The application of exergy analysis in thermodynamic systems is rapidly expanding alongside energy analysis, providing valuable insights into processes causing exergy destruction and losses. Environmental concerns have driven increased investigation on heat recovery, with the Organic Rankine Cycle (ORC) emerging as an effective solution for converting low-temperature waste heat into useful work. This research performs a comparative and optimization assessment of various carbon dioxide Rankine cycles-namely simple, cascade, and split configurations-specifically for recovering waste heat from gas turbines. This research employs a multi-objective optimization strategy, validated by simulation outcomes, that integrates a Genetic Algorithm with various machine learning techniques-such as Random Forest, XGBoost, Artificial Neural Networks, Ridge Regression, and K-Nearest Neighbors- to forecast the performance of the cycle. Results highlight the split cycle's superior power generation, achieving optimized performance metrics of 7.99 MW net power output, 76.17% heat recovery, 26.38% system efficiency, and 57.96% exergy efficiency, positioning it as a promising solution for waste heat recovery applications.

Accurately predicting wall temperature and emissions in coal combustor is essential for design and control, yet full-fidelity simulations are too slow for rapid studies. We propose a hybrid approach that couples computational fluid dynamics (CFD) of a 2-D, radiating, axisymmetric coal flame with a multilayer perceptron (MLP) surrogate. The CFD model resolves turbulence, devolatilization, and volatile/char oxidation and generates a dataset across coal/air flow rates, inlet velocity profiles, and initial particle temperature. The MLP learns the mapping from operating conditions to wall-temperature and emission fields and is validated on unseen cases. The surrogate attains ∼8% error while cutting evaluation from hours to milliseconds. Physically, higher initial coal temperature shifts reaction zones upstream, enhances burnout, and modifies CO and SO2 levels. This CFD-to-ML pipeline enables rapid what-if analysis and data-driven optimization, offering a practical path toward real-time monitoring and digital-twin control of coal combustion systems.

This study investigates the application of the Levenberg-Marquardt method in solving inverse heat transfer problems for a lid-driven cavity with four unknown thermal boundary conditions. The direct problem is solved using computational fluid dynamics (CFD) techniques implemented in OpenFOAM, employing the URANS equations. The numerical framework is first validated against experimental data from literature for a cavity with known boundary conditions. The inverse analysis focuses on simultaneously estimating four wall temperatures using temperature measurements at various sensor locations. The effects of sensor quantity and placement, algorithm parameters (fractional increment and damping coefficient), and measurement noise on the solution accuracy are systematically examined. The algorithm demonstrates robust convergence using a fractional increment of 0.0001 and an initial damping value of 1.0. It also maintains stability and accuracy even when measurement noise reaches up to 10 % of the maximum temperature difference. Under various conditions, the proposed approach consistently converges in approximately 12 iterations, confirming its effectiveness for simultaneously estimating multiple thermal boundary conditions in enclosed cavities. This study contributes to the development of reliable inverse methods for industrial applications involving natural convection in temperature-controlled chambers.

This paper employed the Levenberg-Marquardt Algorithm to solve the inverse problem of estimating non-uniform heating boundary conditions in a diagonal lid-driven cavity. The non-uniform thermal conditions on lateral walls were exponential, triangular, and sinusoidal-cosinusoidal. The finite volume method run in the Open FOAM software was used to solve the problem directly. The effect of the numbers and positions of sensors on estimation accuracy was examined for data collection, and sensitivity to noisy data was analyzed at different levels. The results showed that the proposed approach could estimate thermal boundary conditions with acceptable accuracy even when the measured data were noisy. The convergence analysis revealed that the model converged with a steep slope. This approach can be employed to determine the distribution of wall temperature in engineering uses, such as heating and cooling systems and heat transfer phenomena.

The process of managing waste heat from various thermal sources shows promising outcomes in the field of energy conversion. Thermoelectric generators integrated with phase change materials containing porous foams are valuable means for converting waste heat into electricity. Installing these systems on common heat sources and implementing an effective strategy for managing waste heat fills a major gap in current research in this area. The goal of this study is to utilize a novel prototype hybrid configuration to manage waste heat from an industrial chimney for the first time. ten thermoelectric modules equipped with phase change material and copper foam were installed on the chimney body, serving as an energy storage unit on the hot-side of the module and as a heat sink on the cold-side. Therefore, continuous and fluctuating heat loads were imposed to the chimney initiating from ambient temperature. The findings of this study indicate that the proposed system was effectively powered by the waste heat from the chimney body. The phase change material on the hot-side prevented overheating and stabilized the cold-side's temperature, acting as a heat sink without using electrical energy. This created a sufficient temperature difference, enabling the system to generate voltage for an extended period. The system produced maximum output voltages of 3900 mV and 6100 mV under constant loads of 75 W and 125 W, respectively. Under fluctuating loads of 150 W and 200 W, it maintained effective performance with maximum output voltages of 4700 mV and 5300 mV. The hybrid case described offers an innovative approach to managing waste heat in industrial settings, resulting in enhanced cost savings.

In present study, to support the implementation of free cooling concept in unfavorable climatic condition, a new system was proposed and optimized. Building energy simulation (BES) was carried out to evaluate the energy and thermal comfort based optimization of building construction integrated PCM. The total building energy consumption and Predicted Percentage Dissatisfied (PPD) were selected as two objective functions, which are strongly nonlinear, coupled and conflicting. The model was tested on proposed system in Tehran weather conditions. Optimization results showed that for studied wether condition, the system can decrease to tal cooling energy about 36% while at the same time PPD reduces about 35% for PCM energy storage compared to the base design.

Phase Change Materials (PCMs) have recently garnered attention for many new applications. However, one of their main challenges is integrating them into complex geometries. The present study has developed polymer composite capsules containing PCM for Thermal Energy Storage (TES) systems. A simple one-step emulsion polymerization method was used to fabricate paraffin@styren (PCM@ST) nanocapsules. The surface of the spherical nano-encapsulated PCMs was uniform, smooth, and compact, with particle sizes ranging from 200 to 400 nm. These nano encapsulated PCMs demonstrated stability and reliability, with a melting enthalpy of about 64.93 J/g and crystallization enthalpy of about 66.45 J/g. TGA results indicated that the nano-encapsulated PCM degraded in three steps and exhibited good thermal stability, with an encapsulation efficiency (phi) of 52.95%. These findings suggest that PCM@ST nanocapsules could be promising candidates for thermal energy storage applications.

This study investigates pressure gradient dynamics within a porous medium in the context of two-phase fluid flow, specifically water and sand particle interactions. Using experimental data, we refine pressure correction coefficients within a numerical solution framework, employing the Semi-Implicit Method for the Pressure-linked Equations algorithm. Our findings highlight the relative nature of pressure gradient phenomena, with particle size and volume fraction emerging as crucial determinants. Graphical representations reveal a clear trend: an increase in volume fraction, up to 40%, across varying Reynolds Numbers, leads to a transition towards non-Newtonian behavior in the two-phase fluid system. Unlike the linear pressure gradient seen in single-phase fluid flow, the interplay between liquid and solid phases, along with drag forces, imparts a distinctly nonlinear trajectory to the pressure gradient in two-phase fluid flow scenarios. As the two-phase flow enters a porous medium, numerous factors come into play, resulting in a pressure drop. These factors include changes in cross-sectional geometry, alterations in boundary layer dynamics, and ensuing momentum fluctuations. Interestingly, an increase in porosity percentage inversely correlates with pressure gradient, resulting in reduced pressure gradient with higher porosity levels.

The flow field geometry mainly affects the electrochemical reaction, the mass transfer, and gas diffusion layers. All these parameters affect the performance of a PEM fuel cell. In this study, a three-dimensional model is used for all parts of the fuel cell such as the flow channels, gas-diffusion electrodes, catalyst layers, and the membrane. These equations are numerically solved using a finite volume-based computational fluid dynamics technique to investigate the effect of using new geometries such as tubular, rectangular, elliptical, and triangular compared to planner-type fuel cells. Also, a test bench was designed and constructed for checking the cell and a series of experiments were done. The results show that there is good agreement between the numerical and experimental results. In summary, the tubular geometry has the best performance compared to others which can increase the execution of the fuel cell maximum by 43%.

Utilization of waste heat in processes of oilfield plants has been taken into account as the most promising technology to improve thermodynamic performance. This paper proposes and investigates alternative Orangic Rankine Cycle (ORC) based combined systems for recovering moderate- to-low temperature waste heat of flue gas based on energy and exergy analysis. Advanced exergy analysis, splitting the exergy destruction into endogenous/exogenous and avoidable/unavoidable parts, is applied to reveal more detailed information about the components' inefficiency on each other and the real potential of the optimized system for improvement. With the help of the presented model and the genetic algorithm optimization method, the optimal configuration and operating fluid in terms of power generation. The investment cost was chosen for low and medium heat demand. The results showed that the working fluid R123 has a better performance than toluene for medium heat demand, parallel configuration with preheater and R123 working fluid and low heat demand, parallel configuration of preheater and recuperator with R123 working fluid is the most appropriate choice. In these cases, the maximum production power was calculated as 3.56 and 5.12 MW respectively, while the special investment costs for the proposed items were evaluated as 1.631 and 1.63 $/W respectively.

This paper investigates the general form of a problem of stagnation-point flow of a viscous, nanofluid that impinges along z-direction on a stationary flat plate. In this study, a three-dimensional flow is produced by an external flow including Al2O3 nanoparticles that impinge on the plate, along the z-direction, with strain rate a . The density and viscosity of the nanofluid are affected by the nanoparticles. Appropriate formulas are employed to calculate the density and viscosity of the nanofluid. Suitable similarity transformations are introduced for the reduction of the steady, three-dimensional, Navier-Stokes equations to couple non-linear ordinary differential equations. These governing equations are numerically solved using the order Runge-Kutta method along with a shooting technique for a wide range of characterizing parameters. The obtained results illustrate that if the value of particle fraction increases, the value of the velocity components and pressure gradients decreases in the vicinity of the plate. It was also shown that as the flow patterns are moving from a two-dimensional case to an axisymmetric case, the velocity components as well as dimensionless pressure gradients increase in the vicinity of the plate. The problem is particularly important in the cooling process of electronic devices turbine blades and high-pressure washers.

This study aims to investigate density changes and deposition thickness in two-phase fluid flow through a porous medium using a discrete phase model. The deposition process is a complex phenomenon influenced by gravity forces, which cause particles to settle downward. The methodology employed in this study enables particle tracking, sediment layer analysis, and characterization based on sediment particle count. As the sediment layer thickens, the distance between the fluid and the wall decreases, leading to changes in the flux reaching the fluid. Deposition results in a reduction in the concentration of sediment materials in the fluid. Porous media offer an effective means of inducing deposition, which grows uniformly over time. Critical factors such as turbulence, dissipation rate, momentum, eddy formation, and particle diameter significantly influence deposition formation. The findings indicate that at a Reynolds number of 50000, the deposition thickness is lower compared to a Reynolds number of 1000, and the deposition thickness is also lower for a 1 µm particle diameter compared to 500 µm. The introduction of an oscillating frequency to the porous medium increases particle energy and promotes porosity-oriented behavior. Specifically, a frequency of 500 Hz demonstrates enhanced cleaning compared to 50 Hz. The porous medium can be effectively cleaned using oscillating frequencies.

The unsteady, viscous flow of Nanofluid in the vicinity of an axisymmetric stagnation point of an oscillating cylinder is investigated. The cylinder is moving toward or away from the impinging flow. The impinging free stream is steady and with a constant strain rate (k) over bar. Self similar solution of the Navier-Stokes equations is derived from this unsteady problem. A reduction of these equations is obtained by use of appropriate transformations introduced for the first time. All the solutions above are presented for Reynolds numbers Re = (k) over bara(2)/2 upsilon(f) ranging from 1 to 2000, selected values of dimensionless time, and selected values of particle fractions where a is cylinder radius and upsilon(f) is the kinematic viscosity of the base fluid. For all Reynolds numbers, as the particle fraction increases, the depth of diffusion of the fluid velocity field in the radial direction, the depth of the diffusion of the fluid velocity field in z-direction, and shear-stress decreases. Furthermore, it has been determined that the maximum dimensionless shear stress is 370, which corresponds to a volume fraction of 0.05 and T* = 0.45. Additionally, for all volume fractions, the maximum and minimum values of the hydrodynamic boundary layer thickness are associated with T* = 0.75 and T* = 0.45, respectively. The problem is particularly important in pressure -lubricated bearings.

Phase Change Materials (PCMs) have recently found a wide range of new application opportunities. In this study, PCMs microcapsules have been synthesized with urea-formaldehyde polymer shell. The microcapsules have been characterized by FT-IR, SEM, TEM, and DSC analysis. Then, the thermophysical characteristics of the MEPCM suspension including the thermal conductivity, and viscosity have been measured at different particle concentrations (2, 5, and 10 wt%) and different temperatures from 25 to 50 degree celsius. New correlations are developed to predict the thermophysical characteristics of MEPCM suspensions. This work provides a practical and efficient synthetic strategy for the preparation of MEPCMs, which is expected to present a promising future in the field of energy storage.

In this paper, for the first time, a numerical code based on the Levenberg-Marquardt method is presented to solve the inverse heat transfer problem of an annular jet on a cylinder with uniform transpiration and estimate the time -dependent wall temperature using temperature distribution at a point. Also, the effect of noisy data on the final result is studied. For this purpose, the immediate task is to solve the temperature with no dimensions and convection Heat transfer in a cylinder with a radial incompressible flow numerically. The free stream is steady, and the initial strain rate of flow is K. The equations of momentum and energy are transformed into semi -similar equations using similarity variables. After discretizing the new equation system using the finite difference technique, it is solved by using the tri-diagonal matrix algorithm. After that, the wall temperature is calculated throughout using the Levenberg-Marquardt approach. This is a collaborative technique aimed at minimizing the least -square summation of the error values, where the error indicates the difference between the predicted and observed temperatures. This method exhibits considerable stability for noisy input data. In most cases, surface blowing decreases the prediction accuracy by displacement of the boundary layers from the surface, whereas suction acts vice versa. The main reason for this study is that in many industrial applications, it is not possible to insert the sensor on the wall to measure the temperature of the wall the sensor can be inserted in another place and the wall temperature distribution can be obtained by inverse analysis (Determining of unknown boundary condition).

Today, energy efficiency is one of the global requirements. The purpose of this study is thermodynamic modeling of using a horizontal heat pump system in residential houses in Shahrood climate and to investigate its effect on optimal energy consumption. For this purpose, a heat pump system was designed. Through mathematical functions and modeling equations, the technical, environmental and economic aspects of conventional systems and the proposed model were compared. In order to calculate the hot and cold design loads required in the optimization, Carrier HAP software was used. Initially, a hypothetical residential unit with an area of 96 square meters was designed using Google Sketchup software. The modeling results show that the proposed system (GSHP) is superior to conventional systems in all aspects except one, which is the initial cost of design and construction. So that the reduction of electricity consumption is 11.7% and the reduction of energy consumption is 4.4% and the reduction of carbon dioxide emissions is about 83%. Also, the optimal consumption of heat pump for cooling and heating in Shahrood is 2.8 and 6.3, respectively. Finally, the energy efficiency is 77%. As a result, given the rise in fossil fuel costs, rise in concerns regarding the damages to the environment, and the need of countries for sustainable development, growing tendency to this technology is not far from mind.

In this study investigated the deposition of micro-scaled particles using the lattice Boltzmann (LBM) and finite volume (FVM). A real-time data transfer is used to transfer data between LBM and FVM, while a special grid generation algorithm is used to generate a boundary grid around the micro-particles. In order to track particle information such as velocity, direction, and concentration over time, an adaptive interface is developed between FVM and LBM zones. The pore-scale porous media approach is assumed to further improve the results’ quality and reliability. Pores have an average diameter of two mm, while micro-particles have an average diameter of 0.2 mm. The results showed that the deposition layer’s formation directly affected the fluid’s flux rate at the inlet. Heat transfer coefficients of the fluid change in response to the density of the fluid as the deposition layer thickness increases. The thermal conductivity coefficient of the wall decreases as the deposition layer increases, which is variable over time and along the path. Furthermore, we found that heat transfer and pressure drop are affected by the deposition process in the porous medium. Porous media with an increasing pressure drop are also subject to an increasing pressure drop due to the deposition process. In addition, the particles’ thermal conductivity can affect the porous medium’s net heat transfer rate. The heat transfer coefficient has been evaluated, and the results showed that 8.43% exists between the numerical analysis and the results of the empirical test at the highest error value. Existing particles’ density bank in the porous medium beats, such particles exhibit little change due to their extremely small size, resulting in a 0.4 percent and 0.5 percent increase in pressure drop due to deposition at 100. It showed that the suggested method of grid generation based on the cell birth–death algorithm, which serves as the foundation for the particle’s transfer tracking algorithm, the porous medium abled track 70 million particles.

Growing attention to the Geothermal Heat Pump (GHP) system highlights the necessity of using the technology in an optimized way. Since geographic and meteorological conditions have substantial effects on the efficiency of GHP, a technical and economic feasibility study on a regional scale was performed on residential buildings using R600a as a natural refrigerant. The investigation consists of numerical modeling and enhancement of Horizontal Geothermal Heat Pump Systems (HGHP) by a meta-heuristic algorithm, spatial cooling/heating design load calculation, and regional data exploration to attain a priority map based on economic factors of 96 geographical points in Iran as a case study. The modeling and optimization approach validation was investigated by comparing the computed results with those published in references. Particle Swarm Optimization (PSO) was used as an optimization tool due to its simplicity and accuracy. The effects of geographical factors, including heating & cooling load, cooling to heating load ratio, and different soil types on the objective function, and Total Yearly Cost (TYC) were presented in a table and investigated to have a better picture in a general exploration study. Finally, Iran's HGHP priority map was accurately presented in this study to help policymakers with decisions concerning technology subsidization. This map helps the investigators to have a better picture of the total affecting parameters on GHP system installation.

Combustion phenomenon in combustion chambers used in gas turbines is a complex process in which various factors are involved. Energy loss in these combustion chambers due to chemical reaction factors, internal heat transfer, mass transfer and viscous losses reduces the efficiency of these units and ultimately greatly reduces the overall efficiency of a gas turbine unit. Therefore, it will be very useful to provide a method by which the combustion process and the type of flame can be modelled. Since the fuel used in combustion chambers as an energy carrier may change, it is both time-consuming and costly to perform testing processes under the conditions of using new fuels to determine operating point parameters, so the novelty of this paper presents a general approach. It can be used for any type of fuel only by changing the environmental parameters. The β-PDF approach is proposed to model the thermochemical scalars (i.e. temperature, species mass fractions, and density) as functions of mixture fraction by assuming the fast chemistry. Next, the entropy generation analysis is applied to quantify the contribution of each irreversible process (i.e. heat transfer, mass transfer, chemical reaction, and viscous dissipation) to the total exergy destruction, and theoretical findings are finally presented to relate the exergy losses to the design parameters of the combustor. In this regard, a well-known non-premixed jet flame is considered as the case study in this paper, named the Sandia/ETH H2/He flame. A comparison of the obtained results based on the proposed modelling method and the experimental results confirms the effectiveness of the proposed estimation strategy. Also, entropy generation analysis of the flame demonstrates that the chemical reaction is the dominant irreversible process in the total exergy destruction in turbulent non-premixed flames (85.13%), followed by mass transfer (8.05%) and heat transfer (6.80%). By modelling any desired flame based on the proposed PDF method, two main goals are achieved: first, all the necessary parameters to determine the physical model of the flame can be estimated, thus avoiding multiple experimental tests. Secondly, it is possible to identify the factors affecting the entropy production and ultimately the effect on heat loss by estimating the model for each flame, and by optimizing these factors, heat loss in combustion chambers can be prevented.

Using the Combined Heat and Power (CHP) systems are known as one of the most effective ways to raise the power coefficient and reduce fuel consumption and operational costs. In this study, a CHP system with the prime movers of a gas turbine and a horizontal axis wind turbine under the strategy of providing electric charge has been investigated based on the first and second laws of thermodynamics. This study aims to evaluate the effect of a wind turbine on the CHP system. The results show that the proposed CHP system has significant advantages compared to the CHP system working without the wind turbine. The best operating condition for the wind turbine is at the wind speed of 12 m/s, the pitch angle of 5ο and the tip speed ratio of 3. Moreover, the effects of the wind speed and tip speed ratio on the exergy efficiency of the total system become considerable when the gas turbine works at the high-pressure ratios (more than 10) and the combustion chamber temperature below 1250οc. Also, it is shown this integrated system can reduce operational costs and fuel consumption by 55 % and 60%, respectively. Finally, regarding the interest rate, the payback period will be equal to 5.4 years.