基于H∞滤波的变权多通道数据融合方法研究

在对多通道定位数据进行数据融合中，采用H∞滤波可有效地解决各传感器数据误差模型不确定的滤波和状态估计问题。但由于数据采样时刻及精度的不一致性，对于多通道数据的融合应采用变权融合方式，以提高融合后数据的可靠性。该由此给出了一种基于H∞滤波的变权数据融合计算方法，通过对实测实时数据的仿真计算表明，其方法具有很好的实用性。     

Transport with a Very Low Density Contrast in Hele–Shaw Cell and Porous Medium: Evolution of the Mixing Zone

The optimal concentration of a blue dye solution with 'tracer' properties, enabling a pollutant to be marked was determined by the use of numerical, theoretical and experimental approaches. Experimental investigations were performed on a transparent Hele–Shaw cell and the concentration distribution was analyzed using an optical technique based on dye light absorption properties. The injected optimal concentration was established thanks to a theoretical and experimental study carried out on the output signal dynamics. Using the same experimental conditions, numerical simulations were performed. The very good agreement between the data (experimental and numerical) clarified that: (i) the choice of the blue dye optimal concentration was valid and (ii) the concentration-dependent density should not be neglected in flow and transport equations even if it concerns a so-called 'tracer'. Following this remark, a theoretical aspect was developed in order to determine the analogous conditions between a Hele–Shaw cell and a porous medium for the variable density transport phenomenon. The structure of the concentration-dependent dispersion tensor used in the numerical code was obtained by homogenizing the Stokes flow of a bi-component mixture. The numerical results show that, as long as the tracer density does not exceed a certain value, it is not necessary to take into account a density contrast in terms of the dispersion tensor. The classical form of the Taylor dispersion tensor can be used successfully.     

Measurement of thermal expansion coefficients of composites using strain gages

The measurement of the coefficients of thermal expansion (CTEs) of composite materials using electrical resistance strain gages is addressed. Analytical expressions for the CTEs of an orthotropic lamina are derived, accounting for the effects of transverse sensitivity and possible misalignment of the gages. Experiments are performed for the characterization of the thermal expansion behavior of a fiber-glass-reinforced epoxy unidirectional lamina using an invar specimen as reference material. Preliminary training cycles are performed for the determination of an optimal heating rate for the measurements, which ensures thermal equilibrium conditions. Three measurement cycles yield the principal CTEs of the lamina α₁, α₂ and α₁₂ with repeatability within ±0.34×10⁻⁶, ±0.85×10⁻⁶ and ±2.8×10⁻⁶/°C, respectively. It is noted that inhomogeneity of the specimen and variation in thermomechanical properties of the gages can cause a noticeable spead in the measurements.     

添加剂与RDX的界面作用及对撞击感度的影响研究

研究了石蜡、硬脂酸等添加剂与RDX的界面作用及其对撞击感度的影响。得出添加剂对RDX(Hexogen)的铺展系数越大,钝感效果越好的结论,并获得了铺展系数与特性落高的经验函数关系。     

Molecular insight for the role of key residues of calreticulin in its binding activities: A computational study

Calreticulin (CRT) is localized to and has functions in multiple cellular compartments, including the cell surface, the endoplasmic reticulum, and the extracellular matrix. Mutagenesis studies have identified several residues on a concave β-sheet surface of CRT critical for CRT binding to carbohydrate and other proteins/peptides. How the mutations of these key residues in CRT affect the conformation and dynamics of CRT, further influencing CRT binding to carbohydrates and other proteins to signal the important biological activities remain unknown. In this study, we investigated the effect of three key point mutations (C105A, C137A and W319A) on CRT conformation and dynamics via atomistic molecular dynamics simulations. Results show that these three key residues mutations induced the changes of CRT local backbone flexibility and secondary structure of CRT N-domain, which could further affect CRT’s binding activity. C137A mutation led to dramatic decrease of the overall size of CRT due to the P-domain fold back to the globular domain and formed new inter-domain contacts, which can cause blockage of CRT’s binding with other large substrates. Furthermore, for CRT concave β-strand surface patch containing lectin binding site, CRT C105A, C137A and W319A point mutation resulted in the changes in solvent accessible surface area, key residues’ side chain atom positions and dynamical correlated motions between residues. All these changes could directly affect CRT binding behavior. Results of this study provide molecular and structural insights into understanding the role of key residues of CRT in its binding behavior.     

基于L1正则化的随机梁式结构静力损伤识别方法

提出了一种结合摄动法和L1正则化方法的随机梁式结构静力损伤识别方法。考虑初始模型误差和测量误差的影响,建立了关于随机损伤指数的控制方程,并将摄动法和L1正则化方法相结合,对随机损伤指数的控制方程进行求解,进而从概率的角度对结构的损伤进行识别。损伤试验结果表明,和传统的最小二乘求解法相比,本文方法能够更为准确地识别多处局部损伤的位置及大小,对实际结构损伤检测具有较好的参考价值。     

A note on Herglotz’s theorem for time series on function spaces

In this article, we prove Herglotz’s theorem for Hilbert-valued time series. This requires the notion of an operator-valued measure, which we shall make precise for our setting. Herglotz’s theorem for functional time series allows to generalize existing results that are central to frequency domain analysis on the function space. In particular, we use this result to prove the existence of a functional Cramér representation of a large class of processes, including those with jumps in the spectral distribution and long-memory processes. We furthermore obtain an optimal finite dimensional reduction of the time series under weaker assumptions than available in the literature. The results of this paper therefore enable Fourier analysis for processes of which the spectral density operator does not necessarily exist.     

Adaptive Neuro-Fuzzy Inference System and a Multilayer Perceptron Model Trained with Grey Wolf Optimizer for Predicting Solar Diffuse Fraction

The accurate prediction of the solar diffuse fraction (DF), sometimes called the diffuse ratio, is an important topic for solar energy research. In the present study, the current state of Diffuse irradiance research is discussed and then three robust, machine learning (ML) models are examined using a large dataset (almost eight years) of hourly readings from Almeria, Spain. The ML models used herein, are a hybrid adaptive network-based fuzzy inference system (ANFIS), a single multi-layer perceptron (MLP) and a hybrid multi-layer perceptron grey wolf optimizer (MLP-GWO). These models were evaluated for their predictive precision, using various solar and DF irradiance data, from Spain. The results were then evaluated using frequently used evaluation criteria, the mean absolute error (MAE), mean error (ME) and the root mean square error (RMSE). The results showed that the MLP-GWO model, followed by the ANFIS model, provided a higher performance in both the training and the testing procedures.     

DIOPTAS: a program for reduction of two-dimensional X-ray diffraction data and data exploration

The amount of data collected during synchrotron X-ray diffraction (XRD) experiments is constantly increasing. Most of the time, the data are collected with image detectors, which necessitates the use of image reduction/integration routines to extract structural information from measured XRD patterns. This step turns out to be a bottleneck in the data processing procedure due to a lack of suitable software packages. In particular, fast-running synchrotron experiments require online data reduction and analysis in real time so that experimental parameters can be adjusted interactively. Dioptas is a Python-based program for on-the-fly data processing and exploration of two-dimensional X-ray diffraction area detector data, specifically designed for the large amount of data collected at XRD beamlines at synchrotrons. Its fast data reduction algorithm and graphical data exploration capabilities make it ideal for online data processing during XRD experiments and batch post-processing of large numbers of images.