离焦散斑技术研究Kirchhoff板在动载作用期的弯曲

本文使用动态离焦散斑技术,测试板的动态弯曲获得成功。并推导了Kirchhoff板动态变形的有关分析,提出了由最大斜率确定材料常数的思想。显然,这是同离焦散斑方法所测数据直接相关的处理手法。     

On spanning tree problems with multiple objectives

We investigate two versions of multiple objective minimum spanning tree problems defined on a network with vectorial weights. First, we want to minimize the maximum ofQ linear objective functions taken over the set of all spanning trees (max-linear spanning tree problem, ML-ST). Secondly, we look for efficient spanning trees (multi-criteria spanning tree problem, MC-ST).Problem ML-ST is shown to be NP-complete. An exact algorithm which is based on ranking is presented. The procedure can also be used as an approximation scheme. For solving the bicriterion MC-ST, which in the worst case may have an exponential number of efficient trees, a two-phase procedure is presented. Based on the computation of extremal efficient spanning trees we use neighbourhood search to determine a sequence of solutions with the property that the distance between two consecutive solutions is less than a given accuracy.Partially supported by Deutsche Forschungsgemeinschaft and HCº Contract no. ERBCHRXCT 930087.Partially supported by Alexander von Humboldt-Stiftung.     

Control and scheduling in a two-station queueing network: Optimal policies and heuristics

Consider a two-station queueing network with two types of jobs: type 1 jobs visit station 1 only, while type 2 jobs visit both stations in sequence. Each station has a single server. Arrival and service processes are modeled as counting processes with controllable stochastic intensities. The problem is to control the arrival and service processes, and in particular to schedule the server in station 1 among the two job types, in order to minimize a discounted cost function over an infinite time horizon. Using a stochastic intensity control approach, we establish the optimality of a specific stationary policy, and show that its value function satisfies certain properties, which lead to a switching-curve structure. We further classify the problem into six parametric cases. Based on the structural properties of the stationary policy, we establish the optimality of some simple priority rules for three of the six cases, and develop heuristic policies for the other three cases.     

Local minima of the trust region problem

We consider the minimization of a quadratic formzVz+2zq subject to the two-norm constraint z=. The problem received considerable attention in the literature, notably due to its applications to a class of trust region methods in nonlinear optimization. While the previous studies were concerned with just the global minimum of the problem, we investigate the existence of all local minima. The problem is approached via the dual Lagrangian, and the necessary and sufficient conditions for the existence of all local minima are derived. We also examine the suitability of the conventional numerical techniques used to solve the problem to a class of single-instruction multiple-data computers known as processor arrays (in our case, AMT DAP 610). Simultaneously, we introduce certain hardware-oriented multisection algorithms, showing their efficiency in the case of small to medium size problems.This research was partially supported by the National Physical Laboratories of England under Contract RTP2/155/127.     

Numerical solution of eigenvalue problems for Hamiltonian systems

This paper discusses the numerical solution of eigenvalue problems for Hamiltonian systems of ordinary differential equations. Two new codes are presented which incorporate the algorithms described here; to the best of the author’s knowledge, these are the first codes capable of solving numerically such general eigenvalue problems. One of these implements a new new method of solving a differential equation whose solution is a unitary matrix. Both codes are fully documented and are written inPfort-verifiedFortran 77, and will be available in netlib/aicm/sl11f and netlib/aicm/sl12f.     

Binary neutron stars gravitational wave detection based on wavelet packet analysis and convolutional neural networks

This work investigates the detection of binary neutron stars gravitational wave based on convolutional neural network(CNN).To promote the detection performance and efficiency,we proposed a scheme based on wavelet packet(WP)decomposition and CNN.The WP decomposition is a time-frequency method and can enhance the discriminant features between gravitational wave signal and noise before detection.The CNN conducts the gravitational wave detection by learning a function mapping relation from the data under being processed to the space of detection results.This function-mapping-relation style detection scheme can detection efficiency significantly.In this work,instrument effects are con-sidered,and the noise are computed from a power spectral density(PSD)equivalent to the Advanced LIGO design sensitivity.The quantitative evaluations and comparisons with the state-of-art method matched filtering show the excellent performances for BNS gravitational wave detection.On efficiency,the current experiments show that this WP-CNN-based scheme is more than 960 times faster than the matched filtering.     

Some optimizations on detecting gravitational wave using convolutional neural network

This work investigates the problem of detecting gravitational wave (GW) events based on simulated damped sinusoid signals contaminated with white Gaussian noise. It is treated as a classification problem with one class for the interesting events. The proposed scheme consists of the following two successive steps: decomposing the data using a wavelet packet, representing the GW signal and noise using the derived decomposition coefficients; and determining the existence of any GW event using a convolutional neural network (CNN) with a logistic regression output layer. The characteristic of this work is its comprehensive investigations on CNN structure, detection window width, data resolution, wavelet packet decomposition and detection window overlap scheme. Extensive simulation experiments show excellent performances for reliable detection of signals with a range of GW model parameters and signal-to-noise ratios. While we use a simple waveform model in this study, we expect the method to be particularly valuable when the potential GW shapes are too complex to be characterized with a template bank.     

Cavitation onset caused by a dynamic pressure wave in liquid pipelines

When liquids flow in the pipelines, the onset of cavitation can be characterized by a variant of the Euler number known as the cavitation number (CN), which is based on the velocity and denoted by C in this paper. Conventionally, cavitation is considered to be induced when C ~ 1. However, experimental observations and several pipe bursts indicate that the CN may incorrectly predict the onset of cavitation. For example, when leakage occurs in the pipeline or a valve in the pipeline is opened, the resultant pressure loss generates a dynamic pressure wave with a small amplitude, which may lead to bubble formation, even though C ~ 1 is not satisfied. Hence, this paper proposes another CN based on the amplitude of the generated dynamic pressure wave, rather than the velocity, for ascertaining the onset of cavitation. The validity of the proposed CN was verified through experiments and a case study. The results indicated that the proposed CN can be effectively used for cavitation prediction induced by pressure fluctuations and for investigating phenomena such as pressure fluctuation, leakage, and corrosion in liquid pipelines, tanks, and pressure vessels, as well as the safety design of liquefied natural gas tanks and tankers.     

Dynamic magnetic hysteresis behavior and dynamic phase transition in the spin-1 Blume-Capel model

The nature (time variation) of response magnetization m(wt) of the spin-1 Blume-Capel model in the presence of a periodically varying external magnetic field h(wt) is studied by employing the effective-field theory (EFT) with correlations as well as the Glauber-type stochastic dynamics. We determine the time variations of m(wt) and h(wt) for various temperatures, and investigate the dynamic magnetic hysteresis behavior. We also investigate the temperature dependence of the dynamic magnetization, hysteresis loop area and correlation near the transition point in order to characterize the nature (first- or second-order) of the dynamic transitions as well as obtain the dynamic phase transition temperatures. The hysteresis loops are obtained for different reduced temperatures and we find that the areas of the loops are decreasing with the increasing of the reduced temperatures. We also present the dynamic phase diagrams and compare the results of the EFT with the results of the dynamic mean-field approximation. The phase diagrams exhibit many dynamic critical points, such as tricritical (•), zero-temperature critical (Z), triple (TP) and multicritical (A) points. According to values of Hamiltonian parameters, besides the paramagnetic (P), ferromagnetic (F) fundamental phases, one coexistence or mixed phase region, (F+P) and the reentrant behavior exist in the system. The results are in good agreement with some experimental and theoretical results.     

Computation and conversion of brain pH values obtained with two algorithms of phosphorus magnetic resonance spectroscopy data analysis

The intracellular brain pH in phosphorus magnetic resonance spectroscopy is calculated using the chemical shift between the inorganic phosphate and phosphocreatine with the Henderson–Hasselbalch equations. Researchers use various mathematical formulas that have different parameters and get various results for the same input data as a consequence. Thus, the aim of this article was to determine the mathematical formulas that allow the conversion of the pH values obtained by the most popular analysis methods to each other. To determine the relationships between pH results and the applied mathematical formula, the pH values were calculated using two algorithms for the theoretical chemical shift values. The pH results were compared with each other using the appropriate t-tests. Mathematical formulas were designed to simplify the conversion of pH values obtained by two data analysis methods to each other. The pH values with were obtained this way did not differ significantly from the pH values calculated directly from the given formula. The computed mathematical formulas will make it possible to simplify pH conversions without knowing the chemical shift between inorganic phosphate and phosphocreatine but only basing on the final pH values obtained by one of the formulas.