An innovative concentrated solar power system driven by high-temperature cascade organic Rankine cycle

Direct steam generation (DSG) solar power systems eliminate synthetic oils and molten salts in the solar field and enable efficient heat collection. Commercial DSG solar plants usually have a steam generation temperature of 250–285 °C to reduce the technical challenges of wet steam turbines and the costs of high-pressure water storage tanks. The power conversion efficiency is relatively low due to the limited steam generation temperature. This paper proposes a high-temperature solar power system driven by the cascade organic Rankine cycle (CORC). It has three features: water/steam for solar heat transfer, water and phase change material (PCM) for heat storage, and CORC for power conversion. It is the first time that the storage tank temperature is independent of the steam generation temperature in a DSG. Steam can be generated in the solar field at a temperature of 310 °C or even 370 °C. The fundamental of the innovative system is illustrated. The thermodynamic performances during the normal operation and discharge processes are investigated. The results show the maximum thermal efficiency of the CORC system in the normal operation mode is 32.85% at a steam temperature of 311 °C, while the top and bottom cycle efficiencies are 15.38% and 20.86%, respectively. The efficiency increases to more than 37% at 370 °C. Combining the two-tank storage and the PCM unit can overcome the problems of decreasing the heat release rate from PCM during heat discharge while maintaining the CORC system's power output and prolonging the heat storage time. The proposed system is potentially more cost-effective than the existing DSG solar plants

The progenitors of type Ia supernovae in the semidetached binaries with red giant donors

Context. The companions of the exploding carbon-oxygen white dwarfs (CO WDs) for producing type Ia supernovae (SNe Ia) are still not conclusively confirmed. A red-giant (RG) star has been suggested to be the mass donor of the exploding WD, named as the symbiotic channel. However, previous studies on the this channel gave a relatively low rate of SNe Ia. Aims. We aim to systematically investigate the parameter space, Galactic rates and delay time distributions of SNe Ia from the symbiotic channel by employing a revised mass-transfer prescription. Methods. We adopted an integrated mass-transfer prescription to calculate the mass-transfer process from a RG star onto the WD. In this prescription, the mass-transfer rate varies with the local material states. Results. We evolved a large number of WD+RG systems, and found that the parameter space of WD+RG systems for producing SNe Ia is significantly enlarged. This channel could produce SNe Ia with intermediate and old ages, contributing to at most 5% of all SNe Ia in the Galaxy. Our model increases the SN Ia rate from this channel by a factor of 5. We suggest that the symbiotic systems RS Oph and T CrB are strong candidates for the progenitors of SNe Ia.Comment: 8 pages, 6 figure

Thermodynamic and economic investigation of a screw expander-based direct steam generation solar cascade Rankine cycle system using water as thermal storage fluid

Solar electricity generation system (SEGS) which employs cascade steam-organic Rankine cycle (SORC) and steam screw expander (SE) is promising due to the high efficiency at moderate heat source temperature. This paper puts a special emphasis on heat storage and thermo-economic evaluation. Preferable operating temperature of the system is first clarified on the basis of SE characteristics. The temperature-dependent permissible stress of steam accumulator is modelled and the capital cost is investigated. Comparison between the direct steam generation (DSG) SEGS and an indirect one using thermal oil is made at a power capacity of 1 MW and storage of 6.5 h. The results indicate the DSG system has both thermodynamic and economic superiorities. The hot side temperature (THTH) of SORC generally does not exceed 250 °C to achieve an optimum solar thermal power efficiency. Given radiation of 750 W/m2, the maximum efficiency (ηT,mηT,m) is 14.3% with a corresponding THTH around 240 °C. The material cost of pressure vessels is 2.55 million RMB. For the indirect system, the optimal THTH is about 230 °C and ηT,mηT,m approximates to 13.2% and the estimated oil cost is 7.92 million RMB. It is recommended to adopt steam accumulators in the SE-driven SEGS

Improving multi-objective reservoir operation optimization with sensitivity-informed dimension reduction

There is another ORE record for this article: http://hdl.handle.net/10871/21284This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed method dramatically reduces the computational demands required for attaining high-quality approximations of optimal trade-off relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed dimension reduction and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform dimension reduction of optimization problems when solving complex multi-objective reservoir operation problems.China Postdoctoral Science FoundationNatural Science Foundation of Chin

EfficientSRFace: An Efficient Network with Super-Resolution Enhancement for Accurate Face Detection

In face detection, low-resolution faces, such as numerous small faces of a human group in a crowded scene, are common in dense face prediction tasks. They usually contain limited visual clues and make small faces less distinguishable from the other small objects, which poses great challenge to accurate face detection. Although deep convolutional neural network has significantly promoted the research on face detection recently, current deep face detectors rarely take into account low-resolution faces and are still vulnerable to the real-world scenarios where massive amount of low-resolution faces exist. Consequently, they usually achieve degraded performance for low-resolution face detection. In order to alleviate this problem, we develop an efficient detector termed EfficientSRFace by introducing a feature-level super-resolution reconstruction network for enhancing the feature representation capability of the model. This module plays an auxiliary role in the training process, and can be removed during the inference without increasing the inference time. Extensive experiments on public benchmarking datasets, such as FDDB and WIDER Face, show that the embedded image super-resolution module can significantly improve the detection accuracy at the cost of a small amount of additional parameters and computational overhead, while helping our model achieve competitive performance compared with the state-of-the-arts methods