Suchergebnisse

The heat and mass transfer processes of natural convective condensation with noncondensable gases are very important for the passive containment cooling system of water cooled reactors. Numerical simulation of natural convective condensation with noncondensable gases was realized in the Fluent software by adding condensation models. The scaled AP600 containment condensation experiment was simulated to verify the numerical method. It was shown that the developed method can predict natural convective condensation with noncondensable gases well. The velocity, species, and density fields in the scaled AP600 containment were presented. The heat transfer rate distribution and the influences of the mass fraction of air on heat transfer rate were also analyzed. It is found that the driving force of natural convective condensation with noncondensable gases is mainly caused by the mass fraction difference but not temperature difference. The natural convective condensation with noncondensable gases in AP1000 containment was then simulated. The temperature, species, velocity, and heat flux distributions were obtained and analyzed. The upper head of the containment contributes to 35.1% of the total heat transfer rate, while its area only takes 25.4% of the total condensation area of the containment. The influences of the mass fraction of low molecular weight noncondensable gas (hydrogen) on the natural convective condensation were also discussed based on the detailed species, density, and velocity fields. The results show that addition of hydrogen (production of zirconium-water reaction after severe accident) will weaken the intensity of natural convection and the heat and mass transfer processes significantly. When hydrogen contributes to 50% mole fraction of the noncondensable gases, the heat transfer coefficient will be reduced to 45%.

AbstractThe adsorption process of inorganic arsenic (As) plays an important role in its mobility, bioavailability, and toxicity in the river environment. In this work, the adsorption of dissolved arsenite (As(III)) and arsenate (As(V)) by microplastics (MPs) pellets (polystyrene (PS) and low-density polyethylene (LDPE)), river sediment, and their mixture were investigated to assess the adsorption affinities and mechanism. The adsorption kinetics showed slow and mild rising zones from the natural behavior of the chemical adsorption. The results indicated that both MP characteristics and water properties played a significant role in the adsorption behavior of inorganic As species. The As adsorption equilibrium was modeled well by both Langmuir and Freundlich isotherms and partly fitted with the Sips model suggesting that both mono-layer and multi-layer adsorption occurred during adsorption The spontaneous adsorption process for both As(III) and As(V) was evidenced by the adsorption thermodynamics. The maximum adsorption capacities of As(III) and As(V) reached 143.3 mg/kg and 109.8 mg/kg on PS in deionized water, which were higher than those on sediment-PS mixture (119.3 mg/kg, 99.2 mg/kg), which were all lower than on sediment alone (263.3 mg/kg, 398.7 mg/kg). The Fourier transform infrared spectroscopy analysis identified that As(III) and As(V) interaction with sediment surface functional groups was the main adsorption mechanism from surface complexation and coordination. Two functional groups of polystyrene (-NH2, -OH) were mainly involved in the adsorption of inorganic As species on PS, while -COO- and -OH functional groups contributed to the adsorption mechanism of inorganic As species on LDPE. The findings provide valuable insight on the adsorption behavior and mechanisms of As(III) and As(V) in river systems in the presence of MPs particles. Both PS and LDPE were shown to be less effective than river sediment in the adsorption of As species from water, which provides a different perspective in understanding the scale of MPs impact in pollutant transport in the aquatic environment.
Graphical Abstract

The impact of the built environment and weather conditions on travel behavior has been widely studied. However, limited studies have focused on better understanding such effects in medium-sized cities with bus-oriented transit systems, particularly from a separate perspective of travelers' origins and destinations. We took Weinan, China, as a representative of second-tier cities in developing countries that concentrate on bus-oriented development strategies. New evidence of feature importance and nonlinear effects of crucial factors were revealed by an interpretable machine learning-based approach combining XGBoost and Shapley Additive Explanation (SHAP) with multi-source data. Most key factors were critical at both origins and destinations, such as the density of residential and commercial facilities. However, several important factors, such as road density and boarding time, had strong imbalanced effects on travel behavior. These findings provide novel insights and empirical implications to support urban planning strategies in medium-sized cities.