Experimental and numerical simulation of loading rate effects on failure and strain energy characteristics of coal-rock composite samples

The deformation and failure of coal and rock is energy-driving results according to thermodynamics.It is important to study the strain energy characteristics of coal-rock composite samples to better understand the deformation and failure mechanism of of coal-rock composite structures.In this research,laboratory tests and numerical simulation of uniaxial compressions of coal-rock composite samples were carried out with five different loading rates.The test results show that strength,deformation,acoustic emission(AE)and energy evolution of coal-rock composite sample all have obvious loading rate effects.The uniaxial compressive strength and elastic modulus increase with the increase of loading rate.And with the increase of loading rate,the AE energy at the peak strength of coal-rock composites increases first,then decreases,and then increases.With the increase of loading rate,the AE cumulative count first decreases and then increases.And the total absorption energy and dissipation energy of coal-rock composite samples show non-linear increasing trends,while release elastic strain energy increases first and then decreases.The laboratory experiments conducted on coal-rock composite samples were simulated numerically using the particle flow code(PFC).With careful selection of suitable material constitutive models for coal and rock,and accurate estimation and calibration of mechanical parameters of coal-rock composite sample,it was possible to obtain a good agreement between the laboratory experimental and numerical results.This research can provide references for understanding failure of underground coalrock composite structure by using energy related measuring methods.

The sampling apparatus of volatile organic compounds for wood composites

Terpenes, aldehydes, ketones, benzene, and toluene are the important volatileorganic compounds (VOCs) emitted from wood composites. A sampling apparatus of VOCs for woodcomposites was designed and manufactured by Northeast Forestry University in China. Theconcentration of VOCs derived from wood based materials, such as flooring, panel wall, finishing,and furniture can be sampled in a small stainless steel chambers. A protocol is also developed inthis study to sample and measure the new and representative specimens. Preliminary research showedthat the properties of the equipment have good stability. The sort and the amount of differentcomponents can be detected from it. The apparatus is practicable.

Influence of sampling on face measuring system based on composite structured light

Human face can be rebuilt to a three-dimensional (3 D) digital profile based on an optical 3D sensing system named Composite Fourier-Transform Profilometry (CFTP) where a composite structured light will be used. To study the sampling effect during the digitization process in practical CFTP, the pectinate function and convolution theorem were introduced to discuss the potential phase errors caused by sampling the composite pattern along two orthogonal directions. The selecting criterions of sampling frequencies are derived and the results indicate that to avoid spectral aliasing, the sampling frequency along the phrase variation direction must be at least four times as the baseband and along the orthogonal direction it must be at least three times as the larger frequency of the two carrier frequencies. The practical experiment of a model face reconstruction verified the theories.

Upgraded Analytical Protocols in Bauxite Refining Industry Using Composite Sampling Approach to Minimize Laboratory Analysis Load

The laboratories in the bauxite processing industry are always under a heavy workload of sample collection, analysis, and compilation of the results. After size reduction from grinding mills, the samples of bauxite are collected after intervals of 3 to 4 hours. Large bauxite processing industries producing 1 million tons of pure aluminium can have three grinding mills. Thus, the total number of samples to be tested in one day reaches a figure of 18 to 24. The sample of bauxite ore coming from the grinding mill is tested for its particle size and composition. For testing the composition, the bauxite ore sample is first prepared by fusing it with X-ray flux. Then the sample is sent for X-ray fluorescence analysis. Afterwards, the crucibles are washed in ultrasonic baths to be used for the next testing. The whole procedure takes about 2 - 3 hours. With a large number of samples reaching the laboratory, the chances of error in composition analysis increase. In this study, we have used a composite sampling methodology to reduce the number of samples reaching the laboratory without compromising their validity. The results of the average composition of fifteen samples were measured against composite samples. The mean of difference was calculated. The standard deviation and paired t-test values were evaluated against predetermined critical values obtained using a two-tailed test. It was found from the results that paired test-t values were much lower than the critical values thus validating the composition attained through composite sampling. The composite sampling approach not only reduced the number of samples but also the chemicals used in the laboratory. The objective of improved analytical protocol to reduce the number of samples reaching the laboratory was successfully achieved without compromising the quality of analytical results.

Neural Network-Based Second Order Reliability Method(NNBSORM)for Laminated Composite Plates in Free Vibration

Monte Carlo Simulations(MCS),commonly used for reliability analysis,require a large amount of data points to obtain acceptable accuracy,even if the Subset Simulation with Importance Sampling(SS/IS)methods are used.The Second Order Reliability Method(SORM)has proved to be an excellent rapid tool in the stochastic analysis of laminated composite structures,when compared to the slower MCS techniques.However,SORM requires differentiating the performance function with respect to each of the random variables involved in the simulation.The most suitable approach to do this is to use a symbolic solver,which renders the simulations very slow,although still faster than MCS.Moreover,the inability to obtain the derivative of the performance function with respect to some parameters,such as ply thickness,limits the capabilities of the classical SORM.In this work,a Neural Network-Based Second Order Reliability Method(NNBSORM)is developed to replace the finite element algorithm in the stochastic analysis of laminated composite plates in free vibration.Because of the ability to obtain expressions for the first and second derivatives of the NN system outputs with respect to any of its inputs,such as material properties,ply thicknesses and orientation angles,the need for using a symbolic solver to calculate the derivatives of the performance function no longer exists.The proposed approach is accordingly much faster,and easily allows for the consideration of ply thickness uncertainty.The present analysis showed that dealing with ply thicknesses as random variables results in 37%increase in the laminate’s probability of failure.

STACKING SEQUENCE OPTIMIZA-TION OF LAMINATED COMPOSITE CYLINDER SHELL FOR MAXIMAL BUCKLING LOAD

A new optimization method for the optimization of stacking of composite glass fiber laminates is developed. The fiber orientation and angle of the layers of the cylindrical shells are sought considering the buckling load. The proposed optimization algorithm applies both finite element analysis and the mode-pursuing sampling （MPS）method. The algorithms suggest the optimal stacking sequence for achieving the maximal buckling load. The procedure is implemented by integrating ANSYS and MATLAB. The stacking sequence designing for the symmetric angle-ply three-layered and five-layered composite cylinder shells is presented to illustrate the optimization process, respectively. Compared with the genetic algorithms, the proposed optimization method is much faster and efficient for composite staking sequence plan.

Mechanical property of single-bolted composite laminates

In order to investigate the effects of different geometrical parameters and pretightening loads on failure mode and bearing strength,a large number of single-bolted T300/QY8911 composite laminates were tested under static tension load.Box-plot was used to extract the singular testing values of bearing strength and effective statistical values were obtained.T-test method of independent samples was used to study how much pretightening loads influence bearing strength.The results show that the geometrical parameters,such as ratios of width to hole diameter(w/d) and edge distance to hole diameter(e/d),remarkably influence failure mode and bearing strength.Net-section failure will occur when w/d is smaller than 4,and shear-out failure will occur when e/d is smaller than 2.Bearing failure or bearing and shear-out combined failure will occur when w/d is greater than 4 and e/d is greater than 2.There is an optimal combination of geometrical parameters to achieve the highest bearing strength.For most of specimens,pretightening loads do not explicitly influence bearing strength.

Stress Ratio-Strain Relation of Pile and Soil in Composite Foundation

A series of triaxial compression tests were arried out by means of composite-reinforced soil samples to simulate the interaction between soil and pile. The samples are made of gravel or lime-soil with different length at the center. The experiment indicates that the strength of the composite samples can not be obtained by superimposure of reinforcing pile and soil simply according to their replacement proportion. It also indicates the law for stress ratio of reinforcing column to soil. The stress ratio of reinforcing column to soil increases and reaches peak rapidly while load and strain is small. Then the ratio decreases. This law is in accordance with the measuring resuits in construction site.

Deconvolution of the Error Associated with Random Sampling

In this work empirical models describing sampling error (Δ) are reported based upon analytical findings elicited from 3 common probability density functions (PDF): the Gaussian, representing any real-valued, randomly changing variable x of mean μ?and standard deviation σthe Poisson, representing counting data: i.e., any integral-valued entity’s count of x (cells, clumps of cells or colony forming units, molecules, mutations, etc.) per tested volume, area, length of time, etc. with population mean of μ?and;binomial data representing the number of successful occurrences of something (x+) out of n observations or sub-samplings. These data were generated in such a way as to simulate what should be observed in practice but avoid other forms of experimental error. Based upon analyses of 104 Δ?measurements, we show that the average Δ?() is proportional to ?(σx•μ-1;Gaussian) or ?(Poisson & binomial). The average proportionality constants associated with these disparate populations were also nearly identical (;±s). However, since ?for any Poisson process, . In a similar vein, we have empirically demonstrated that binomial-associated ?were also proportional to σx•μ-1. Furthermore, we established that, when all ?were plotted against either ?or σx•μ-1, there was only one relationship with a slope = A (0.767 ± 0.0990) and a near-zero intercept. This latter finding also argues that all , regardless of parent PDF, are proportional to σx•μ-1?which is the coefficient of variation for a population of sample means (). Lastly, we establish that the proportionality constant A is equivalent to the coefficient of variation associated with Δ?() measurement and, therefore, . These results are noteworthy inasmuch as they provide a straightforward empirical link between stochastic sampling error and the aforementioned Cvs. Finally, we demonstrate that all attendant empirical measures of Δ?are reasonably small (e.g., ) when an environmental microbiome was well-sampled: n = 16 - 18 observations with μ∼3?isolates per observation. These colony counting results were supported by the fact that the two major isolates’ relative abundance was reproducible in the four most probable composition observations from one common population.

Optimal Sampling and Assay for Estimating Soil Organic Carbon

The world needs around 150 Pg of negative carbon emissions to mitigate climate change. Global soils may provide a stable, sizeable reservoir to help achieve this goal by sequestering atmospheric carbon dioxide as soil organic carbon (SOC). In turn, SOC can support healthy soils and provide a multitude of ecosystem benefits. To support SOC sequestration, researchers and policy makers must be able to precisely measure the amount of SOC in a given plot of land. SOC measurement is typically accomplished by taking soil cores selected at random from the plot under study, mixing (compositing) some of them together, and analyzing (assaying) the composited samples in a laboratory. Compositing reduces assay costs, which can be substantial. Taking samples is also costly. Given uncertainties and costs in both sampling and assay along with a desired estimation precision, there is an optimal composite size that will minimize the budget required to achieve that precision. Conversely, given a fixed budget, there is a composite size that minimizes uncertainty. In this paper, we describe and formalize sampling and assay for SOC and derive the optima for three commonly used assay methods: dry combustion in an elemental analyzer, loss-on-ignition, and mid-infrared spectroscopy. We demonstrate the utility of this approach using data from a soil survey conducted in California. We give recommendations for practice and provide software to implement our framework.

Diversity and Structure of Miombo Woodlands in Mozambique Using a Range of Sampling Sizes

Forest assessments are essential to understand the tree population structure and diversity status of forests and to provide information for biodiversity recovery planning. Unfortunately, the majority of Miombo woodlands in Mozambique lack of inventory data, and consequently are often insufficient for management. This study aimed to assess the species richness, diversity and structure of Miombo woodlands using a range of sampling sizes in Mocuba district, Mozambique. Plant inventory was carried out in 128 systematically selected sample plots in 71.6 ha, which was divided into eight treatments, i.e., TI： 0.1 ha; T2：0.25 ha; T3：0.375 ha; T4：0.5 ha; T5：0.625 ha; T6：0.75 ha; T7：0.875 ha; T8：1.0 ha, with 16 repetitions. All stems _〉 10 cm diameter at breast height, and species name to evaluate the floristic composition, richness of tree species, diversity and diameter distribution were recorded. A total of 36,535 individuals were recorded, belonging 124 species, 83 genera and representing 31 botanical families. The most important species was the Brachystegia spiciformis Benth. and the richest botanical family was Fabaceae. The forest showed an average of 517 ＋ 85 trees/ha, and high species diversity and evenness. Analysis of covariance shows that the intercepts and slope of exponential function for diameter distribution are not significantly different for the eight treatments. Compared with the entire composite forest, inventory means were accurately estimated and size class distributions were well represented for plots 〈 0.25 ha, for selecting an efficient sampling design suited to forest characteristics and the inventory＇s purpose.

Analysis of carbon and oxygen stable isotopes in carbonate rocks by the laser micro-sampling technique

The analysis of stable isotopes of carbon and oxygen in different carbonate rocks by the phosphoric acid method is not easier than that by the laser sampling method developed in recent years, which optically focuses laser beams with sufficient energy on a micro area of a thin section in a vacuum sample box via microscope. CO 2 produced by heating decomposition of carbonate was purified by the vacuum system, and the stable isotopic values of carbon and oxygen were calculated and analyzed on a mass spectrometer. This paper adopted the laser micro-sampling technique to analyze the stable isotopes of carbon and oxygen in dolomite, carbonate cement, stromatolite and different forms of dawsonite (donbassite). Results indicated that the laser micro-sampling method is effective in analyzing carbonate composition and could be a convincing proof for justification on carbonate composition analysis.

基于改进NSGA-Ⅱ的纤维缠绕落纱点轨迹采样特征权重优化

针对基于空间特征曲线特征函数的纤维缠绕落纱点轨迹采样算法无法自动选择特征权重的问题,建立以特征权重为变量,以得到采样点线性插值生成曲线与原曲线的MAE,RMSE为目标函数的双目标优化模型。提出基于改进NSGA-Ⅱ算法的双目标优化求解方法以优化特征权重。实例验证表明,与传统NSGA-Ⅱ算法相比,改进NSGA-Ⅱ算法求得Pareto解集的MAE,RMSE平均下降了0.002和0.105,算法选取特征权重的MAE,RMSE比特征权重为(0.1,0.3)的MAE,RMSE分别降低了约12.9%和8.5%,比特征权重为(0.9,0.1)的MAE,RMSE分别降低了约20.6%和11.4%,有效地提高了落纱点轨迹采样的精度。

强度比对类复合岩样冲击破碎特征的影响

为了保证复合地层中施工效率及工程安全,揭示动荷载作用下复合岩层的力学特征,通过分离式霍普金森压杆对三种不同强度比的类复合岩样进行动态巴西劈裂试验,基于破碎分形理论,探究强度比、应变率、入射角对类复合岩样的破碎程度及能耗特性的影响。试验结果表明:层理面倾角对类复合岩样破碎形态有较大影响,当应变率为146.36 s^(-1)时,沿层理面加载试样易发生劈裂拉伸破坏,且强度比越低试样破坏所需吸收的能量越少;当入射角为0°时,类复合岩样分形维数随着强度比的增大而增大,但当入射角为90°时强度比为1.5的复合岩样分形维数最大;类复合岩样吸收的能量主要用于裂纹扩展,单位体积内试样吸收的能量越大,试样越破碎,即类复合岩样分形维数与能耗密度呈正相关。

基于微结构量化的枣园根土复合体各向异性试验

为确定南疆枣园切根抚育作业工艺,测定了枣园土壤含水率、坚实度、孔隙度、容重、粒径分布等物理参数,统计了枣园待切根区的根系聚集深度、土壤含根量等,确定了切根区位置为距树干750 mm和切根作业深度应在0~200 mm范围内可调的农业技术要求。研究结果表明,根土复合体具有各向异性,取样角θ为0°、45°、90°时,根土复合体抗剪强度T关系为T0°45°90°。为分析根土复合体产生各向异性现象的原因,采用扫描电镜(SEM)获取了根土复合体在不同取样方向上的微观结构图像,通过PCAS软件处理并获取了根土复合体微观结构参数。将根土复合体的宏观图像、微观图像、微观结构参数、抗剪强度参数结合,定性和定量分析了根土复合体产生各向异性的原因及规律,得到微观结构参数与抗剪切强度相关性由强到弱依次为孔隙概率熵、孔隙形态分维数、颗粒形状系数、孔隙形状系数、颗粒概率熵、颗粒形态分维数。根据研究结果提出根土复合体抗剪强度测定时,环刀应垂直于耕作过程产生的实际剪切发生面方向取样。本研究可为枣园切根抚育机具设计和研发提供理论依据,为土壤耕作类部件优化设计、耕作类部件与土壤相互作用关系等研究提供参考。

膨润土组合试样的热传导和水分迁移规律试验研究

缓冲材料砌块接缝作为高放废物处置库工程屏障系统中潜在的薄弱部位必须被深入研究。为此,利用研制的试验装置测定了进水前与进水后两种情况下高庙子(GMZ)膨润土组合试样不同位置处的温度和体积含水量随时间的演化规律,并根据试验结果得到了组合试样接缝愈合后的热传导系数和水力传导系数。试验结果表明膨润土组合试样内部温度的变化主要受温度边界的影响,而其内部水分的变化对其影响较小。在短时间内,加载水力边界条件仅使得靠近水力边界处的土体的体积含水量大幅度增加,而对其它位置影响较小。由于受到温度边界的影响,靠近温度边界位置处的土体的体积含水量随时间逐渐降低。愈合后接缝位置的导热性能和渗透性能够满足高放废物处置库工程屏障的要求。

基于复合多尺度等概率符号化样本熵的两相流动态特性分析

多尺度样本熵(MSE)在两相流动态特性分析中存在两点不足:一是熵值无法单纯反映时间序列信息增长速率,在高尺度下稳定性较差;二是传统粗粒化过程中有部分数据信息丢失.针对上述问题,提出复合多尺度等概率符号化样本熵(CMESSE),并通过对几种典型非线性时间序列进行分析验证了其有效性.与MSE相比,CMESSE不仅能够有效表征不同动力系统非线性时间序列复杂性,而且在时间序列较短时稳定性更好.在此基础上分析了123组流动条件下垂直上升管内空气-水两相流压差波动时间序列.研究结果表明,泡状流、塞状流及混状流的CMESSE变化趋势能够在不同尺度下定性表征不同流型的动态特性,CMESSE复杂性指数可跨多尺度定量描述不同流型的动力学复杂性.

PM_(2.5)粉末样品中不同组分的氧化潜势及影响因素

基于大流量旋风式冲击采样器在西安市采集了四季大气PM_(2.5)粉末样品,分别测定其水溶和非水溶相的氧化潜势(OP)､无机元素､水溶性离子､金属组分､碳组分和有机官能团,揭示水溶相/非水溶相的化学组分对OP的影响.结果显示,西安市PM_(2.5)粉末样品总OP的趋势为秋冬(秋7.24μmol/(min·mg),冬5.19μmol/(min·mg))显著高于春夏季(春2.06μmol/(min·mg),夏3.15μmol/(min·mg));春夏季PM_(2.5)粉末样品的OP以水溶相OP为主(70.0%),秋冬季以非水溶相为主(73.9%).水溶性金属Ni､Pb､Ba､Mn､Cu､Ti(0.60<R<0.80,P<0.05)和水溶性有机碳(TOC)(R=0.54,P<0.05)与水溶相OP呈较显著的正相关.非水溶性金属(Cu､Fe､Cr等)与非水溶相OP普遍呈较显著的正相关(0.48<R<0.71,P<0.05),非水溶性元素碳(EC)与非水溶相OP则呈显著负相关(-0.63<R<-0.45,P<0.05).傅里叶红外光谱的结果显示,酚､醇､醚､酯等含氧水溶性有机物对PM_(2.5)粉末样品中水溶相OP有重要的影响.

基于语义嵌入空间的离心泵未知复合故障识别

针对离心泵各类型故障相互耦合难以诊断的问题,提出了一种语义嵌入空间的未知复合故障识别框架。首先采用深度学习与加权交叉熵损失建模来提取数据不平衡分布下的离心泵已知单一故障特征。接着采用零样本学习结合语义编码将单一故障属性构建成复合故障语义空间。最后通过全连接神经网络将样本特征映射到语义空间,并通过相似度测量来识别未知复合故障。在自吸和单级单吸离心泵两个数据集上进行验证,结果表明:在复合样本缺失的前提下,该方法对四组数据不平衡分布下的未知复合故障平均识别率为73.63%和82.25%,验证了所提方法的有效性和泛化性。

An evaluation of the effects of sample size on estimating length composition of catches from tuna longline fisheries using computer simulations

Length composition analysis can provide insights into the dynamics of a fish population.Accurate quantification of the size structure of a population is critical to understand the status of a fishery and how the population responds to environmental stressors.A scientific observer program is a reliable way to provide such accurate information.However,100%observer coverage is usually impossible for most fisheries because of logistic and financial constraints.Thus,there is a need to evaluate observer program performance,identify suitable sample sizes,and optimize the allocation of observation efforts.The objective of this study is to evaluate the effects of sample size on the quality of length composition data and identify an optimal coverage rate and observation ratio to improve the observation efficiency using an onboard observer data set from China's tuna longline fishery in the western and central Pacific Ocean.We found that the required sample size varies with fish species,indices used to describe length composition,the acceptable accuracy of the estimates,and the allocation methods of sampling effort.Ignoring other information requirements,1000 individuals would be sufficient for most species to reliably quantify length compositions,and a smaller sample size could generate reliable estimates of mean length.A coverage rate of 20%would be sufficient for most species,but a lower coverage rate(5%or 10%)could also be effective to meet with the accuracy and precision requirement in estimating length compositions.A nonrandom effort allocation among fishing baskets within a set could cause the length composition to be overestimated or underestimated for some species.The differences in effective sample sizes among species should be included in the consideration for a rational allocation of observation effort among species when there are different species management priorities.