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Abstract In this paper, coupled governing equations were proposed to simulate three-dimensional heat conduction and moisture transport in the nuclear waste repository. Because there will be a large temperature gradient near inner and outer boundaries of the bentonite buffer layer, and the heat driven moisture transport is introduced in the governing equation of moisture transport. By applying the Fourier and Laplace transforms, the governing equations were converted to the Bessel equations, and the Laplace-domain solutions to temperature and moisture distributions were derived through the inverse Fourier transform. The reliability of the proposed solutions was verified through comparative analysis with the line heat source model. These analytical solutions were applied to obtain the evolutions of temperature field and moisture distribution near the waste canister. Finally, a sensitivity study was performed to analyze the effects of relevant parameters on the heat driven moisture transport.

Abstract Molten salt reactors (MSRs) are a class of next-generation nuclear reactors that have received recent industrial and research interest. A generalized species transport solver was implemented in the Virtual Environment for Reactor Applications (VERA) computing suite to extend this tool to analyze liquid-fueled MSRs. This core simulator has been extended to model the transport of fission product gases into a collection of circulating gas bubbles with the purpose of removing the gases. This paper presents the governing species transport equation, along with various nuclear source terms. Development of the source term for phase migration is discussed, along with a simplified interfacial area tracking method. Finally, a case study on a simplified MSR loop is presented in which modeling parameters were varied to assess their impact on gas removal. The steady state results show that parameters such as bubble diameter, gas injection rate and mass transfer coefficient have a low to moderate effect on the fraction of xenon in the core region. Removal efficiency has the greatest effect on the fraction in the core region. After the pump bowl, bubble diameter has a minor effect on the fraction of xenon in the gas void. These results point out that increasing parameters such as mass transfer coefficient, gas injection rate, and removal efficiency drives the xenon into the circulating gas void, while decreasing bubble diameter also drives xenon into the gas void by increasing interfacial area.

In this study, pyrolysis of residual biomass from the agro-alimentary industry of Argentina was investigated. The studied biomasses were rice husk, peanut shell and wheat straw. The effect of pyrolysis temperature over solid (bio-char), liquid (bio-oil) and gas (bio-gas) fractions weight yields were evaluated for each biomass, in the range of 350-650 °C. The maximum yield of bio-oil was obtained at 550 °C for rice husk (45 wt%) and wheat straw (58 wt%), and at 500 °C for peanut shells (51 wt%). At those temperatures, the data recorded the smallest spread around the mean. Different characterization techniques of raw biomass were reported, namely, thermal behavior; proximate and ultimate analysis; content of Ca, Al, K, Si and Fe; and hemicellulose, cellulose and lignin composition. Bio-oils characterization included water content and chemical compounds identification. Furthermore, bio-char HHV and BET surface area were measured. Rice husk bio-oil showed 21% selectivity towards furans of which 75% corresponded to furfural and 5-HMF. Peanut shell bio-char presented the highest Higher Heating Value (7250 kcal/kg) and BET surface area (215 m2/g). In addition, co-pyrolysis reactions and the synergistic effects over obtained products completed this study. Co-pyrolysis bio-oils yields varied between 41 and 46 wt%, for all the mixtures. Bio-oil water content decreased up to 15% for rice husk mixed with peanut shell or wheat straw. Moreover, 5-HMF was detected in all bio-oils, and furfural selectivity was higher than 5% in the three mixtures investigated.

This paper presents a novel modified interactive honey bee mating optimization (IHBMO) base fuzzy stochastic long-term approach for determining optimum location and size of distributed energy resources (DERs). The Monte Carlo simulation method is used to model the uncertainties associated with long-term load forecasting. A proper combination of several objectives is considered in the objective function. Reduction of loss and power purchased from the electricity market, loss reduction in peak load level and reduction in voltage deviation are considered simultaneously as the objective functions. First, these objectives are fuzzified and designed to be comparable with each other. Then, they are introduced into an IHBMO algorithm in order to obtain the solution which maximizes the value of integrated objective function. The output power of DERs is scheduled for each load level. An enhanced economic model is also proposed to justify investment on DER. An IEEE 30-bus radial distribution test system is used to illustrate the effectiveness of the proposed method.

Abstract Thermal performance of three naturally ventilated public buildings in which the wind tower is an important architectural freature is studied. One of the three builidings as well as it's wind tower is instrumented for temperature, relative humidity and airflow velocity measurements, and the other two are instrumented for temperature measurement. The results have led to a discussion concerning the degree of wind tower effectiveness in achieving thermal comfort.

This paper presents a multi-objective optimization model for a long-term generation mix in Indonesia. The objective of this work is to assess the economic, environment, and adequacy of local energy sources. The model includes two competing objective functions to seek the lowest cost of generation and the lowest CO2 emissions while considering technology diffusion. The scenarios include the use of fossil reserves with or without the constraints of the reserve to production ratio and exports. The results indicate that Indonesia should develop all renewable energy and requires imported coal and natural gas. If all fossil resources were upgraded to reserves, electricity demand in 2050 could be met by domestic energy sources. The maximum share of renewable energy that can be achieved in 2050 is 33% with and 80% without technology diffusion. The least cost optimization produces lower generation costs than the least CO2 emissions, as well as the combined scenario. Total CO2 emissions in 2050 are five to six times as large as current emissions. The least CO2 emissions scenario can reduce almost half of the CO2 emissions of the least cost scenario by 2050. The proposed multi-objective optimization model leads some optimal solutions for a more sustainable electricity system.

Impact loads in large iron and steel enterprise bring the power system reactive power impact, which makes the fluctuation of the system voltage, power factor and other parameters are out of the limitation of the national standard. Substation bus reactive load forecasting in large iron and steel enterprise can be introduced to determine reactive power optimization strategy and the switching of capacitors. In this paper, a combination forecasting model of quadratic self-adaptive exponential smoothing (QSES) model and converse exponential (CE) model has been proposed for substation bus reactive load forecasting. The numerical results in Jinan iron and steel Group show the application of this model is encouraging. Introduction

An all-round supramolecular zwitterionic hydrogel electrolyte with the advantages ofin siturepair, H2O-poor interface, and boosting the desolvation of hydrated Zn2+is proposed to enable the fabrication of environment-adaptive dendrite-free zinc ion capacitors.