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Silicon carbide fiber reinforced silicon carbide matrix (SiCf/SiC) composite is the key cladding material of nuclear fuel, which determines the safety and reliability of nuclear fuel storage and transportation. The replacement of its storage and transportation scenario needs to be completed by the manipulator, but the application of SiCf/SiC wear, fracture, and nuclear leakage in the snatching process of brittle-flexible-rigid contact in the irradiation environment has been seriously restricted due to unclear understanding of the damage mechanism. Therefore, the effects of irradiation dose and clamping load on the friction characteristics of the contact interface between SiCf/SiC clad tube are studied in this paper, and the effects of irradiation parameters and clamping force on the static friction coefficient of the contact interface between the clad tube and flexible nitrile are obtained. Based on the Greenwood-Williamson tribological model, a numerical model of the shape and structure of the contact micro-convex at the micro-scale of the clamping interface is constructed by introducing the multi-surface integral, and finally verified by experiments. The research results show that there is a unique "Irradiation suppression zone" under the clamping condition of SiCf/SiC cladding tube under the nuclear irradiation environment, and the growth of static friction coefficient slows down until stagnates after irradiation reaches a certain extent (600 kGy), and there will be a decline when the irradiation dose continues to increase, among which the clamping force of 15.2 N within the irradiation interval of 1,000 kGy can meet the safety of nuclear environment operation. The results of this paper can provide an important theoretical basis and application guidance for the safe operation of SiCf/SiC cladding tubes in the storage and transportation clamping process. [ABSTRACT FROM AUTHOR]

Continuous silicon carbide fiber-reinforced silicon carbide matrix (SiCf/SiC) composites are widely used in nuclear fuel cladding due to their excellent physical and chemical properties. The application of nuclear energy puts forward higher requirements on the structural stability and mechanical properties of SiCf/SiC components. Therefore, in this study, a multiscale analysis strategy considering the microscopic interface parameters and mesoscopic structure response to the failure of ceramic matrix composites (CMCs) was constructed for in-depth investigation of the failure behavior mechanism of CMCs. Among them, a microscopic representative volume element model coupled with a phase field fracture approach and a cohesion zone model was used to capture matrix brittle cracking and fiber/matrix debonding behaviors. The progressive damage behavior of fiber/matrix interfacial strength on unidirectional CMCs (UD-CMCs) was investigated. The results show that the presence of a weak interface causes a dramatic decrease in the strength of UD-CMCs by 70%. Based on the real winding path of three-dimensional (3D) filament, a 3D wound SiCf/SiC tube model reflecting the overlapping effect between fiber bundles was established, and by combining with the matrix cracking theory and LaRC05 failure criterion, the effect of winding angle on the mechanical properties of 3D wound SiCf/SiC tube was studied. The results reveal that the established 3D winding model can capture not only the overall response, but also the local response, providing an effective tool for the structural design, failure analysis, and safety service design of CMC components. [ABSTRACT FROM AUTHOR]

Conventional methods of machine learning have been widely used to generate spatial prediction models because such methods can adaptively learn the mapping relationships among spatial data with limited prior knowledge. However, the direct application of these methods to build a global model without considering spatial heterogeneity cannot accurately describe the local relationships among spatial variables, which might lead to inaccurate predictions. To avoid these shortcomings, we have presented a unified framework for handling spatial heterogeneity by incorporating the geographically weighted scheme into machine learning methods. The proposed framework has the potential to extend the existing models of machine learning for analysing heterogeneous spatial data. Furthermore, geographically weighted support vector regression (GWSVR) has been introduced as an implementation of the proposed framework. Experimental studies on environmental datasets were used to test the ability of model predictions. The results show that the mean absolute percentage error, normalized mean square error, and relative error percentage of the GWSVR model are 0.436, 0.903, and 0.558, respectively, when analysing soil metal chromium (Cr) concentrations and 0.221, 0.287, and 0.206, respectively, when predicting PM2.5 concentrations; these values are lower than those obtained using support vector regression, geographically weighted regression (GWR), and GWR-kriging models. These case studies have proved the validity and feasibility of the proposed framework. [ABSTRACT FROM AUTHOR]

Prediction of drought class transitions has been received increasing interest in the field of water resource management. Markov chain models are effective prediction tools that are widely used to analyse drought class transitions by describing the temporal dependency of drought events. However, geophysical events or phenomena (such as drought events) can exhibit spatial effects resulting from spatial heterogeneity and/or dependency. This means that on the one hand the drought processes may vary over space, and on the other hand the state change of a drought event may not only depend on its previous state but also on the previous states of its neighbours, and it is thus unreasonable to directly apply Markov chain models without considering spatial effects. Therefore, this paper proposes a framework that considers spatial effects when employing drought class transition analysis. Three types of Markov chain models are introduced (traditional, local and spatial). To test for the existence of spatial effects, spatial clustering technology is selected to identify spatial heterogeneity, and a Q statistic is used to determine the existence of spatial dependency. Based on the results of these tests, a corresponding type of Markov chain models is then selected to analyse drought class transitions. Monthly rainfall time series data for Southwest China from 1951 to 2010 are employed in a case study, and the results show that spatial heterogeneity exists for both the 3- and 9-month SPI time series; however, the existence of spatial dependency is not confirmed. Forward and backward estimation rules are also obtained for drought class transitions using local Markov chain models. [ABSTRACT FROM AUTHOR]

Word embeddings are the semantic representations of the words. They are derived from large corpus and work well on many natural language tasks, with one downside of costing large memory space. In this paper, we propose binary word embedding models based on inspirations from biological neuron coding mechanisms, converting the spike timing of neurons during specific time intervals into binary codes, reducing the space and speeding up computation. We build three types of models to post-process the original dense word embeddings, namely, the homogeneous Poission processing-based rate coding model, the leaky integrate-and-fire neuron-based model, and the Izhikevich's neuron-based model. We test our binary embedding models on word similarity and text classification tasks of five public datasets. The experimental results show that the brain-inspired binary word embeddings (which reduce approximately 68.75% of the space) get similar results to original embeddings for word similarity task while better performance than traditional binary embeddings on text classification task. [ABSTRACT FROM AUTHOR]

Conventional rigid electronics are usually unconformable with soft skins and tend to fail in accurate physiological monitoring and precise treatment. Electronic skins (e-Skins) made by conductive and stretchable materials offer mechanical compliance for fabricating flexible and conformable wearables. Compared to common organic or inorganic conductive materials, gallium-based liquid metals alone own superior conductivity and compliance. Here, we demonstrate a highly conductive and stretchable electronic skin with liquid metal circuits (LMCs) embedded in silicone rubber film, which are functionalized for physiological signals monitoring. Through the designs of serpentine structure, LMCs maintained good electrical conductivity and functionality under over 100% strain. Also, a wearable electrocardiogram (ECG) recording device was fabricated and tested. The device was able to acquire steady signals during real-time measurement of physical activities. The proposed liquid metal e-Skin can be further extended to conformable bio-integrated healthcare devices and intelligent health monitoring networks. [ABSTRACT FROM AUTHOR]

The pulse tube refrigerator (PTR) is a promising small-scale cryocooler. This paper first briefly introduces the history of the pulse tube refrigerator. It has pointed out that technology improvements and theoretical developments of the pulse tube refrigerator closely relate with the internal streaming effects. Then the discovering history and classification of the streaming or DC (direct current) flow effect are summarized. It proposes for the first time that the physical significance of the streaming contains the driving mechanisms and the transport mechanisms. It demonstrates that the driving mechanisms are the asymmetry of fluid flow and temperature while the transport mechanisms are a loop or vorticity, which transmits nonlinear dissipations. The important advancements have been made over the past two decades all over the world in research of streaming of the pulse tube refrigerator including Gedeon DC flow, Rayleigh streaming, the third type of DC flow and the regenerator circulation. With regard to Gedeon DC flow, theoretical and experimental analyses have been made and different suppression methods are summarized. In the aspect of Rayleigh streaming, it mainly focuses on the analytical solution of the second-order mass flow and the research of tapered pulse tubes. In particular, limited research on the third type of DC flow and regenerator circulation is presented. The experimental measurement techniques of streaming also are summarized. Finally, this paper briefly discusses the key scientific and technical issues of the current research, and foretells the future development trends of streaming research in PTR. [ABSTRACT FROM AUTHOR]

The nascent field of nanotechnology-enabled metallurgy has great potential. However, the role of eutectic alloys and the nature of alloy solidification in this field are still largely unknown. To demonstrate one of the promises of liquid metals in the field, we explore a model system of catalytically active Bi-Sn nano-alloys produced using a liquid-phase ultrasonication technique and investigate their phase separation, surface oxidation, and nucleation. The Bi-Sn ratio determines the grain boundary properties and the emergence of dislocations within the nano-alloys. The eutectic system gives rise to the smallest grain dimensions among all Bi-Sn ratios along with more pronounced dislocation formation within the nano-alloys. Using electrochemical CO2 reduction and photocatalysis, we demonstrate that the structural peculiarity of the eutectic nano-alloys offers the highest catalytic activity in comparison with their non-eutectic counterparts. The fundamentals of nano-alloy formation revealed here may establish the groundwork for creating bimetallic and multimetallic nano-alloys. The combination of metallurgy concepts and nanotechnology with liquid metal processing has been largely unexplored. Here the authors use liquid-phase ultrasonication to produce a model system of catalytically active nano-alloys, demonstrating electrocatalysis and photocatalysis. [ABSTRACT FROM AUTHOR]