Optimal Operating Parameters Research Articles

花生清选筛台架的设计与试验

In order to address the high impurity and loss rates in the cleaning process of existing peanut combine harvesters, the design basis of the cleaning sieve was explored. Tests were conducted to determine the composition of the peanut picking fruit and the characteristics of the material suspension mixture. Additionally, the mechanical relationship between the fruit and miscellaneous mixtures and the cleaning sieve was investigated. The wind speed ranged from 8 m/s to 10 m/s, the vibration frequency ranged from 6 Hz to 8 Hz, and the inclination angle of the sieve ranged from 5° to 9°. The scavenger sieve platform was constructed and tested using Box-Behnken’s central combination test method. The optimal combination of fan wind speed (9 m/s), sieve surface inclination angle (8°), and sieve vibration frequency (7 Hz) resulted in a pod impurity rate of 1.16% and a loss rate of 1.4%. The device significantly reduces impurity content and loss rate during peanut harvesting. The study's results can serve as a reference for improving the design of the peanut combine harvester cleaning mechanism and optimizing operating parameters.

Green approach for fabricating hybrids of food waste-derived biochar/zinc oxide for effective degradation of bromothymol blue dye in a photocatalysis/persulfate activation system

This study presents novel composites of biochar (BC) derived from spinach stalks and zinc oxide (ZnO) synthesized from water hyacinth to be used for the first time in a hybrid system for activating persulfate (PS) with photocatalysis for the degradation of bromothymol blue (BTB) dye. The BC/ZnO composites were characterized using innovative techniques. BC/ZnO (2:1) showed the highest photocatalytic performance and BC/ZnO (2:1)@(PS + light) system attained BTB degradation efficiency of 89.47% within 120 min. The optimum operating parameters were determined as an initial BTB concentration of 17.1 mg/L, a catalyst dosage of 0.7 g/L, and a persulfate initial concentration of 8.878 mM, achieving a BTB removal efficiency of 99.34%. The catalyst showed excellent stability over five consecutive runs. Sulfate radicals were the predominant radicals involved in the degradation of BTB. BC/ZnO (2:1)@(PS + light) system could degrade 88.52%, 84.64%, 81.5%, and 77.53% of methylene blue, methyl red, methyl orange, and Congo red, respectively. Further, the BC/ZnO (2:1)@(PS + light) system effectively activated PS to eliminate 97.49% of BTB and 85.12% of dissolved organic carbon in real industrial effluents from the textile industry. The proposed degradation system has the potential to efficiently purify industrial effluents which facilitates the large-scale application of this technique.

Reuse and Recovery of Water from Industrial Textile Dyeing Effluent Using High-Performance Electrodes Continuous Flow Electrocoagulation Reactor

The dye effluents released from the textile and printing industries contain strong colorants, inorganic salts, and other toxic compounds. The conventional coagulation technique of dye effluent treatment is plagued with issues of low removal rate of color, generation of large quantities of sludge, and toxic end-products. Recently electrocoagulation technique gained immense attention due to its high efficiency. This technique involves the dissolution of the sacrificial anodes to provide an active metal hydroxide as a strong coagulant that destabilizes the pollutants and removes them by precipitation or flocculation. This study is about the efficiency of the electrocoagulation process using titanium coated - aluminum and mild steel electrodes to treat industrial dye wastewater. Effects of parameters such as current density & initial dye concentration were investigated. It was observed that, for the same current density, electrode consumption was higher with TiO2/Al electrode than with mild steel electrode, resulting in more color removal efficiency (CRE) using TiO2/Al electrode. The settling rate of the flocs was higher in the rector having TiO2/Al electrode at the 100 mL with current density (2.5 mL.min-1 to 5.3 mL.min-1), while in the reactor with mild steel electrode, the settling rate was very less. The results showed that dye removal was 95.11% and 92.1% for mild steel and titanium-coated electrodes, respectively. It was observed that 50 % of Aluminum was removed from the treated effluent after the final stage of filtration. Based on the multicriteria analysis to identify the optimum operational parameters to be applied at the field level, it was observed that maximum CRE may be obtained with TiO2/Al electrode and the applied current of 1 Amps with a flow rate of 100 mL.min-1. It can be concluded that electrocoagulation is a highly efficient and the fastest method to treat dye effluents from industries.

Operation parameters study on the performance of PEMFC based orthogonal test method

By selecting five key operational parameters—inlet temperature, operating temperature, anode humidity, cathode humidity, and operating pressure—and using PEMFC power density, membrane temperature difference, and membrane water content as performance indicators, simulations were conducted using 3D CFD modeling and orthogonal experiments to identify the most significant factors influencing PEMFC performance and determine the optimal operational parameter combination. The results show that working pressure has the most significant impact on PEMFC performance. Pressure variations cause significant changes in diffusion and heat conduction within the PEMFC. When the working pressure increases from 1.0 MPa to 3.0 MPa, the power density increases by approximately 11.2 %, but the temperature difference within the membrane increases by about 30.5 %. The difference between operating temperature and inlet temperature directly leads to changes in the temperature difference within the membrane. Moreover, changes in operating temperature greatly affect the water content within the proton exchange membrane, which in turn impacts the PEMFC's power density. When the operating temperature increases from 60 °C to 100 °C, the water content within the membrane decreases by approximately 50.5 %, and the power density decreases by 60.4 %. By optimizing the combination of operating parameters using a comprehensive scoring method, the temperature difference within the membrane can be controlled at 27.78 °C while ensuring the power density is increased to 0.92 W/cm2.

Research on operation parameter optimization of deep peaking boiler in thermal power plant based on data mining

Abstract At present, the structure of power supply in China has changed, and the positioning of thermal power units has gradually changed from the original main power supply to the adjustable power supply for peak regulation and frequency modulation. Peaking unit need to respond quickly to load changes while also considering economic efficiency, which means setting operating parameters more accurately. Association rules have achieved good application effects in the data mining of thermal power plant operation data. This article uses the historical operation data of a certain 600MW unit to explore the relationship between operating parameters and coal consumption under various peak load conditions, and obtain the optimized values of operating parameters. The results indicate that optimized parameters can improve the economic efficiency of peaking unit, and have certain practical value for setting operating parameters of boilers in deep peaking unit.

Obtaining high H2-rich syngas yield and carbon conversion efficiency from biomass gasification: From characterization to process optimization using machine learning with experimental validation

Gasification, among the other thermochemical processes, stands as a promising method for sustainable waste management while generating valuable H2-rich syngas. In the last few years, there has been a significant surge in the adoption of machine learning (ML) techniques for modelling biomass as well as gasification and pyrolysis of waste. The present study unveiled the supremacy of Gaussian Process Regression (GPR) algorithm as compared to other ML models, in predicting syngas yield [Ysyn (Nm3/kg of biomass)] and carbon conversion efficiency[ηCarbon(%)] respectively, with a high prediction accuracy of R2 > 0.9 in both the cases. The necessary datasets were collected from experimental trials, at reaction conditions of temperature (T): 550–1000 °C, air flow rate (AFR): 0.02–0.04 L/min, and reaction time of 2 h, in a two-stage fixed bed reactor, which were identified on the Basis of thermodynamic as well as stoichiometric analysis. Additionally, the models were employed in Bayesian optimization within a weighted multi-objective framework to obtain the optimal operational parameters, focusing on maximizing both yield and conversion simultaneously. Finally, this result was validated experimentally to check the sanctity of the data-driven optimization.

Application of polymer coagulants and optimization of operational parameters to improve total phosphorus removal efficiency in wastewater treatment plants

Application of polymer coagulants and optimization of operational parameters to improve total phosphorus removal efficiency in wastewater treatment plants

Thermodynamic, economic, and environmental analyses and multi-objective optimization of an organic flash regenerative cycle with an ejector for geothermal heat utilization

Based on the existing organic flash regenerative cycle (OFRC), this paper presents a novel OFRC system incorporating an ejector (E-OFRC). The ejector replaces the high-pressure throttle valve for initial flash evaporation and utilizes a low-pressure throttle valve for the second flash evaporation of saturated liquid separated from the first flash. The gaseous working fluid from the second flash is employed as the ejecting fluid. The E-OFRC system employs an ejector to mitigate irreversible losses associated with high-pressure throttle and to drive gaseous working fluids from secondary flash to circulate to enhance overall system performance. Thermodynamic, economic, and environmental models are established, and the impacts of flash pressure (P4), endothermic pressure (P3), and geothermal water temperature (THS,in) on system performance are analyzed and compared with those of the OFRC system. Multi-objective optimization using the Dragonfly algorithm is conducted, while the TOPSIS method is utilized to determine optimal operating parameters for the E-OFRC system. The findings indicate that, in comparison to the OFRC system, the thermal efficiency of the E-OFRC system is only lower under P3, while its thermodynamic, economic, and environmental performance is enhanced under other considered conditions. This underscores the advantages of the E-OFRC system. The optimal operating parameters for the E-OFRC system are THS,in = 423.53 K, P3 = 1.89 MPa, P4 = 0.96 MPa; yielding a net output power of 84.75 kW, a specific investment cost of 2833.54$/kW, and an annual CO2 equivalent emission reduction of 0.807 × 106kg − providing valuable technical support for engineering applications.

Efficient capacitive deionization with hierarchical porous carbon flow electrodes

Flow-electrode capacitive deionization (FCDI) represents an innovative, chemically-free, and environmentally-friendly approach for desalination. However, the long-standing challenge of constrained electronic and ionic transport within its flow-electrode has impacted overall desalination performance. In this study, we explore novel concepts and advancements in capacitive deionization by utilizing hierarchical porous carbon (HPC) flow electrodes. By employing widely available sodium carboxymethyl cellulose as a carbon precursor and NaCl as an activator, we have successfully synthesized a carbon-based particle electrode featuring a hierarchical porous structure. The HPC electrode was further optimized through precise adjustments to its pore structure. The optimized electrode exhibited excellent dispersion, viscosity, and remarkable specific capacitance of 283.96 F g−1. Under optimal conditions of a 10% mass loading and an applied voltage of 1.2 V, the electrode demonstrated an average salt removal rate of 82.11 μg cm−2 min−1, a charge efficiency of 101.44%, and an energy consumption of 9.32 × 10−3 kWh mol−1. Furthermore, we investigated the optimal operating parameters for the FCDI device equipped with the HPC flow electrode. Impressively, the HPC flow electrode achieved a salt removal efficiency exceeding 80% over five cycles, maintaining an average salt removal rate of 54.00 μg cm−2 min−1 during 12 h of continuous operation. Detailed textural analysis and electrochemical characterizations revealed that the superior desalination performance is attributed to the hierarchical porous structure of the electrode. This unique structure significantly enhances both electronic and ionic transport within the FCDI system. Our study underscores the critical role of hierarchical porous carbon flow electrodes in capacitive deionization, paving the way for novel strategies to optimize ion and electron transport.

Assessing the Impact of Transport Phenomena on Modeling and Optimization of Solid-State Fermentation for the Revalorization of Agro-Industrial Residues in a Wall‐Cooled Packed‐Bed Bioreactor

This work assesses the influence of transport phenomena on the growth of Yarrowia lipolytica 2.2ab (Yl2.2ab) and protease production during Solid-State Fermentation (SSF) in a bench-scale wall-cooled tubular bioreactor packed with substrate-based pellets derived from agro-industrial residues. Our engineering methodology, in a novel manner, includes: (i) developing a new pseudo-heterogeneous model, (ii) identifying and quantifying the impact of all transport phenomena on microbial kinetics, (iii) elucidating how fluid dynamics enhances heat and mass transfer processes, and hence microbial kinetics, and (iv) determining the operational and geometric parameters for optimal bioreactor performance. As main results: (i) all transport phenomena occurring within the bench-scale bioreactor are fundamental for its reliable simulation and will be essential for its scale-up, and (ii) the maximum production of proteases, 420 U kgDS‐1−1, is achieved under the following operational conditions: a tube to particle diameter ratio of 5.6, a bath temperature of 45°C, an inlet airflow rate of 1 L min−1, and inlet fluid temperature of 43 °C. Finally, the pseudo-heterogeneous model is assessed by describing SSF-based observations from the literature, appropriately predicting the performance of Yl2.2ab in a bench-scale bioreactor. These results pave the way for future exploration of Yl2.2ab in SSF within larger-scale packed-bed bioreactors.

Intelligent generation method of infection risk map and management system in hospital waiting room for respiratory infectious diseases

Respiratory infectious diseases, such as seasonal influenza, pose significant risks to public health safety through airborne transmission. This study aims to explore methods for controlling airborne infection risk in waiting rooms, a hotspot for cross-infection. A database of 990 samples was established by integrating the results of computational fluid dynamics and social force model simulations into the Wells-Riley equation. We introduced two indicators, Pr (Particle Removal Efficiency) and Hr (High-risk Area Ratio), to evaluate the cleanliness performance of waiting room spaces. Additionally, the Sci (Space Cleanliness Index) was proposed as a criterion for evaluating architectural designs and fine-tuning fresh air system operational parameters. We also unveiled the mapping relationship between spatial morphology parameters and ventilation design parameters in relation to the cleanliness performance of waiting rooms. An infection-risk prediction proxy model was established based on machine learning methods, suitable for rapid prediction of spatial infection risks in waiting rooms and optimization of fresh air system operational parameters. The findings can be applied to the selection of hospital design schemes and the optimization of ventilation operational control strategies, aiding in strengthening infectious disease control and reducing the public health safety risks of cross-infection from respiratory infections during peak seasons in hospitals.

Parametric Optimization Study of Novel Winglets for Transonic Aircraft Wings

This paper deals with the topic of reducing drag force acting on aircraft wings by incorporating novel winglet designs, such as multi-tip, bird-type, and twisted. The high-speed NASA common research model (CRM) was selected as the baseline model, and winglet designs were retrofitted while keeping the projected wingspan constant. Computational analysis was performed using RANS coupled with the Spalart–Allmaras turbulence model to determine aerodynamic coefficients, such as CL and CD. It was observed that the multi-tip and bird-type designs performed exceptionally well at a low angle of attack (0°). A parametric study was conducted on multi-tip winglets by tweaking the parameters such as sweep angle (Λ), tip twist (Є), taper ratio (λ), and cant angle (Φ). The best combination of parameters for optimal aerodynamic performance while maintaining the wing root bending moment was determined using both the Taguchi method and Taguchi-based grey relational analysis (T-GRA) coupled with principal component analysis (PCA). Also, the percentage contribution of each parameter was determined by using the analysis of variance (ANOVA) method. At the design point, the optimized winglet design outperformed the baseline design by 18.29% in the Taguchi method and by 20.77% in the T-GRA coupled with the PCA method based on aerodynamic efficiency and wing root bending moment.

Experimental Study on the Performance and Internal Flow Characteristics of Liquid–Gas Jet Pump with Square Nozzle

In order to ascertain the impact of working water flow rate and inlet pressure on the performance of the liquid–gas jet pump with square nozzle, the pumping volume ratio and efficiency of the liquid–gas jet pump with square nozzle were experimentally investigated at different inlet pressures and working water flow rates. Furthermore, the internal flow characteristics of the liquid–gas jet pump with square nozzle were explored through the utilization of visualization technology in the self-designed square-nozzle liquid–gas jet pump experimental setup. The findings indicate that the pumping ratio of the liquid–gas jet pump increases in conjunction with an elevation in the inlet pressure. Liquid–gas jet pump efficiency is higher at lower inlet pressures, up to 42.48%, and drops rapidly as inlet pressure increases. The pumping volume ratio of the liquid–gas jet pump increases significantly as the working water flow rate increases, and the working water flow rate exerts a minimal effect on the working efficiency of the liquid–gas jet pump. In the context of extreme vacuum conditions, a considerable number of droplets undergo substantial reflux in the posterior section of the throat, with a notable absence of bubbles in the diffusion tube. The size and number of bubbles diminish gradually along the axial direction. The objective of this paper is to provide a reference point for determining the optimal operational parameters for a square-nozzle liquid–gas jet pump in a practical context.

Integrated hybrid membrane system for enhanced water treatment and desalination for environmental preservation

Technology advancements in desalination, water treatment, and energy efficiency are crucial to preserving our planet. It is critical to find solutions for the future that save natural resources and lessen environmental damage because the freshwater shortage is getting worse, and energy demand is increasing. They face various obstacles, even though their breakthroughs are extremely important. Lot of energy can be utilized for the traditional desalination techniques, as it negatively impacts the environment. Then, the process of the existing Water Treatment (WT) are expensive and ineffective. An Integrated Hybrid Membrane System for Enhanced WT (IHMS-EWT) is a unique technique for WT and desalination was suggested in this study. The integration of many membrane procedures like nanofiltration, reverse and forward osmosis, and membrane distillation, and these will helps in facilitating the best WT and desalination methods. Due to the incorporating Renewable Energy (RE), the IHMS-EWT also demonstrates the (SWMS) Sustainable Water Management System, as it enhances the EE and thereby reducing the environmental impact. The great potential in the wide range of applications was offered by the IHMS-EWT technique. Providing the decentralized WT solutions in the remote areas, this unique approach has the ability to reduce the fresh water scarcity in the coastal areas based on the demands of the municipal, industrial and agricultural demands. The environmental sustainability throughout the lenghthy operations was ensured by the support of IHMS-EWT. It also helps in providing resilience in the crisis situations. The cost-effective evaluations, operating parameter optimization, and performance prediction of the method was enabled by employing the computational modelling. Through simulatimg different contexts, the effective configurations and operational techniques are focussed on the study for enhancing the IHMS-EWT technology.The model shift in the SWM, the IHMS-EWT technique addresses the main problems and brings one step for more secure environment. Comparing to other existing methods, Improving the water purification by 98.2 %, 94.2 % efficiency rate, the EC prediction rate of 96.2 %, the cost-effectiveness rate by 82.4 % and the performance rate by 96.7 % by the suggested IHMS-EWT model and it was demonstrated by the outcomes of the experiment.

A Study on the Optimization of Water Jet Decontamination Performance Parameters Based on the Response Surface Method

The substrate that adheres between the teeth of the traveling track plate during the operation of a deep-sea polymetallic nodule mining vehicle affects the driving performance, so this study aimed to investigate the effect of the water jet on the cleaning and decontamination performance of the track under different conditions. An optimization design method based on response surface methodology (RSM) is proposed. Based on the Box–Behnken design, the optimization variables of jet pressure, jet target distance, and impact angle, and the target response of jet strike pressure on tracks, were selected, and the numerical simulation method was combined with the response surface method to establish the regression model of the response of each optimization variable to the jet strike pressure on tracks and to determine the optimal parameter combinations. The study findings indicate that the primary factor influencing the pressure of the jet striking the crawler is the jet pressure. The hierarchical order of influence on the pressure of the jet striking the crawler, under the interaction of the three factors, is as follows: jet pressure and impact angle, jet pressure and target distance of the jet, and target distance of the jet and impact angle. The maximum pressure of the jet striking the crawler occurs when the jet pressure is 0.983 MPa, the target distance is 0.14 m, and the impact angle is 89.5°. Overall, the proposed design serves as a systematic framework for parameter optimization in the cleaning and decontamination process, and the research method and results provide theoretical references for the optimal design of mining truck desorption efficiency, which is critical for increasing mining efficiency and lowering energy consumption.

Design of gravity assisted heat exchanger and its application on enhanced waste heat recuperation utilizing organic Rankine and LNG system

Waste heat recovery involves capturing and reusing heat from a system that would typically be discarded. In industries like manufacturing and power generation, this method is gaining importance due to its potential to reduce greenhouse gas emissions and fuel consumption. This paper discusses a novel heat exchanger system that utilizes gravity to extract heat from exhaust gas, providing an alternative solution to the difficulties encountered by the conventional heat recovery techniques. Moreover, by adding both the ORC (Organic Rankine Cycle) and LNG (Liquefied Natural Gas) cycle to this system, excess heat can be used more efficiently, allowing for better energy recovery. The gravity-pipe heat exchanger and two cycles are used in the combined energy recovery system to extract useful heat from a low-grade waste stream. Energy performance is measured by using heat transfer analysis, energy efficiency testing, and exergy analysis followed by a comprehensive parametric analysis. To identify the optimal operating parameters for maximizing energy recovery and minimizing energy losses including economic analysis of GPHE with conventional HE, mathematical optimization models are developed. The heat exchanger demonstrates good effectiveness, close to 52.3 %, at an optimum temperature of approximately 275 °C to 280 °C for a 35 kg/s air flow rate. The ORC cycle is most efficient with optimum operating condition when pentane's mass flow rate is 3.3 kg/s. The maximum work output is obtained at a condenser pressure of 0.21 MPa, reaching 280 kW. When using pentane, the cycle's maximum efficiency is 36.8 %. However, the system's exergy efficiency drops by 4.94 % when the pinch temperature goes up by 7 °C. The output of ORC turbine increases from 220 kW to 240 kW, and the output of LNG turbine increases from 25 kW to 40 kW, as the condenser pressure rises. From economic analysis it's attain that the designed GPHE is economically viable for waste heat recovery from dirty exhaust gas. This paper develops a theoretical model to evaluate several cycles for extracting energy from waste heat, which could reduce fuel use and greenhouse gas emissions in industries.

Comparative assessment of waste-to-energy scenarios to mitigate GHG emission from MSW in a developing mega city

The search for sustainable municipal solid waste management in urban areas has become a dire need as the generated unprecedented volumes of waste eventually end up in landfills and emits greenhouse gas (GHG). To offer sustainable waste management in Dhaka, Bangladesh, the performance of incineration, anaerobic digestion, and hydrothermal carbonization (HTC) based Waste to Energy (WtE) processes were assessed and compared. The population and the GDP of Dhaka North City Corporation from 2015 to 2023 were used to estimate the MSW generation rate with an empirical multivariable linear regression model. In 2023 around 3600 tons/day of MSW was generated which was 35 % higher than in 2015. The IPCC decay models, ZODM, FODM, and modified triangular model (MTM) yielded 87.3, 41.3, and 38-k tonnes of CH4 generation, respectively. The power generation from incineration-based plants can fall from 30 MW to 3 MW if the moisture content of MSW increases from 70 % to 90 %. Anaerobic digestion produces 34 MW of power. The Optimization of the HTC operating parameters was done and it demonstrates substantial energy potential (up to 65 MW with co-feeding of 420 tons/day of hydrochar with 426 tons/day of plastic from MSW) and GHG emission reduction (221.5 %) compared to landfilling. Additionally, HTC-derived wastewater presents an opportunity for nutrient recovery with 8.16 and 2.66, 0.3 tons/day of K, Na, and P reclamation potential, respectively. A comparison of different scenarios in plastic recycling in incineration and sensitivity analysis for three WtE schemes were conducted. Thus, the study provides a rigorous assessment of different pathways to offer a comprehensive framework for sustainable MSW management that contributes to a cleaner urban environment.

Pareto Optimization and Tuning of a Laser Wakefield Accelerator.

Optimization of accelerator performance parameters is limited by numerous trade-offs, and finding the appropriate balance between optimization goals for an unknown system is challenging to achieve. Here, we show that multiobjective Bayesian optimization can map the solution space of a laser wakefield accelerator (LWFA) in a very sample-efficient way. We observe that there exists a wide range of Pareto-optimal solutions that trade beam energy versus charge at similar laser-to-beam efficiency. Moreover, many applications such as light sources require particle beams at certain target energies. We demonstrate accurate energy tuning of the LWFA from 150 to 400MeV via the simultaneous adjustment of eight parameters. To further advance this use case, we propose an inverse model that allows a user to specify desired beam parameters. Trained on the forward Gaussian process model, the inverse model generates input parameter value ranges within which the desired setting is likely to be reached. The method reveals different strategies for accelerator tuning and is expected to drastically facilitate the operation of LWFAs in the near future.

An experimental parametric analysis of the acoustic response in dielectric elastomer loudspeakers

This article presents an experimental parametric analysis of dielectric elastomer (DE) loudspeakers, which generate sound by means of soft lightweight electroactive polymer membranes, with no need for electromagnetic actuators. Attention is set on a simple topology, which consists of a DE actuator membrane deformed out-of-plane in a conical shape between fixed frames. Different scaled replicas of the system were built, featuring different diameters and elastomer membrane thickness, with the aim of highlighting the dependence of the acoustic response on the design parameters. An experimental analysis of the effect of different electrical and mechanical pre-loads was also carried out. Results suggest that the acoustic response is affected by both geometrical factors, possible effects of aero-elastic interactions, and the level of mechanical stress acting on the DE membrane. These findings provide valuable insights for the optimisation of DE loudspeaker design and operational parameters.

A stepped vibrating screening device with a crushing function based on the difference in tuber-soil aggregate breakage behaviour

To increase the difference in the particle size distribution of root tuber and soil aggregates and further promote the segregation effect of the binary mixture under external force. The present study investigates the bulbs of Fritillaria thunbergii (BFT) as the research subject. Initially, static compression and dynamic impact tests were conducted on BFT and soil aggregates. Subsequently, a breakage model of BFT and soil aggregates was established based on the Tavares UFRJ Breakage Model, and the accuracy of the breakage model and mechanical parameters was verified. Lastly, the optimal structural and operating parameters of the screening device with a crushing function were determined through single-factor testing and multi-objective optimization. The results indicate that the breakage resistance of BFT was significantly higher than that of soil aggregates, as evident from the differences in fracture energy and damage parameters. Furthermore, the optimal operating parameters of the new vibrating screen were determined by maximizing the soil aggregate breakage rate and minimizing the BFT breakage rate.