Heat Transfer of Helix Energy Pile: Part 2—Novel Truncated Cone Helix Energy Pile

Owing to the fact that severe thermal interferences exist in the radial and generatrix directions of the traditional cylinder helix energy pile due to the limited thermal heat capacity of the pile and small ratio between coil pitch and radius of pile, therefore, a novel truncated cone helix energy pile (CoHEP) is presented to weaken the thermal interferences and improve the heat transfer efficiency. Further, both the analytical solution model and numerical solution model for CoHEP are built to discuss the dynamic characteristics of thermal interferences and heat transfer performance. The results indicate that the thermal interference of CoHEP is dynamic. The thermal interference in the upper part of the CoHEP is much smaller than the traditional CyHEP. And in general the heat flux per unit pipe length of the novel CoHEP is larger than that of the traditional CyHEP. Heat flux per unit pipe length of the CoHEP increases linearly with inlet water temperature. For the same inlet water temperature, the thermal short circuit is serious at the bottom of the CoHEP, and it’s weak in the upper part of CoHEP. Also it’s obvious that as the inlet water temperature increases, the thermal short circuit becomes more serious

Heat Transfer of Helix Energy Pile: Part 1: Traditional Cylinder Helix Energy Pile

Helix energy pile (HEP) is a new popular ground heat exchanger that has the advantages of large heat exchange rate and low initial cost. As for the traditional helix energy pile, the tube is wound on the cylindrical wall, which is called the cylinder helix energy pile (CyHEP). Further, both analytical solution model and numerical solution model for CyHEP are built to discuss the dynamic characteristics of thermal interferences and heat transfer performance. The results indicate that four heat exchange stages for the spiral pile geothermal heat exchanger along the fluid flow direction are revealed: inlet heat exchange stage, grout thermal short-circuiting stage, small temperature difference stage and outlet heat exchange stage. Each stage has corresponding heat transfer characteristics, and reducing the length of small temperature difference stage and increasing the other stages would enhance the heat exchange of spiral geothermal ground heat exchanger. As the pile diameter increases, the heat transfer per unit tube length decreases, and the heat exchange per unit pile depth increases. As the pile depth increases, the heat transfer per unit tube length and the heat exchange per unit pile depth are reduced. And as the pitch increases, the heat transfer per unit tube length increases, and the heat exchange per unit pile depth decreases

Regulation of Mitochondrial Respiration by Hydrogen Sulfide

Hydrogen sulfide (H2S), the third gasotransmitter, has positive roles in animals and plants. Mitochondria are the source and the target of H2S and the regulatory hub in metabolism, stress, and disease. Mitochondrial bioenergetics is a vital process that produces ATP and provides energy to support the physiological and biochemical processes. H2S regulates mitochondrial bioenergetic functions and mitochondrial oxidative phosphorylation. The article summarizes the recent knowledge of the chemical and biological characteristics, the mitochondrial biosynthesis of H2S, and the regulatory effects of H2S on the tricarboxylic acid cycle and the mitochondrial respiratory chain complexes. The roles of H2S on the tricarboxylic acid cycle and mitochondrial respiratory complexes in mammals have been widely studied. The biological function of H2S is now a hot topic in plants. Mitochondria are also vital organelles regulating plant processes. The regulation of H2S in plant mitochondrial functions is gaining more and more attention. This paper mainly summarizes the current knowledge on the regulatory effects of H2S on the tricarboxylic acid cycle (TCA) and the mitochondrial respiratory chain. A study of the roles of H2S in mitochondrial respiration in plants to elucidate the botanical function of H2S in plants would be highly desirable

Spatiotemporal Exploration of Chinese Spring Festival Population Flow Patterns and Their Determinants Based on Spatial Interaction Model

Large-scale population flow reshapes the economic landscape and is affected by unbalanced urban development. The exploration of migration patterns and their determinants is therefore crucial to reveal unbalanced urban development. However, low-resolution migration datasets and insufficient consideration of interactive differences have limited such exploration. Accordingly, based on 2019 Chinese Spring Festival travel-related big data from the AMAP platform, we used social network analysis (SNA) methods to accurately reveal population flow patterns. Then, with consideration of the spatial heterogeneity of interactive patterns, we used spatially weighted interactive models (SWIMs), which were improved by the incorporation of weightings into the global Poisson gravity model, to efficiently quantify the effect of socioeconomic factors on migration patterns. These SWIMs generated the local characteristics of the interactions and quantified results that were more regionally consistent than those generated by other spatial interaction models. The migration patterns had a spatially vertical structure, with the city development level being highly consistent with the flow intensity; for example, the first-level developments of Beijing, Shanghai, Chengdu, Guangzhou, Shenzhen, and Chongqing occupied a core position. A spatially horizontal structure was also formed, comprising 16 closely related city communities. Moreover, the quantified impact results indicated that migration pattern variation was significantly related to the population, value-added primary and secondary industry, the average wage, foreign capital, pension insurance, and certain aspects of unbalanced urban development. These findings can help policymakers to guide population migration, rationally allocate industrial infrastructure, and balance urban development

Modulating Structure and Properties of Glutinous Rice Flour and Its Dumpling Products by Annealing

In this study, annealed glutinous rice flour treated under different conditions (ANN1, ANN2 and ANN3) were prepared. The structure as well as physicochemical characteristics of the flour and its dumpling products were investigated. The crystallinity of the annealed flour samples increased, while the hydration ability decreased. The content of bound water raised, and immobilized water as well as the freezing enthalpy value decreased for the fast-frozen dumplings made from annealed flour samples. It showed that annealed treatment could reduce the formation of large ice crystals, thus decrease the cracking of fast-frozen dumplings. The freezing enthalpy value of annealed dumplings decreased which was conducive to protect the structure and quality of products. The boiled dumplings made of annealed flour had better eating quality as demonstrated by the increase in the transmittance of the soup. It indicated that moderate annealed glutinous rice flour ANN2 had optimal physicochemical properties to make high quality dumplings. This study would pave the way for further study of the annealing glutinous rice flour and provide theoretical guidance for the application of annealing treatment in starchy food product

A Field Study on the Indoor Thermal Environment of the Airport Terminal in Tibet Plateau in Winter

In order to study the characteristics of indoor thermal environment in the airport terminal in Tibet Plateau with radiant floor heating in winter, a field measurement of the indoor thermal environment was conducted in Lhasa Gonggar Airport terminal 2. First, the unique climate characteristics in Tibet Plateau were analyzed through comparison of meteorological parameters in Beijing and Lahsa. The thermal environment in the terminal was divided into outer zone and inner zone as well as south zone and north zone. Thermal environment parameters including air temperature, black globe temperature, relative humidity in each zone, and inner surface temperature of envelope were measured and analyzed. Meanwhile, temperature and relative humidity in the vertical direction were measured. In addition, PMV and PPD were calculated for evaluating the thermal environment in the terminal. The findings can provide guidance for the design and regulation of thermal environment in terminals in Tibet Plateau in China

Optimizing hydropower scheduling through accurate power load prediction: A practical case study

Hydropower stations that are part of the grid system frequently encounter challenges related to the uneven distribution of power generation and associated benefits, primarily stemming from delays in obtaining timely load data. This research addresses this issue by developing a scheduling model that combines power load prediction and dual-objective optimization. The practical application of this model is demonstrated in a real-case scenario, focusing on the Shatuo Hydropower Station in China. In contrast to current models, the suggested model can achieve optimal dispatch for grid-connected hydropower stations even when power load data is unavailable. Initially, the model assesses various prediction models for estimating power load and subsequently incorporates the predictions into the GA-NSGA-II algorithm, specifically an enhanced elite non-dominated sorting genetic algorithm. This integration is performed while considering the proposed objective functions to optimize the discharge flow of the hydropower station. The outcomes reveal that the CNN-GRU model, denoting Convolutional Neural Network-Gated Recursive Unit, exhibits the highest prediction accuracy, achieving R-squared and RMSE (i.e., Root Mean Square Error) values of 0.991 and 0.026, respectively. The variance between scheduling based on predicted load values and actual load values is minimal, staying within 5 (m3/s), showcasing practical effectiveness. The optimized scheduling outcomes in the real case study yield dual advantages, meeting both the demands of ship navigation and hydropower generation, thus achieving a harmonious balance between the two requirements. This approach addresses the real-world challenges associated with delayed load data collection and insufficient scheduling, offering an efficient solution for managing hydropower station scheduling to meet both power generation and navigation needs

Thermal Performance Optimization Simulation Study of a Passive Solar House with a Light Steel Structure and Phase Change Walls

Phase change materials are used in passive solar house construction with light steel structure walls, which can overcome the problems of weak heat storage capacity and poor utilization of solar heat and effectively solve the thermal defects of light steel structure walls. Based on this, on the basis of preliminary experimental research, this study further carried out theoretical analysis and simulation research on the thermal performance of a light steel structure passive solar house (Trombe form) with PCM walls. Through the heat balance analysis of heat transfer in the heat collecting partition wall, the theoretical calculation formula of the phase change temperature of the PCM was obtained, and it verified theoretically that the phase change temperature value should be 1–3 °C higher than the target indoor air temperature. The evaluation index “accumulated daily indoor temperature offset value” was proposed for evaluating the effect of phase change materials on the indoor temperature of the passive solar house, and “EnergyPlus” software was used to study the influence of the phase change temperature, the amount of material, and the thickness of the insulation layer on the indoor air temperature in a natural day. The results showed that there was a coupling relationship among the performance and between of the thickness of the PCM layer and the phase change temperature. Under typical diurnal climate conditions in the northern Tibetan Plateau of China, the optimal combination of the phase change temperature and the layer thickness was 17 °C and 15 mm, respectively. Especially at a certain temperature, excessive increases in the thickness of the phase transition layer could not improve the indoor thermal environment. For this transition temperature, there exists an optimal transition layer thickness. For a Trombe solar house, the thickness of the insulation layer has an independent impact on indoor temperature compared to other factors, which has an economic value, such as 50 mm in this case. In general, this paper studied the relationship between several important parameters of the phase change wall of a solar house by using numerical simulation methods and quantitatively calculated the optimal parameters under typical meteorological conditions, thus providing a feasible simulation design method for similar engineering applications

dbMDEGA: a database for meta-analysis of differentially expressed genes in autism spectrum disorder

Abstract Background Autism spectrum disorders (ASD) are hereditary, heterogeneous and biologically complex neurodevelopmental disorders. Individual studies on gene expression in ASD cannot provide clear consensus conclusions. Therefore, a systematic review to synthesize the current findings from brain tissues and a search tool to share the meta-analysis results are urgently needed. Methods Here, we conducted a meta-analysis of brain gene expression profiles in the current reported human ASD expression datasets (with 84 frozen male cortex samples, 17 female cortex samples, 32 cerebellum samples and 4 formalin fixed samples) and knock-out mouse ASD model expression datasets (with 80 collective brain samples). Then, we applied R language software and developed an interactive shared and updated database (dbMDEGA) displaying the results of meta-analysis of data from ASD studies regarding differentially expressed genes (DEGs) in the brain. Results This database, dbMDEGA ( https://dbmdega.shinyapps.io/dbMDEGA/ ), is a publicly available web-portal for manual annotation and visualization of DEGs in the brain from data from ASD studies. This database uniquely presents meta-analysis values and homologous forest plots of DEGs in brain tissues. Gene entries are annotated with meta-values, statistical values and forest plots of DEGs in brain samples. This database aims to provide searchable meta-analysis results based on the current reported brain gene expression datasets of ASD to help detect candidate genes underlying this disorder. Conclusion This new analytical tool may provide valuable assistance in the discovery of DEGs and the elucidation of the molecular pathogenicity of ASD. This database model may be replicated to study other disorders