On the calibration of a shear stress criterion for rock joints to represent the full stress-strain profile

Conventional numerical solutions developed to describe the geomechanical behavior of rock interfaces subjected to differential load emphasize peak and residual shear strengths.The detailed analysis of preand post-peak shear stress-displacement behavior is central to various time-dependent and dynamic rock mechanic problems such as rockbursts and structural instabilities in highly stressed conditions.The complete stress-displacement surface(CSDS)model was developed to describe analytically the pre-and post-peak behavior of rock interfaces under differential loads.Original formulations of the CSDS model required extensive curve-fitting iterations which limited its practical applicability and transparent integration into engineering tools.The present work proposes modifications to the CSDS model aimed at developing a comprehensive and modern calibration protocol to describe the complete shear stressdisplacement behavior of rock interfaces under differential loads.The proposed update to the CSDS model incorporates the concept of mobilized shear strength to enhance the post-peak formulations.Barton’s concepts of joint roughness coefficient(JRC)and joint compressive strength(JCS)are incorporated to facilitate empirical estimations for peak shear stress and normal closure relations.Triaxial/uniaxial compression test and direct shear test results are used to validate the updated model and exemplify the proposed calibration method.The results illustrate that the revised model successfully predicts the post-peak and complete axial stressestrain and shear stressedisplacement curves for rock joints.

Nonparametric Control Scheme for Monitoring Phase Ⅱ Nonlinear Profiles with Varied Argument Values

Profile monitoring is used to check the stability of the quality of a product over time when the product quality is best represented by a function at each time point.However,most previous monitoring approaches have not considered that the argument values may vary from profile to profile,which is common in practice.A novel nonparametric control scheme based on profile error is proposed for monitoring nonlinear profiles with varied argument values.The proposed scheme uses the metrics of profile error as the statistics to construct the control charts.More details about the design of this nonparametric scheme are also discussed.The monitoring performance of the combined control scheme is compared with that of alternative nonparametric methods via simulation.Simulation studies show that the combined scheme is effective in detecting parameter error and is sensitive to small shifts in the process.In addition,due to the properties of the charting statistics,the out-of-control signal can provide diagnostic information for the users.Finally,the implementation steps of the proposed monitoring scheme are given and applied for monitoring the blade manufacturing process.With the application in blade manufacturing of aircraft engines,the proposed nonparametric control scheme is effective,interpretable,and easy to apply.

A hybrid algorithm for reengineering the refractive index profile of inhomogeneous coatings from optical in-situ broadband monitoring data

Reengineering the refractive index profile of inhomogeneous coatings is a troublesome task. Multiplicity of solutions may significantly reduced by providing additional information. For this reason an in-situ broadband monitoring system was developed to measure the transmittance of the growing film directly at the rotating substrate. For characterization of these coatings, a new model was developed, which significantly reduces the number of parameters. The refractive index profile may be described by a proper number of equally spaced volume fraction values using the Bruggeman effective media approach. A good initial approximation of the refractive index profile can be generated based on deposition rates for both materials recorded with quartz crystal monitor during manufacturing. During the optimization process, a second order minimization algorithm was used to vary the refractive index profile of the whole coating and film thickness of the intermediate stages. Finally, a significantly improved accuracy of the modelled transmittance was achieved.

Development of a scintillating-fiber-based beam monitor for the coherent muon-to-electron transition experiment

The coherent muon-to-electron transition(COMET)experiment is a leading experiment for the coherent conversion of μ^(-)N→e^(-)N using a high-intensity pulsed muon beamline,produced using innovative slow-extraction techniques.Therefore,it is critical to measure the muon beam characteristics.We set up a muon beam monitor(MBM),where scintillating fibers woven in a cross shape were coupled to silicon photomultipliers to measure the spatial profile and timing structure of the extracted muon beam for the COMET.The MBM detector was tested successfully with a proton beamline at the China Spallation Neutron Source and took data with good performance in the commissioning run.The development of the MBM,including its mechanical structure,electronic readout,and beam measurement results,are discussed.

基于DHNN的非线性profile异常状态监控方法

针对数据关系复杂且样本量较小的非线性轮廓控制问题,提出一种基于离散Hopfield神经网络的轮廓异常状态监控方法。对于收集的小样本数据,首先采用支持向量回归机拟合出样本轮廓;然后将该过程的标准轮廓设置为吸引子,按照一定的编码方法将其存储于Hopfield网络中,再利用该网络的联想功能,判断新的样本轮廓是否发生了变异;最后将该方法与支持向量数据描述算法方法进行对比。研究显示,所提方法平均误识率以及平均运行链长均较小,较适用于复杂生产过程中的异常轮廓监控。

Current Model Analysis of South China Sea Based on Empirical Orthogonal Function(EOF) Decomposition and Prototype Monitoring Data

Environmental load is the primary factor in the design of offshore engineering structures and ocean current is the principal environmental load that causes underwater structural failure. In computational analysis, the calculation of current load is mainly based on the current profile. The current profile model, which is based on a structural failure criterion, is conducive to decreasing the uncertainty of the current load. In this study, we used prototype monitoring data and the empirical orthogonal function(EOF) method to investigate the current profile in the South China Sea and its correlation with the design of underwater structural strength and the dynamic design of fatigue. The underwater structural strength design takes into account the size of the structure and the service water depth. We propose profiles for the overall and local designs using the inverse first-order reliability method(IFORM). We extracted the characteristic profile current(CPC) of the monitored sea area to solve dynamic design problems such as vortex-induced vibration(VIV). We used random sampling to verify the feasibility of using the EOF method to calculate the CPC from the current data and identified the main problems associated with using the CPC, which deserve close attention in VIV design. Our research conclusions provide direct references for determining current load in this sea area. This analysis method can also be used in the analysis of other sea areas or field variables.

Solid phase microextraction chemical biopsy tool for monitoring of doxorubicin residue during in vivo lung chemo-perfusion

Development of a novel in vivo lung perfusion(IVLP)procedure allows localized delivery of high-dose doxorubicin(DOX)for targeting residual micrometastatic disease in the lungs.However,DOX delivery via IVLP requires careful monitoring of drug level to ensure tissue concentrations of this agent remain in the therapeutic window.A small dimension nitinol wire coated with a sorbent of biocompatible morphology(Bio-SPME)has been clinically evaluated for in vivo lung tissue extraction and determination of DOX and its key metabolites.The in vivo Bio-SPME-IVLP experiments were performed on pig model over various(150 and 225 mg/m^(2))drug doses,and during human clinical trial.Two patients with metastatic osteosarcoma were treated with a single 5 and 7 μg/mL(respectively)dose of DOX during a 3-h IVLP.In both pig and human cases,DOX tissue levels presented similar trends during IVLP.Human lung tissue concentrations of drug ranged between 15 and 293 μg/g over the course of the IVLP procedure.In addition to DOX levels,Bio-SPME followed by liquid chromatography-mass spectrometry analysis generated 64 metabolic features during endogenous metabolite screening,providing information about lung status during drug administration.Real-time monitoring of DOX levels in the lungs can be performed effectively throughout the IVLP procedure by in vivo Bio-SPME chemical biopsy approach.Bio-SPME also extracted various endogenous molecules,thus providing a real-time snapshot of the physiology of the cells,which might assist in the tailoring of personalized treatment strategy.

The Use of 'In Process' Monitoring Equipment in Heat Treatment Today

This paper looks at how in-process temperature monitoring systems are being increasingly used in heat treatment applications such as surface hardening, annealing, normalizing, tempering etc. We look at the basic equipment required to successfully monitor from within a furnace and how developments such as RF transmission have enhanced the effectiveness of profiling trials to the point where on line adjustments to furnace conditions can be seen and analyzed in real time. We examine how continuous processes can benefit from this type of monitoring and also how routine operations such as furnace surveying in batch furnaces can benefit greatly from in-process monitoring. Advances in software are also considered, showing how packages are now designed to speed up the processing of data in day to day heat treatment operations.

基于提升小波与SVDD的非线性profile监控

针对函数式复杂且观测点位置固定的非线性profile监控问题,提出一种基于提升小波重构与支持向量数据描述(Support Vector Data Description,SVDD)的方法来监控非线性轮廓图的异常波动。首先采用提升小波对原始数据进行去噪重构处理,还原初始数据的有用信息。其次对去噪后的重构数据进行SVDD模型训练,通过Bootstrap重采样的方法确定控制限,提高模型寻参效率。最后对训练的模型进行生产过程的异常轮廓监控性能研究。通过计算机仿真实验表明,该方法在质量监控过程中的平均链长较短,能及时发现异常轮廓。

Thermal integrity profiling of cast-in-situ piles in sand using fiber-optic distributed temperature sensing

Defects in cast-in-situ piles have an adverse impact on load transfer at the pile‒soil interface and pile bearing capacity. In recent years, thermal integrity profiling (TIP) has been developed to measure temperature profiles of cast-in-situ piles, enabling the detection of structural defects or anomalies at the early stage of construction. However, using this integrity testing method to evaluate potential defects in cast-in-situ piles requires a comprehensive understanding of the mechanism of hydration heat transfer from piles to surrounding soils. In this study, small-scale model tests were conducted in laboratory to investigate the performance of TIP in detecting pile integrity. Fiber-optic distributed temperature sensing (DTS) technology was used to monitor detailed temperature variations along model piles in sand. Additionally, sensors were installed in sand to measure water content and matric suction. An interpretation method against available DTS-based thermal profiles was proposed to reveal the potential defective regions. It shows that the temperature difference between normal and defective piles is more obvious in wet sand. In addition, there is a critical zone of water migration in sand due to the water absorption behavior of cement and temperature transfer-induced water migration in the early-age concrete setting. These findings could provide important insight into the improvement of the TIP testing method for field applications.

同位素注入剖面测井解释智能化批量处理技术的实现与应用

同位素注入剖面测井是水驱油田了解各小层吸水状况的主要监测手段,该测井方法在中国油田的年测井工作量在3万井次左右,在注水油藏动态监测中占主导地位。传统的同位素注水剖面测井结果依赖人工解释,工作效率低、工作量大且多解性强,容易受到不同分析员人为因素影响,已经无法满足日益增长的生产需求。运用大数据监测和机器学习等技术,解决了基础数据录入、原始数据解编、深度匹配、工具识别、曲线叠合、综合评价等关键环节技术难题,形成了智能化批量处理技术。通过在CIFLog测井解释平台上的集成运行,单井处理时间从30~60min缩短到30s,人工干预率低于12%,验证了该处理流程及算法的有效性。

基于动态血糖监测结果评价门诊教育对2型糖尿病患者血糖谱的影响研究

背景 动态血糖监测(CGM)在门诊患者治疗中应用较少,基于CGM进行糖尿病教育,改变不良的生活、饮食习惯对血糖谱的影响尚不清楚。目的 基于回顾性CGM结果,对使用口服降糖药的门诊2型糖尿病(T2DM)患者进行饮食、运动等门诊教育,评价其对患者血糖谱的影响。方法 选取2021于南京市第一医院内分泌科门诊就诊使用口服降糖药的T2DM患者88例,其中男60例、女28例,给予CGM。入组患者给予门诊教育,即第1~3天维持原降糖治疗方案及生活习惯;第4天下载并分析CGM数据,结合患者饮食、运动等门诊教育,第6天取下CGM传感器和记录器,下载数据。比较第2天和第5天动态血糖数据[24 h平均血糖(MBG),平均血糖波动幅度(MAGE),葡萄糖目标范围内时间(TIR)]。结果 基于CGM结果,给予门诊教育后(第5天)T2DM患者的MBG由(8.34±1.97)mmol/L下降到(7.85±1.65)mmol/L,TIR由(78.21±24.64)%上升到(84.28±21.87)%,MAGE由(4.53±2.25)mmol/L下降到(3.80±1.80)mmol/L(P<0.05)。按糖尿病病程、年龄进行分层分析:病程<10年组(62例)和病程≥10年组(26例)干预后MBG均较干预前降低,干预后病程<10年组标准差(SD)、MAGE、TAR较干预前降低,TIR较干预前升高(P<0.05);按年龄分为<65岁组(55例)和≥65岁组(33例),两组干预后MBG、TAR较干预前降低,TIR较干预前升高,干预后<65岁组SD、MAGE较干预前降低(P<0.05)。结论 基于CGM结果,对使用口服降糖药物的门诊T2DM患者进行饮食、运动等门诊教育,可以有效改善患者MBG、提高TIR水平,改善血糖变异度;<65岁、糖尿病病程<10年的患者获益更大。

剖面浮标变体积油囊式浮力调节系统设计

为精准控制剖面浮标的垂向运动,提出一种可精确控制油量的变体积油囊式浮力调节系统,包含外油囊、增压油箱、密封性能良好的电磁球阀和可调节转速的液压泵等组件。采用拉线位移传感器实时采集增压油箱液面位置实现油量监控,并对外油囊体积进行高精度闭环反馈控制;设计极低泄漏量的液压系统,实现系统在待机状态下浮力保持长期稳定。为精确控制浮力调节系统,构建控制系统数学模型,引入比例积分微分(Proportional Integral Differential,PID)控制算法,并采用Simulink进行稳定性仿真。试验结果表明,系统可实现浮力精确控制,最大超调量低于1%,稳定性与响应速度均符合预期,验证了控制策略的可靠性。

Japanese candlestick charts for diabetes

Continuous glucose monitoring(CGM)is a popular technology among the diabetic population,especially in patients with type 1 diabetes and those with type 2 diabetes treated with insulin.The American Diabetes Association recommends standardization of CGM reports with visual cues,such as the ambulatory glucose profile.Nevertheless,interpreting this report requires training and time for CGM to be cost-efficient.In this work it has been proposed to incorporate Japanese candlestick charts in glucose monitoring.These graphs are used in price analysis in financial markets and are easier to view.Each candle provides extra information to make prudent decisions since it reports the opening,maximum,minimum and closing glucose levels of the chosen time frame,usually the daily one.The Japanese candlestick chart is an interesting tool to be considered in glucose control.This graphic representation allows identification of glucose trends easily through the colors of the candles and maximum and minimum glucose values.

基于行为轮廓矩阵增强的业务流程结果预测方法

预测性过程监控依赖于预测效果,针对如何增强预测性过程监控预测效果的问题,提出了一种基于行为轮廓矩阵增强的业务流程结果预测方法。首先,通过分析活动间的行为关系提取行为轮廓矩阵,并将其与事件序列一同输入到模型中。随后,结合卷积神经网络(CNN)和长短期记忆网络(LSTM)分别学习矩阵图像特征和序列特征。最后,引入注意力机制以整合图像特征和序列特征进行预测。通过真实事件日志进行验证,在预测事件日志结果方面,提出的增强方法对比基准的LSTM预测方法提高了预测效果,验证了方法的可行性。该方法结合行为轮廓矩阵增强了预测模型对事件日志中行为之间关系的理解,进而提升了预测效果。

智能贴片示踪剂装载工具的研制及应用

常规水平井分段压裂监测过程中,使用液体示踪剂存在监测周期短、扩散作用较大、影响测试精度等问题,而智能贴片示踪剂是一种固体示踪剂,具有缓释性能,能够满足水平井长期监测(监测周期大于1年)的需求,但国内尚无配套的工具短节用于智能贴片示踪剂使用。由此设计了一种智能贴片示踪剂装载工具,该工具主要由锚卡、护罩及连接短节组成,配套生产管柱使用,能实现长期监测的目的。文章介绍了智能贴片示踪剂、装载工具设计及制造,并结合国内首次应用的案例,阐述了装载工具进行产能剖面监测的安装过程及工艺流程。现场应用表明,装载工具具有良好的稳定性能,可满足智能贴片示踪剂监测需求,填补了国内在该项技术上的空白。

黄土-古土壤地层深竖井受力变形特征研究

研究目的:为准确认识黄土-古土壤地层条件下的深竖井受力变形特征,以53.5 m深圆形竖井工程为依托,开展竖井侧向土压力、变形、结构内力及周边地层的竖直和水平向变形的系统监测。研究结论:(1)黄土-古土壤地层深竖井开挖过程中,井壁结构整体变形较小,水平变形“先挤出后收敛”,竖向变形“先下沉后隆起”,竖井开挖至设计深度后,15~30 d进入结构受力变形稳定阶段;(2)竖井井壁收敛变形、侧向土压力和结构内力在深度方向上存在拐点,出现在0.5~0.7倍竖井设计深度处,其受力变形指标和土层性质存在良好的对应关系,在古土壤范围内,井壁变形量和土压力明显减小,约为邻近深度处黄土层的40%~50%,古土壤的存在,限制了竖井变形和土压力的发展;(3)黄土-古土壤地层深竖井井壁结构侧向土压力与静止土压力和主动土压力有显著差异,在0~12 m深度范围内,侧向土压力接近静止土压力;12~28 m范围内,侧向土压力接近主动土压力;28~48 m范围内,侧向土压力均小于主动土压力,为其35%~65%;(4)本研究成果可为相近地层条件下深竖井的土压力计算和支护结构设计提供参考依据。

型钢轧制中的质量监测与控制技术创新

在传统的型钢轧制过程中,质量监测与控制主要依赖人工经验和一些简单的测量工具,存在一定的局限性。针对此,提出了一种以机器视觉、人工智能和自动化控制为核心的方法。利用机器视觉技术捕获轧制过程中的图像数据,并运用人工智能算法进行深度学习和特征提取,以实现快速、准确的质量检测与分类。经过试验分析,该方法能够有效地实时监测和识别多种质量缺陷。利用自动化控制技术的精准实施,成功降低了废品率,并提高了生产效率,旨在为型钢轧制中的质量监测与控制技术的创新提供理论依据和实践指导。

基于行为轮廓的二维傅里叶变换流程预测

现有的预测性流程监控大多数侧重于深度学习技术,很少有将流程中的行为与此结合.针对这一问题,结合行为关系提出了一个基于二维离散傅里叶变换的流程预测方法,对流程的下一个活动进行预测.将数据进行预处理,利用数据转换工程将时间数据转换为包括活动通道和性能通道的二维空间数据,对活动之间的行为关系进行活动行为编码,并将得到的矩阵进行二维离散傅里叶变换,输入CNN网络中进行训练并预测.使用仿真事件日志和真实事件日志进行评估,在仿真数据集和Helpdesk数据的测试集、BPIC12W数据的测试集上,本文方法预测准确度相比于CNN方法分别提高了2.57%、4.63%和1.67%.实验结果展示了本文方法能有效地提高流程预测的准确度.

基于多数据融合的水电机组全息监测系统及应用

随着全息检测技术与计算机性能的发展,水电站智能化研究逐渐成为评价水电行业的重要指标。提出了融合多数据的水电站相关设备的智能化监测系统,利用数字全息轮廓测量技术扫描转换原始模型的流道特征,利用传感器采集的不同工况下的运行参数与流场特性,基于云计算技术、大数据分析方法和人工智能等技术构建高效的数据分析与处理平台,逐级学习故障特征,进行故障预警定值的挖掘。该系统涵盖在线监测、故障诊断和预警、健康评估以及数据挖掘等功能,消除了水电站运行状态难监控、故障预警难发现和调度策略难实施等痛点,可为水电站全息监测系统的智能化改造、研究和发展提供一定的参考。