A new method for prediction of Gurney velocity of explosives is introduced in which energy output is correlated with the heat of detonation, the number of moles of gaseous products of detonation per gram of explosive and the average molecular weight of gaseous products. It is assumed that the CHNO explosive reacts to form products composed of N2 , CO, H2O, CO2, H2,O2 and C(s) as determined by the oxygen balance of the unreacted compound. Good agreement is obtained between measured and calculated values of Gurney velocity as compared to previous correlations which assumed the reaction products to consist of N2 , H2O, CO2 and either C(s) or O2. 相似文献
Summary Nonlinear natural convection in a mushy layer during solidification of a binary alloy is investigated under a high gravity environment where the rotation axis is inclined to the high gravity vector. Asymptotic and scaling analyses are applied to convective flow within the mushy layer and in vertical chimneys. The main result is that, for some particular moderate rotation range, vertical velocity in the chimneys decreases rapidly with increasing rotation rate and appears to have opposite signs across some rotation dependent vertical level. 相似文献
The present work aimed to evaluate and optimize the design of an artificial neural network (ANN) combined with an optimization algorithm of genetic algorithm (GA) for the calculation of slope stability safety factors (SF) in a pure cohesive slope. To make datasets of training and testing for the developed predictive models, 630 finite element limit equilibrium (FELE) analyses were performed. Similar to many artificial intelligence-based solutions, the database was involved in 189 testing datasets (e.g., 30% of the entire database) and 441 training datasets; for example, a range of 70% of the total database. Moreover, variables of multilayer perceptron (MLP) algorithm (for example, number of nodes in any hidden layer) and the algorithm of GA like population size was optimized by utilizing a series of trial and error process. The parameters in input, which were used in the analysis, consist of slope angle (β), setback distance ratio (b/B), applied stresses on the slope (Fy) and undrained shear strength of the cohesive soil (Cu) where the output was taken SF. The obtained network outputs for both datasets from MLP and GA-MLP models are evaluated according to many statistical indices. A total of 72 MLP trial and error (e.g., parameter study) the optimal architecture of 4 × 8 × 1 were determined for the MLP structure. Both proposed techniques result in a proper performance; however, according to the statistical indices, the GA–MLP model can somewhat accomplish the least mean square error (MSE) when compared to MLP. In an optimized GA–MLP network, coefficient of determination (R2) and root mean square error (RMSE) values of (0.975, and 0.097) and (0.969, and 0.107) were found, respectively, to both of the normalized training and testing datasets.
Summary Finite amplitude fluid motion is investigated in a horizontal layer of an infinite Prandtl number fluid with an upper free surface for the case where thermocapillary effects are significant and gravitational effects are negligible. It is found that subcritical instability exists and that two-dimensional rolls and down-hexagons (where motion is downward at the cells' centers) are always unstable. But up-hexagons (where motion is upward at the cells' centers) are stable for sufficiently small amplitude , while both uphexagons and squares are stable in a range of larger where hysteresis effects exist.With 1 Figure 相似文献
Catalysis Letters - Several highly efficient and magnetically recyclable cobalt catalytic systems were prepared using magnetic chitosan and some safe and available organic compounds... 相似文献
Silicon - In this paper, a new structure: triple work function metal gate SOI MESFET, intended for integration into the deep-submicron CMOS technology, is proposed. The gate of the device consists... 相似文献
This paper presents a novel approach to the problem of nondestructive pipeline testing using ultrasonic imaging. The identification of the flaw type and its dimensions are the most important problems in the pipeline inspection. Unlike typical methods, a decision based neural network is used for the detection of flaws. We train a generalized regression neural network to determine the dimensions of the corrosions and generate the whole image of both the internal and external walls of the oil pipeline. As an improvement to the detection algorithm, we introduce fuzzy decision-based neural network algorithms for the detection and classification of the corrosions. The simulation and experimental systems results show that these new methods outperform the existing methods. 相似文献