Service life planning and performance requirements

Service life planning comprises a model for the determination of a reasonable expected service life for buildings and components, and it establishes a routine for the assessment of design alternatives. A design option is considered reasonable when it meets or exceeds performance requirements over time that have been drawn up specifically for the specific project. Due to this assessment reference, there is a very evident link to the concept of performance-based building. Any stakeholder involved in the value chain or in the design process of the building, as well as regulators and building users, can express performance requirements. Identified requirements, both in relevance and in quality, will vary with the stakeholder and his/her perspective of interest. As building sector manufacturers develop most products with reference to standards rather than with reference to specific requirements, there is no direct link from user requirements to the product design. Instead, the building designer has the responsibility to ensure performance requirements are met by the performance of products integrated into the design. As these design decisions also have to be made at the material and component level, a performance-based building would benefit from an established rationale that enables the communication of performance requirements across the relevant system levels in the relevant design processes. A path for the connection of the established concepts of service life planning and performance-based building is presented. The aim is to identify key elements that need to be developed for the successful linkage of performance-based building with service life planning.     

中华丹参酒的研制

以丹参为主 ,配以12种中药材 ,经热回流提取 ,回流时夹层气压为0.2MPa,锅内气压小于0.05MPa,时间2h,按配比将提取液与酒母液在冷冻罐内混合 ,在0.05MPa下反吹混匀 ,取上清液为半成品 ,再经过滤等处理为成品。(孙悟)     

论老年教育的地位、作用和发展方向

老年教育在社会中具有重要的地位和作用。它是终身教育的重要组成部分,是社会发展的客观需要,是解决老龄问题的重要途径和方法。探讨了随着社会经济的发展和老龄化社会进程的加快,在21世纪老年教育的发展方向。     

High temperature low cycle fatigue

Fatigue at high temperature is a complex phenomenon as it is influenced by a number of time-dependent processes which become important at elevated temperatures. These processes include creep, oxidation, phase instabilities and dynamic strain ageing (DSA), acting either independently or synergistically influence fatigue behaviour, often lowering the fatigue life. Current design approaches employ linear summation of fatigue and creep damage with suitable factors on permissible damage to take care of uncertainties in interaction between cyclic and time-dependent processes. It is, therefore, important to develop a deeper understanding of the processes that occur during high temperature fatigue so that realistic life predictions could be made. Results on the high temperature fatigue behaviour of austenitic stainless steels, ferritic steels and nickel base alloys are presented here. The important mechanisms of interaction of high temperature time-dependent processes with fatigue under various conditions are discussed in detail. Emphasis is placed on cyclic stress response, fatigue life, deformation substructure and fracture behaviour. This is followed by a review of important life prediction techniques under combined creep-fatigue loading conditions. Life prediction techniques considered here include linear damage summation, strain range partitioning, ductility exhaustion approach, frequency modified and frequency separation methods, techniques based on hysteresis energy and damage rate models, and methods based on crack-cavitation interation models.     

AI paradigms

The aim of this paper is comparative analysis of most important AI paradigms. An AI paradigm is defined as the pair composed by a concept of intelligence and a methodology in which intelligent computer systems are developed and operated. Three paradigms, the behaviourist paradigm, the agent paradigm, and the artificial life paradigm are discussed.     

高炉长寿技术的新发展

高炉长寿是目前国内外炼铁界关注的主要课题。在此介绍了国内外高炉的长寿状况，高炉长寿技术的最新发展趋势以及应用情况。     

RFID技术在电网资产全寿命周期管理应用模式探讨

为了配合电网企业建立RFID资产实物标识电子身份证系统,集成资产的实物流、信息流和价值流,实现账、卡、物相符一致,实现资产管理各阶段信息共享及开展资产全生命周期的跟踪管理,同时也为了提高电网设备的现代化管理水平,文章总结了多年来在电网设备RFID实物标识实施的切身体会,对RFID在国内外电力电网设备的应用方面进行了研究,重点对RFID技术在电网资产全寿命周期管理模式进行了探讨。     

基于BA-WPHM的滚动轴承两阶段剩余寿命预测方法

为了提高滚动轴承剩余寿命预测的准确性,根据滚动轴承运行过程的两阶段性特点,提出了一种基于蝙蝠算法(BA)和威布尔比例风险模型(WPHM)的滚动轴承两阶段剩余寿命预测方法。首先,构建基于WPHM的剩余寿命预测模型;其次,提出了两阶段极大似然估计法,建立新的似然函数,并利用BA算法进行求解,以提高参数估计的准确性;最后,建立BA-WPHM模型对滚动轴承进行剩余寿命预测。案例分析表明,相比于Newton-Raphson算法、自组织分层猴群算法(SHMA)和独特的自适应粒子群算法(UAPSO),提出的方法参数估计的准确性更高,剩余寿命的预测精度优于支持向量回归(SVR)方法,验证了所提方法的有效性,为滚动轴承维修决策的可行性提供了依据。     

Physics-guided logistic classification for tool life modeling and process parameter optimization in machining

This paper describes a physics-guided logistic classification method for tool life modeling and process parameter optimization in machining. Tool life is modeled using a classification method since the exact tool life cannot be measured in a typical production environment where tool wear can only be directly measured when the tool is replaced. In this study, laboratory tool wear experiments are used to simulate tool wear data normally collected during part production. Two states are defined: tool not worn (class 0) and tool worn (class 1). The non-linear reduction in tool life with cutting speed is modeled by applying a logarithmic transformation to the inputs for the logistic classification model. A method for interpretability of the logistic model coefficients is provided by comparison with the empirical Taylor tool life model. The method is validated using tool wear experiments for milling. Results show that the physics-guided logistic classification method can predict tool life using limited datasets. A method for pre-process optimization of machining parameters using a probabilistic machining cost model is presented. The proposed method offers a robust and practical approach to tool life modeling and process parameter optimization in a production environment.     

注意力ConvLSTM模型在RUL预测中的应用

预测性维护的应用能够极大地降低企业运维成本,而设备剩余使用寿命(Remaining Useful Life,RUL)预测是预测性维护的关键技术之一.针对传统RUL预测算法难以提取时序数据的潜藏特征以及特征权重分配不合理的问题,本文提出一种基于注意力机制(Attention Mechanism)的卷积长短时记忆(Convolution Long-Short Term Memory,ConvLSTM)预测模型,该模型充分利用LSTM网络处理和预测长期时间序列的优势,并引入注意力机制对产生显著影响的特征因子提高权重,极大地优化了模型的时空特征提取能力.为验证模型预测效果,本文以NASA提供的CMAPSS数据集为对象进行实验,以均方根误差(Root Mean Squared Error,RMSE)和数据集自定义的Score为评价指标,将预测结果与其他RUL预测算法作比对,证明了该模型具有更佳的预测准确性.