Optimal Operating Parameters Research Articles

Development of high-speed precision maize metering device for dense planting pattern with standard ridges

This study proposed a high-speed precision dual-chamber maize metering device for the dense planting pattern with standard ridge promoted in China. Through theoretical analysis of the sowing process, parameters for the key components have been designed. The metering device is capable of planting two rows in a single pass for high-speed precision seeding. The effect of operating speed and negative pressure on seed metering quality was investigated. A high-speed camera was used to capture the trajectory of maize seed at different operating speeds, and it was found that intra-row shifts were caused by collisions at the mouth of the seed guide tube and rotation of the seed as it fell. Employing a two-factor, five-level orthogonal rotation test, Investigated the optimal operating parameters for the maize metering device. Response surface analysis showed that optimum seed metering quality was achieved at 14.2 km/h and 13.5 kPa. Validation tests showed a qualified rate of 97.93%, with a coefficient variation of 8.97% for this method. Additionally, an energy consumption analysis indicated a reduction in operating energy consumption of approximately 32% compared to conventional air suction seed metering devices for dense planting with large ridges on the same area of farmland. This study provides insights for reducing energy consumption in the seeding process, contributing to the sustainable development of agricultural resources.

The Impact of Non‐Monolithic Semiconductor Capacitance on Organic Electrochemical Transistors Performance and Design

AbstractThe existing device models for organic electrochemical transistors (OECTs) fail to provide any device design guidelines for optimized performance parameters such as transconductance that are pivotal for the applications OECTs in sensing. Moreover, the current models are based on the questionable assumption of a homogenous organic semiconductor layer, and all predict a linear behavior of the resistance with the OECT channel length. Consequently, the experimentally observed nonlinear resistance behavior in OECTs has been overlooked thus far. Here, an OECT device model is developed that accurately describes the nonlinear behavior of the OECT channel resistance and offers the first guidelines for maximizing transconductance. The model is inherently nonlinear and the nonlinearity stem from the non‐monolithic capacitance of the organic semiconductor layer. Moreover, the model provides a consistent and reliable estimations for the contact resistance in OECTs. The success of the model in accurately describing and providing predictions of the OECT operation by relating the device's geometrical parameters with electrochemical parameters of the semiconductor layer paves the way toward unlocking OECT potentials in diverse applications, from biosensing to neuromorphic computing and flexible electronics.

Multi‐aspect assessment and multi‐objective optimization of preheated tallow biodiesel‐diesel blend as alternate fuel in CI engine

AbstractThis study meticulously examined the impact of preheated tallow biodiesel on the performance and emission characteristics of a diesel engine. Employing a single‐cylinder, water‐cooled diesel engine configured with exhaust gas recirculation in this investigation, exhaust gas temperature (EGT) could be used to preheat the biodiesel, reducing its viscosity and density. This improvement in viscosity and density could enhance the injection process, which is often hindered by the higher density and viscosity of biodiesel compared with diesel fuel. The investigation achieved a peak preheat temperature of 70°C for the biodiesel, leading to notable improvements in brake thermal efficiency and brake power, particularly under high‐load conditions. A significant reduction in emissions was observed, with hydrocarbon and carbon monoxide levels decreasing by 46.87% and 50%, respectively, when using preheated biodiesel. To refine the engine's performance further, this study utilized response surface methodology (RSM) for the optimization of operational parameters, including injection timing, engine load, and biodiesel preheat temperatures. Optimal conditions were identified at an injection timing of 21° before top dead centre, a preheat temperature of 64°C, and an engine load of 45.45% for which output response was 18.68% brake thermal efficiency, 307°C EGT, 0.0247% vol. CO, 15.32 ppm hydrocarbons, and 131.37 ppm nitrogen oxides (NOx). The successful implementation of preheated tallow biodiesel signifies a crucial step forward in the pursuit of a more sustainable and efficient transportation industry. This advancement holds the promise of reducing reliance on traditional fossil fuels, thereby contributing to the global efforts towards achieving a more environmentally friendly energy landscape.

Review of Modelling the Compaction of High Aspect Ratio AgriculturalFeedstock Materials

Agriculture feedstock materials have low bulk density and are difficult to handle and transport. Compaction can enhance the agricultural feedstock density and could be an effective solution for handling problems. To develop a better compaction process, mathematical modelling can help understand the compaction mechanism and can help predict the mechanical behaviour of feedstock materials. This paper presents a review on the energy consumption, applied pressure, as well as rheological models to predict their compaction behaviour and thus help improve compacts’ mechanical strength and reduce densification costs. In summary, energy requirement for densification of biomass depends primarily upon the pressure applied, holding on time and properties of the material. From the published literature, it could be found that the Cooper-Eaton and the Kawakita-Ludde models that considers particle rearrangement and deformation mechanism can fit pressure and density of feedstock materials during compaction. The parameters in the rheological models were correlated to the properties of the feedstock materials and can be used for optimization of machine and operational parameters.

Experimentation of Grate Combustion of Municipal Solid Waste in Ouagadougou: Influence of Primary and Secondary Air Flow on Thermal Potential

The present work concerns the study of the influence of combustion air flows on the thermal potential during the combustion of a 2 kg mixture of solid model waste from the city of Ouagadougou. This mixture consists primarily of wood, cardboard and plastic. The prototype model is a natural laterite internal-walled grate furnace. During these investigations, we were interested in the temperature variation measured by 4 thermocouples K1 to K4 placed respectively from the waste bed to the top of the furnace. These variations are considered according to a variable primary and secondary air flow. The maximum primary and secondary airflow is 3000 L/min. Measurements are taken throughout the experiment at a step of 18 seconds and a maximum duration of 3 minutes for each case of flow considered. Maximum temperatures reaching 450oC are observed following the injection of secondary air only. This is explained by the supply of oxygen making the combustion more complete. The results show that the injection of primary and secondary air at a flow rate of 1500 L/min gives a more stable temperature result, i.e. 362,18oC 186,82oC 109,27oC 72,41oC respectively for the thermocouples K1, K2, K3, K4. An increase in the primary and secondary air flow to a maximum of 3000 L/min leads to a drop in temperatures due to the dilute internal atmosphere. These results allow to set the optimal operating parameters of the furnace in order to produce more heat for its recovery into electricity through a heat exchanger and a steam turbine.

Performance Analysis and Operation Parameter Optimization of Shaker-Type Harvesting for Camellia Fruits

This study aims to address the challenges of achieving a high harvesting rate and low flower bud damage rate during the harvesting of camellia fruits. To this end, a dynamic model of the camellia osmantha tree and a self-developed shaker-type harvesting machine were used as research subjects. The first 24 natural frequencies and mode shapes of the camellia tree were solved using the finite element method, and the effects of vibration frequency, excitation position, and vibration duration on the harvesting rate and flower bud damage rate were quantitatively analyzed through an orthogonal experiment. The numerical analysis results indicate that the camellia tree exhibits good response characteristics at vibration frequencies of 10–15.5 Hz and 38.5 Hz. The three-factors orthogonal experiment figured out that the optimal operational parameters for shaker-type harvesting were determined to be a vibration duration of 30 s, a motor output frequency of 12.5 Hz, and a gripping position height of 50 to 60 cm above the ground. Meanwhile, under these operational parameters, the harvesting efficiency reached 96.97%, while the flower bud damage rate was only 6%.

Technological line for the production of sunflower cake

BACKGROUND: The results of the study conducted to increase the shelf life of sunflower cake by justifying the optimal operating parameters of the ozonizer in the line of the sunflower cake production are presented. Studies of the processing of sunflower cake with an ozone-air mixture at optimal operating parameters, such as its concentration, the duration of its processing and the intensity of the high-frequency field, have been conducted. AIM: Increasing of the long-term storage of protein feed by improving the basic design parameters of the device for its production. METHODS: Resulting from the conducted theoretical research, the technological line for the protein feed production was developed according to the patent for the invention of the Russian Federation No. 2706188. To determine the optimal operating parameters of the device in the sunflower cake production line, which affect its shelf life, the design of experiment theory was used. RESULTS: A regression equation in coded values, characterizing the effect of the concentration of the ozone-air mixture, the duration of the sunflower cake treatment and the intensity of the high-frequency field on the sunflower cake shelf life, is obtained. The analysis of the obtained mathematical model of the processing process is performed. CONCLUSION: Experimental studies of the developed line for the production of sunflower cake with quality control of its treatment with an ozone-air mixture have shown that the sunflower cake shelf life depends on the ozone-air mixture concentration and the duration of treatment of the sunflower cake, as well as on the intensity of the high-frequency field. At the same time, with a decrease in the ozone-air mixture concentration, the duration of treatment of the sunflower cake and the intensity of the high-frequency field during the treatment increase. In the area of low concentration, increased duration up to 120 s and intensity up to 15250 V/m, the shelf life of the cake increases. It is reasonable to process sunflower cake with the ozone-air mixture to increase its shelf life from 3 to 5.45 months according to the GOST 80-96 using the developed line (patent RF 2706188) at a concentration of 23.03 mg/m3, processing time of 134 s and a high-frequency field strength of 17374 V/m.

Synergistic effect during co-pyrolysis of tea seed shell and waste printed circuit board: Thermogravimetric characteristics and operation parameter optimization

Synergistic effect during co-pyrolysis of tea seed shell and waste printed circuit board: Thermogravimetric characteristics and operation parameter optimization

Processing of Sludge Water from Alumina Production by Electrodialysis

The possibility of using the electrodialysis for processing weak aluminate solutions (sludge water) for the purpose of their concentration and causticization is analyzed. For testing, a three-chamber electro-dialysis cell with heterogeneous cation exchange membranes MK-40 was used. The optimal operating parameters of the process were determined, as follows: pole-to-pole distance 3–4 cm and current density 2 A/dm2 at the operating voltage on the cell of 20–26 V. Specific electricity consumption was established as 9.7–20.6 kWh/kg alkali, causticization efficiency 56.1–69.6%, alkali yield – 81%.

Enhanced Organics Removal Using 3D/GAC/O3 for N-Containing Organic Pharmaceutical Wastewater: Accounting for Improved Biodegradability and Optimization of Operating Parameters by Response Surface Methodology

Pharmaceutical industry effluents often contain high concentrations of refractory organic solvents, chemical oxygen demand (COD), and total dissolved solids (TDSs). These wastewaters, including N-containing organic solvents known for their persistence and toxicity, pose significant environmental challenges. The study evaluated the efficacy of 3D/Granular Activated Carbon (GAC)/O3 treatment compared to linear process additions when treating real pharmaceutical wastewater, and revealed a 2.73-fold enhancement in COD mineralization. The process primarily involves the direct oxidation of monoprotic organic acids found in real pharmaceutical effluents, such as acetic and formic acid, crucially influencing mineralization rates. Optimal conditions determined via the response surface methodology were 125 g/L GAC, 30 mA/cm2, and 75 mg/L O3, achieving high total organic carbon (TOC) and COD removal efficiencies of 87.19 ± 0.19% and 89.67 ± 0.32%, respectively (R2 > 0.9), during verification runs. Current density emerged as the key parameter for organic abatement, aligning with the emphasis on direct oxidation at the anode surface. This integrated approach enhances biodegradability (BOD5/COD) and reduces acute toxicity associated with persistent N-containing solvents, demonstrating promising applications in pharmaceutical wastewater treatment.

Simultaneous dehalogenation and oxidation of dichloroacetamide by Cu-modified CoFe-LDH in three-dimensional continuous flow aerated electrocatalytic reactor

Searching for catalysts and degradation systems for synchronous dehalogenation and oxidation of haloacetamides (HAcAms) is pressing. In this study, a novel three-dimensional continuous flow aerated electrocatalytic reactor (3D CFAER) system, which employed Cu-modified CoFe layered double hydroxides (CoFe-LDH) composite/activated carbon as a catalytic particle electrode for the degradation of dichloroacetamide (DCAcAm) was constructed. Under the experiment’s optimal operating parameters, the maximum degradation rate of DCAcAm reached 91.7 %. The superior performance for the degradation of DCAcAm was due to the enhanced electron transfer induced by the modification of Cu in CoFe-LDH. Moreover, Density Functional Theory (DFT) calculations indicated that Cu doping improved the ability of LDH to dissociate water, thereby enhancing its electrocatalytic performance. Scavenger experiments and Electron Paramagnetic Resonance (EPR) results revealed that •OH, O2•– and electrochemical direct dehalogenation were responsible for DCAcAm removal. Additionally, the electrocatalytic stability of the electrode was tested upon repeated use with DCAcAm degradation remaining as high as 81.7 % after five consecutive experiments. More importantly, in 3D CFAER, electrocatalytic treatment lasting 90 min reduced the TOC and COD of the actual chlorine disinfection wastewater by 64.1 % and 74.9 %, respectively. This study provides new theoretical basis and technical support for control of HAcAms.

Microbial symbiotic electrobioconversion of carbon dioxide to biopolymer (poly (3-hydroxybutyrate)) via single-step microbial electrosynthesis cell

This study proposes an novel single-stage microbial electrosynthesis system (MES) that bioelectrochemically converts CO2 into poly(3-hydroxybutyrate) (PHB). This innovative approach utilizes a symbiotic co-culture of electroactive acetogenic bacteria and PHB-accumulating bacteria within a single reactor, bypassing the need for separate acetate production and extraction. Systematic optimization of key operational parameters, including applied voltage, carbon source, and cathode material, was conducted to maximize PHB production. Results demonstrate that using a voltage of 2.5 V yielded a 7.14-fold increase in PHB content compared to open circuit conditions. Furthermore, functionalizing the cathode with a conductive and hydrophilic PEDOT: PSS polymer coating significantly enhanced the system’s performance, resulting in a 1.5-fold increase in both acetate and PHB production compared to unmodified carbon felt electrodes. The long-term stability and effectiveness of the co-culture system were validated through comprehensive microbial and metagenomic analyses. Results revealed a significant enrichment of CO2-utilizing electrotrophs within the cathode biofilm, including Acetobacterium and Clostridium. Concurrently, a 4 to 14-fold increase in the relative abundance of PHB-biosynthesizing bacteria, such as Pseudomonas, Rhodobacter and Caulobacter was observed in the planktonic phase. This study offers a promising pathway towards a circular bioeconomy by enabling the valorization of CO2 into valuable bio-based products via single-stage MES, utilizing a symbiotic co-culture.

Iron Separation from Iron-Rich Manganese Ore Leachate: Comprehensive Optimization of Operating Parameters and Economic Viability

In the current electrolytic manganese industry, iron separation and reuse from iron-rich manganese ore leachate (IRMOL) has become one of the most pressing challenges. This study aimed to investigate the optimal conditions for iron separation from IRMOL and to assess the economic and practical advantages of iron separation or removal in industrial manufacturing. To identify more cost-effective and technologically advanced production circumstances, we examined five key elements that weaken Fe(OH)3 colloidal production conditions in enterprises: reaction temperature, pH, crystal species, aging, and reaction time. The screening results showed that when the conditions were optimized, the efficiency of reducing manganese loss decreased from 6.15% to 4.69%. Additionally, the generation of iron-rich electrolytic manganese residue (IREMR) was decreased by 44.32%, and the filtration velocity of IREMR increased from 0.0030 to 0.0220 mL/(s·cm2) compared to the production conditions before optimization at the enterprise. Through multiphase equilibria modeling with Visual MINTEQ, we have determined that raising the temperature and pH levels increases the expenses associated with chemicals and energy usage and results in an elevation of Fe(OH)2+ concentration. This can lead to the creation of Fe(OH)3 colloidal, causing a high water content in IREMR, inefficient filtration, and significant loss of manganese. This strategy is highly significant for the production of electrolytic manganese and the reduction of electrolytic manganese residue.

Applying machine learning for biomass gasification prediction: enhancing efficiency and sustainability

Abstract In the contemporary era, marked by the increasing significance of sustainable energy sources, biomass gasification emerges as a highly promising technology for converting organic materials into valuable fuel, offering an environmentally friendly approach that not only mitigates waste but also addresses the growing energy demands. However, the effectiveness of biomass gasification is intricately tied to its predictability and efficiency, presenting a substantial challenge in achieving optimal operational parameters for this complex process. It is at this precise juncture that machine learning assumes a pivotal role, initiating a transformative paradigm shift in the approach to biomass gasification. This article delves into the convergence of machine learning and the prediction of biomass gasification and introduces two innovative hybrid models that amalgamate the Support Vector Regression (SVR) algorithm with Coot Optimization Algorithm (COA) and Walrus Optimization Algorithm (WaOA). These models harness nearby biomass data to forecast the elemental compositions of CH4 and C2Hn, thereby enhancing the precision and practicality of biomass gasification predictions, offering potential solutions to the intricate challenges within the domain. The SVWO model (SVR optimized with WaOA) is an effective tool for predicting these elemental compositions. SVWO exhibited outstanding performance with notable R 2 values of 0.992 for CH4 and 0.994 for C2Hn, emphasizing its exceptional accuracy. Additionally, the minimal RMSE values of 0.317 for CH4 and 0.136 for C2Hn underscore the precision of SVWO. This accuracy in SVWO’s predictions affirms its suitability for practical, real-world applications.

Analysis of forces on nodules during Coandă-effect-based hydraulic collection

The nodule pickup device is a crucial component of a deep-sea mining system. It is widely perceived that leveraging water flow for the separation and retrieval of nodules is a promising approach. A series of experiments and numerical simulations were conducted to examine the impact of non-dimensional parameters on the force characteristics and flow field of the particle in Coandă-effect-based hydraulic collection. The results showed that the lift coefficient of the particle initially increased before subsequently diminishing from the jet nozzle to the rear. Notably, the lift coefficient α reached its maximum at the convex curved surface between x/d = −0.17 and 0.33. Furthermore, a distinct linear correlation was established between the maximum lift coefficient αmax and Froude number Fr across varying h/d, and an empirical formula for predicting the lift coefficient was developed through data fitting. Upon experimental validation, the prediction exhibited a maximum error of less than 20%. Additionally, numerical simulations revealed that the particle significantly influenced the flow dynamics within the collection area, and the flow field characteristics and the particle forces can be corroborated with each other. The findings not only provided a reliable quantitative tool for assessing the particle force but also facilitated precise predictions of collection performance, aiding in the selection of optimal operational parameters in deep-sea hydraulic collection.

Assessing the potential accuracy of a small-sized goniometer with extended dynamic range based on nuclear magnetic resonance

This paper evaluates potential accuracy characteristics of a small-sized goniometer based on nuclear magnetic resonance with an extended dynamic range. This required constructing a model of goniometer errors, estimating its accuracy based on this model, and formulating practical recommendations for the design of such a device based on the accuracy assessment. To evaluate the accuracy of a nuclear goniometer, a theoretical model was built that makes it possible to determine the optimal operating parameters of the cell gas mixture, the ranges of their permissible changes, the sensitivity of the goniometer, and the dependence of its characteristics on external and internal factors. In particular, the dependence of output signal of the device on the parameters of gas mixture and optical pumping has been determined. For a goniometer with a cell volume of 8 cm3, the optimum temperature is 130 °C, and the optimum intensity of the pumping radiation is 5 mW. The dependence of output signal on the measured angle of rotation was also established, as well as the noise and error dependence of the device on the permissible values of its parameters. Based on the model built, parameters of a goniometer with a cell volume of 8 cm3 were determined; the maximum angular sensitivity of such a goniometer with complete suppression of technical noise is δφsen=1.0 arcsec. The greatest contribution to the angle measurement error is from the instability of pumping power Ip (ΔIp/Ip=0.05) – 85 %, magnetic field B0 (ΔB0/B0=10-8) – 13 %, temperature T (ΔT/T=0,1) – 2 %. The goniometer under consideration corresponds to the medium accuracy class, δφtot≥10 arcsec. It could be used in optical manufacturing for operational control, calibration, and certification of optical products. To improve the angular accuracy of the goniometer, it is necessary to increase the stability of the laser pumping intensity

Design and Testing of a Branched Air-Chamber Type Pneumatic Seed Metering Device for Rice

To meet the diverse seeding requirements of super hybrid rice, common hybrid rice, and conventional rice—which vary from 1 to 3 seeds, 2 to 4 seeds, and 5 to 8 seeds per hole, respectively—this study developed a branched air-chamber type pneumatic seed metering device for rice. The device utilizes an air chamber control board to manage the branched air chamber casing, enabling precise adjustments to the seeding quantity. This study presents a theoretical analysis of the seed metering device’s operation and its critical components. Structural parameter optimization was conducted using Ansys-Fluent (2021 R1) software, followed by multi-objective optimization of operational parameters through bench testing. Simulation results indicated that optimal vacuum pressure in the seed metering disc pores reached a maximum of 857 Pa with a chamber depth of 22 mm, an angle of 100°, and a cavity depth of 25 mm, achieving a minimal coefficient of variation of 0.86%. Bench test results showed that for seeding targets of 1 to 3 rice seeds per hole, the optimal operational parameters were: two openings, a working vacuum of 1355 Pa, and a rotor speed of 32.78 r/min, resulting in a missed seeding rate of 4.70%, a qualification rate of 85.81%, and a re-seeding rate of 9.49%. For targets of 2 to 4 seeds per hole, the best parameters included three openings, a working vacuum of 1357 Pa, and a speed of 32.87 r/min, with a missed seeding rate of 4.60%, a qualification rate of 85.59%, and a re-seeding rate of 9.81%. For 5 to 8 seeds per hole, optimal parameters were six openings, a vacuum of 1339 Pa, and a rotor speed of 31.07 r/min, yielding a missed seeding rate of 4.09%, a qualification rate of 87.27%, and a re-seeding rate of 8.64%. These findings demonstrate that the branched air-chamber type pneumatic seed metering device effectively meets the varied direct seeding requirements of rice, enhancing the adaptability of pneumatic seed metering devices to different seeding quantities in rice and potentially informing the design of pneumatic seeders for other crops.

Phosphate pre-concentration from wastewater by a continuous flow bench-scale forward osmosis membrane: A circular economy approach on nutrient recovery

Phosphate is a vital element necessary for the growth and development of plants, making it a crucial element in agricultural fertilizers. Extracting phosphate from wastewater for recovery aligns with the principles of a circular economy by closing the loop on nutrient cycles. Instead of viewing wastewater as a waste product, treating it as a resource for recovering valuable nutrients like phosphate promotes a more sustainable and efficient use of resources. In this study, the phosphate from synthetic wastewater was pre-concentrated by a continuous flow forward osmosis membrane system to facilitate effective precipitation. The pre-concentration feasibility of forward osmosis was studied by changing the draw concentration, feed concentration, feed pH, and flow rate of the feed solution. With the optimum operational parameters in batch mode such as pH of 7, the draw solute concentration of 0.4 M MgSO4, the feed and draw flowrate of 0.7 L/min and 0.3 L/min, the phosphate concentration was increased from 30 mg/L to 525 mg/L after 60 min, the average osmotic flux and reverse solute flux was 2.7 L/m2/h and 0.43 g/m2/h, respectively. As operated with continuous mode, the final phosphate concentration was increased four times, the average osmotic flux was higher with 8.1 L/m2/h and the reverse solute flux was 0.86 g/m2/h, which could improve the efficiency of calcium phosphate crystallization in precipitation/ crystallization reactors. This integrated system, which includes forward osmosis as a pretreatment method followed by a precipitation process, is technically possible for application on a larger scale as a circular economy approach.

Simulation Optimization and Experimental Validation of Hydraulic Impact in Pruning Machines

Abstract This study addresses the instability caused by hydraulic shocks in fruit tree pruning machines during operation and proposes an optimization scheme that combines simulation with experimentation. We investigated the mechanisms of load shock in the hydraulic system through mathematical modeling and LS-DYNA simulation analysis. The optimal operating parameters were determined using mechanical and orthogonal analyses: a forward speed of 4 km/h, a pruning tool angle of 60°, and a saw blade rotation speed of 1200 r/min.Additionally, we employed AMESim simulation to optimize the hydraulic system of the pruning machine by designing a dual accumulator configuration to effectively suppress hydraulic shocks.We validated the optimized system through simulations and experimental tests, demonstrating significant reductions in pressure fluctuations, with cutting efficiency improved by 30% and pressure fluctuations reduced by 26.7%.This study not only presents an innovative dual accumulator design but also validates its effectiveness in pruning machines through simulations and experiments, thereby enhancing the operational efficiency and stability of agricultural machinery.

Heat energy utilization of a double-flash geothermal source efficiently for heating/electricity supply through particle swarm optimization method

The principal aim of this article is to optimize the thermal and electrical efficiency of a geothermal combined heat and power system through metaheuristic particle swarm optimization (PSO) method. The objective of this research is to conduct a thorough analysis of the incorporation of metaheuristic PSO technique, with a specific emphasis on the potential advantages and obstacles associated with the utilization of metaheuristic approaches in improving the effectiveness of geothermal energy systems. The utilization of a double-flash geothermal system in conjunction with a transcritical carbon dioxide Rankine cycle is utilized for the co-generation of electricity and thermal energy. The research utilized a PSO method to enhance power generation, heating capacity, and overall system efficiency. The PSO algorithm was employed to determine the optimum operational parameters for a pressure level of 820 kPa and a pressure ratio of 1.59, leading to the maximization of power output to 2591.4 kW The PSO algorithm effectively identified the optimal operational parameters as a pressure of 820 kPa and a pressure ratio of 1.59, resulting in the achievement of a peak power output of 2591.4 kW. The methodology has determined that a pressure of 916.4 kPa and a pressure ratio of 1.5 represent the optimal parameters for achieving a maximum heating capacity of 12329.1 kW.