Numerical Simulation and Experimental Study of the Tube Receiver's Performance of Solar Thermal Power Tower

AbstractA water-vapor tube receiver is a significant component in the solar thermal power tower plant. However, the tube flow performance is much different from others. Because semi-circumference of the tube is heated with an uneven heat flux, which is into a Gaussian distribution in this paper, and the other semi-circumference is insulated. A 5kW- Xe-arc lamp was used to simulate a solar light source. In this study, the effect of different entrance velocity on the flow performance and thermal efficiency of the tube receiver are investigated with numerical and experimental methods. The results of experiment and simulation agree well. The results show that the temperature distribution of water and tube wall are very uneven both in the axial and radial directions. The thermal efficiency of the tube receiver increases with the increase of entrance velocity

Gas-Solids Hydrodynamics in a CFB with 6 Cyclones and a Pang Leg

Solids volume fraction and particle velocity profiles were measured with a fiber optical probe in a cold circulating fluidized bed test rig with 6 parallel cyclones and a pant leg. Results in the pant leg zone, main bed zone and exit zone of the furnace are reported. The work also includes the influences of superficial gas velocity, secondary air rate and static bed height on the gas-solids hydrodynamics

Premixed jet flame characteristics of syngas using OH planar laser induced fluorescence

Lean premixed flame characteristics of several typical low calorific value (LCV) syngases (basis CO/H-2/CH4/CO2/N-2), including bituminous coal, wood residue, corn core, and wheat straw gasification syngas, were investigated using OH planar laser induced fluorescence (PLIF) technology. OH radical distributions within the turbulent flame were measured for different turbulence intensities. Flame structures of syngases were analyzed and characterized with respect to burnt and unburnt regions, flame curvature (sharp cusp), local extinction (holes and penetration), OH reaction layer thickness, wrinkling, and other features, with OH-PLIF instantaneous images and statistical analysis. Results show that H-2 content, LCV, and turbulence intensity are the most effective factors influencing the OH radical intensity and thickness of OH radical layers. The bituminous coal gasification syngas with relatively higher LCV and H-2 content tends to burn out easily. Through changes in thickness of the OH radical layers and signal intensities, the reaction layer can be compressed by intensifying turbulence and thereby the combustion processes of syngas

Boosting biomethane yield and production rate with graphene: the potential of direct interspecies electron transfer in anaerobic digestion

Interspecies electron transfer between bacteria and archaea plays a vital role in enhancing energy efficiency of anaerobic digestion (AD). Conductive carbon materials (i.e. graphene nanomaterial and activated charcoal) were assessed to enhance AD of ethanol (a key intermediate product after acidogenesis of algae). The addition of graphene (1.0 g/L) resulted in the highest biomethane yield (695.0 ± 9.1 mL/g) and production rate (95.7 ± 7.6 mL/g/d), corresponding to an enhancement of 25.0% in biomethane yield and 19.5% in production rate. The ethanol degradation constant was accordingly improved by 29.1% in the presence of graphene. Microbial analyses revealed that electrogenic bacteria of Geobacter and Pseudomonas along with archaea Methanobacterium and Methanospirillum might participate in direct interspecies electron transfer (DIET). Theoretical calculations provided evidence that graphene-based DIET can sustained a much higher electron transfer flux than conventional hydrogen transfer

Improving fermentative hydrogen and methane production from an algal bloom through hydrothermal/steam acid pretreatment

Algal blooms can be harvested as renewable biomass waste for gaseous biofuel production. However, the rigid cell structure of raw algae may hinder efficient microbial conversion for production of biohydrogen and biomethane. To improve the energy conversion efficiency, biomass from an algal bloom in Dianchi Lake was subjected to a hydrothermal/steam acid pretreatment prior to sequential dark hydrogen fermentation and anaerobic digestion. Results from X-ray diffraction and Fourier transform infrared spectroscopy suggest that hydrothermal acid pretreatment leads to stronger damage of the amorphous structure (including hemicellulose and amorphous cellulose) due to the acid pretreatment, as evidenced by the higher crystallinity index. Scanning electron microscopy analysis showed that smaller fragments (∼5 mm) and wider cell gaps (∼1 μm) on algal cell surfaces occurred after pretreatment. In comparison to steam acid pretreatment, hydrothermal acid pretreatment resulted in a maximum energy conversion efficiency of 44.1% as well as production of 24.96 mL H2/g total volatile solids (TVS) and 299.88 mL CH4/g TVS

Measurement of atomic sodium release during pyrolysis and combustion of sodium-enriched Zhundong coal pellet

National Natural Science Foundation of China; Ph.D. Programs Foundation of Ministry of Education of Chin

Back-propagation neural network and support vector machines for gold mineral prospectivity mapping in the Hatu region, Xinjiang, China

Machine Learning technologies have the potential to deliver new nonlinear mineral prospectivity mapping (MPM) models. In this study, Back Propagation (BP) neural network Support Vector Machine (SVM) methods were applied to MPM in the Hatu region of Xinjiang, northwestern China. First, a conceptual model of mineral prospectivity for Au deposits was constructed by analysis of geological background. Evidential layers were selected and transformed into a binary data format. Then, the processes of selecting samples and parameters were described. For the BP model, the parameters of the network were 9-10-1; for the SVM model, a radial basis function was selected as the kernel function with best C=1 and= 0.25. MPM models using these parameters were constructed, and threshold values of prediction results were determined by the concentration-area (C-A) method. Finally, prediction results from the BP neural network and SVM model were compared with that of a conventional method that is the weight- of- evidence (W- of- E). The prospectivity efficacy was evaluated by traditional statistical analysis, prediction-area (P-A) plots, and the receiver operating characteristic (ROC) technique. Given the higher intersection position (74% of the known deposits were within 26% of the total area) and the larger AUC values (0.825), the result shows that the model built by the BP neural network algorithm has a relatively better prediction capability for MPM. The BP neural network algorithm applied in MPM can elucidate the next investigative steps in the study area