Joint Depth Estimation and Mixture of Rain Removal From a Single Image

Rainy weather significantly deteriorates the visibility of scene objects, particularly when images are captured through outdoor camera lenses or windshields. Through careful observation of numerous rainy photos, we have found that the images are generally affected by various rainwater artifacts such as raindrops, rain streaks, and rainy haze, which impact the image quality from both near and far distances, resulting in a complex and intertwined process of image degradation. However, current deraining techniques are limited in their ability to address only one or two types of rainwater, which poses a challenge in removing the mixture of rain (MOR). In this study, we propose an effective image deraining paradigm for Mixture of rain REmoval, called DEMore-Net, which takes full account of the MOR effect. Going beyond the existing deraining wisdom, DEMore-Net is a joint learning paradigm that integrates depth estimation and MOR removal tasks to achieve superior rain removal. The depth information can offer additional meaningful guidance information based on distance, thus better helping DEMore-Net remove different types of rainwater. Moreover, this study explores normalization approaches in image deraining tasks and introduces a new Hybrid Normalization Block (HNB) to enhance the deraining performance of DEMore-Net. Extensive experiments conducted on synthetic datasets and real-world MOR photos fully validate the superiority of the proposed DEMore-Net. Code is available at https://github.com/yz-wang/DEMore-Net.Comment: 11 pages, 7 figures, 5 table

Design and Research of Thermoelectric Generator Simulation System for Boiler Flue Gas Waste Heat

One of the significant factors contributing to high energy consumption is the unutilized waste heat from flue gas in industrial boilers. Thermoelectric generator (TEG) technology can directly convert thermal energy into electrical energy, and has been gradually applied in the field of waste heat recovery due to its simple and reliable structure, environmental protection, and other advantages. In this paper, a thermoelectric generator simulation system of boiler flue gas waste heat is proposed. The experimental platform is designed by simulating the flue gas waste heat temperature condition of boiler, and the structure of cold end module and hot end module is optimized. During the experiment, the fixed temperature difference was set at 120 °C (hot end:150 °C~cold end: 30 °C). An analysis is conducted on the volt-ampere characteristics and output power of the TEG module. The output characteristics of the TEG system are analyzed under the conditions of variable load, constant load, different pump speed, different heat dissipation modes, and series and parallel connection method. The results show that the experimental platform can instantaneously and accurately test the output parameters of the TEG system, and ensure the intended design requirements. When the ratio of the load resistance to the internal resistance of the TEG module is approximately 1–1.15, the output power of the system reaches its maximum. In order to optimize the output power of the TEG system, a power prediction-based adaptive variable step size maximum power point tracking (MPPT) algorithm is introduced. Additionally, a corresponding mathematical model is formulated. Simulations demonstrate that the time of the improved algorithm to reach the stable maximum power point is 1.54 s faster than that of the traditional algorithm. The improved MPPT algorithm satisfies the criteria for speed and accuracy, diminishes superfluous energy waste, and enhances the overall system efficiency. The research results have certain guiding significance for the design and application of subsequent TEG system

An Efficient Reliability Method with Multiple Shape Parameters Based on Radial Basis Function

Structural reliability analysis has an inherent contradiction between efficiency and accuracy. The metamodel can significantly reduce the computational cost of reliability analysis by a simpler approximation. Therefore, it is crucial to build a metamodel, which achieves the minimum simulations and accurate estimation for reliability analysis. Aiming at this, an effective adaptive metamodel based on the combination of radial basis function (RBF) model and Monte Carlo simulation (MCS) is proposed. Different shape parameters are first used to generate the weighted prediction variance, and the search for new training samples is guided by the active learning function that achieves a tradeoff of (1) being close enough to limit state function (LSF) to have a high reliability sensitivity; (2) keeping enough distance between the existing samples to avoid a clustering problem; and (3) being in the sensitive region to ensure the effectiveness of the information obtained. The performance of the proposed method for a nonlinear, non-convex, and high dimensional reliability analysis is validated by three numerical cases. The results indicate the high efficiency and accuracy of the proposed method

Energy efficiency comparison between geothermal power systems

The geothermal water which can be considered for generating electricity with the temperature ranging from 80℃ to 150℃ in China because of shortage of electricity and fossil energy. There are four basic types of geothermal power systems: single flash, double flash, binary cycle, and flash-binary system, which can be adapted to geothermal energy utilization in China. The paper discussed the performance indices and applicable conditions of different power system. Based on physical and mathematical models, simulation result shows that, when geofluid temperature ranges from 100℃ to 130℃, the net power output of double flash power is bigger than flash-binary system. When the geothermal resource temperature is between 130℃ and 150℃, the net power output of flash-binary geothermal power system is higher than double flash system by the maximum value 5.5%. However, the sum water steam amount of double flash power system is 2 to 3 times larger than flash-binary power system, which will cause the bigger volume of equipment of power system. Based on the economy and power capacity, it is better to use flash-binary power system when the geofluid temperature is between 100℃ and 150℃

ENERGY EFFICIENCY COMPARISON BETWEEN GEOTHERMAL POWER SYSTEMS

The geothermal water which can be considered for generating electricity with the temperature ranging from 80 degrees C to 150 degrees C in China because of shortage of electricity and fossil energy. There are four basic types of geothermal power systems: single-flash, double flash, binary cycle, and flash-binary system, which can be adapted to geothermal energy utilization in China. The paper discussed the performance indices and applicable conditions of different power system. Based on physical and mathematical models, simulation result shows that, when geofluid temperature ranges from 100 degrees C to 130 degrees C, the net power output of double flash power is bigger than flash-binary system. When the geothermal resource temperature is between 130 degrees C and 150 degrees C, the net power output offlash-binary geothermal power system is higher than double flash system by the maximum value 5.5%. However, the sum water steam amount of double flash power system is 2 to 3 times larger than flash-binary power system, which will cause the bigger volume of equipment of power system. Based on the economy and power capacity, it is better to use flash-binary power system when the geofluid temperature is between 100 degrees C and 150 degrees C

The case study of binary power plant based on thermoeconomics in Sichuan, China

In China, renewable energy power plant will be built from the year 2016 to 2020, because of CO2 emission assignment and energy company demand. A geothermal power plant will be designed in Sichuan province. The wet temperature 15ºC is selected for cooling temperature. Thermoeconomics of geothermal power system are analyzed using the engineering equation solver. The results show that the capacity of binary power system is 3506 kW and optimum vaporizing pressure is 28 bar, the thermal and exergy efficiency is 13% and 45%. The turbine shaft work of flash power system is 2301 kW and the parasitic load is 71 kW, the optimum flash pressures is 0.95 bar, the thermal and exergy efficiency is 7.9% and 34.7%. the total capital investment of binary system is about 9,767,000 US$, the average annual profit is 1,308,000$/year; the average rate of return is 13.39%; the payback period is less than 6 years. Condenser destruction and loss exergy is more than other components in the power system. The geothermal power production cost is 0.04 US$/kWh in Sichuan province

Grey relational analysis of an integrated cascade utilization system of geothermal water

With the drastic decrease in fossil resources and rapid deterioration of the global environment, the utilization of geothermal resources has been strongly advocated. The combination of heat, power, and cold utility generation is commonly used to increase the utilization efficiency of geothermal resources. In this study, an integrated cascade utilization system of waste geothermal water (ICUWGW) from a flash geothermal power plant in China is established to increase the utilization efficiency of geothermal water. The waste geothermal water leaving the power plant is proposed for further use in cascade for two-stage LiBr/H2O absorption cooling, agricultural product drying, and residential bathing. Twelve candidate temperature schemes showing different inlet and outlet temperatures of every subsystem are proposed for the ICUWGW. Several criteria are selected for the evaluation and screening of the candidate schemes. Grey relational analysis incorporating analytic hierarchy process is conducted to screen the optimal temperature scheme for the ICUWGW to meet the comprehensive criteria of thermodynamics and economics. Results show that the optimal scheme features significant improvement in energy efficiency, exergy efficiency, and equivalent electricity generation efficiency compared with those of the current geothermal power plant. The investment payback time of the additional subsystems for cooling, drying, and bathing is 1.85 years. Exergy analysis is also conducted to determine the further optimization potential of the optimal ICUWGW. Sensitivity analysis of electricity price on the performance of the optimal ICUWGW is also performed

THE CASE STUDY OF BINARY POWER PLANT BASED ON THERMOECONOMICS IN SICHUAN, CHINA

In China, renewable energy power plant will be built from the year 2016 to 2020, because of CO, emission assignment and energy company demand. A geothermal power plant will be designed in Sichuan province. The wet temperature 15 degrees C is selected for cooling temperature. Thermoeconomics of geothermal power system are analyzed using the engineering equation solver. The results show that the capacity of binary power system is 3506 kW and optimum vaporizing pressure is 28 bar, the thermal and exergy efficiency is 13% and 45%. The turbine shaft work of flash power system is 2301 kW and the parasitic load is 71 kW, the optimum flash pressures is 0.95 bar, the thermal and exergy efficiency is 7.9% and 34.7%. the total capital investment of binary system is about 9,767,000 US$, the average annual profit is 1,308,000$/year; the average rate of return is 13.39%; the payback period is less than 6 years. Condenser destruction and loss exergy is more than other components in the power system. The geothermal power production cost is 0.04 US$/kWh in Sichuan province

Wnt5a/Ror2 promotes vascular smooth muscle cells proliferation via activating PKC

Introduction. Abnormal proliferation of vascular smooth muscle cells (VSMCs) can cause various vascular diseases, such as atherosclerosis, restenosis, and pulmonary hypertension. However, the effect and underlying mechanism of Wnt5a on the proliferation of VSMCs remain unclear. Our study aimed to investigate whether Wnt5a/Ror2 promotes vascular smooth muscle cell proliferation via activating protein kinase C (PKC), thereby effectively alleviating vascular proliferative diseases.Material and methods. The proliferation of HA-VSMC cell line was evaluated by CCK-8, EdU, and Plate clone formation assays. The Wnt5a gene knockdown and overexpression were carried out by standard methods. The interaction between Wnt5a and Ror2 was explored by co-immunoprecipitation. Western blotting and immunofluorescence were used to determine the expression levels of key proteins in VSMCs.Results. The present study found that the expression of Wnt5a protein increased significantly in the proliferation of VSMCs stimulated by 10% serum in a time-dependent manner. Furthermore, the proliferative rate of VSMCs overexpressing Wnt5a was dramatically accelerated, whereas Wnt5a knockdown using siWnt5a reversed thisproliferative effect. Wnt5a up-regulated the expression of receptor tyrosine kinase-like orphan receptor 2 (Ror2) by binding to it. Further studies indicated that Wnt5a induces the PKC expression in VSMCs and knockdown of Wnt5a or Ror2 could inhibit PKC phosphorylation.Conclusions. Wnt5a could effectively promote the proliferation of VSMCs, which might be related to the binding of Wnt5a and Ror2 to activate PKC