Evaluation and Application of Quantitative Precipitation Forecast Products for Mainland China Based on TIGGE Multimodel Data

We evaluated 24-h control forecast products from The International Grand Global Ensemble center over the 10 first-class water resource regions of Mainland China in 2013–18 from the perspective of precipitation processes (continuous) and precipitation events (discrete). We evaluated the forecasts from the China Meteorological Administration (CMA), the Centro de Previsão de Tempo e Estudos Climáticos (CPTEC), the Canadian Meteorological Centre (CMC), the European Centre for Medium-Range Weather Forecasts (ECMWF), the Japan Meteorological Agency (JMA), the Korea Meteorological Administration (KMA), the United Kingdom Met Office (UKMO), and the National Centers for Environmental Prediction (NCEP). We analyzed the differences among the numerical weather prediction (NWP) models in predicting various types of precipitation events and showed the spatial variations in the quantitative precipitation forecast efficiency of the NWP models over Mainland China. Meanwhile, we also combined four hydrological models to conduct meteo-hydrological runoff forecasting in three typical basins and used the Bayesian model averaging (BMA) method to perform the ensemble forecast of different scenarios. Our results showed that the models generally underestimate and overestimate precipitation in northwestern China and southwestern China, respectively. This tendency became increasingly clear as the lead time rose. Each model has a high reliability for the forecast of no-rain and light rain in the next 10 days, whereas the NWP model only has high reliability on the next day for moderate and heavy rain events. In general, each model showed different capabilities of capturing various precipitation events. For example, the CMA and CMC forecasts had a better prediction performance for heavy rain but greater errors for other events. The CPTEC forecast performed well for long lead times for no-rain and light rain but had poor predictability for moderate and heavy rains. The KMA, UKMO, and NCEP forecasts performed better for no-rain and light rain. However, their forecasting ability was average for moderate and heavy rain. Although the JMA model performed better in terms of errors and accuracy, it seriously underestimated heavy rain events. The extreme rainstorm and flood forecast results of the coupled JMA model should be treated with caution. Overall, the ECMWF had the most robust performance. Discrepancies in the forecasting effects of various models on different precipitation events vary with the lead time and region. When coupled with hydrological models, NWP models not only control the accuracy of runoff prediction directly but also increase the difference among the prediction results of different hydrological models with the increase in NWP error significantly. Among all the single models, ECMWF, JMA, and NCEP have better effects than the other models. Moreover, the ensemble forecast based on BMA is more robust than the single model, which can improve the quality of runoff prediction in terms of accuracy and reliability.

Enhancements in Day-Ahead Forecasts of Solar Irradiation with Machine Learning: A Novel Analysis with the Japanese Mesoscale Model

The objective of this study is to propose and evaluate a set of modifications to enhance a machine-learning-based method for forecasting day-ahead solar irradiation. To assess the proposed modifications, they were implemented in an initial forecast method, and their effectiveness was analyzed using two years of data on a national scale in Japan. In addition, the accuracy of the modified method was compared with one of the forecast methods for solar irradiation used by the Japan Meteorological Agency (JMA), namely, the mesoscale model (MSM). Such forecasts were made publicly available only recently, which makes this study one of the first ones to compare them with machine-learning-based forecasts. The annual root-mean-square error (RMSE) of local forecasts of the JMA-MSM varied from 0.1 to 0.14 kW h m−2; the regional equivalent varied from 0.062 to 0.091 kW h m−2. In comparison with these results, the modified model achieved an average RMSE reduction of 7.5% on the local scale and 16% on the regional scale. The modified model also had a skill score that was 23% higher than that of the JMA model. Furthermore, the performance of the JMA model had strong spatial and seasonal dependencies, which were reduced in the machine-learning-based forecasts. The results show that the proposed modifications are effective in reducing large forecasts errors, but they cannot compensate for situations in which the input data used to make the forecasts are highly inaccurate.

Study on Transformation Mechanism and Kinetics of α’ Martensite in TC4 Alloy Isothermal Aging Process

The law of microstructure evolution and transformation mechanism of the α′ martensite decomposition during 400–600 °C were studied by the isothermal dilatometry. The transformation process of α′ martensite was quantitatively characterized based on Johnson–Mehl–Avrami (JMA) model, and the microstructure evolution under different aging processes was observed and compared on Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM). The results showed that α′ → α + β is the elemental diffusion transformation, the position and shape of the precipitate gradually change with the holding time and temperature. The decomposition rate of α′ martensite was positively correlated with the aging temperature. The whole transformation process was divided into two stages based on the value of the Avrami exponent n, and the corresponding average values of the transformation activation energies Q are 46.1 kJ/mol and 116.8 kJ/mol, respectively. The calculated model had good agreement with the experimental data, and the transformation curve of α′ martensite with time and temperature during the isothermal aging at 400–600 °C was drawn.

Effect of cobalt content on non-isothermal crystallization kinetics of Fe-based amorphous alloys

In the present study, FeSiBP and FeCoSiBP ribbons with a fully amorphous structure were made by melt spinning technique. A detailed analysis of the isochronal crystallization behavior is presented in this paper. The influence of cobalt on the crystallization kinetics of the alloys was studied under isochronal conditions using differential scanning calorimetry (DSC). Apparent and local activation energy values were determined by Kissinger, Ozawa and Kissinger-Akahira-Sunose (KAS) methods. The results indicate that appropriate amounts of cobalt can significantly enhance the thermal stability of Fe-based alloys, through an increase in nucleation activation energy from 538kJ/mol to 701kJ/mol, obtained by Kissinger method. Furthermore, with the method proposed by Matusita, it was possible to obtain global values for the Avrami exponent, noting that from a general perspective, Co changes the mechanism from diffusion controlled to interface controlled. This leads to the conclusion that the crystallization process is complex and takes place in more than one stage. Therefore, the determination of nucleation mechanisms and dimensional growth is difficult due to the inapplicability of the Johnson-Melh-Avrami (JMA) model. As such, a study under isothermal conditions is suggested, in order to achieve a full understanding of the mechanisms involved.

Study on Non-Isothermal Transformation of Ti-6Al-4V in Solution Heating Stage

In order to understand the non-isothermal transformation behavior of Ti-6Al-4V titanium alloy in the continuous heating stage of solution treatment, thermal dilatometry tests with heating rates of 0.1~0.8 °C/s were designed. The conversion between the expansion amount and the transformed volume fraction was realized by the lever principle, and the transformation characteristics of α + β → β were quantified based on the Kissinger-Akahira-Sunose (KAS) theory and the modified Johnson–Mehl–Avrami (JMA) model. The results show that the phase transformation kinetics curves present typical “S” patterns, and the element diffusion transformation controls the nucleation and growth of new grains during the transformation of α + β → β. The phase transformation interval gradually moves to high temperature regions with the increase of heating rates, and the phase transformation activation energy is 445.5 kJ·mol−1. The phase transformation process is divided into three stages according to the relationship between the Avrami exponent n and the transformed volume fraction fT. These three stages correspond to different stages of grain nucleation or growth.

Structural, morphological, magnetic and hydrogen absorption properties of LaNi5 alloy: A comprehensive study

A comprehensive study of structural, morphological, magnetic and hydrogen absorption properties of LaNi 5–H system was investigated. The X-ray diffraction patterns show that as-synthesized LaNi 5 alloy is single phase with CaCu5-type structure while some weak peaks of elemental nickel also appeared after several hydrogenation/dehydrogenation (H/D) cycling. The presence of pure Ni was also followed using the room temperature magnetic measurements. After H/D cycling, the particle size decreases and particle size distribution was found nearly uniform compared to noncycled alloy. The pressure-composition isotherms (PCIs) of the hydrogen absorption reaction were determined in the temperature range 20–80°C using a homemade Sievert's type experimental apparatus, and then the enthalpy and entropy of hydride formation were calculated. The hydriding kinetic mechanism of LaNi 5 was evaluated using the different fitting models: Jander diffusion model (JDM), Johnson–Mehl–Avrami (JMA) and Chou models. All employed models confirm an increase in the hydriding reaction rate with temperature. However, the calculated results using JMA model show a better agreement with the experimental data and hence we believe that diffusion along with nucleation and growth is the rate-controlling step for the hydriding reaction. The values of activation energy for hydriding reaction were also obtained by JD and JMA models.

Experimental Study on the Hydrogen Storage Properties of LaNi5 Alloy in Repeated Hydriding/Dehydriding Cycles

LaNi5 alloy is one of the promising materials for hydrogen storage. It has good activation property, fast reaction rate and moderate plateau pressure. However, some of its hydrogen storage properties will change after repeated hydriding/dehydriding cycles, which limits its practical application. Therefore, this paper investigated the cycling properties of LaNi5 alloy by volumetric method. The results showed that the reaction rate increased with cycling. The hydriding/dehydriding hydrogen content decreased with cycling. For hydriding reaction, the equilibrium pressure increased with cycling, while it decreased for dehydriding at 40°C and 60°C. After 100 cycles, the LaNi5 alloy has been severely pulverized and oxygenated. The oxidation products include LaNiO2, La2NiO4, La2NiO4.18 and LaNiO3. The JMA model was found to fit the kinetic data well, suggesting a nucleation and growth controlling mechanism. The intrinsic reaction rate constant ka increases from 21.87 s-1to 24.81 s-1, while the activation energy decreases from the initial value of 19459 to 19373 J/mol after 100 cycles.

Crystallization Behavior of Mg60Ni23.6La16.4 Metallic Glass

Mg60Ni23.6La16.4 amorphous ribbon was prepared by melting-spinning method and the crystallization behavior was investigated by differential scanning calorimetry (DSC). The Mg60Ni23.6La16.4 crystallization process exhibits two stages of crystallization and shows an obviously kinetic nature. Isothermal DSC curves indicate that the crystallization is a nucleation-and-growth procedure. The activation energy analysis based on Kissinger Method shows that the growth process for the first crystallization procedure is more difficult than that for the second one. Calculation based on the Johnson-Mehl-Avrami (JMA) model shows that the primary crystallization starts from small crystalline grains with an increasing nucleation rate.