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Heating steel charges is essential for proper charge formation. At the same time, it is a highly energy-intensive process. Limiting the scale formed is critical for reducing heat consumption in this process. This paper applies fuzzy logic to model heating and scale formation in industrial re-heating furnaces. Scale formation depends on the temperature of the initial charge, heating time, excess air coefficient value, and initial scale thickness. These parameters were determined based on experimental tests, which are also the inputs in the model of the analyzed process. The research was carried out in walking beam furnaces operating in hot rolling mill departments. To minimize the excess energy consumption for heating a steel charge in an industrial furnace before forming, a heating and scale formation (HSF) model was developed using the fuzzy logic-based approach. The developed model allows for the prediction of the outputs, i.e., the charge's final surface temperature and the scale layer's final thickness. The comparison between the measured and calculated results shows that the model's accuracy is acceptable. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive review of recent advancements in computational methods for modeling, simulation, and optimization of complex systems in materials engineering, mechanical engineering, and energy systems. We identified key trends and highlighted the integration of artificial intelligence (AI) with traditional computational methods. Some of the cited works were previously published within the topic: "Computational Methods: Modeling, Simulations, and Optimization of Complex Systems"; thus, this article compiles the latest reports from this field. The work presents various contemporary applications of advanced computational algorithms, including AI methods. It also introduces proposals for novel strategies in materials production and optimization methods within the energy systems domain. It is essential to optimize the properties of materials used in energy. Our findings demonstrate significant improvements in accuracy and efficiency, offering valuable insights for researchers and practitioners. This review contributes to the field by synthesizing state-of-the-art developments and suggesting directions for future research, underscoring the critical role of these methods in advancing engineering and technological solutions. [ABSTRACT FROM AUTHOR]

More efficient use of the primary energy contained in fuels translates into tangible earnings for power plants while reductions in the amounts of fuel burned, and of non-renewable resources in particular, certainly have a favourable impact on the natural environment. The main aim of the paper is to investigate the contribution of theuse of adsorption chillers to improve the production energy efficiencyin combined cycle gas turbine. Simulation calculations were performed using Sim tech's IPSEPro software.

An innovative idea, shown in the paper constitutes in the use of the fluidized bed of sorbent, instead of the conventional, fixed-bed, commonly used in the adsorption chillers. Bed–to–wall heat transfer coefficients for fixed and fluidized beds of adsorbent are determined. Sorbent particles diameters and velocities of fluidizing gas are discussed in the study. The calculations confirmed, that the bed–to–wall heat transfer coefficient in the fluidized bed of adsorbent is muchhigher than that in a conventional bed.

Adsorption heat pumps are becoming increasingly popular. Due to their design, they enable application of low-temperature heat sources. Evaporators for adsorption chillers make one of the basic design elements determining the correct operation of these devices. The specificity of operation in low pressures and temperatures is the reason why their design significantly differs from that of conventional evaporators. The pluralities of existing solutions as well as the lack of a systematic review of them cause difficulties in correct evaluation and choice of design. The paper presents the current state of art as well as a review of the existing solutions of evaporators used in adsorption heat pumps. The purpose of the review research is to present various solutions of evaporators as well as indicating their advantages and disadvantages in order facilitate the choice of the optimal design.

Adsorption chillers can be a promising part of sustainable development concept of the global economy due to the utilization of low grade thermal energy sources for cooling production. Therefore, research aiming at improving their performance i.e. Coefficient of Performance (COP) by optimizing the heat and mass transfer condition in the adsorption beds are crucial. Innovative modification of the sorbent layer structure are proposed in the paper in order to improve the heat transfer characteristics in the heat exchanger boundary layer. The analysis of desorption conditions in the parametric model of a coated adsorption bed construction is presented in the paper. The computational fluid dynamics with conjugate heat transfer analysis are used to determine the crucial input parameters for further analytical calculations. The heat transfer condition in novel coated design and a conventional fixed bed are compared in the paper. The developed computational model consisted of three subdomains representing heating water, heat exchanger material (copper) and sorbent (silica gel).

The simultaneous production of electricity, heat and cooling, the so-called trigeneration, allows for substantial savings in the chemical energy of fuels. More efficient use of the primary energy contained in fuels translates into tangible earnings for power plants while reductions in the amounts of fuel burned, and of non-renewable resources in particular, certainly have a favourable impact on the natural environment. The main aim of the above-described project was to analyse the influence of use adsorption contacted to conventional CHP power plant. An adsorption chiller is an item of industrial equipment that is driven by low grade heat and intended to produce chilled water and desalinated water. Adsorption chillers ACH can by used for utilization heat from many industrial process where temperature medium is too low for use absorption chillers. In this article modelled the cycle of a conventional heat power plant integrated with an adsorption chiller-based plant. Multi-variant simulation calculations were performed using IPSEpro simulation software.

A distinct advantage of adsorption chillers is their ability to be driven by heat of near ambient temperature. However the performance of the thermally driven adsorption systems is lower than that of other heat driven heating/cooling systems. It is the result of a poor heat transfer coefficient between the bed and the immersed heating surfaces of a built-in heat exchanger system. The aim of this work is to study the effect of thermal conductance values as well as other design parameters on the performance of a re-heat two-stage adsorption chiller. One of the main energy efficiency factors in cooling production, i.e. cooling capacity (CC) for wide-range of both design and operating parameters is analyzed in the paper. Moreover, the work introduces artificial intelligence (AI) approach for the optimization study of the adsorption cooler. The Adaptive Neuro – Fuzzy Inference System (ANFIS) was employed in the work. The developed ANFIS model can be applied for optimizations purposes and may constitute a submodel or a separate module in engineering calculations, capable to predict the CC of the re-heat two-stage adsorption chiller.

The discretization of computational domain is a crucial step in Computational Fluid Dynamics (CFD) because it influences not only the numerical stability of the analysed model but also the agreement of obtained results and real data. Modelling flow in packed beds of granular materials is a very challenging task in terms of discretization due to the existence of narrow spaces between spherical granules contacting tangentially in a single point. Standard approach to this issue results in a low quality mesh and unreliable results in consequence. Therefore the common method is to reduce the diameter of the modelled granules in order to eliminate the single-point contact between the individual granules. The drawback of such method is the adulteration of flow and contact heat resistance among others. Therefore an innovative method is proposed in the paper: single-point contact is extended to a cylinder-shaped volume contact. Such approach eliminates the low quality mesh elements and simultaneously introduces only slight distortion to the flow as well as contact heat transfer. The performed analysis of numerous test cases prove the great potential of the proposed method of meshing the packed beds of granular materials.

The paper presents the results of experimental and numerical research focused on the reduction of fuel consumption of vehicles driving one after another in a so-called platoon arrangement. The aerodynamic parameters and safety issues were analyzed in order to determine the optimal distance between the vehicles in traffic conditions. The experimental research delivered the results concerning the drag and was performed for simplified model of two vehicles positioned in wind tunnel equipped with aerodynamic balance. The additional numerical analysis allowed investigating the pressure and velocity fields as well as other aerodynamics parameters of the test case.

Computational methods have been widely applied in conjugate heat transfer analysis. The very first and crucial step in such research is the meshing process which consists in dividing the analysed geometry into numerous small control volumes (cells). In Computational Fluid Dynamics (CFD) applications it is desirable to use the hexahedral cells as the resulting mesh is characterized by low numerical diffusion. Unfortunately generating such mesh can be a very time-consuming task and in case of complicated geometry - it may not be possible to generate cells of good quality. Therefore tetrahedral cells have been implemented into commercial pre-processors. Their advantage is the ease of its generation even in case of very complex geometry. On the other hand tetrahedrons cannot be stretched excessively without decreasing the mesh quality factor, so significantly larger number of cells has to be used in comparison to hexahedral mesh in order to achieve a reasonable accuracy. Moreover the numerical diffusion of tetrahedral elements is significantly higher. Therefore the polyhedral cells are proposed within the paper in order to combine the advantages of hexahedrons (low numerical diffusion resulting in accurate solution) and tetrahedrons (rapid semi-automatic generation) as well as to overcome the disadvantages of both the above mentioned mesh types. The major benefit of polyhedral mesh is that each individual cell has many neighbours, so gradients can be well approximated. Polyhedrons are also less sensitive to stretching than tetrahedrons which results in better mesh quality leading to improved numerical stability of the model. In addition, numerical diffusion is reduced due to mass exchange over numerous faces. This leads to a more accurate solution achieved with a lower cell count. Therefore detailed comparison of numerical modelling results concerning conjugate heat transfer using tetrahedral and polyhedral meshes is presented in the paper.

The experimental results presented in the paper and achieved using real datasets from Shanghai Telecom indicate that DQN-ESPA outperforms state-of-the-art algorithms such as the simulated annealing placement algorithm, Top-K placement algorithm, K-Means placement algorithm, and random placement algorithm. High-performance supercomputers and emerging computing clusters created in research and development centres are rapidly increasing available computing power, which scientists are eager to use to implement increasingly advanced computing methods [[1]]. Thus, computationally demanding artificial intelligence algorithms and computational fluid dynamics methods are used more widely to consider complex engineering issues and verify and provide new information on entropy or information theory concepts [[2]]. As can be seen above, the original research articles, as well as review articles focused on optimization by artificial intelligence (AI) algorithms on computational and entropy issues, have been submitted to the Special Issue. [Extracted from the article]

The problem of flow field in the urban boundary-layer (UBL) in aspects of wind comfort around buildings and pollutant dispersion has grown in importance since human activity has become so intense that it started to have considerable impact on environment. The issue of wind comfort in urban areas is the result of complex interactions of many flow phenomena and for a long time it arouses a great interest of the research centres. The aim of article is to study urban atmospheric flow at the local scale, which allows for both a detailed reproduction of the flow phenomena and the development of wind comfort criteria. The proposed methodology involves the use of PIV wind tunnel experiments as well as numerical simulations (Computational Fluid Dynamics, CFD) in order to enhance understanding of the flow phenomena at this particular scale in urban environments. The analysis has been performed for the 3D case of two surface-mounted buildings arranged in tandem, which were placed with one face normal to the oncoming flow. The local characteristics of flow were obtained by the use of commercial CFD code (ANSYS Fluent). The validation was carried out with reference to the PIV results.

Chemical Looping Combustion (CLC) is a technology that allows the separation of CO2, which is generated by the combustion of fossil fuels. The majority of process designs currently under investigation are systems of coupled fluidized beds. Advances in the development of power generation system using CLC cannot be introduced without using numerical modelling as a research tool. The primary and critical activity in numerical modelling is the computational domain discretization. It influences the numerical diffusion as well as convergence of the model and therefore the overall accuracy of the obtained results. Hence an innovative approach of computational domain discretization using polyhedral (POLY) mesh is proposed in the paper. This method reduces both the numerical diffusion of the mesh as well as the time cost of preparing the model for subsequent calculation. The major advantage of POLY mesh is that each individual cell has many neighbours, so gradients can be much better approximated in comparison to commonly-used tetrahedral (TET) mesh. POLYs are also less sensitive to stretching than TETs which results in better numerical stability of the model. Therefore detailed comparison of numerical modelling results concerning subsection of CLC system using tetrahedral and polyhedral mesh is covered in the paper.

Chemical looping combustion (CLC) is one of the most advanced technologies allowing for the reduction in CO2 emissions during the combustion of solid fuels. The modified method combines chemical looping with oxygen uncoupling (CLOU) and in situ gasification chemical looping combustion (iG-CLC). As a result, an innovative hybrid chemical looping combustion came into existence, making the above two technologies complementary. Since the complexity of the CLC is still not sufficiently recognized, the study of this process is of a practical significance. The paper describes the experiences in the modelling of complex geometry CLC equipment. The experimental facility consists of two reactors: an air reactor and a fuel reactor. The paper introduces the fuzzy logic (FL) method as an artificial intelligence (AI) approach for the prediction of SO2 and NOx (i.e., NO + NO2) emissions from coal and biomass combustion carried out in air-firing; oxyfuel; iG-CLC; and CLOU conditions. The developed model has been successfully validated on a 5 kWth research unit called the dual fluidized bed chemical looping combustion of solid fuels (DFB-CLC-SF). [ABSTRACT FROM AUTHOR]

Adsorption cooling and desalination technologies have recently received more attention. Adsorption chillers, using eco-friendly refrigerants, provide promising abilities for low-grade waste heat recovery and utilization, especially renewable and waste heat of the near ambient temperature. However, due to the low coefficient of performance (COP) and cooling capacity (CC) of the chillers, they have not been widely commercialized. Although operating in combined heating and cooling (HC) systems, adsorption chillers allow more efficient conversion and management of low-grade sources of thermal energy, their operation is still not sufficiently recognized, and the improvement of their performance is still a challenging task. The paper introduces an artificial intelligence (AI) approach for the optimization study of a two-bed adsorption chiller operating in an existing combined HC system, driven by low-temperature heat from cogeneration. Artificial neural networks are employed to develop a model that allows estimating the behavior of the chiller. Two crucial energy efficiency and performance indicators of the adsorption chiller, i.e., CC and the COP, are examined during the study for different operating sceneries and a wide range of operating conditions. Thus this work provides useful guidance for the operating conditions of the adsorption chiller integrated into the HC system. For the considered range of input parameters, the highest CC and COP are equal to 12.7 and 0.65 kW, respectively. The developed model, based on the neurocomputing approach, constitutes an easy-to-use and powerful optimization tool for the adsorption chiller operating in the complex HC system. [ABSTRACT FROM AUTHOR]