Adsorption heat storage holds great promise for solar energy applications. The development of new adsorbent materials is currently the research focus in this area. The present work designs several activated carbon models with different functional groups, including -OH, -NH₂, -COOH, and -SO₃H, and explores the influence of functional groups’ categories and numbers on the water adsorption capacity of the activated carbon using the GCMC method. The adsorption mechanism between functional groups and water molecules is analyzed using density functional theory. The results show that the functional groups could significantly improve the water adsorption capacity of activated carbon due to the hydrogen bond between functional groups and water molecules. In the scope of this paper, under low pressure, the activated carbon with -SO₃H exhibits the best adsorption capacity, followed by the activated carbon with -COOH. Under low and medium pressure, increasing the number of -SO₃H functional groups could increase the water adsorption capacity; however, when the pressure is high, increasing the functional group numbers might decrease the water adsorption capacity. As the temperature increases, the water adsorption capacity of activated carbons decreases, and the activated carbon with -SO₃H is proven to have excellent application prospects in heat energy storage.

The formation of gas hydrates due to temperature and pressure changes during gas storage in the wellbore poses significant danger, necessitating the prediction of temperature and pressure distribution as well as of hydrate formation locations. We establish a temperature model that couples total thermal resistance and temperature in the wellbore-stratum composite medium system. Utilizing the two-phase pressure model alongside the temperature model, we conduct coupling calculations of temperature and pressure. Based on both temperature and pressure distribution within the wellbore and hydrate formation curve, we predict hydrate formation regions during production and analyze factors influencing temperature and pressure distribution. Results indicate that gas production rate and specific gravity of natural gas are major influencers on wellbore temperature and pressure distribution, while production time has minimal impact.

This paper presents a numerical study on thermal energy mining from hot dry rock (HDR) using an enhanced geothermal system (EGS). In these simulations, the thermal–hydraulic–mechanical (THM) coupling model is employed on the basis of the embedded discrete fracture model. The evolution of physical fields of the fractured reservoir, including temperature field, pressure field, and stress field is studied over time, and the effects of different controllable factors, such as fracture morphology, fluid injection rate, and the distances between the injection well and producing well on the heat recovery capacity are investigated. The results show that the fracture morphology significantly influences heat extraction performance. The working fluid mainly flows along with the fracture networks, which causes locally low temperatures and low mean effective stress near fractures. The porosity and permeability increase due to the decrease in mean effective stress. For reservoir models with inclined fractures, there will be a significant decrease in the extraction temperature. In the 30th year, the decline in the heat recovery rate is 46.6%, which is much higher than the model without inclined fractures. Moreover, the increasing injection temperature barely influences the production temperature, while it significantly decreases the heat recovery of the EGS. When the injection and production well spacing is small, increasing the well spacing is an effective way to improve the thermal extraction performance of the EGS. In the model in the paper, the heat production increases up to 13.7% when the injection-production well spacing is increased from 150 m to 450 m. The results of this work could provide guidance for the optimization and operation of EGS.

Plate–fin heat exchangers (PFHEs) are widely used in petrochemical, energy and electric power, aerospace, and other industries with large heat transfer requirements. The development of performance prediction and optimization methods for PFHEs has become increasingly important in the design and operation of such heat exchangers (HEs). This paper establishes a database of flow and heat transfer characteristics for four types of PFHEs with different structural parameters. Based on this database, the back-propagation artificial neural network (BP-ANN) model was optimized using the particle swarm optimization (PSO) algorithm to form the PSO-BP-ANN model for the performance prediction of these four types of PFHEs. This combination has been found to improve the prediction accuracy and generalization ability of the BP-ANN model. Additionally, the non-dominated sorting genetic algorithm II (NSGA-II) method was used to characterize the relationship between four structural parameters to be optimized (the length, height, spacing, and thickness of the HE fin) and the two objective functions (j and f) of the serrated PFHE in laminar flow. This enables the Pareto optimal solution to be obtained. The results show that, under laminar flow conditions (Re = 800), the serrated fin HE achieves the best heat transfer performance when the fin height, spacing, thickness, and length are 9.29, 1.22, 0.16, and 3.06, respectively.

A finite volume method based unstructured grid is presented to solve the two dimensional viscous and incompressible flow. The method is based on the pressure-correction concept and solved by using a semi-staggered grid technique. The computational procedure can handle cells of arbitrary shapes, although solutions presented in this paper were only involved with triangular and quadrilateral cells. The pressure or pressure-correction value was stored on the vertex of cells. The mass conservation equation was discretized on the dual cells surrounding the vertex of primary cells, while the velocity components and other scale variables were saved on the central of primary cells. Since the semi-staggered arrangement can’t guarantee a strong coupling relationship between pressure and velocity, thus a weak coupling relationship leads to the oscillations for pressure and velocity. In order to eliminate such an oscillation, a special interpolation scheme was used to construct the pressure-correction equation. Computational results of several viscous flow problems show good agreement with the analytical or numerical results in previous literature. This semi-staggered grid method can be applied to arbitrary shape elements, while it has the most efficiency for triangular cells.