A mechanistic model of a PWR-based nuclear power plant in response to external hazard-induced station blackout accidents

Natural hazard-induced nuclear accidents, such as the Fukushima Daiichi Accident that occurred in Japan in 2011, have significantly increased reactor safety studies in understanding nuclear power plant (NPP) responses to external hazard events such as earthquakes and floods. Natural hazards could cause the loss of offsite power in nuclear power plants, potentially leading to a Station Blackout (SBO) accident that significantly contributes to the overall risk of nuclear power plant accidents. Despite the fact that extensive research has been conducted on the station blackout accident for nuclear power plant, further understanding of these events is needed, particularly in the context of the dynamic nature of external hazards such as external flooding. This paper estimates the progression of station blackout events for a generic pressurized water reactor (PWR) in response to external flooding events. The original RELAP5-3D model of the Westinghouse four-loop design pressurized water reactor was adopted and modified to simulate the external flood-induced station blackout accident, including the short-term and long-term station blackout scenarios. A sensitivity analysis of long-term station blackout, examining reactor operation times and analyzing key parameters over time, was also conducted in this work. The results of the analyses, especially the critical timing parameters of key event sequences, provide useful insights about the time during the external flooding event, which is important for plant operators to make timely decisions to prevent potential core damage. This paper represents significant progress toward developing an integrated risk assessment framework for further identifying and assessing the effects of the critical sources of uncertainties of nuclear power plant under external hazard-induced events

15.34% efficiency all-small-molecule organic solar cells with an improved fill factor enabled by a fullerene additive

Solution processed organic solar cells (OSCs) composed of all small molecules (ASM) are promising for production on an industrial scale owing to the properties of small molecules, such as well-defined chemical structures, high purity of materials, and outstanding repeatability from batch to batch synthesis. Remarkably, ASM OSCs with power conversion efficiency (PCE) beyond 13% were achieved by structure improvement of the electron donor and choosingY6as the electron acceptor. However, the fill factor (FF) is an obstacle that limits the further improvement of the PCE for these ASM OSCs. Herein, we focus on the FF improvement of recently reported ASM OSCs withBTR-Cl:Y6as the active layer by miscibility-induced active layer morphology optimization. The incorporation of fullerene derivatives, which have good miscibility with bothBTR-ClandY6, results in reduced bimolecular recombination and thus improved FF. In particular, whenca.5 wt% ofPC(71)BMwas added in the active layer, a FF of 77.11% was achieved without sacrificing the open circuit voltage (V-OC) and the short circuit current density (J(SC)), leading to a record PCE of 15.34% (certified at 14.7%) for ASM OSCs. We found that the optimized device showed comparable charge extraction, longer charge carrier lifetime, and slower bimolecular recombination rate compared with those of the control devices (w/o fullerene). Our results demonstrate that the miscibility driven regulation of active layer morphology by incorporation of a fullerene derivative delicately optimizes the active layer microstructures and improves the device performance, which brings vibrancy to OSC research

A New Phylogenetic Inference Based on Genetic Attribute Reduction for Morphological Data

To address the instability of phylogenetic trees in morphological datasets caused by missing values, we present a phylogenetic inference method based on a concept decision tree (CDT) in conjunction with attribute reduction. First, a reliable initial phylogenetic seed tree is created using a few species with relatively complete morphological information by using biologists’ prior knowledge or by applying existing tools such as MrBayes. Second, using a top-down data processing approach, we construct concept-sample templates by performing attribute reduction at each node in the initial phylogenetic seed tree. In this way, each node is turned into a decision point with multiple concept-sample templates, providing decision-making functions for grafting. Third, we apply a novel matching algorithm to evaluate the degree of similarity between the species’ attributes and their concept-sample templates and to determine the location of the species in the initial phylogenetic seed tree. In this manner, the phylogenetic tree is established step by step. We apply our algorithm to several datasets and compare it with the maximum parsimony, maximum likelihood, and Bayesian inference methods using the two evaluation criteria of accuracy and stability. The experimental results indicate that as the proportion of missing data increases, the accuracy of the CDT method remains at 86.5%, outperforming all other methods and producing a reliable phylogenetic tree

A Combined Approach of High-Throughput Sequencing and Degradome Analysis Reveals Tissue Specific Expression of MicroRNAs and Their Targets in Cucumber

MicroRNAs (miRNAs) are endogenous small RNAs playing an important regulatory function in plant development and stress responses. Among them, some are evolutionally conserved in plant and others are only expressed in certain species, tissue or developmental stages. Cucumber is among the most important greenhouse species in the world, but only a limited number of miRNAs from cucumber have been identified and the experimental validation of the related miRNA targets is still lacking. In this study, two independent small RNA libraries from cucumber leaves and roots were constructed, respectively, and sequenced with the high-throughput Illumina Solexa system. Based on sequence similarity and hairpin structure prediction, a total of 29 known miRNA families and 2 novel miRNA families containing a total of 64 miRNA were identified. QRT-PCR analysis revealed that some of the cucumber miRNAs were preferentially expressed in certain tissues. With the recently developed ‘high throughput degradome sequencing’ approach, 21 target mRNAs of known miRNAs were identified for the first time in cucumber. These targets were associated with development, reactive oxygen species scavenging, signaling transduction and transcriptional regulation. Our study provides an overview of miRNA expression profile and interaction between miRNA and target, which will help further understanding of the important roles of miRNAs in cucumber plants

Effect of Al-5Ti-1B and Y on Casting Mg-5Al-5Si Alloy

Purposes In order to refine the coarse Mg2Si phase in Mg-Al-Si alloy, the Mg-5Al-5Si alloys are modified by adding Al-5Ti-1B and rare earth Y. Methods The Mg-Al-Si alloys with different compositions were prepared by smelting. Various means were used to analyze the composition, microstructure, and mechanical properties of alloys before and after modification, and discuss modification mechanism. Findings The results show that, adding Al-5Ti-1B to the Mg-5Al-5Si alloy transforms the morphology of the primary phase from coarse bulk to fine dendritic or polygon, the number of eutectic phases decreases with the increase of Al-5Ti-1B, while the hardness of the alloys increases significantly, which is attributed to TiB2 phase acting as the heterogeneous nucleation sites for primary Mg2Si phase. On the foundation of adding 1.0% Al-5Ti-1B, rare earth Y can further modify the size and morphology of Mg2Si. When 1.0% Al-5Ti-1B and 1.0% Y are added together, the average size of the primary Mg2Si is decreased to 10.2 μm, the morphology of primary Mg2Si is fine polygonal, and the alloy has the best tensile mechanical properties, with the modification mechanism of rare earth Y mainly adsorption and poisoning

Pseudo-C2-Symmetric Bimetallic Bissalen Catalysts for Efficient and Enantioselective Ring-Opening of meso-Epoxides

Bimetallic catalysts have been synthesised based on Jacobsens C2-symmetric bissalen ligand. They constitute the first examples of compounds with pseuodo-C2 symmetry, owing to the presence of two different metal ions. They have been investigated in the ring-opening of meso-epoxides by trimethylsilyl azide (TMSN3). Pseudo-C2-symmetric [CrIII?Co]bissalen complexes were the best in inducing ee (9394?%) in the ring-opened product of cyclohexene oxide by TMSN3 under solvent-free conditions, whereas a pseudo-C2-symmetric [CrIII?MnIII]-bissalen complex displayed the highest turnover frequency (183 h-1) but induced a lower ee (66?%). A broad substrate scope was displayed by a pseudo-C2-symmetric [CrIII?Co]bissalen catalyst: at 0.1 mol?% catalytic loading and under solvent-free conditions, it induced the highest ee to date in the ring-opened product of a range of different meso-epoxides by using TMSN3

Neural Network Based Deep Learning Method for Multi-Dimensional Neutron Diffusion Problems with Novel Treatment to Boundary

In this paper, the artificial neural networks (ANN) based deep learning (DL) techniques were developed to solve the neutron diffusion problems for the continuous neutron flux distribution without domain discretization in advance. Due to its mesh-free property, the DL solution can easily be extended to complicated geometries. Two specific realizations of DL methods with different boundary treatments are developed and compared for accuracy and efficiency, including the boundary independent method (BIM) and boundary dependent method (BDM). The performance comparison on analytic benchmark indicates BDM being the preferred DL method. Novel constructions of trial function are proposed to generalize the application of BDM. For a more in-depth understanding of the BDM on diffusion problems, the influence of important hyper-parameters is further investigated. Numerical results indicate that the accuracy of BDM can reach hundreds of times higher than that of BIM on diffusion problems. This work can provide a new perspective for applying the DL method to nuclear reactor calculations