Thermal Science and Engineering Progress最新文献

The growing solar industry and technological developments that increase the efficiency and affordability of solar plants are driven by the growing need for sustainable energy sources. The selection of the type of cooling tower technology significantly impacts the overall performance of concentrating solar power (CSP) plants because the cooling towers are essential elements for heat expulsion. The primary objective is to assess the influence of cooling tower technology on CSP plants from the perspective of techno-economic performance by implementing wet, dry, and hybrid cooling systems and optimizing the variables affecting solar tower power plants by conducting a parametric analysis. Moreover, a unique stacking ensemble model comprising a dual-layer structure is developed for solar tower power plant performance prediction. Following the findings, dry and wet cooling technologies came in second and third, respectively, with the hybrid cooling technique achieving the best performance outcomes. By incorporating wet-dry as well as hybrid cooling towers at the Benban location, the levelized cost of electricity for the solar tower was determined to be 13.99, 13.62, and 13.37 ¢/kWh. The results show that based on the parametric assessment; the capacity factor rose from 11.73 to 73.13% when the mirror reflectance changed from 0.6 to 0.95% and the reflective area to profile ratio from 0.5 to 0.9%. The proposed stacking ensemble demonstrated superior performance compared to standalone base models and existing techniques.

As the global focus on sustainable development intensifies, green buildings have become an important way to reduce energy consumption and improve environmental quality. The purpose of this study is to explore the application of technology based on optical imaging equipment in the heat saving of green buildings, especially in the landscape optimization of waterfront space, and evaluate its effectiveness and feasibility. In this study, light imaging equipment was used to monitor the heat distribution of different green buildings in the waterfront space, and combined with environmental data and energy consumption, the influence of architectural design and landscape configuration on heat energy conservation was analyzed. Through case study and quantitative analysis, the optimization effect of different design schemes on thermal effect is evaluated. The study found that rational allocation of buildings and surrounding landscape can significantly reduce heat loss, reflecting the importance of heat management. Light imaging technology effectively reveals the thermal energy dynamics of buildings under different weather conditions, verifying the potential of green buildings to reduce energy consumption. Therefore, the research based on optical imaging equipment provides a new perspective and method for the energy saving of green buildings in the waterfront space, and demonstrates the important role of optimizing landscape design in improving building energy efficiency.

Solar energy and biomass are both important renewable energy, and the studies on them contribute to current goal of global carbon neutral. The solar gasification process directly employs solar radiation to drive the conversion from biomass to syngas via endothermic gasification reactions. This process relies on the biomass feedstock absorbing incident solar irradiation to sustain these reactions. The thermal radiation characteristics of biomass materials, such as spectral emissivity and absorptivity, determine its capacity for solar energy absorption versus losses from self-emission. Thus, these parameters are critical inputs for accurate thermal-balance modeling of the solar reactor. In this study, the reflectance of 9 biomass samples were experimentally measured in the main solar spectrum range of 200–2500 nm. Based on measurement results, the refractive index ($n$) and extinction coefficient ($k$) of each biomass materials are obtained via Kramers-Kronig relations. Besides, the dielectric function of the 9 biomass samples are also modeled using a 5-th Lorentz oscillator model and the model parameters are determined. The results indicate that the 5-th Lorentz oscillator model adequately characterizes the thermal radiation properties of diverse biomass feedstocks over the measured spectrum. This work contributes important spectral property data to enable accurate modeling and optimization of solar thermochemical conversion based on biomass gasification processes.

In the manufacturing process, there are a large number of complex tasks, and refining them into smaller subtasks can better handle and schedule them. By dividing tasks into smaller units and understanding the characteristics and requirements of each subtask, targeted control and optimization can be carried out. Reasonably arranging the procurement and usage cycle of equipment based on changes in demand and production capacity can avoid waste caused by idle and excessive use of equipment, and maximize the utilization of equipment resources to reduce production costs. The aim of this study is to explore the method of manufacturing task optimization decomposition and equipment cycle ordering based on cost control, in order to optimize the cost-effectiveness of the manufacturing process. The task decomposition and equipment cycle ordering process are abstracted into mathematical models, and corresponding optimization objectives and constraints are formulated based on the characteristics of the models. Then, optimization algorithms are used to solve the model and find the optimal task decomposition and equipment cycle ordering strategy. The experimental results show that the use of cost control based manufacturing task optimization decomposition and equipment cycle ordering methods has achieved significant improvements in cost-effectiveness.

This paper examines the feasibility of using waste heat from wastewater treatment plants (WWTPs) for water desalination. A model was developed to utilize waste heat from the gensets at As Samra WWTP in Jordan, using real data and TRNSYS® software to calculate available waste heat. The desalination process was then modeled with ASPEN PLUS® software, focusing on multi-effect desalination (MED). Both series and parallel configurations for the MED system were compared. The study investigated the effects of system feeding flow rate, feeding pressure, and heat input on productivity, performance ratio, and recovery ratio. The study also introduces a novel optimization technique combining machine learning and modern optimization algorithms to maximize system productivity and performance. Initially, a decision tree regression (DTR) model is developed to establish relationships between key independent variables (flow rate, feed pressure, and heat input) and dependent variables (productivity, performance ratio, and recovery ratio). The Pelican Optimization Algorithm (POA) is then used to identify the optimal values of the independent variables for maximum productivity and performance. The results show that using a series configuration yields a system productivity of 3984.2 kg/hr, a performance ratio of 3.78, and a recovery ratio of 0.991 at a feed flow rate of 4000 kg/hr, feed pressure of 3 bars, and heat input of 719 kW. Optimal productivity (4421 kg/hr), performance ratio (3.81), and recovery ratio (0.851) are achieved at a feed flow rate of 5166 kg/hr, feed pressure of 3.2 bars, and heat input of 794 kW. The techno-economic assessment indicates a levelized cost of water of 1.63 USD/m³ for parallel configurations and 1.65 USD/m³ for series configurations, with a payback period of less than two years.

The objective of this study is to examine the impact of various material and processing factors on the hardness (Shore D) and tensile strength of PLA/graphene composites. The study employed the Taguchi method to systematically optimize and statistically analyze various process variables, including the content of graphene (0 %, 0.5 %, and 1.0 % by weight), infill density (80 %, 90 %, and 100 %), and print speed (160 mm/s, 170 mm/s, and 180 mm/s). The composite material was fabricated utilizing the fused filament fabrication (FFF) technique, employing polylactic acid (PLA) and graphene as the primary feedstock materials. A standardized experiment was conducted in accordance with ASTM standards to assess the hardness and strength of samples that were prepared based on the experimental design. Based on the S/N ratio response table, it can be concluded that the reinforcement content is the most significant factor affecting both hardness and tensile strength. The optimal combination of process variables for achieving high hardness and tensile strength was found to be a graphene content of 1 %, an infill density of 100 %, and a print speed of 180 mm/s. The analysis of variance (ANOVA) indicated that the variable with the greatest statistical significance and substantial impact on the properties is the content of reinforcement. The analysis of fractures indicated a transition from ductile to brittle behavior with an increase in infill density. Furthermore, both composites demonstrated a brittle mode of failure irrespective of the infill density. Thus this composite material synergistically combines the inherent biodegradability of PLA with the improved thermal conductivity of graphene.

The flame spread behaviors of discrete charring fuels are significantly influenced by ambient wind. This paper studied the horizontal flame spread characteristics of discrete birch rod arrays under ambient wind experimentally and theoretically. Here, seven kinds of array spacings (denoted by S, 7–19 mm) and four kinds of wind speeds (denoted by U, 0.5–2.0 m/s) were designed to develop 28 experiments. The experimental results show that the flame inclination angle decreases as wind speed increases. The non-dimensional flame length and the non-dimensional heat release rate are also found to be correlated, and two ignition modes under the action of ambient wind were differentiated. The flame spread rate and wind speed have a linear relationship based on experimental data. The ratio of wind speed to fuel loading is introduced to further examine the variation of flame spread rate. In this article, a heat transfer model is established by simplifying discrete flame spread process and incorporating both radiative and convective heat transfer. A prediction model for flame spread rate is presented, which aligns well with the experimental results. Finally, the mass loss rate under the ambient wind is discussed.

This paper focuses on the thermodynamic cycle performance modeling and numerical investigation of a high Mach number scramjet with inlet pre-injection of hydrogen. The scramjet model used in this study was the Hyshot-Ⅱ engine model. Flight experiments using this model at high Mach number have been conducted previously, which provides a unique testbed for validating the computational prediction of supersonic combustion. A thermodynamic cycle performance model with inlet pre-injection was developed for operating characteristics studies of the scramjet engine. A set of three-dimensional Reynolds average Navier-Stockes (RANS) simulations of the reactive flow was performed with a 9-specie and 19-step kinetic mechanism for hydrogen combustion. The turbulence is modeled by k-ω shear stress transport (SST) turbulence model. The thermodynamic cycle performance analysis results indicate that inlet pre-injection can enhance the hydrogen mixing efficiency, and a small amount of advanced heat release can improve the overall thermal cycle efficiency. Detailed flow analysis from the three-dimensional simulation results indicates flow can be ignited in the first shock wave induced boundary layer separation (SIBLS) region. Inlet pre-injection enables the propagation of the flame toward the core flow compared to the throat injection. The inlet fuel pre-injection proved to be a promising injection method due to the higher combustion efficiency, elevated from 0.75 to 0.85, and higher specific impulse potential, increased from 1570 s to 1810 s. As the ER of inlet pre-injection increases within the examined range, the performance curve exhibits an optimal point. As the geometric compression ratio increases, the entire combustion process advances, leading to a significant increase in the performance potential of the engine. The comparative analysis of the thermodynamic cycle performance modeling and computational fluid dynamics (CFD) modeling indicates the model shows a good prediction on the performance of the scramjet engine with the inlet pre-injection, with the same trend of performance curves and an error of less than 10 % compared to the numerical simulation.

Due to factors such as groundwater seepage and soil stress coupling effect, significant deformation and instability problems often occur during the construction process of super large deep excavation groups involving iron, seriously affecting the safety and stability of the project. This article aims to explore the coupling effect of super large deep excavation groups involving railways during the construction process, and how to effectively control construction deformation. This article combines theoretical analysis and numerical simulation to study the coupled effects of seepage and stress during the construction process of super deep excavation groups involving iron. With the help of finite element software, a numerical model of a large and deep excavation group involving iron was established, and the deformation and stress distribution at different construction stages were simulated. The research results indicate that the coupling effect of groundwater seepage and soil stress has a significant impact on the deformation and stability of the super deep excavation group involving iron. Therefore, reasonable construction measures and deformation control methods should be taken during the construction process.

A Stirling engine is a heat engine that utilizes the cyclic compression and expansion of the working fluid caused by differential temperature for its operation. The regenerator heat exchanger is one of the core components in these Stirling engines, and the performance of the regenerator determines the performance of the Stirling engine. So, in this project, experimental and numerical simulations have been performed to study and compare the thermal and hydrodynamic properties of single mesh and hybrid mesh regenerators. Both single flow and oscillating flow characteristics were studied for single mesh regenerators with wire screens of mesh numbers 300, 400, 500 and hybrid mesh regenerators with wire mesh numbers 300-400-500 and 500-400-300. The oscillating flow study was carried out for 700 RPM, 500 RPM, 300 RPM and 200 RPM. It was observed that the single mesh regenerator with 500 mesh screens has the highest amount of energy storage but at the same time, it was also observed that the 500 mesh has the highest amount of pressure loss gradient. Upon comparing the pressure loss gradient and energy storage it was observed that the hybrid mesh has a better performance as it can store more heat energy with less pressure loss. A correlation was also developed for estimation of the Nusselt number.