Statistical properties of the model parameters in the continuum approach to high-cycle fatigue

This paper is a sequel to papers studying the continuum approach to the high-cycle fatigue model of Ottosen et al. First, we study the estimation of fatigue limit and statistical characteristics of the estimates. We have two cases. Either the fatigue limit is a material constant or it is a random variable. Finally, we derive approximate distributions for the parameter estimators of the fatigue model due to Ottosen et al.     

Advances in statistical mechanics of rock masses and its engineering applications

To efficiently link the continuum mechanics for rocks with the structural statistics of rock masses,a theoretical and methodological system called the statistical mechanics of rock masses(SMRM)was developed in the past three decades.In SMRM,equivalent continuum models of stressestrain relationship,strength and failure probability for jointed rock masses were established,which were based on the geometric probability models characterising the rock mass structure.This follows the statistical physics,the continuum mechanics,the fracture mechanics and the weakest link hypothesis.A general constitutive model and complete stressestrain models under compressive and shear conditions were also developed as the derivatives of the SMRM theory.An SMRM calculation system was then developed to provide fast and precise solutions for parameter estimations of rock masses,such as full-direction rock quality designation(RQD),elastic modulus,Coulomb compressive strength,rock mass quality rating,and Poisson’s ratio and shear strength.The constitutive equations involved in SMRM were integrated into a FLAC3D based numerical module to apply for engineering rock masses.It is also capable of analysing the complete deformation of rock masses and active reinforcement of engineering rock masses.Examples of engineering applications of SMRM were presented,including a rock mass at QBT hydropower station in northwestern China,a dam slope of Zongo II hydropower station in D.R.Congo,an open-pit mine in Dexing,China,an underground powerhouse of Jinping I hydropower station in southwestern China,and a typical circular tunnel in Lanzhou-Chongqing railway,China.These applications verified the reliability of the SMRM and demonstrated its applicability to broad engineering issues associated with jointed rock masses.     

Study of new flow field geometries to enhance water redistribution and pressure head losses reduction within PEM fuel cell

Efficiency of fuel cell is dependent on reactant distribution, products evacuation, pressure losses and many of these factors is dependent on the design of flow field plate. With an effective design, reactant distribution, pressure drop, and water and heat management can be further improved. In this work, two new designs, as multi-serpentine set-up with additional slots and hybrid geometry, on stainless steel bipolar plates, are presented. Electrical performance, and pressure head losses are analyzed by electrochemical methods such as polarization curve and use of electrochemical noise as a diagnostic tool to further understand the impact of water management on performance. On the one hand, multi-serpentine design shows the best electrical performance with an increase of 0.2 V (66%) at 0.9 A/cm² in comparison of traditional serpentine design. On the other hand, hybrid design reveals the lowest pressure head losses, with a decrease of 2 mbar (about 50%) in comparison of traditional serpentine design, and a higher stability with time that can be useful to downsize compressor and provide lower impact on fuel cell stack durability.     

新一代多模型迭代算法在70 kVp成人副鼻窦CT扫描中的应用

探讨成人在70 kVp副鼻窦CT检查中降低有效辐射剂量的同时,获取最佳图像质量的新一代多模型迭代算法(Adaptive Statistical Iterative Reconstruction-V,Asir-V)的权重。本研究对20例成人患者进行副鼻窦Revolution CT检查,采用70 kVp、230 mA条件下进行螺旋CT扫描,扫描完成后对每例患者的原始数据采用不同权重(0,20%,40%,60%,80%,100%)的后置新一代多模型迭代算法(Adaptive Statistical Iterative Reconstruction-V,Asir-V)重建的方法,共获得120幅图像,并对每例6组图像进行客观评价及主观评分。客观评价包括噪声(standard deviations, SD)和对比噪声比(contrast noise ratio,CNR),主观评价由2名评价医生对图像质量评分并对两者的主观一致性进行评价。每例患者扫描完成后,记录其剂量长度乘积(dose-length product,DLP)和CT容积剂量指数(CT dose index volume,CTDI_vol),并计算其平均有效辐射剂量(effective dose,ED)。客观评价结果表明不同权重的Asir-V图像噪声随着Asir-V权重的提升而降低,CNR值随着Asir-V权重的提升而升高,且有效辐射剂量ED较常规头颈部CT检查的平均辐射剂量明显减少;主观评价结果表明不同权重的Asir-V图像评分不同,在Asir-V 60% 时评分最高,且2名医生主观评价一致性好。结合主客观评价结果,认为在70 kVp、230 mA成人副鼻窦Revolution CT检查中,Asir-V 60％的图像既可满足临床诊断的需要,也可明显降低有效辐射剂量。     

Fix-and-relax approaches for controlled tabular adjustment

Controlled tabular adjustment (CTA) is a relatively new protection technique for tabular data protection. CTA formulates a mixed integer linear programming problem, which is challenging for tables of moderate size. Even finding a feasible initial solution may be a challenging task for large instances. On the other hand, end users of tabular data protection techniques give priority to fast executions and are thus satisfied in practice with suboptimal solutions. This work has two goals. First, the fix-and-relax (FR) strategy is applied to obtain good feasible initial solutions to large CTA instances. FR is based on partitioning the set of binary variables into clusters to selectively explore a smaller branch-and-cut tree. Secondly, the FR solution is used as a warm start for a block coordinate descent (BCD) heuristic (approach named FR+BCD); BCD was confirmed to be a good option for large CTA instances in an earlier paper by the second and third co-authors (Comput Oper Res 2011;38:1826–35 [23]). We report extensive computational results on a set of real-world and synthetic CTA instances. FR is shown to be competitive compared to CPLEX branch-and-cut in terms of quickly finding either a feasible solution or a good upper bound. FR+BCD improved the quality of FR solutions for approximately 25% and 50% of the synthetic and real-world instances, respectively. FR or FR+BCD provided similar or better solutions in less CPU time than CPLEX for 73% of the difficult real-world instances.     

Failure analysis of power transformer for effective maintenance planning in electric utilities

In this paper, power transformer failures are analyzed and their root causes are systematically investigated in Tamil Nadu Transmission Corporation Limited (TANTRANSCO)/Tamil Nadu Generation and Distribution Corporation Limited (TANGEDCO) electric utilities, based on 196 failure cases from the year 2009–2013. Failure analysis is conducted in two phases. Initially, voltage level, geographical zone and power transformer components based failure analysis are performed through statistical analysis. Secondly, the most significant factors that cause power transformer failures are identified by using root cause analysis (RCA). Finally, current maintenance practice is reviewed and an effective maintenance planning has been proposed for implementation in order to prevent these failures and to maintain the power transformers in good operating condition during their life cycle. This study provides a practical guidance to help maintenance personnel for the best utilization of the power transformer in electric utilities.     

Root cause analysis of process fault conditions on an industrial concentrator circuit by use of causality maps and extreme learning machines

Model-based fault diagnosis tends to be too expensive or time-consuming to apply in the mineral processing industries, owing to the complexity and variability of operations. In contrast, data-based methods are inexpensive, but do not exploit the availability of first principle knowledge of plant operations. In this investigation, the use of process causality maps in conjunction with data-based fault diagnosis is considered as a hybrid methodology that can leverage the advantages of both approaches. Extreme learning machine algorithms are used to implement the data-based component of the approach. These algorithms can be deployed rapidly on large-scale systems and have the ability to deal with highly nonlinear systems. Two different variants are considered, viz. one used in combination with principal component analysis, as well as one with a bagging algorithm for fault diagnosis and applied to an industrial concentrator circuit in South Africa. The use of process causality maps led to significantly more effective fault diagnosis, while the use of extreme learning machines in combination with principal component analysis likewise allowed markedly better fault detection and diagnosis. In contrast, fault diagnosis with the bagging approach did not perform particularly well, owing to the high degree of correlation between the variables, which made it difficult to isolate individual causal variables.     

Dynamic Profile Monitoring for Flooding Prognosis in Packed Columns

In the chemical industry, real‐time flooding prognosis is a necessity for packed‐column operation because the flooding phenomenon interferes with the performance of production systems. In this work, the profile monitoring technique is utilized to capture the dynamic behavior of pressure drop, which is an important indicator for the flooding phenomenon. In each moving window, the pressure drop signals are described by using an exponential generalized autoregressive conditional heteroskedastic model. The onset of the flooding phenomenon is then indicated by changes in model parameters. Moreover, to efficiently capture the process change, a nonparametric approach is utilized to establish a statistical control chart. Experimental and comparison results show the advantages of the proposed method.     

基于小波变换的影像融合算法与效果评价

在众多的图像融合技术中，基于小波变换的图像融合方法已成为目前研究的一个热点。小波变换具有多分辨率等特点，可以有效地将特征明显、分辨率高的图像融合在一起，得到比任何一幅源图像效果都好的图像。在阐述小波变换的Mallat算法的同时，对遥感影像融合的分析与评价进行了深入的探讨，提出了综合利用3类统计参数进行评价的方法。经实验，评价结果与理论分析结果和目视效果相吻合，说明这些参数可以作为遥感影像融合客观效果的评价准则。     

Precision of in-place concrete strenghts predicted using core strength correction factors obtained by weighted regression analysis

A two-step method for converting a concrete core compression test result to the in-place strength of the corresponding volume of concrete is presented. The strength of a non-standard core is first converted to the equivalent strength of a standard core, and then the standard core strength is converted to the equivalent in-place strength. Strength correction factors required for these conversions, obtained from weighted linear and nonlinear regression analyses presented elsewhere, are summarized. The accuracy of the predicted in-place strength is affected by the inherent error of the core strength measurement itself, and by the uncertainty of the various strength correction factors. It is shown that confidence intervals on the estimates of the strength correction factors obtained by regression analysis underestimate the true model error because the underlying models are imperfect. Instead, the accuracy of the strength correction factors is determined by a weighted regression analysis of ratios of observed-to-predicted values which accounts for the non-uniform variances of the dependent and independent variables. The coefficient of variation of the in-place strength predicted from a test of a 100 or 150 mm diameter core is between 4 and 5.5.%. If the in-place strength is predicted from a test of a 50 mm diameter core, the coefficient of variation of the predicted in-place strength is approximately 12.5%. These error estimates do not account for possible variation of in-place strength throughout the volume of the element being cored.