The wettability and infiltration of molten ZrSi2 and ZrSi2-Lu2O3 alloys into Cf/SiC and B4C-infiltrated Cf/SiC composites were investigated to understand the interfacial interactions that occur during the development of Cf/SiC-ZrC and Cf/SiC-ZrB2-ZrC-Lu2O3 materials. A significant evaporation of Si from the liquid affected the wetting behaviour of the alloy when tested in a vacuum at 1670 °C. The better wetting and spreading of the alloy over the surface was observed for the composites with lower overall porosity (12 %). On the other hand, the formation of an outer dense layer, followed up by the uniform infiltrated region up to ~ 1 mm was observed for the Cf/SiC with higher porosity (21 %). The infiltrated alloy reacted with SiC matrix to form ZrC or with B4C-infiltrated SiC matrix to form ZrB2-ZrC-SiC. The Lu2O3 particles were not wetted by the melt, and were pushed away of the reaction zone by the solidification front. 相似文献
Fine powders of aluminum were produced in a pilot-plant, inert-gas atomizerwith a confined-design nozzle, which operated vertically upward. Argonand helium at 1.85 MPa and nitrogen at 1.56 MPa were used as the atomizingagent. The morphology of the powder particles was examined by SEM. Powderswere sieved dry and wet. The Sauter mean diameter of the powders varied from20.70 to 10.25 m depending on the atomizing gas. The distribution ofsizes was bimodal. The mean thickness of oxide on the surface of the powderwas calculated from the total oxygen contents of powder samples (determinedby a Leco analyzer). In addition, ESCA measurements and BET tests werecarried out for surface-oxide thickness and area measurements,respectively. The finest powder produced under helium incorporated thinnersurface-oxide layers than the coarser ones produced under argon andnitrogen. This was due to differences in physical properties (such asdensity, thermal conductivity) and flow properties (such as gasvelocity and relative velocity) of the atomizing gases used, i.e., helium,argon, and nitrogen. The oxide was very irregular in thickness in thecoarse-size range of the Al powders produced under argon and nitrogen. Thiswas presumably because of the high- and low-temperature oxidation ofaluminum droplets during the atomization and subsequent solidification andcooling periods leading to the rough surfaces observed with SEMinvestigation in the present work. 相似文献
We present a comprehensive review of the evolutionary design of neural network architectures. This work is motivated by the fact that the success of an Artificial Neural Network (ANN) highly depends on its architecture and among many approaches Evolutionary Computation, which is a set of global-search methods inspired by biological evolution has been proved to be an efficient approach for optimizing neural network structures. Initial attempts for automating architecture design by applying evolutionary approaches start in the late 1980s and have attracted significant interest until today. In this context, we examined the historical progress and analyzed all relevant scientific papers with a special emphasis on how evolutionary computation techniques were adopted and various encoding strategies proposed. We summarized key aspects of methodology, discussed common challenges, and investigated the works in chronological order by dividing the entire timeframe into three periods. The first period covers early works focusing on the optimization of simple ANN architectures with a variety of solutions proposed on chromosome representation. In the second period, the rise of more powerful methods and hybrid approaches were surveyed. In parallel with the recent advances, the last period covers the Deep Learning Era, in which research direction is shifted towards configuring advanced models of deep neural networks. Finally, we propose open problems for future research in the field of neural architecture search and provide insights for fully automated machine learning. Our aim is to provide a complete reference of works in this subject and guide researchers towards promising directions.
In this study, Y3+ ion-substituted M-type barium hexaferrites (BaM; BaFe12O19) were fabricated via facile ceramic route. As-prepared powders were characterized by X-ray powder diffractometry (XRD), Fourier transform infrared (FT-IR) spectroscopy, and impedance spectroscopy. XRD (Rietveld) analyses confirmed the presence of a single characterization of all samples (except x = 0.0 and 0.1 samples). The crystallite sizes of products are found in the range of 47.2–63.2 nm. Spectral analysis (FT-IR) also presented the formation of spinel structure for all products. The ac conductivity of the substituted samples was found to initially decrease slightly with increase in Y3+ compared with unsubstituted, and then variation tendency changes at the medium substitution ranges are observed with a different attitude against temperature. In the end, the lower conductivity for high substitutions is recorded and increases as functions of frequency while it also increases with the elevation of temperature. It was observed that ac conductivities of products increased by increasing frequency which indicate that observed ac conductivity is due to both electronic and polaron hopping mechanism. 相似文献
Higher‐order finite element methods have emerged as an important discretization scheme for simulation. They are increasingly used in contemporary numerical solvers, generating a new class of data that must be analyzed by scientists and engineers. Currently available visualization tools for this type of data are either batch oriented or limited to certain cell types and polynomial degrees. Other approaches approximate higher‐order data by resampling resulting in trade‐offs in interactivity and quality. To overcome these limitations, we have developed a distributed visualization system which allows for interactive exploration of non‐conforming unstructured grids, resulting from space‐time discontinuous Galerkin simulations, in which each cell has its own higher‐order polynomial solution. Our system employs GPU‐based raycasting for direct volume rendering of complex grids which feature non‐convex, curvilinear cells with varying polynomial degree. Frequency‐based adaptive sampling accounts for the high variations along rays. For distribution across a GPU cluster, the initial object‐space partitioning is determined by cell characteristics like the polynomial degree and is adapted at runtime by a load balancing mechanism. The performance and utility of our system is evaluated for different aeroacoustic simulations involving the propagation of shock fronts. 相似文献
This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for automatic detection of electroencephalographic changes. Decision making was performed in two stages: feature extraction by computation of Lyapunov exponents and classification by the ANFIS trained with the backpropagation gradient descent method in combination with the least squares method. Five types of electroencephalogram (EEG) signals were classified by five ANFIS classifiers. To improve diagnostic accuracy, the sixth ANFIS classifier (combining ANFIS) was trained using the outputs of the five ANFIS classifiers as input data. The proposed ANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach. Some conclusions concerning the saliency of features on classification of the EEG signals were obtained through analysis of the ANFIS. The performance of the ANFIS model was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed ANFIS model has potential in classifying the EEG signals. 相似文献