Analysis and improvement of the influence of sample shape on Pu measurement results

ABSTRACT

The analysis method of Fast Neutron Multiplicity Counting (FNMC) plays an increasingly important role in the measurement of nuclear material properties. Based on the assumption of point model, fast neutron multiplicity measurement equation is derived which can be used to measure the mass of Pu sample. However, the deviation of the simulated measurement of 1 kg Pu sample reaches 16.6% and increases with mass. Because nonpoint source samples of different shapes do not fully satify the hypothesis. To correct this deviation, a set of fast neutron multiplicity counters was built by Geant4 to simulate and study the mass attribute of Pu samples.The cylindrical sources of different shapes and different masses were simulated, the self-multiplication factor and α coefficient were corrected.And the corresponding third-order polynomial fitting equation was obtained, the goodness of fit was greater than 0.970. In the same way, the spherical and spherical shell source samples in the mass range of 0–5 kg were analyzed, the corrected mass deviation of samples was less than 10% in this interval. The results show that the combination of the fast neutron multiplicity counter and parameter correction can accurately measure the sample mass attribute.     

Relationships between the accumulative damage and dielectric properties of woven BN-coated Hi-Nicalon™ SiC fibre-reinforced SiC matrix composites

The accumulative damage behaviour of BN-coated Hi-Nicalon™ SiC fibre-reinforced SiC matrix composite was examined under tensile cyclic loading at room and elevated temperatures. The accumulative damage occurring during the cyclic loading was quantitatively characterised using the damage parameter obtained by the hysteresis loop curves. The damage parameter increased with increasing applied stress beyond the matrix cracking stress, and it subsequently retained a nearly constant value until just before fracture. Moreover, the dielectric constant, dielectric loss and loss tangent of the composite were measured before and after the fracture in the frequency range 1–1000 MHz. The dielectric properties had similar frequency dependency before and after the fracture. However, the dielectric constant, dielectric loss and loss tangent were lower in the post-fractured specimens than in the pristine ones. The reduction of the dielectric properties was associated with the accumulative damage stored in the specimens. In addition, the relationships between the dielectric properties and the damage parameter were described in detail.     

An investigation of energy loss mechanisms in water-jet assisted underwater laser cutting process using an analytical model

The water-jet assisted underwater laser cutting processes has relatively low overall efficiency compared to gas assisted laser cutting process due to high convective loss in water-jet from the hot melt layer and scattering loss of laser radiation by the water vapour formed at the laser–workpiece–water interaction region. However, the individual contribution of different losses and their dependency on process parameters are not fully investigated. Therefore, a lumped parameter analytical model for this cutting process has been formulated considering various laser–material–water interaction phenomena, different loss mechanisms and shear force provided by the water-jet, and has been used to predict various output parameters including the maximum cutting speed, cut front temperature, cut kerf and the loss of laser power through different mechanisms as functions of laser power and water-jet speed. The predictions of cutting speed, kerf-width and cut front temperature were validated with the experimental results. The modeling revealed that the scattering in water vapour is the dominant loss mechanism, causing ~40–50% of laser power loss. This also predicted that the percentage losses are lower for higher laser powers and lower water-jet speeds. In order to minimize the deleterious effect of vapour, dynamics of its formation due to laser heating and its removal by water-jet was experimentally studied. And, the cutting was done with modulated power laser beam of different pulse on- and off-times to determine the pulse on-time sufficiently short to disallow growth of vapour layer, still cutting be effected and the off-time enough long for water-jet to remove the vapour layer from the interaction zone before next pulse arrives. Compared to CW laser beam the modulated laser beam of same average power yielded higher process efficiency.     

破碎围岩回采巷道锚网索支护参数优化

针对镇城底煤矿8"煤层工作面巷道围岩破碎、支护困难等问题,分析了原有巷道支护方式失效的原因,进而针对性的优化了巷道支护参数,采用①20 mm X 2500 mm左旋螺纹钢锚杆,①17.8 mm X 6500 mm锚索,并进行了验算。最后通过现场实测巷道顶板离层量得到有效的控制,实现了安全髙效开采。     

Data-driven model reduction-based nonlinear MPC for large-scale distributed parameter systems

Model predictive control (MPC) has been effectively applied in process industries since the 1990s. Models in the form of closed equation sets are normally needed for MPC, but it is often difficult to obtain such formulations for large nonlinear systems. To extend nonlinear MPC (NMPC) application to nonlinear distributed parameter systems (DPS) with unknown dynamics, a data-driven model reduction-based approach is followed. The proper orthogonal decomposition (POD) method is first applied off-line to compute a set of basis functions. Then a series of artificial neural networks (ANNs) are trained to effectively compute POD time coefficients. NMPC, using sequential quadratic programming is then applied. The novelty of our methodology lies in the application of POD's highly efficient linear decomposition for the consequent conversion of any distributed multi-dimensional space-state model to a reduced 1-dimensional model, dependent only on time, which can be handled effectively as a black-box through ANNs. Hence we construct a paradigm, which allows the application of NMPC to complex nonlinear high-dimensional systems, even input/output systems, handled by black-box solvers, with significant computational efficiency. This paradigm combines elements of gain scheduling, NMPC, model reduction and ANN for effective control of nonlinear DPS. The stabilization/destabilization of a tubular reactor with recycle is used as an illustrative example to demonstrate the efficiency of our methodology. Case studies with inequality constraints are also presented.     

Quantification of the effects of geometric approximations on the performance of a vertical axis wind turbine

With the soaring energy demands, an urge to explore the alternate and renewable energy resources has become the focal point of various active research fronts. The scientific community is revisiting the inkling to tap the wind resources in more rigorous and novel ways. Recent idea of net-zero buildings has prompted the realization of novel ideas such as employment of omni-directional vertical-axis wind turbine (VAWT) for roof-top application etc. Generally, owing to the high computational cost and time, different levels of geometric simplifications are considered in numerical studies. It becomes very important to quantify the effect of these approximations for realistic and logical conclusions. The detailed performance of a 2.5 m diameter VAWT is sequentially presented with various levels of approximations spanning from two-dimensional to complete three-dimensional geometry. The performance along with the flow physics with focus on tip effects, spanwise flow effects, effect of supporting arms and central hub is discussed. We conclude that two-dimensional approximation can over predict the performance by 32%. Similar trend is also observed for other geometric and flow approximations.     

基于多项式变换的参数估计方法

本文给出一种采用DPT估计SNCK信号时宽—带宽积的方法,并通过仿真该估计方法的性能与其它估计方法进行比较.首先给出SNCK信号参数估计的一般过程.为了便于计算和理论推导,根据估计出的中心频率将接收到的SNCK信号搬移到零频,从而进一步估计其它参数,如采用DPT估计SNCK信号时宽带宽积.本文将重点研究采用DPT算法估计SNCK信号值的方法.     

Fully distributed tracking control for non‐identical multi‐agent systems with matching uncertainty

This article addresses the fully distributed consensus tracking control problem of linear multi‐agent systems with parameter uncertainties. First, a new class of distributed protocol, based on the relative states of neighbors, is proposed. Theoretical analysis indicates that the considered problem can be solved if the control gain constant of the protocol is larger than the norm bound of the leader's nonlinear inputs. Furthermore, a distributed adaptive control protocol is proposed for the case without available global information. The distributed consensus tracking control problem of uncertain linear multi‐agent systems is solved based only on local information under the proposed adaptive protocol. Finally, an application in low‐Earth‐orbit satellite formation flying is provided to illustrate the theoretical results. Copyright © 2014 John Wiley & Sons, Ltd.     

Improving the prediction of petroleum reservoir characterization with a stacked generalization ensemble model of support vector machines

The ensemble learning paradigm has proved to be relevant to solving most challenging industrial problems. Despite its successful application especially in the Bioinformatics, the petroleum industry has not benefited enough from the promises of this machine learning technology. The petroleum industry, with its persistent quest for high-performance predictive models, is in great need of this new learning methodology. A marginal improvement in the prediction indices of petroleum reservoir properties could have huge positive impact on the success of exploration, drilling and the overall reservoir management portfolio. Support vector machines (SVM) is one of the promising machine learning tools that have performed excellently well in most prediction problems. However, its performance is a function of the prudent choice of its tuning parameters most especially the regularization parameter, C. Reports have shown that this parameter has significant impact on the performance of SVM. Understandably, no specific value has been recommended for it. This paper proposes a stacked generalization ensemble model of SVM that incorporates different expert opinions on the optimal values of this parameter in the prediction of porosity and permeability of petroleum reservoirs using datasets from diverse geological formations. The performance of the proposed SVM ensemble was compared to that of conventional SVM technique, another SVM implemented with the bagging method, and Random Forest technique. The results showed that the proposed ensemble model, in most cases, outperformed the others with the highest correlation coefficient, and the lowest mean and absolute errors. The study indicated that there is a great potential for ensemble learning in petroleum reservoir characterization to improve the accuracy of reservoir properties predictions for more successful explorations and increased production of petroleum resources. The results also confirmed that ensemble models perform better than the conventional SVM implementation.     

Control theory for stochastic distributed parameter systems,an engineering perspective

The main purpose of this paper is to survey some recent progresses on control theory for stochastic distributed parameter systems, i.e., systems governed by stochastic differential equations in infinite dimensions, typically by stochastic partial differential equations. We will explain the new phenomenon and difficulties in the study of controllability and optimal control problems for one dimensional stochastic parabolic equations and stochastic hyperbolic equations. In particular, we shall see that both the formulation of corresponding stochastic control problems and the tools to solve them may differ considerably from their deterministic/finite-dimensional counterparts. More importantly, one has to develop new tools, say, the stochastic transposition method introduced in our previous works, to solve some problems in this field.