to significantly influence the maximum temperature (Tmax) of LIBs. The number of channels (N) is optimized to enhance temperature distribution and reduce maximum temperature variation (ΔTmax) within LIBs. Furthermore, adjusting the channel width (D) substantially mitigated pressure drop (ΔP) in the BLL channel liquid cooling plate, thereby improving hydraulic pump efficiency. The identified optimal combination (M = 1.0 g s-1, N = 4, D = 2.5 mm, α = 90°) ensures that Tmax remains below 29.732 °C even during a 5C discharge, a critical requirement. Compared to a traditional serpentine channel with equivalent heat transfer area and inlet mass flow, the optimized BLL channel showed a decrease in Tmax by 0.776 °C, ΔTmax reduction by 2.445 °C, and ΔP reduced to only 43.44 % of that in the serpentine channel. The BLL channel proposed in this research can serve as a valuable reference for BTMS.

SELECTION OF OPTIMAL TECHNOLOGICAL PARAMETERS FOR FORMING NOMINALLY FLAT SURFACES WITH LUBRICATING MICROCAVITIES

This article demonstrates a multi-step process for forming a nominally flat surface with circumferential lubricating microcavities on a tribological assembly of an Х38CrSi steel shaft. The process includes finish turning, preliminary strengthening burnishing, deformation profiling of microcavities by a honing stone and smoothing of microprotrusions. The study determines the optimal technological parameters for each of the transitions based on microhardness and oil absorption power maximization, as well as roughness and periodic impact minimization. The process optimization is conducted using the Tagichi experiment design method. The optimal combination of technological parameters for hardening burnishing was discovered to be: normal force F = 200 N; feed rate f = 0.025 mm/rev and three tool passes. These burnishing parameters practically eliminate the influence of periodic impacts at spatial frequencies determined by the tool feed rate and the number of spindle rotations during turning. We determined suitable honing stone grit parameters and application force that yield microcavities 3.8 to 8.1 μm in depth, as well as the optimal parameters for smoothing of microprotrusions, resulting in a bearing area roughness of Sa = 0.15 µm and oil absorption power of 13.74×10–5 mm3/mm2.

Best practices for machine learning strategies aimed at process parameter development in powder bed fusion additive manufacturing

AbstractThe process parameters used for building a part utilizing the powder-bed fusion (PBF) additive manufacturing (AM) system have a direct influence on the quality—and therefore performance—of the final object. These parameters are commonly chosen based on experience or, in many cases, iteratively through experimentation. Discovering the optimal set of parameters via trial and error can be time-consuming and costly, as it often requires examining numerous permutations and combinations of parameters which commonly have complex interactions. However, machine learning (ML) methods can recommend suitable processing windows using models trained on data. They achieve this by efficiently identifying the optimal parameters through analyzing and recognizing patterns in data described by a multi-dimensional parameter space. We reviewed ML-based forward and inverse models that have been proposed to unlock the process–structure–property–performance relationships in both directions and assessed them in relation to data (quality, quantity, and diversity), ML method (mismatches and neglect of history), and model evaluation. To address the common shortcomings inherent in the published works, we propose strategies that embrace best practices. We point out the need for consistency in the reporting of details relevant to ML models and advocate for the development of relevant international standards. Significantly, our recommendations can be adopted for ML applications outside of AM where an optimum combination of process parameters (or other inputs) must be found with only a limited amount of training data.

Different origins of magnetic disturbances during substorm growth and expansion phases and insufficiency of the AL index as their sole measure

The paper examines the relationship between the PC index, characterizing the solar wind energy input into the magnetosphere, and the AL index, characterizing the magnetic substorm intensity for the expansion phase of isolated substorms recorded in 1998–2017. Magnetic disturbances in the course of the expansion phase are produced by the DP11 current system with a powerful westward electrojet disposed in the midnight auroral zone. It is generally accepted that this electrojet is generated by the “substorm current wedge” system of fieldaligned currents (SCW FAC) providing closure of the magnetotail plasma sheet currents through the auroral ionosphere. As this takes place, magnetic disturbances in the course of the substorm growth phase are produced by the DP12 current system with westward and eastward electrojets located, correspondingly, in the morning and evening sectors of the auroral zone, with the electrojets generated by the R1/R2 FAC system operating in the inner (closed) magnetosphere. The intensity of R1 currents is determined by the “coupling function” EKL, which represents the optimal combination of all geoeffective solar wind parameters affecting the magnetosphere. The DP2 magnetic disturbances generated by the R1 FAC system in polar caps forms the basis for estimating the PC index, which strongly follows the EKL field changes and correlates well with the development of magnetic substorms. Analyses performed in AARI revealed the principally distinctive character of the relationships between the PC index and AL index in the course of the substorm growth (DP12 disturbances) and explosive (DP11 disturbances) phases. The DP12 disturbances, generated by FAC systems in the closed magnetosphere, are developed in strong relation to the PC index. The DP11 disturbances, generated by the SCW FAC system, related to the magnetotail plasma sheet, show quite irregular character of relationship between the PC and AL values: the sudden jumps of the substorm intensity (ALpeaks) might occur, time and again, at any value of the PC index and with quite different delay times relative to sudden substorm onset. It means that the processes in the tail plasma sheet, leading to the formation of a “substorm current wedge” are determined by the state of the magnetotail plasma sheet itself. The solar wind influence (evaluated by the PC index) affects but does not control the processes in the magnetotail, unlike those in the inner magnetosphere. It should be noted in this connection that the intensity of magnetic DP12 and DP11 disturbances, observed in the course of the substorm growth and explosive phases, is estimated by a single AL index, in spite of the different origin of these disturbances (R1/R2 and SCW FAC systems). It is necessary to employ two separate indices characterizing DP12 and DP11 disturbances in order to allow for the effects of the solar wind on the processes in the inner magnetosphere and in the magnetotail.

Preparation, Mechanical and Thermal Insulation Properties of Graphene Oxide/Polydopamine/Polyurethane Foam‐Based Tunnel Insulation Liner Material

This article designs a novel tunnel insulation liner material based on polyurethane foam (PUF), aiming to improve the liner material's mechanical properties, hydrophobicity, thermal insulation properties and to reduce the self‐weight of the material. Firstly, PUF is self‐made using a one‐step method, and the optimal parameter combination is optimized through the single‐parameter (SP) method. Secondly, based on the optimal parameter combination of PUF, a new process is employed to prepare polydopamine (PDA)/graphene oxide (GO)/PUF. Compression experiments and contact angle tests are conducted to assess the physical mechanical properties of PDA/GO/PUF. Infrared thermography and combustion experiments are employed to characterize the thermal insulation performance of PDA/GO/PUF. Microscopic mechanisms are explained through thermogravimetric analysis (TG), scanning electron microscopy (SEM), and Fourier‐transform infrared spectroscopy (FTIR). The results show that: the optimal parameter combination of tin(II) bis(2‐ethylhexanoate) (TEH), water (H2O), and toluene‐2,4‐diisocyanate (TDI) content optimized by the SP method is 4 parts, 2.8 parts, and 19 parts. PUF prepared based on the optimal parameter combination exhibits a dense and uniform cell structure with low density. Under cyclic loading, PDA/GO/PUF composite material exhibits excellent mechanical stability and fatigue resistance; the hydrophobicity, thermal insulation, and thermal stability of PDA/GO/PUF are significantly improved compared to PUF.

Experimental investigation on in-situ laser-assisted machining of single crystal silicon based on response surface methodology

Abstract In this paper, Response Surface Methodology (RSM) was utilized as a robust and convenient predictive tool to establish the correlation between process parameters in in-situ laser-assisted machining and the surface roughness of single-crystal silicon. Based on the optimally designed diamond tool, a novel temperature field analysis method and RSM. The contribution rate of each process parameter on surface roughness was laser power > rotation speed > cutting depth > feed rate. The optimal process parameter combination is: rotation speed as 1001r/min, feed rate as 4.9μm/r, cutting depth as 7.55μm, and laser power as 28.81 W. Experimental validation of these optimal parameters compared surface roughness values obtained experimentally with those predicted. The surface roughness model showed a maximum relative error of 5.2%, with an average error of 4.8% across three experimental sets. These errors are within acceptable limits, indicating an alignment between predicted and experimental results.

Optimization of Clamping and Conveying Parameters for Spinach Orderly Harvesting with Low Damage by Simulation and Experiment

The leaves of spinach are delicate and easily injured during harvesting. To reduce the spinach damage rate and increase the conveyance success rate, an orderly harvester was designed and manufactured, and the key conveying parameters of the harvester were optimized by simulation and experiments. The compression damage stress of spinach was determined by compression tests. Then, a finite element simulation model for spinach clamping was established, and the influence of different clamping heights on the spinach deformation and equivalent stress were simulated and analyzed. Finally, response surface Box–Behnken experiments were conducted to optimize the combinations of the twisting angle, clamping distance, and height difference. The results of the compression tests showed that the compression damage stresses of spinach leaves, stems, and their connection points were 8.04 × 10−2 MPa, 7.85 × 10−2 MPa, and 11.63 × 10−2 MPa, respectively. The optimal clamping height of spinach for orderly conveyance was obtained to be 20 mm according to the finite element simulation. The response surface experimental results indicated that the significance order of factors affecting the extrusion force was the clamping distance, the height difference, and the twisting angle. The significance order of factors affecting the conveyance success rate was the clamping distance, the twisting angle, and the height difference. The optimal parameter combination was ae twisting angle of 60°, clamping distance of 24 mm, and a height difference of 20 cm. The experimental validation of the optimization results from the finite element simulation and response surface tests demonstrated that the extrusion force and conveyance success rate were 2.37 N and 94%, respectively, with a conveying damage rate of 3% for spinach, meeting the requirements for the low-damage and orderly harvesting of spinach.

Refractured Well Hydraulic Fractures Optimization in Tight Sandstone Gas Reservoirs: Application in Linxing Gas Field

Poorly producing wells in sandstone gas reservoirs are often refractured to enhance production. Considering the mutual interference of initial/refractured fractures, conductivity dynamic evolution, non-uniform inflow, and variable mass flow in the fracture comprehensively, a semi-analytical reservoir-fracture coupled production model fusing spatial and time separation methods is introduced to model refractured well performance. The proposed model is verified by CMG. The field applications indicate that the refracture job should be carried out when production is lower than the desired value. Restoring the Cf-ini and constructing the Cf-ref can increase productivity, which increases over 8 D•cm. The production growth rate just obtained a slight improvement. The production increased significantly with Lf-ini increasing from 120~270 m and Lf-ref increasing from 100~150 m. Hence, it is essential to extend the Lf-ini under engineering conditions. The ks/km = 10 can obviously increase production, but further enlarging ks does not contribute to well performance. Conversely, further producing larger bs is vital to enhancing production. Subsequently, the optimal parameter combinations (ds > Lf-ini > Lf-ref > Cf-ini > ks > Cf-ref) for well(X1) are carried out by orthogonal experiments. This work proposes a novel method to simulate refractured vertical well performance in tight gas reservoirs for refracture optimization.

Optimizing MFCC parameters for the automatic detection of respiratory diseases

Voice signals originating from the respiratory tract are utilized as valuable acoustic biomarkers for the diagnosis and assessment of respiratory diseases. Among the employed acoustic features, Mel Frequency Cepstral Coefficients (MFCC) are widely used for automatic analysis, with MFCC extraction commonly relying on default parameters. However, no comprehensive study has systematically investigated the impact of MFCC extraction parameters on respiratory disease diagnosis. In this study, we address this gap by examining the effects of key parameters, namely the number of coefficients, frame length, and hop length between frames, on respiratory condition examination. Our investigation uses four datasets: the Cambridge COVID-19 Sound database, the Coswara dataset, the Saarbrücken Voice Disorders (SVD) database, and a TACTICAS dataset. The Support Vector Machine (SVM) is employed as the classifier, given its widespread adoption and efficacy. Our findings indicate that the accuracy of MFCC decreases as hop length increases, and the optimal number of coefficients is observed to be approximately 30. The performance of MFCC varies with frame length across the datasets: for the COVID-19 datasets (Cambridge COVID-19 Sound database and Coswara dataset), performance declines with longer frame lengths, while for the SVD dataset, performance improves with increasing frame length (from 50 ms to 500 ms). Furthermore, we investigate the optimized combination of these parameters and observe substantial enhancements in accuracy. Compared to the worst combination, the SVM model achieves an accuracy of 81.1%, 80.6%, and 71.7%, with improvements of 19.6%, 16.10%, and 14.90% for the Cambridge COVID-19 Sound database, the Coswara dataset, and the SVD dataset respectively. To validate the generalization of these findings, we employ the Long Short-Term Memory (LSTM) model as a validation model. Remarkably, the LSTM model also demonstrates improved accuracy of 14.12%, 10.10%, and 6.68% across the datasets when utilizing the optimal combination of parameters. The optimal parameters are validated using an external voice pathology dataset (TACTICAS dataset). The results demonstrate the generalization capabilities of the optimized parameters across various pathologies, machine-learning models, and languages.

Thermal performance optimization for a tapered heat sink of bus bar conductor using definitive screening design

This study examines and optimizes four design parameters of a bus duct conductor's heat sink: fin pitch, fin height, fin thickness, and the number of fin valleys. Average surface temperature and Nusselt number are chosen as the thermal performance criterion of the heat sink. A Definitive Screening Design is employed as a statistical method to reduce the number of optimization runs required while minimizing the aliasing. The regression analysis, analysis of variance, main effect analysis and optimization are conducted to optimize the heat sink design parameter and its thermal performance. The current results provide an ideal heat sink design for the casing of bus duct conductors. A fin pitch of 4 mm, fin height of 6.5 mm, fin thickness of 1 mm, and six fin valleys are determined to be the most optimal combination of design parameters. The optimized responses' average surface temperature and Nusselt numbers are 72.05 °C and 21.59, respectively, with 2.97 % and 6.25 % deviation from the predicted values of the empirical equation. The experimental results are benchmarked against the IEC 60439-1 and IEC 60439-2 standards. The current analysis is expected to provide more insight into the impact of design factors on the thermal performance of a bus duct conductor.

Analyzing the effect of different shielding atmospheres on fiber laser welding parameters for modified 9Cr-1Mo steel

The present research aims to investigate the influence of and the relationship between welding speed ( v), focal position ( FP), and laser power ( LP) as input parameters for fiber laser to weld P91 under pure argon and CO2 shielding atmospheres using response surface methodology and using the desirability approach; optimization of input parameters has been performed to maximize the depth of penetration ( DP) while minimizing the top bead width ( TW) and heat-affected zone width ( HW). The results indicate that laser power ( LP) has the most significant impact on depth of penetration ( DP), whereas welding speed ( v) affects top bead width ( TW) and heat-affected zone width ( HW). The optimal combination of parameters under argon shielding results in a significantly low heat input of 48 J/mm (0.048 kJ/mm) and 50 J/mm (0.050 kJ/mm) pure argon and CO2 shielding atmospheres, respectively. Despite the difference in heat input being only 4.08%, an 11.618% increase in DP is observed under the CO2 shielding atmosphere. Due to the high-speed nature of the welding process (argon: 82.65 mm/s and CO2: 79.283 mm/s) combined with the significant reduction in heat input, the heat-affected zone is limited to a mere width of 0.203 mm under an argon shielding atmosphere and 0.263 mm under the CO2 shielding atmosphere compared with that reported in the other welding processes without the dissolution of precipitates in the fusion boundary of heat-affected zone. Microstructural characterization of the fusion zone has revealed the presence of an untempered lath martensite structure with precipitate dissolution. The precipitate dissolution has resulted in grain coarsening of 47.76% in argon weld and 39.65% in CO2 weld compared with the base metal grain size of 6.07 µm.

Research on Multi-Parameter Optimization of Conical Roller Line Processing Technology Based on Satisfaction Function

In the process of conical roller line processing, there will be problems such as low precision of processing parameters, long processing time, low utilization rate of machine tools, high rejection rate, and high processing cost, which will lead to low production efficiency. In order to solve this problem, it is necessary to iteratively optimize the size parameters, including inner diameter, ovality, and taper. By obtaining the optimal parameter combination, the size parameters in the production process are kept consistent, that is, the accuracy and performance of the workpiece during the processing are guaranteed so as to avoid the problem of quality difference, improve the production efficiency and reduce the processing cost. In view of the fact that there are often some constraints on the accuracy and efficiency in the machining process of tapered roller lines, how to optimize the parameters affecting the accuracy and the parameters affecting the efficiency to achieve balance between accuracy and efficiency in order to better meet the needs of customers for multi-objective optimization of the machining process has become the focus of research. Based on the existing research, this paper explores the multi-parameter optimization modeling and application in the machining process of tapered roller lines by constructing a satisfaction function, and then uses a genetic algorithm to iteratively search for the optimal solution by simulating natural selection and the genetic mechanism. Based on Python software v3.12, the production process of tapered roller bearings is simulated. The AHP analytic hierarchy process and CRITIC weight method are used to redistribute the parameter weights respectively. After eight iterations, it is concluded that the weight value assigned by the AHP analytic hierarchy process makes the satisfaction function value reach the best value of 0.99795 and tend to converge stably. The optimized parameter configuration significantly improves the machining accuracy and production efficiency of the tapered roller line. The optimal parameter combination is obtained: inner diameter: 9.9982 mm, ovality: 0.7 mm, taper: 0.5 degrees, production efficiency: 101.0.97 piece/h. In order to verify the optimization effect, the single value (X) and moving extreme difference (Rs) control charts in the measurement value control chart are used to analyze and verify the tolerance values of important parameters in the processing technology of the tapered roller line. The results show that the data points are all within the control limit, indicating that the processing process is in a statistical control state.

Discrete element modeling of JLU-H lunar highland simulant

In order to accurately model the machine-lunar soil simulant interaction, this study combined physical and simulation experiments to calibrate the discrete element simulation parameters of the JLU-H lunar highland simulant. First, the intrinsic parameters and the true angle of repose of the JLU-H were determined through physical tests to provide data for subsequent simulation tests. A Plackett-Burman test was designed to identify and select the parameters that have a significant effect on the angle of repose. The range of values of the significant parameters was then optimized using the steepest climb test. The Box-Behnken test was then utilized to calibrate and obtain the optimal parameter combinations. Finally, a validation test of the angle of repose was conducted using the calibrated DEM parameters. The relative error between the simulation results and the test results was 1.54 %. Then further straight shear tests were conducted to verify the accuracy and validity of the DEM parameters. The results show that the calibrated parameters can provide a reference for the selection of discrete element simulation parameters for lunar soil simulant and the design and optimization of drilling and excavation machinery for lunar exploration.

Peanut Pickup Combine Harvester Seedling Vines Crushing Mechanism Performance Enhancement and Pilot Studies

Aiming at the current peanut pickup combine harvester seedling vines crushing mechanism operation qualified seedling length rate is low, the impurity rate is high, and the seedling vines crushing mechanism is optimized design. On the basis of the material characteristics of peanut seedling vines, taking the crushing mechanism as the research carrier, the interaction mechanism of the seedling vine mechanism was analyzed. Establish the mechanical model and motion trajectory model in the crushing process, simulate the peanut seedling vines crushing process based on the discrete element method, analyze the influence of the cutter shaft rotational speed, movement speed, and bending angle on the crushing of peanut seedling vines, and establish the regression model, and the results of the research show that the influence factors in the main order of priority are: knife shaft speed > movement speed > bending angle The optimal parameter combination is knife shaft speed 2171.94 r/min, movement speed 0.79 m/s, and bending angle 45°. According to the field test conditions, it is determined that the knife shaft rotational speed of 2170 r/min, movement speed of 0.8 m/s, and bending angle of 45° can make the peanut seedling vines crushing mechanism of the work performance to achieve a qualified seedling length rate of 97.292%, the rate of impurity content of 2.746%, and the error with the predicted value is less than 2%, which indicates that this study can provide a reference for the optimal design of the seedling vines crushing mechanism of the peanut pickup combine harvester.

Imitating pangolin scale structure for reducing adhesion and resistance of rotary tillage in wet-adhesive soil

The bionic design of soil-engaging components has recently received much attention in conservation tillage and is extremely important for reducing tillage resistance and increasing implement passability in wet-adhesive rice paddy soil. In this paper, to reduce adhesion and resistance of rotary tillage in wet-adhesive soil, a novel imitating pangolin scale structure is first proposed, and the bionic non-smooth surface parameters affecting the soil adhesion effect is clarified. Afterwards, based on the JKR attached Bonding contact model, an accurate discrete element interaction model of the designed rotary tillage blade -wet adhesive soil is established, and the effect of spindle speed, bump size and bump distance on the tillage resistance and soil disturbance is analyzed using the proposed model. Finally, the proposed imitating pangolin scale structure is optimized to improve the anti-adhesive and drag reduction properties using response surface method, furthermore, the corresponding model validation experiments and field tests are also conducted. Results reveal that the relative errors between the simulated and experimental values of the bionic blade rotary torque and soil adhesion mass are only respectively 4.4 % and 8.3 %. In addition, the optimal parameter combinations of anti-adhesion and drag reduction are also determined: the spindle speed is 180 rpm, the bump width is 10.6 mm and the bump distance is 17.9 mm, respectively, at the time, the effect of soil breaking of the designed blade is reduced by 9.95 % compared to that of the traditional blades but the effect of anti-adhesion and drag reduction is improved by 18.81 %.

A microscopic oxygen transport model for ultra-high dose rate radiotherapy in vivo: The impact of physiological conditions on FLASH effect.

Ultra-high dose rate irradiation (≥40Gy/s, FLASH) has been shown to reduce normal tissue toxicity, while maintaining tumor control compared to conventional dose-rate radiotherapy. The radiolytic oxygen (O2) depletion (ROD) resulting from FLASH has been proposed to explain the normal tissue protection effect; however, in vivo experiments have not confirmed that FLASH induced global tissue hypoxia. Nonetheless, the experiments reported are based on volume-averaged measurement, which have inherent limitations in detecting microscopic phenomena, including the potential preservation of stem cells niches due to local FLASH-induced O2 depletion. Computational modeling offers a complementary approach to understand the ROD caused by FLASH at the microscopic level. We developed a comprehensive model to describe the spatial and temporal dynamics of O2 consumption and transport in response to irradiation in vivo. The change of oxygen enhancement ratio (OER) was used to quantify and investigate the FLASH effect as a function of physiological and radiation parameters at microscopic scale. We considered time-dependent O2 supply and consumption in a 3D cylindrical geometry, incorporating blood flow linking the O2 concentration ([O2]) in the capillary to that within the tissue through the Hill equation, radial and axial diffusion of O2, metabolic and zero-order radiolytic O2 consumption, and a pulsed radiation structure. Time-evolved distributions of [O2] were obtained by numerically solving perfusion-diffusion equations. The model enables the computation of dynamic O2 distribution and the relative change of OER (δROD) under various physiological and radiation conditions in vivo. Initial [O2] level and the subsequent changes during irradiation determined δROD distribution, which strongly depends on physiological parameters, i.e., intercapillary spacing, ultimately determining the tissue area with enhanced radioresistance. We observed that the δROD/FLASH effect is affected by and sensitive to the interplay effect among physiological and radiation parameters. It renders that the FLASH effect can be tissue environment dependent. The saturation of FLASH normal tissue protection upon dose and dose rate was shown. Beyond ∼60Gy/s, no significant decrease in radiosensitivity within tissue region was observed. In turn, for a given dose rate, the change of radiosensitivity became saturated after a certain dose level. Pulse structures with the same dose and instantaneous dose rate but with different delivery times were shown to have distinguishable δROD thus tissue sparing, suggesting the average dose rate could be a metric assessing the FLASH effect and demonstrating the capability of our model to support experimental findings. On a macroscopic scale, the modeling results align with the experimental findings in terms of dose and dose rate thresholds, and it also indicates that pulse structure can vary the FLASH effect. At the microscopic level, this model enables us to examine the spatially resolved FLASH effect based on physiological and irradiation parameters. Our model thus provides a complementary approach to experimental methods for understanding the underlying mechanism of FLASH radiotherapy. Our results show that physiological conditions can potentially determine the FLASH efficacy in tissue protection. The FLASH effect may be observed under optimal combination of physiological parameters, not limited to radiation conditions alone.

Optimization of Tool Wear and Cutting Parameters in SCCO2-MQL Ultrasonic Vibration Milling of SiCp/Al Composites

Silicon carbide particle-reinforced aluminum matrix (SiCp/Al) composites are significant lightweight metal matrix composites extensively utilized in precision instruments and aerospace sectors. Nevertheless, the inclusion of rigid SiC particles exacerbates tool wear in mechanical machining, resulting in a decline in the quality of surface finishes. This work undertakes a comprehensive investigation into the problem of tool wear in SiCp/Al composite materials throughout the machining process. Initially, a comprehensive investigation was conducted to analyze the effects of cutting velocity vc, feed per tooth fz, milling depth ap, and milling width ae on tool wear during high-speed milling under SCCO2-MQL (Supercritical Carbon Dioxide Minimum Quantity Lubrication) ultrasonic vibration conditions. The results show that under the condition of SCCO2-MQL ultrasonic vibration, proper control of milling parameters can significantly reduce tool wear, extend tool service life, improve machining quality, and effectively reduce blade breakage and spalling damage to the tool, reduce abrasive wear and adhesive wear, and thus significantly improve the durability of the tool. Furthermore, a prediction model for tool wear was developed by employing the orthogonal test method and multiple linear regression. The model’s relevance and accuracy were confirmed using F-tests and t-tests. The results show that the model can effectively predict tool wear, among which cutting velocity vc and feed rate fz are the key parameters affecting the prediction accuracy. Finally, a genetic algorithm was used to optimize the milling parameters, and the optimal parameter combination (vc = 60.00 m/min, fz = 0.08 mm/z, ap = 0.20 mm) was determined, and the optimized milling parameters were tested. Empirical findings suggest that the careful selection of milling parameters can significantly mitigate tool wear, extend the lifespan of the tool, and enhance the quality of the surface. This work serves as a significant point of reference for the processing of SiCp/Al composite materials.

Engineering Discrete Element Method-Based Design and Optimization of the Key Components of a Spoon-Wheel Spinach Seed-Metering Device

In view of issues affecting manual on-demand sowing of spinach, such as high working intensity, low seeding efficiency, and high cost, a mechanized precision seeding device for spinach seeds is proposed, based on a spoon-wheel including a combined cell with two intersecting surfaces. The key structure was designed, and motion analysis was conducted employing SolidWorks software (2022). Additionally, the seeding process was simulated using EDEM simulation software (2022). The number of spoons, the radius of the spoons, and the speed of the seed wheel were chosen as the influencing factors, while the qualified index, reseeding index, and missing index were utilized as the evaluation indexes. A response surface method test based on the Box–Behnken design was carried out, and the test results were analyzed to obtain the optimal parameter combination for the seed-metering device. The field test results showed that when the rotation speed was 18 rpm, the radius of each seed spoon was 2.5 mm, and the number of seed spoons was 50, the average qualified index was 90.89%, the reseeding index was 8.22%, and the missed seeding index was 0.89%. The test results satisfy the technical production requirements for spinach seed sowing.

基于 EDEM 离散元方法的盐碱土壤参数标定与测试

In this study, saline soil parameters were calibrated based on EDEM discrete element method, soil density, soil elastic modulus, soil shear modulus, soil particle size distribution and Poisson's ratio were determined. The Hertz-Mindlin with Johnson-Kendall-Roberts (JKR) model was used to simulate the characteristics of soil stress and strain of particles under external forces. The JKR contact parameter between saline soil particles was used as a test factor, and the soil accumulation angle was used as a test index to carry out the saline soil contact parameter calibration test. It was finally determined that an elastic recovery coefficient of 0.262, a static friction coefficient of 0.263, a dynamic friction coefficient of 0.234, and a JRK surface energy of 10.084 were the optimal combinations of contact parameters for saline soils.