Mass Flow Rate Research Articles

How to Effectively Cool Blade Batteries in Extreme High-Temperature Environments?

The market share of blade batteries is rising rapidly due to their high energy density, efficient space utilization, and low cost. Nevertheless, effective cooling solutions for blade batteries are crucial to ensure the safe operation of electric vehicles, especially in extreme high-temperature environments. This paper numerically investigates the effects of a cooling plate and the blade battery parameters on maximum battery temperature, maximum temperature difference, and cooling water pressure drop. Additionally, the energy efficiency of these solutions under various cooling demands is analyzed. The numerical results show that increasing the channel number and changing the flow direction does not significantly improve the cooling performance of the cooling plate. Moreover, the effect of cooling water temperature on the maximum temperature difference in blade batteries is negligible. Furthermore, increasing the cooling water mass flow rate and the rotational speed of the cooling fan is preferred when Tmax − Ta > 6 K, while reducing the cooling water temperature is more energy-efficient when Tmax − Ta < 6 K. These results are expected to offer theoretical guidance and data support for designing cooling systems for blade batteries in extreme high-temperature environments.

Enhancement of Heat Transfer rate using Axially Interrupted Rectangular Fins in Double Pipe Heat Exchanger

The current investigates the thermo-fluid behavior of a double pipe heat exchanger (DPHE) featuring axially interrupted rectangular fins (AIRF) on the annulus part. The inner tube under this study with AIRF represents an interruption of straight longitudinal fins. This modification introduces periodic breaks along the tube's surface, effectively disrupting the boundary layer of the fluid flow. Consequently, it enables a non-continuous fluid passage along the length of the tube, potentially enhancing heat transfer. The experimentation employs standard liquid water, for investigations conducted under varying cold water mass flow rate 0.136 Kg/s to with 0.374 Kg/s keeping hot water at constant flow rate of 0.34 Kg/s with a fin split interval of four different lengths 7mm,27mm,55mm,100mm. A comprehensive investigation of the AIRF arrangements is carried out in contrast to the plain pipe arrangement, concentrating on fluid flow parameters such as Nusselt number (Nu), friction factor, heat transfer rate, and overall performance factor. The findings reveal that heat transfer rates in an annulus equipped with 7mm AIRF exceed those of a plain pipe by 59.31% under similar fluid flow conditions. The Nusselt number shows 1.5 times increase in the 0.007 m AIRF arrangement compared to the plain pipe. Thermal performance factor for 7mm interrupted length of AIRF outperforms other models.

A Comprehensive Literature Review on the Resolution of Turbine Engine Performances' Inverse Problems

Abstract Turbine engine monitoring is a well-known and well-studied subject that proves to be essential for the aeronautic industry. A popular approach in engine monitoring is constructing indicators that reflect systems' health states by leveraging operational measurements (i.e., sensors' data during flights)—this is known as the engine performance's inverse problem. There exists an extensive literature on this topic, especially revolving around two well-used types of performance indicators of aircraft engines: efficiencies and air mass flow rates of engine's modules. This review aims to provide a comprehensive survey of this particular literature, which so far has not been properly organized and structured. Our first contribution is to propose a novel taxonomy of the relevant methods. In particular, we consider the role of physics-based models—an element that provides specific advantages and challenges in the context of aircraft engines monitoring—and see if each method exploits such models inside or outside the main algorithmic process (or not exploiting them at all). Our second contribution is to identify the pros and cons of each method, along with additional insights with respect to two commonly encountered challenges: under-determined scenarios and time-series data. Finally, we give some guidelines for selecting appropriate strategies in practical situations and perspectives for future works.

Techno-Economic Feasibility Study of a Combined Cycle Power Plant Utilizing Natural Gas and Biogas from Cattle Manure Co-firing in South Central Timor

The low electrification ratio in East Nusa Tenggara, particularly in South Central Timor Regency, poses a significant issue. Despite reaching an electrification rate of 92.33%, efforts to achieve 100% are ongoing. South Central Timor as one of the largest cattle farming areas in Indonesia, with its large grasslands and dry climate ideal for cattle farming, has substantial biogas potential from beef cattle manure through anaerobic digestion. Biogas from beef cattle manure has a net calorific value of 18.36 MJ/kg. Based on projections for 2027 using best fit regression, the average daily manure production capacity from 260,217 cattle in South Central Timor is 7.55 kilotons, which is equivalent to approximately 301,852 m3 of biogas. A small-scale combined cycle power plant (CCPP) is proposed to capitalize on this, with a capacity of 20.73 MW and a net thermal efficiency of 55.33%. The plant’s fuel mix will consist of 30% biogas and 70% natural gas by mass, with a fuel mass flow rate of 1 kg/s. The levelized cost of electricity (LCOE), internal rate of return (IRR), and net present value (NPV) obtained from the economic calculations are Rp1,126.76/kWh, 9.62%, and 222 billion IDR with assumptions of a 20-year plant lifetime, an electricity selling price of Rp1,352/kWh, and a discount rate of 6%. The plant is expected to reduce carbon emissions by 61 kilotons annually, while creating new job opportunities in the energy, livestock, and logistics sectors.

Turbine cooling air estimation in thermodynamic simulations

AbstractModern gas turbines utilize a high amount of the core mass flow rate for component cooling. Thus, a coherent thermodynamic gas turbine representation demands a well-modeled secondary air system, which is able to estimate mass flow rates depending on respective design decisions. In this paper, the focus is set on the estimation of turbine blade cooling air. For this purpose, five different methods are presented and analyzed. The described concepts can be split into empirical and semi-empirical approaches. The semi-empirical approaches, the Horlock [1], Jonsson [2] and the Halliwell [3] method, are able to predict the blade temperature based on a given cooling mass flow rate or the needed cooling air based on a given blade temperature. In contrast, the empirical methods, the Grieb [4] and the Walsh [5] method, can only predict the cooling air consumption. Due to the fully empirical approaches the field of application is limited to the considered engine structures. On the other hand, the empirical methods lead to a better convergence behavior in comparison to the semi-empirical approaches due to their relatively simple calculation methods. The selected cooling air estimations are implemented in the performance code DLRp2 [6–8]. Therefore, processes and methods are deployed that allow to estimate turbines with unlimited cooled stages. Additionally, an off-design procedure is proposed to consider the occurring stagnation temperature drop between stator and rotor based on a reference temperature offset. A simplified thermodynamic gas turbine model is used to analyze the different cooling air estimation methods. For this purpose, sensitivity analyses for the main cooling air parameters are carried out. Moreover, all methods that were developed for the most stressed operating point are compared. Finally, the simplified model is calibrated to NASA’s energy efficient engine [9].

Shock-Induced Fan Cowl Separation During Aeroengine Windmilling at Diversion from Cruise

When a civil aircraft engine is operated at windmill during the cruise flight phase, there is supersonic flow acceleration around the leading edge of the fan cowl toward the external surface. The terminating normal shock wave can separate the turbulent boundary layer developing on this external surface. A series of experiments at a flight-relevant Reynolds number (1.2 million based on lip thickness) are performed in a quasi-two-dimensional wind tunnel rig to investigate the underlying flow physics. At a nominal inflow Mach number of 0.65 and a nacelle incidence angle of 4.5 deg, as the equivalent engine mass-flow rate is reduced, an increase in shock strength results in flow separation when the shock exceeds Mach 1.4. Over a 10% range in the notional engine mass-flow rate, the boundary layer developing on the external fan cowl thickens by a factor of three on the onset of separation. A reduction in the incoming Mach number from 0.65 to 0.60 weakens the shock wave and thus delays separation. An increase in surface roughness has no significant effect in situations where the boundary layer remains attached. However, for separated cases, an increased local roughness height causes a greater separation extent and a thicker boundary layer downstream of the shock wave.

Effect of Ceramic Matrix Composites on the Thermal Efficiency of a Power Generation Turbine

Abstract Ceramic matrix composites (CMCs) offer higher allowable temperatures and reduced weight, making them an attractive prospect for parts in the hot section of a gas turbine engine. As CMCs are increasingly adapted into aero and land-based engines, there is a need to quantify the performance increase based on the potential for reduced cooling and increased firing temperatures. In this work, two static hot section components—the first-stage turbine vane and the first-stage turbine tip shroud (outer casing above the blade)—of a mid-sized power generation engine were modeled. Informed approximations about part geometry and cooling architectures were made to determine the cooling requirements of each part. Thermal boundary conditions for the turbine tip shroud and turbine vane were generated as a function of coolant mass flowrate using data from literature and applied to a 2D finite element analysis of the parts to determine maximum temperatures for both metallic and ceramic materials. A gas turbine cycle model was developed to simulate the performance of a mid-sized power generation turbine and used to determine the increase in efficiency due to a reduction in the cooling requirement for the CMC part compared to a conventional metal superalloy-based part. The potential reduction in chargeable cooling seen for the tip shroud ring was between 0.09% and 0.4% of the compressor mass flowrate, which corresponds to an increase in thermal efficiency between 0.11% and 0.45%. A similar analysis of the turbine vane resulted in a cooling reduction of 10.71% at the maximum turbine entry temperature considered which corresponds to a 3.4% increase in thermal efficiency.

Artificial Neural Network Modeling to Predict Electrical Conductivity and Moisture Content of Milk During Non-Thermal Pasteurization: New Application of Artificial Intelligence (AI) in Food Processing

This study proposed applying artificial intelligence (AI) to predict the actual electrical conductivity (EC) of raw and pasteurized milk using moderate electric field (MEF) based on the electric field strength (EFS) and mass flow rate (MFR) along with modeling moisture content (MC) based on the EC. To this end, an artificial neural network (ANN) was implemented for conventionally (CP) and non-thermally (NP) pasteurized milk. The findings indicated no significant difference (p > 0.05) between the experimental and predicted data for EC and MC. The MFR and EFS affected the actual EC. The raw milk samples had an EC of 0.468812–0.46913 S/m and MC of 87.3218–87.35941%, while these values in NP pasteurized milk were 0.457441–0.638224 S/m and 87.33986–87.40851%. With correlation coefficients (R) of 0.736478106–0.951840323 and mean square errors (MSE) of 0.005539–0.0064, the ANN accurately predicted the raw and pasteurized milk MC based on the EC using the sixth-order polynomial model and the EC based on the EFS and MFR using a quadratic model. The EC of pasteurized milk by NP was significantly (p < 0.05) lower than that of CP and raw dairy by 15.44% and 11.30%, respectively. The results show that the EFS and MFR might be used for the online assessment of milk’s physical attributes (e.g., EC), followed by using the assessed parameter to determine other properties (e.g., MC) by developing AI approaches based on optimized models. These observations showcase the innovative use of ANN-based AI to predict milk’s EC and MC accurately. Integrating such AI platforms into non-thermal food processing could eventually develop more sustainable food production and enhance food security and quality through process innovation and sustainable manufacturing, contributing to the industrial revolution and sustainable development goals.

Design and performance evaluation of a 3D printed aerostatic bearing concept with high number of micro-orifices

This study suggests a 3D printed aerostatic bearing concept. The design has a high number of orifices distributed around the bearing to obtain smoother pressure distribution for performance. Inner channels are formed to connect and feed air to each orifice using the advantage of additive manufacturing. The concept is investigated numerically to determine the performance gain of the high number of orifices by calculating bearing stiffness and load carrying capacity. In order to validate the simulation and performance gain an experimental study is conducted by testing Stereolithography (SLA) type 3D printed bearings with various orifice numbers. The bearing stiffnesses and mass flow rates of the specimens are measured, and results are discussed in terms of performance by comparing numerical results. The 3D printed bearings concept has shown promising results in terms of performance while keeping air consumption limited compared to conventional air bearings.

Speed controller design for turboshaft engine using a high-fidelity AeroThermal model

Abstract One of the main objectives of this research is to construct a high-fidelity aerothermal model for controlling the turboshaft engine power turbine rotational speed. Firstly, a high-fidelity aerothermal model of General Electric T700 is formed. The turboshaft engine aerothermal model is simulated and compared to engine design point data on MATLAB/Simulink environment. Thermodynamic equations and some algebraic equations are used. In predicting compressor mass flow rate, the adaptive neuro-fuzzy inference system method is preferred. A propeller model is also added to the turbo shaft engine aerothermal model and to keep the power turbine rotational speed at a constant value, a Proportional Integral Derivative controller is designed and applied. Open-loop and closed-loop simulations are conducted and successful outcomes are achieved. Results indicate that the differences between simulation and actual engine data are within acceptable limits. The suggested model can be readily updated and expanded to control additional parameters of the engine. PACS 2010 Classification: Control theory in mathematical physics, 02.30. Yy, Computer modeling and simulation, 07.05.Tp, 05.70.Ce Thermodynamic functions and equations of state.

Investigation of the impact of utilizing PCM into a coil in a single-pass air heater (experimental study)

This study aims to design, build, and assess the SAH's performance with an integrated enhanced phase-change material (PCM) absorber storage system. Using materials found locally, two single-pass solar air heaters were designed and produced for this study. The first solar heater was made without phase change material (Conventional SAH), and the second included PCM by adding paraffin wax to the coil tube (Improved SAH). In February, March, and April of 2024, real - results were carried out on the air heaters in Mosul city, Iraq. At a mass flow rate of 0.0147 kg/s, the experiments were conducted with and without a PCM system. As opposed to the first case without PCM, the study's findings indicated that the air temperature outside of the heater increased significantly in the second case with (the addition of paraffin wax). The highest recorded outlet temperatures in February, March, and April for both cases were (39.5, 50.7 °C), (49.4,58.9°C), and (57.4,70.6°C). To compare the efficiencies of the SAHs for both instances (Conventional and Improved), the efficiency of the improved SAH is higher than the efficiency of conventional SAH, such as (48.1% and 68.32 %), (58.6% and 72.8%), and (67.1% and 86.47%) in February, March, and April.

CO2 transport in supercritical state: Nikiski, Alaska pipeline study

AbstractCarbon dioxide (CO2) in the supercritical state, being denser yet less viscous, is suitable for long‐distance transportation. Despite this well‐known principle, implementing an operational scheme with appropriate inlet pressure and mass flow rate for supercritical CO2 (srCO2) transportation is challenging due to the complex interplay among state variables, fluid properties, pipeline dimensions and materials, and the intricate boundary and ambient conditions surrounding the pipeline. This paper utilizes PIPESIM software to conduct a feasibility study of srCO2 transportation over a 10‐mile‐long model pipeline in the Cook Inlet region of Alaska, USA. The study aims to understand the limitations of operational parameters and develop a scheme for selecting feasible parameters for srCO2 transportation. Considering geographic location, elevation profiles, and ambient conditions, the simulations calculated pressure and temperature profiles, erosion kinetics, and fluid states for various conditions derived from a combinatorial set of pipeline diameters ranging from 11 to 16 in, inlet pressures between 1,400 and 1,900 psia, and mass flow rates from 10 to 275 lbm/s, with an inlet temperature of 200 °F. The major findings indicate that larger pressure losses are expected in smaller pipelines that are well‐insulated and/or operated at lower inlet pressures. Turbulent flow is more likely to occur in smaller pipelines and at higher mass flow rates, potentially altering the state of the transported fluid. The parametric modeling results provide a scenario‐driven approach to determining a feasible range of mass flow rates, pipeline inner diameters, and inlet pressures for srCO2 transportation. © 2024 Society of Chemical Industry and John Wiley & Sons, Ltd.

Thermal performance prediction of a V-trough solar water heater with a modified twisted tape using ANFIS, G.L.R., R.T. and SVM models of machine learning

Four distinct neural models were used to evaluate the efficiency of a V-trough solar water heater (VTSWH) equipped with square-cut twisted tape (SCTT) and V-cut twisted tape (VCTT) at two different twist ratios, 3 and 5. The objective of this study was the use of ANFIS (Adaptive Neuro-Fuzzy Inference System), G.L.R. (Generalised linear regression), R.T. (Regression tree), and SVM (Support Vector Machine). A total of 162 data sets were acquired for these models through a variety of trials. Outdoor experiments were done using a twist ratio of Y = 3 and Y = 5, using both SCTT and VCTT. The models included eight distinct variables: ambient temperature, water mass flow rate, water intake temperature, water exit temperature, absorber plate temperature, tube temperature, solar intensity, and twist ratio. The dependent variables in this study are the Nusselt number (Nu), friction factor (FF), and efficiency (η). 130 datasets were chosen for training purposes, while 32 were used for testing. Using the ANFIS, G.L.R., R.T., and SVM techniques, the correlation coefficient (R2) values for Nusselt number were 0.9990, 0.9961, 0.9562, and 0.9280 for friction factor 0.9966, 0.9683, 0.9810, and 0.9560, and for efficiency 0.9997, 0.9976, 0.9845, and 0.9614, respectively. Comparing all models shows that ANFIS is the most effective of the four strategies studied. The ANFIS model outperformed the other models regarding Nu, FF, and η, with RMSE values of 0.0805, 0.0.0004, and 0.4534. According to the above data, the VTSWH thermal performance predicted using the ANFIS approach has the highest accuracy.

A Comparative Study on Laser Cutting Performance with Varying Speeds at 10 M Underwater

Despite the dismantling structures that are submerged to significant depths of water during the decommissioning of nuclear power plants, there is limited research on deep-water laser cutting processes. A self-designed pressurized chamber was used in this study and successfully conducted the world’s first laser cutting experiment in a simulated 10 m water depth environment. laser cutting was performed in a 10 m underwater environment, and the cutting efficiency was compared to that observed in a 1 m underwater environment. Therefore, A 100 mm thickness of 304 stainless steel was successfully cut underwater, and the highest cutting speed of 100 mm/min was achieved. The result indicates that, as the cutting speed increased during underwater laser cutting, both the heat input and the mass flow rate of the assist gas decreased, resulting in a narrower rear kerf width and an ineffective evacuation of the molten metal.

A new method to improve the thermal performance of high-level water collecting cooling tower based on the migration of vortices

This study proposes a novel annular inlet hat structure designed to address internal vortex flow within high-level water collecting cooling towers (HCTs). To investigate the effect mechanism of inlet hat, a three-dimensional numerical model for an HCT equipped with inlet hat was developed, allowing for a comprehensive analysis of the flow and temperature fields, as well as several performance parameters. The results manifest that the inlet hat strengthens the tower thermal performance by migrating the longitudinal vortices from the interior to the exterior and reducing the number of longitudinal vortices induced by crosswinds. The strengthening effect of inlet hat shows minimal variation when its width exceeds 8 m. Under the studied water flow rates, an 8-m inlet hat results in increases in air mass flow rate, water temperature drop, Merkel number, and evaporation rate by a maximum of 4.3 %, 4.2 %, 6.4 %, and 1.5 %, respectively. In terms of crosswinds, the inlet hat operates with optimal efficiency at a direction of 0° and a velocity of 13 m/s, achieving maximum increases in air mass flow rate, water temperature drop, and Merkel number of 23.3 %, 25.4 %, and 33.6 %, respectively. These findings demonstrate the feasibility and practical value of the proposed inlet hat.

A novel integrated solar-driven system with Ag@SiO2 nanofluid filters for generating hydrogen using seawater: Parametric assessment and optimization

Both renewable energy and fresh water inputs are required to develop sustainable green hydrogen. However, there is still a lack of an integrated system generating hydrogen cleanly. Therefore, this study aims to develop a full spectrum solar energy-driven system to co-generate fresh water and hydrogen. The seawater desalination and proton exchange membrane (PEM) electrolysis are introduced into a Ag@SiO2 nanofluid-filtered photovoltaic/thermal (PV/T) system. The desalinated seawater can be directly used for the electrolysis, realizing the self-supply of water for the hydrogen production process. A comprehensive examination is performed via modelling the integrated system to assess the influences of mass flow rates and nanofluid parameters on system function. Results reveal that the system performance is more sensitive to the mass flow rate of nanofluid than that of coolant, and concentrated nanofluids can easily affect system performance by adjusting their depth. Furthermore, mass flow rates and nanofluid parameters are optimized using a genetic algorithm with multiple-objectives. It was determined that the direct contact membrane distillation (DCMD) unit is capable of producing sufficient water for the electrolysis process. The optimal system attains a hydrogen production rate of 1.95 × 10−5 kg/s, a specific thermal energy consumption of 310.18 kWh/m3, and a system efficiency of 22.39%.

WISE J152614.95-111326.4, an Unusual Variable Star

ABSTRACT New time series photometry of WISE J152614.95-111326.4, an eclipsing binary candidate, has been obtained. Full cycles of variation were covered in five filters, ranging from B to z. Archival time series photometry is also available from several sources. The phased light curve shape changes from a double wave form in the red, to a single wave at shorter wavelengths. Analysis of the spectral energy distribution and SALT spectra shows the presence of a cool (∼ 7250−7900 K) white dwarf and an M6 star. The light curves can be explained by a hot spot on the opposing hemisphere of the white dwarf. The star may be in a pre-cataclysmic variable phase with a very low rate of mass flow from the red dwarf to the white dwarf, such that no flickering is evident. Evidence in favour of this hypothesis is that the period of the system (2.25 h) is in the cataclysmic variable period gap. It is speculated that a weak magnetic field associated with the white dwarf funnels accreted material onto a magnetic pole. Amplitudes of the W1 and W2 WISE light curves are anomalously large. The possibility is discussed that variability in this spectral region is primarily driven by electron cyclotron radiation.

Experimental Study on Cryogenic Compressed Hydrogen Jet Flames

Cryogenic compressed hydrogen (CcH2) technology combines the advantages of high pressure and low temperature to achieve high hydrogen storage density without liquefying the hydrogen, which has broad application prospects. However, the safety concerns related to cryogenic hydrogen need to be carefully addressed beforehand. In the present work, cryogenic hydrogen jet flames are experimentally investigated for various release pressures and initial temperatures. The flame length and thermal radiation flux were measured for horizontally releasing with nozzle diameters of 0.5–2 mm, temperatures ranging from 93 to 298 K, and initial pressures of 2–10 MPa. The results show that the flame length is dependent on the nozzle diameter, stagnation pressure and temperature. At a given pressure, the flame length, size and total radiant power increase with decreasing temperature, which is attributed to the lower jet flow velocity and higher density of low-temperature hydrogen. The normalized flame length Lf/D is correlated with the pressure ratio and temperature ratio. The correlation can be used to predict the flame length at various hydrogen pressures and temperatures. The normalized flame length of the cryogenic hydrogen jet flame is greater than that of the room-temperature hydrogen jet flame. The radiative heat flux of the flame can be predicted by the mass flow rate of the jet flow.

Experimental Characterization of a Bladeless Air Compressor

Abstract The Tesla compressor is an innovative technology that offers a unique approach to fluid compression. Unlike traditional compressors that use rotating blades, bladeless compressors utilize closely spaced disks to create compression. The purpose of this article is to design a prototype Tesla air compressor with optimal design parameters and investigate the performance and loss characteristics based on numerical analysis and experimental demonstration. The prototype model has been numerically investigated at different rotational speeds, and the results have been compared with those obtained in experiments. Computational fluid dynamics (CFD) simulations indicate that the rotor-only efficiency is greater than 90% at very low mass flowrates, while the coupling of the rotor and volute leads to a total-to-static efficiency of approximately 58% (without losses) at 14 g/s. At a nominal mass flow of 4 g/s, the highest total-to-static pressure ratio would be around 1.27. Experimental results indicate leakage losses greatly reduce net mass flow, while pressure ratio values are in good agreement with CFD predictions. During this experiment, a maximum isentropic efficiency of 32.4% is measured. Indeed, the prototype included ventilation and leakage losses, which were not modeled in the CFD analysis. It is remarkable that the compressor does not show any unstable behavior down to zero mass flow (closed valve test), where the CFD and the experiment show consistent pressure ratios. An estimation of the losses from end-wall friction and leakage flow is carried out using numerical simulations at different exit radial clearances. Increasing radial clearance results in an increase in leakage and end-wall power loss, the latter being driven mainly by the axial clearance with the casing, which remained unchanged. To minimize leakage, a Teflon ring has been used as a first measure. Numerical calculations have indicated that the leakage rate is approximately 6 g/s at design speed. A brush seal-type solution can improve the sealing system to reduce leakage.

Multi-objective optimization and exergoeconomic analysis of a novel solar desalination system with absorption cooling

This paper presents a novel design for a solar-powered desalination system utilizing a single-effect absorption refrigeration cycle with a flat-plate solar collector. The NH3-H2O working fluid pair in the refrigeration subsystem produces chilled water while the rejected heat from the condenser drives a humidification-dehumidification (HDH) subsystem for freshwater generation. This cycle has been analyzed thermodynamically and exergetically to understand its key performance parameters. Furthermore, for a detailed examination and optimization, an exergoeconomic analysis was also conducted. Design parameters for this study include the tilt angle of the solar collector, Volume fraction of nanoparticles in the CuO nanofluid, Solar collector area, Base fluid mass flow rate in the collector, Mass flow rate of the strong solution, Absorber and condenser temperatures, Mass ratio and Humidifier effectiveness. The Objective functions used to evaluate the system, performance are the Cooling effect of performance (COP), Energy performance (EP), Exergy efficiency (μExe), and the Total product cost rate of the system (Ċp,Tot). The genetic algorithm optimization is employed to find the best system performance using two sets of three objective functions. The effectiveness of multi-objective optimization using LINMAP, TOPSIS, and Shannon Entropy methods is demonstrated. LINMAP and TOPSIS consistently achieved improvements in COP (32–42 %), exergy efficiency (33–48 %), and reduced total cost (89–90 %) compared to the base point, while Shannon Entropy offered slightly lower gains. These methods consistently identify superior system configurations, achieving significant improvements in performance while minimizing the total product cost rate.