The application of zero-dimensional mathematical modelling offers significant advantages in the domain of energy systems. Firstly, it serves as a crucial support tool for the design process. Secondly, it facilitates the optimisation of operating parameters, thereby enhancing the efficiency of energy systems. Furthermore, it offers, depending on the accuracy of a model, a comprehensive analysis of the impact of various factors on the performance of a specific system. The present article focuses on a model of a gas turbine unit that has been developed using the EBSILON Professional software. The model was employed to assess the operating parameters that are characteristic of gas turbines, including the turbine inlet temperature and compression ratio, that are crucial for the efficiency and unit power of the abovementioned power system. Moreover, this approach enables the determination of the optimal operating points for the considered assumptions. Next, for the selected case, an analysis was conducted to determine the impact of changes in atmospheric air parameters on the operation of the gas turbine, applying two different approaches. Research has demonstrated that daily, and particularly seasonal, fluctuations in temperature can exert a substantial influence on the efficiency and capacity of the system, while fluctuations in pressure and relative humidity have a much smaller impact on turbine operation. Finally, the simplified model was utilised to ascertain the effect of incorporating hydrogen into fuel on the operational parameters of a gas turbine, indicating the effect of both quantitative and qualitative changes of stream in the combustion chamber and turbine.
The article presents the results of thermal and flow analysis of the working conditions of neighbouring waterwall tubes, loaded with heat streams of different values for two different widths of tube spacing. The numerical model used for the analysis allows us to calculate the temperature distribution in the tubes and in the fluid flowing through them at each time step, depending on the thermophysical parameters of the fluid and the material from which the tubes and fins were made. By using the algorithm, it is possible to precisely determine the three-dimensional temperature distribution in the tubes, allowing us to identify the locations where the greatest temperature differences occur and where the highest thermal stresses may develop. The analysis of several adjacent tubes makes it possible to determine the effect of temperature differences in the tubes and the fins connecting them, and to collect data that may be used to determine the stress distribution in the tubes and fins. In the presented Case 3, smooth tubes connected by fins were used, and the heat flux on the centre tube was 50% higher than that on the outer tubes.
In the present review article, an effort has been made to review various experimental and numerical research, which include heat transfer rate and fluid flow characteristics of a modified solar air heater (SAH) using various artificial roughness. As it is clear that artificial roughness enhances the heat transfer and performance, in this review study, various types of roughened SAH performances have been examined. These various roughness patterns are V-shape, W-rib, arc shape, spherical ball and S-type, and their placement arrangements, like transverse, inclined and longitudinal, are discussed in this article. The comparative studies of thermo-hydraulic performance with heat transfer and fluid flow investigations of various roughened SAHs have been described to identify optimal performance parameters to select the optimum configuration that can be further used for various applications. In addition to this, various correlations of the Nusselt number and friction factor developed by various investigators have also been reported. The main aim of this study is to evaluate the SAH performance using various roughness patterns. It also provides several essential recommendations for effectively designing and implementing SAHs. This review encompasses a comprehensive analysis of 178 research articles published between 1988 and 2024, focusing on advancements in the field. The findings showcase the peak values for the Nusselt number as 7.61, the friction factor reaching 6.48 times that of a smooth duct for discrete multiple-arc ribs, and the maximum thermal-hydraulic performance reported at 4.73 for dimple or protrusion ribs.
Solar air heaters are attractive for low-carbon thermal applications, but their performance is constrained by weak convective heat transfer in the near-wall region. In this work, a single-pass rectangular solar air heater duct equipped with spherical turbulators is investigated numerically and then accelerated using machine-learning surrogate models for rapid prediction of thermal–hydraulic responses. Five turbulator arrangements (V-, M-, W-shaped, inclined, and arc-shaped) were evaluated at three discrete spacing levels (pitch ratio P/D = 3, 6, 9) with a constant sphere diameter of 25 mm over Re = 3500–23 500, consistent throughout all the simulations. The computational fluid dynamics model employed a constant heat flux of 1000 W/m² and standard pressure–velocity coupling/discretisation practices, and was validated against established previous work. A leakage-safe machine-learning dataset (675 samples, 36 variables) was constructed from computational fluid dynamics outputs and physics-informed engineered features; models were trained using geometry-grouped cross-validation to ensure generalisation across turbulator arrangements and spacing levels. Among candidate regressors, histogram gradient boosting provided the best Nu surrogate (OOF RMSE = 3.299, R² = 0.9908, MAPE = 2.44%), while ridge regression yielded the most accurate friction factor surrogate (OOF RMSE = 4.70×10⁻⁴, R² = 0.9886, MAPE = 1.12%). The combined computational fluid dynamics and machine-learning framework enables fast, reliable evaluation of solar air heater thermo-hydraulic performance for configuration screening and optimisation within the validated operating envelope.
This experimental study examines the efficiencies of a cogeneration plant under various constant turbine inlet temperatures. The study considers the effects of changes in mass flow rate, inlet pressure, and inlet temperature on the electrical and overall efficiencies of the system. The findings indicate that the electrical and overall efficiencies are relatively consistent across different mass flow rates but vary slightly across different inlet pressures. The highest overall efficiency and electrical efficiency are obtained at a mass flow rate of 21.56 kg/s, an inlet pressure of 83 kG/cm², and an inlet temperature of 507°C. Under these operating conditions, the overall efficiency reached 58.06%, and the electrical efficiency was 26.26%. These findings suggest that the optimum operating conditions for this system depend on the specific requirements and priorities.
Biomagnetic nanofluids have attracted considerable attention because of their potential applications in biomedical engineering, particularly in drug delivery, cancer therapy, and thermal management systems. In the present study, a nonsimilar analysis of biomagnetic blood-based nanofluid containing multiwalled carbon nanotubes over an exponential stretching/shrinking sheet is investigated. The model incorporates several important physical effects, including a transverse magnetic field, viscous dissipation, suction/injection, particle volume fraction, particle radius, and particle spacing during nanoparticle–blood interaction. The governing partial differential equations are transformed using nonsimilarity transformations and solved numerically through the local nonsimilarity technique with the bvp4c solver in MATLAB. The effects of the physical parameters on velocity, temperature distribution, skin friction coefficient and local Nusselt number are analysed in detail. The results indicate that increasing the magnetic field parameter, particle radius and nanoparticle volume fraction significantly reduces the velocity profile while enhancing the temperature distribution. Moreover, an increase in particle spacing improves both velocity and temperature profiles. Quantitatively, the heat transfer rate decreases by approximately 23.46% and 8.83% in the stretching and shrinking cases, respectively, when the nanoparticle volume fraction increases from 0 to 0.1. Moreover, the skin friction coefficient increases by approximately 24.15% and 23.9% with the increasing magnetic field strength, while increasing the particle radius from 1 to 2 reduces the skin friction coefficient by approximately 16.52% and 33.18% in the stretching and shrinking cases, respectively. These findings provide useful insights for the design and optimisation of biomagnetic nanofluid systems in biomedical and thermal engineering applications.
Use of nanofluids to improve heat transfer properties has drawn considerable concern due to their wide use in various applications such as electronic appliances, fuel cell batteries and hybrid-powered engines. These are only a few examples of the many applications of heat transfer that can greatly utilise the distinctive properties of nanofluids. A magnetohydrodynamic nanofluid convective study is carried out for a sheet stretched under a non-uniform heat source/sink in a permeable medium. The heat transfer analysis simulations entail dissipation of porosity and the presence of Ohmic heating. Non-similarity transformations are then applied to the equations that have been formulated to derive dimensionless partial differential equations. Local non-similarity approach has been used to transform partial differential equations into an equation where partial differential equations can be solved as ordinary differential equations, using the bvp4c MATLAB tool. Every physical parameter is represented in a graphical representation. Moreover, the tables that present the summary of the skin friction coefficient and Nusselt number are evaluated in detail. The main findings of this study include the fact that an increase in the strength of the magnetic field decreases the fluid velocity but improves the thermal distribution. It has been observed that the higher the porosity, the lower the skin friction. In addition, high radiation levels also help in having a more favourable temperature field.
The current study focuses on the numerical analysis of magnetohydrodynamic Casson hybrid nanofluid blood flow carrying hybrid nanoparticles through a porous stenotic artery. To improve thermal conductivity and flow management in the presence of a heat source/sink, gold-silver nanoparticles are suspended in the base fluid (blood). The governing highly nonlinear differential equations for momentum and energy are solved using MATLAB's bvp4c solver, ensuring high accuracy and stability. The effects of various physical parameters, including the magnetic parameter, permeability, curvature, Casson parameter, Eckert number, and heat source/sink parameter, are examined on the velocity, temperature, skin friction, and Nusselt number profiles. The results indicate that higher magnetic field strength and permeability reduce velocity due to Lorentz and frictional resistance, while increases in curvature and the Casson parameter enhance the flow rate. The temperature distribution is notably elevated by magnetic forces, viscous dissipation, and internal heating, with hybrid nanoparticles contributing to enhanced thermal energy. The correctness of the model is validated by its strong agreement with previously reported results. These findings provide important insights for biomedical applications such as targeted drug delivery, heat-assisted therapies, and blood flow regulation in diseased arteries, offering a reliable computational framework for future research on nanoparticle-assisted magnetohydrodynamic flow through porous biological channels.
The present study investigates the influence of a non-uniform heat sink/source on the unsteady flow of Boger liquid via a slowly rotating stretching disk subjected to suction and convective boundary conditions. This study is significant because it helps optimise cooling and heating processes in chemical, pharmaceutical and energy systems. The research also highlights methods for managing heat and mass transport in porous and industrial materials. Overall, it helps to improve performance, stability and energy efficiency in engineering and applied science. Dimensionless ordinary differential equations are obtained by transforming the governing partial differential equations using similarity variables. The resultant non-dimensional ordinary differential equations are solved numerically utilising the finite difference method. Furthermore, the fluid flow, mass and heat transfer are evaluated using an artificial neural network approach. Additionally, the response surface methodology is used to assess the heat transmission rate statistically. The influence of different parameters on the concentration, velocity and thermal profiles is exemplified graphically. Increasing the suction parameter, relaxation time ratio and magnetic parameter reduces the velocity profile. The thermal profile enhances as the space- and temperature-dependent heat sink/source parameters increase.
This paper aims to clarify the conditions required to derive, within the framework of Finite Time Thermodynamics, the efficiency of "endoreversible cycles" (Eq. (1) of this paper). It is shown that the steady-state enthalpy and entropy balances of the working fluid at maximum power, the finite time thermodynamics optimum, lead to this efficiency. This result is obtained without introducing the "finite time" of the cycle, the most usual approach. To compute this efficiency for real systems, the heat source and sink temperatures must be clearly defined. In complex systems such as nuclear reactors, several choices of the upper temperature are possible. For a rational choice - using the steam generator as the heat source - these temperatures are relatively low, and the finite time thermodynamics optimum corresponds to unrealistic operating conditions, slightly underestimating actual efficiencies. Conversely, higher upper temperature values yield more realistic conditions but overestimate efficiency. The finite time thermodynamics limits are revealed by computing all thermodynamic cycle parameters and introducing irreversibilities in the working fluid. The cycle specific net work (MJ/kg) appears to be a more relevant optimisation criterion for real systems. This supports the idea that acceptable predictions from finite time thermodynamics efficiency result from compensating errors: low maximum temperatures balanced by the ideal cycle assumption. A general efficiency equation better illustrates why actual efficiency remains below Carnot's, clarifying optimisation issues in energy conversion systems and the trade-off between reducing irreversibilities and maximising average heat source temperature.
By giving the absorber plate artificial roughness, the efficacy of a solar air heater may be increased. A mathematical study has been performed on solar air heaters roughened with Z-shaped baffles. With the help of MATLAB code, an exergy analysis, estimation of exergetic losses and efficiency have been made. The effect of relative pitch ratio for 45° zig-zag structured baffles with a fixed relative blockage height of 0.3 on various exergy parameters has also been studied. The current study has been done for Reynolds numbers ranging from 3000 to 14 000 and for 1100 W/m² of solar radiation. It is deduced that with the increase in Reynolds number, the effective efficiency enhances up to a certain point, beyond which it begins to decline. Moreover, the pitch ratio of 1.5 has shown the best performance up to the Reynolds number of 5000, while at higher Reynolds numbers, the pitch ratio of 3 has produced better results.
This study employed a three-dimensional CFD model with integrated chemical kinetics using CONVERGE CFD software. We used a detailed mechanism of 42 species and 167 reactions and compared its predictions with a reduced 77-species mechanism developed by Liu and Zhang (2023), both tailored for n-heptane oxidation. Validation of diesel-injection combustion was carried out by comparing the model results with experimental engine data. Numerical simulations were conducted on an MKDIR 620-145 engine at 1400 rpm and 50% load. The chosen models reproduced the mean in-cylinder pressure accurately, with deviations below 4.7%. Analysis of species and thermal fields revealed that key intermediate species emerge near 930 K, where H₂O₂ concentrations become sufficient to trigger auto-ignition and the heat release rate reaches its peak. At higher temperatures (around 1300 K), OH and CO concentrations are notably elevated. Soot production is initiated early in combustion and is dominated by diffusion processes; the peak net soot mass was 3.25×10⁻⁷ kg at 18° before the top dead centre. Throughout combustion, CO₂, H₂O and hydrocarbon concentrations increase markedly while O₂ is consumed, with CO₂ and H₂O rising rapidly during both premixed and diffusion combustion phases. NOx formation closely follows the temperature history, approaching a saturation level near 1.1×10⁻⁴ kg under the studied conditions. Overall, the results indicate that the employed reaction mechanisms capture the temporal evolution of combustion, species formation, soot production and emission trends with good fidelity, supporting their suitability for studying fuel behaviour and emissions in diesel engine environments.
This study explores the potential of converting syringe plastic waste into an alternative fuel through pyrolysis. Since sy-ringes are primarily made of polypropylene, they were thermally decomposed in a batch reactor, producing a maximum pyrolysis oil yield of 76% at 400–500°C. The produced syringe plastic oil (SPO) was characterised for key fuel properties and blended with diesel at 20%, 30%, and 40% proportions. The performance of the engine and the emission characteristics of these blends were tested experimentally on a common rail direct injection diesel engine. Of the fuels tested, the D80SPO20 mixture proved to be as efficient as diesel with the brake thermal efficiency of 26.9% and brake specific fuel consumption of 0.27 kg/kWh at full load. This mixture was also found to result in a significant reduction in carbon mon-oxide, hydrocarbons and smoke emission with a slight increment in NOx relative to diesel. On the whole, the findings show that low-percentage SPO30, especially D80SPO20, provide a favourable combination between engine efficiency and emis-sion reduction, proving the potential of the syringe plastic pyrolysis oil as a sustainable alternative of diesel fuel in part.
Solar heating devices have been extensively investigated to maximise energy utilisation and improve overall thermal efficiency. The present study aims to evaluate the performance of an evacuated tube heat pipe collector with nanofluid and compare it with a conventional heat pipe collector operating without nanofluid, with particular emphasis on the water outlet temperature. In the available literature, several studies have examined the effects of parameters such as the collector inclination angle, nanofluid concentration, and water inlet temperature on the thermal performance of evacuated tube solar collectors. However, a comprehensive comparative analysis incorporating all these parameters on a common experimental platform has not been adequately reported. In the present work, the variation in outlet temperature was systematically analysed by considering independent parameters such as the angle of inclination, copper oxide (CuO) nanofluid concentration, and water inlet temperature. Furthermore, the analysis of variance (ANOVA) was performed on the experimental dataset to evaluate the statistical significance and reliability of the obtained results.
A novel power-cooling system triggered by low-grade thermal energy is proposed and studied in this paper. The power-cooling unit combined the engine (organic Rankine cycle) and cooler (ejector-expansion refrigeration cycle employing a booster). Both cycles employ isobutene (R600a) as a working fluid and share a single condenser unit. The performance characteristics (overall coefficient of performance and working fluid mass flow rate per kW of cooling capacity) of the novel unit was investigated using thermodynamic analysis in comparison to the traditional unit that is commonly used. The latter combines the engine (organic Rankine cycle) with the cooler (vapour compression refrigeration cycle) in various operational conditions, including exit temperatures of a boiler unit (60-90 degrees C), a condenser unit (30-55 degrees C) and an evaporator unit (-15-15 degrees C). It was discovered that in comparison to the traditional unit, the novel unit exhibited lower working fluid mass flow rate per kW of cooling capacity and higher overall coefficient of performance. The overall coefficients of performance for both systems increase by 0.5385 and 0.4476, respectively, when the boiler unit's temperature reaches 90 degrees C and the other input specifications are set to typical values. On the other hand, the working fluid mass flow rate per kW cooling capacity of both systems drops by 0.0096 and 0.0064, respectively. Overall, the study demonstrates that the novel system triggered by low-grade thermal energy can be an alternative to the traditional system.
The collective influence of slip and asymmetric heating is of great importance in many industries involving micro and macro-scale thermal systems, as it is directly related to flow resistance, thermal gradients and entropy generation. These effects are particularly relevant in channels with immiscible fluids, where wall fluid interactions and spatially varying boundary conditions govern the overall transfer behaviour. So the novelty of this work is a numerical analysis of entropy generation and heat and mass transfer in a vertical channel filled with two immiscible fluids, under a non-uniform heat, along with the influence of velocity slip. The system of governing equations of momentum, energy and diffusion is made non-dimensional using relevant variables, and then solved numerically using the Runge-Kutta method. The momentum, temperature and diffusion variations are presented in a graphical mode using data visualisation and smoothing via interpolation in Python for better visibility of the variations. The momentum, heat and mass transfer rates on both plates of the channel are also made non-dimensional. The other important parameter, entropy, is also calculated in the defined domain, and the obtained values are tabulated. The study found that all parameters, including slip effect, have a significant impact. In particular, the temperature, entropy generation and velocity are strongly affected by buoyancy forces and magnetic fields. The increase in Grashof number and molecular Grashof number improves fluid motion and reduces entropy. Both the increasing Reynolds number and magnetic parameter contribute to an increase in entropy generation. Shear stress analysis reveals two flow layers affected by buoyancy and magnetic damping.
This article investigates the parametric effects on heat transfer in cross-flow heat exchangers integrated with a backward splitter plate to enhance the coefficient of performance in a solar assisted vapour absorption refrigeration system. The system replaces conventional electric energy with solar energy, utilising a solar energy collector to heat water between 50-80 degrees C. This heated water vaporises aqueous ammonia in a generator designed as a double pipe heat exchanger. The primary objective is to facilitate efficient heat transfer from the solar energy collector to the solar assisted vapour absorption refrigeration system and evaluate the cooling performance at varying water mass flow rates. Computational fluid dynamics has been used to solve the governing equations under appropriate boundary conditions. While second-order discretisation has been used for momentum and energy equations, coupled equations have been used to address velocity and pressure coupling. Convergence criteria of 10-6 for velocity and continuity, and 10-8 for energy, were employed. Thermal modelling was conducted to find out component-specific heat transfer rates and estimate the cumulative coefficient of performance. A small-capacity (1.5 ton or 5.25 kW) solar vapour absorption cooling system was tested. The study found that increasing the L/D ratio enhances heat transfer; for instance, at Re = 12000 and L/D = 2, the Nusselt number increased by 90% compared to Re = 2000. However, the pressure dropped significantly at L/D = 3, suggesting an optimal design trade-off. Additionally, the impact of key parameters such as absorber, condenser, generator and evaporator temperatures on the system's coefficient of performance was thoroughly analysed.
Experimental research, especially physical modelling, is vital when direct study of real systems is impractical. By applying similarity theory and dimensionless variables, models allow reliable analysis of results. While experiments alone are often qualitative and time-consuming, combining them with theoretical modelling yields stronger quantitative insights. Careful planning, computer-based data collection, and awareness of measurement errors ensure precision and efficiency. The theory of similarity defines the criteria under which the behaviour of a model can be considered representative of the real system. By satisfying these criteria, experimental results obtained from the model can be reliably extrapolated to the actual phenomenon. The present paper aims to present Authors' up-to-date experiences in advanced research using scaled models based on similitude theory, ever since its establishment as a branch of the engineering science to convince the reader about the benefits of physical modelling in comparison to advanced computer based methods governing the contemporary research.
This paper presents the development of a novel experimental device for measuring the thermal conductivities of both nonconductive and conductive solids under transient conditions. The device comprises a sensor assembly coupled with an electronic bridge circuit and a direct current power source. The developed device was successfully used to measure the thermal conductivity of non-conducting and conducting solids, specifically granite and stainless steel 304, at room temperature. The device was also extended to two additional non-conducting solids, namely, limestone and basalt, to validate the testing. The thermal conductivities of granite, stainless steel-304, limestone and basalt were 2.14 W/(m & centerdot;K), 14.93 W/(m & centerdot;K), 2.91 W/(m & centerdot;K), and 2.72 W/(m & centerdot;K), respectively. These findings demonstrate excellent concordance with the existing literature for both nonconducting and conducting solid materials. The standard uncertainty of the developed device was +/- 4.2%. The entire measurement process takes less than 5 s.
In order to accurately predict the energy consumption and design energy-saving retrofits for office buildings, this study proposes a climate adaptation-based energy consumption prediction method by combining depthwise separable convolution and frequency-guided two-dimensional tensorisation algorithm. A multi-objective optimisation retrofit design model is then constructed using the non-dominated sorting genetic algorithm III and ideal point method. Experimental results show that the prediction method achieves the highest accuracy of 96.3% and the lowest error rate of 5.9% under various climate conditions, outperforming comparison algorithms. In practical applications, the retrofit design model responds in as little as 7.3 s and consumes a minimum memory of 189 MB. With a 30% increase in electricity prices, the payback period is only 6.05 years, and the carbon reduction rates for air conditioning and lighting are 59.9% and 58.6%, respectively. The results indicate that the proposed model provides a design solution with high prediction accuracy, robustness and cost-effectiveness, improving the feasibility of office buildings' low-carbon transformation.
