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[en] This letter report presents a probabilistic performance assessment model to evaluate the probability of canister failure (through-wall penetration) by SCC. The model first assesses whether environmental conditions for SCC - the presence of an aqueous film - are present at canister weld locations (where tensile stresses are likely to occur) on the canister surface. Geometry-specific storage system thermal models and weather data sets representative of U.S. spent nuclear fuel (SNF) storage sites are implemented to evaluate location-specific canister surface temperature and relative humidity (RH). As the canister cools and aqueous conditions become possible, the occurrence of corrosion is evaluated. Corrosion is modeled as a two-step process: first, pitting is initiated, and the extent and depth of pitting is a function of the chloride surface load and the environmental conditions (temperature and RH). Second, as corrosion penetration increases, the pit eventually transitions to a SCC crack, with crack initiation becoming more likely with increasing pit depth. Once pits convert to cracks, a crack growth model is implemented. The SCC growth model includes rate dependencies on both temperature and crack tip stress intensity factor, and crack growth only occurs in time steps when aqueous conditions are predicted. The model suggests that SCC is likely to occur over potential SNF interim storage intervals; however, this result is based on many modeling assumptions. Sensitivity analyses provide information on the model assumptions and parameter values that have the greatest impact on predicted storage canister performance, and provide guidance for further research to reduce uncertainties.
[en] Kinetic regularities of arenesulfonylation of N-alkylanilines in binary water-organic solvents of variable composition have been studied. The rate constants for these reactions increase with increasing the water content in a system. The steric factor has the decisive influence on reactivity of N-alkylamines. The character of the influence of the composition and nature of a solvent on the rate constants for arenesulfonylation was discussed with the assistance of results of quantum chemical simulation of molecular complexes of the nucleophiles studied with the components of the binary systems. Calculation of potential energy surface for the reaction of N-methylaniline with benzenesulfonyl chloride showed that in the gas phase the process occurs by the SN2 mechanism.
[en] Models to predict chloride ingress are numerous but all of them have serious limitations that restrict the present use for long term predictions. An overview is given of the fundamental differences between various models, from those based on Fick's 2. with constant or time-dependent diffusion coefficients and surface chloride contents, to those based on chloride transport equations with or without a multi-species approach. The key advantages and limitations of each type of model are identified and the research needs are summarized and discussed. The three main limitations are shown to be (i) the lack of understanding the time-dependency of the apparent chloride diffusion coefficients, (ii) the lack of good long-term data, the chloride content increase with time close to the exposed surface and (iii) the difficulties in quantifying the boundary conditions for sophisticated ingress models. (author)
[en] Highlights: • A new corrosion prediction model incorporating the effects of multiple dynamic environmental factors is proposed. • The multi-parameter method is accurate to describe the dependence of humidity on temperature. • Correction factors calculated with the new model are close to the real value. • The nonlinear accelerating effects of humidity and temperature are remarkable. - Abstract: This paper studies the effects of relative humidity, temperature, sulphur dioxide, and chlorides on the short-term corrosion behavior in the dynamic environment. A multi-parameter method is developed to characterize the statistical distributions of the environmental factors with high accuracy. The results suggest that TOW (time-of-wetness) should be replaced by temperature and relative humidity distributions. A corrosion model which is combined with physical and empirical knowledge of corrosion is presented and gives more accurate corrosion estimation than using the mean values of the environmental factors and fitting them independently. It is also demonstrated that relative humidity is the most influential factor on corrosion and temperature is secondary. The nonlinearity of their accelerating effects on corrosion rate are remarkable and should be considered in the daily dynamic environment. Sulphur dioxide and chlorides are important accelerating variables and their nonlinear accelerating effects are less significant.
[en] Reinforcement corrosion is one of the major durability problems that need to be solved in order to extend the service life of a structure. It is influenced, on one hand, by the concrete itself, sound or polluted (chlorinated or carbonated), and on the other hand, by the environmental conditions (controlled or outdoor). To explore the influence of temperature and humidity, electrochemical characterisations (potential, linear polarisation resistance and corrosion rate) were carried out on reinforced concrete prisms. A database of more than 3000 values has been delivered. The results enabled us to deduce that both parameters have influences on each other. Moreover, considering the four concretes, the corrosion order obtained in controlled conditions may be different from the one obtained in outdoor conditions. (authors)
[en] Aqueous extracts of humic substances constitute one of the alternatives in the group of products used in sustainable agriculture. They are fundamentally obtained from recyclable organic sources, such as compost and vermicompost. The objectives of this study were 1) to define the salinity tolerance of two sweet basil varieties submitted to NaCl-stress; 2) to evaluate the effect of humates as mitigator of NaCl-induce adverse effects and 3) to test the criteria that leaf relative water content (LRWC) and photosynthetic pigments are accepted as salinity tolerance indicators. The plants were subjected to three NaCl concentrations (0, 50, 100 mM) and one dilution (1/60 v/v) of humates isolated from vermicompost and a control (distilled water) in a completely randomized design with factorial arrangement with six replications. The study was developed under shade-enclosure conditions. The results showed that there is a differential response among varieties with respect LRWC and chlorophyll content. Napoletano was most NaCl tolerant than Sweet Genovese. The LRWC and chlorophyll content perhaps used as tolerance indicators, while defining the NaCl tolerance of sweet basil varieties. The capacity of humates isolated from vermicompost to mitigate NaCl-induced adverse effects in basil development has been proved, when improve some physiological indicators like LRWC and chlorophyll. The discussion of the differential response among basil varieties subjected to different NaCl concentrations and humates isolated from vermicompost is addressed. (author)
[en] A new solar hybrid liquid desiccant air conditioning system has been tested and simulated to investigate the technical feasibility of cooling systems for greenhouse applications using weather data for Malaysia. In this paper, experimental tests are carried out to investigate the performance of a counter flow dehumidifier using lithium chloride (LiCl) solution as the desiccant. A single and multilayer artificial neural network is used to predict the performance of the dehumidifier. Five parameters are used as inputs to the ANN, namely: air and desiccant flow rates, air inlet humidity ratio, and air and desiccant inlet temperatures. The outputs of the ANN are the temperature, humidity ratio, moisture removal rate, and the effectiveness. ANN predictions for these parameters are compared with the experimental values. The results show that the optimum testing model for moisture removal rate in the dehumidifier was the 5-5-5-1 structure with R2 = 0.91, whereas the optimum testing model for effectiveness was the 5-11-11-1 structure with R2 = 0.79. The maximum temperature and humidity ratio difference between the ANN model and experimental are 1.2 °C and 1.9 g/kg, respectively. -- Highlights: • Experimental tests are carried out to investigate the performance of a counter flow dehumidifier. • Single and multilayer artificial neural network used to predict the performance of dehumidifier. • Outputs of the ANN are the temperature, humidity ratio, moisture removal rate, and effectiveness. • The results show that the optimum testing model for MRR was the 5-5-5-1 structure with R2 = 0.91. • The optimum testing model for effectiveness was the 5-11-11-1 structure with R2 = 0.79
[en] The dehumidification process involves simultaneous heat and mass transfer and reliable transfer coefficients are required in order to analyze the system. This has been proved to be difficult and many assumptions are made to simplify the analysis. The present research proposes the use of ANN based model in order to simulate the relationship between inlet and outlet parameters of the dehumidifier. For the analysis, randomly packed dehumidifier with lithium chloride as the liquid desiccant is chosen. A multilayer ANN is used to investigate the performance of dehumidifier. For training ANN models, data is obtained from analytical equations. Eight parameters are used as inputs to the ANN, namely: air and desiccant flow rates, air and desiccant inlet temperatures, air inlet humidity, desiccant inlet concentration, dimensionless temperature ratio, and inlet temperature of the cooling water. The outputs of the ANN are the water condensation rate and the outlet desiccant concentration as well as its temperature. ANN predictions for these parameters are validated well with experimental values available in the literature with R2 value in the range of 0.9251-0.9660. This study shows that liquid desiccant dehumidification system can be alternatively modeled using ANN with a reasonable degree of accuracy. -- Research highlights: → Artificial neural network (ANN) based model is used to simulate the performance of the liquid desiccant dehumidification process. → Three ANNs each with eight inputs and one output have been trained. → Water condensation rate, outlet desiccant concentration and its temperature are predicted. → ANNs predicted parameters are validated well with the experimental results.
[en] A new modification of stationary neutron methods for measurement of the content of moisture and anomalous neutron absorbers in soils and rocks is proposed. A new combined logging neutron tool is designed. By the example of the experimental investigations in geohydrologic boreholes, the merits of the proposed approach are demonstrated
[en] Experimental investigations on several commercially available and newly fabricated rotors are conducted in two different laboratories to evaluate performance trends. Experimental uncertainties are analysed and the parameters determining the rotor performance are investigated. It is found that the optimal rotation speed is lower for lithium chloride or compound rotors than for silica gel rotors. Higher regeneration air temperatures lead to higher dehumidification potentials at almost equal dehumidification efficiencies, but with increasing regeneration specific heat input and enthalpy changes of the process air. The influence of the regeneration air humidity was also notable and low relative humidities increase the dehumidification potential. Finally, the measurements show that rising water content in the ambient air causes the dehumidification capacity to rise, while the dehumidification efficiency is not much affected and both specific regeneration heat input and latent heat change of the process air decrease. For desiccant cooling applications in humid climates this is a positive trend. - Highlights: ► New experimental results on a range of desiccant wheels. ► High dehumidification capacities and low enthalpy changes for process air high water content. ► Higher regeneration temperature increases capacity, but lowers energy efficiency.