混凝土结构碳化寿命预测模型分析

混凝土碳化是影响结构耐久性的重要因素.根据碳化寿命准则,对现有混凝土结构碳化寿命预测模型进行分析比较,并用试验值或实测值验证.还对混凝土结构碳化寿命预测模型的影响因素进行了分析,对混凝土结构耐久性设计以及施工和维护期间应控制的影响因素提出了建议.     

Service life prediction of exterior cladding components under standard conditions

An empirical method was developed for the prediction of the service life of building components, based on an evaluation of their actual performance and on the identification of failure mechanisms affecting their durability. The service life of exterior components subjected to normal service conditions is predicted. Four types of exterior claddings are exemplified: cementitious mortar, synthetic rendering, ceramic mosaic, and wet‐fixing stone cladding. The proposed prediction models yield high degrees of fit to the data (R ² in the range of 0.86 to 0.93 at a 0.0001 level of significance). Life cycle costs (LCC) analysis – following service‐life prediction results – leads to the conclusion that maintenance and replacements costs account for 10–80% of initial capital costs. Synthetic rendering exhibited the highest LCC effectiveness, reflecting durability and low capital costs. The method can be used for planning preventive maintenance, evaluating economic implications of failures, and planning service life.     

多因素作用下混凝土碳化模型及寿命预测

本文在回顾国内外混凝土碳化模型的基础上，考虑了包括荷载、温度、湿度及碳化速率系数时间依赖性等因素。结合试验结果初步建立了包括荷载在内的多因素作用下的混凝土碳化模型，并结合具体工程进行了寿命预测。     

混凝土结构耐久性设计与耐久性寿命预测

当前工程结构设计方法正在由强度设计向耐久性设计转变,混凝土结构耐久性设计包括耐久性设计和耐久性寿命预测两部分,作者扼要介绍了仅考虑钢筋锈蚀的寿命预测模型,并提出了耐久性设计今后的发展方向。     

长沙地铁混凝土抗碳化性能及使用寿命预测研究

研究多种因素对长沙地铁混凝土的抗碳化性能的影响,试验结果表明混凝土抗碳化性能随混凝土强度等级增加而增强;采用聚羧酸减水剂混凝土的抗碳化性能优于采用萘系减水剂的混凝土的抗碳化性能。依据Fick第二定律及相似理论,建立了长沙地铁混凝土抗碳化耐久性预测方法。混凝土抗碳化耐久性预测结果表明所设计的不同强度等级的长沙地铁混凝土抗碳化耐久寿命均超过了100年的设计使用寿命。     

基于现场耐久性检测的承台海工混凝土寿命预测

金塘大桥受恶劣的海洋气候环境和海水腐蚀影响严重,其结构设计基准期为100年.根据现场对大桥已建部分承台混凝土检测的保护层厚度、表面氯离子浓度和氯离子扩散系数等耐久性参数,以Fick第二定律为基础的理论模型对混凝土结构抵抗氯离子侵蚀耐久寿命进行预测.此研究成果可为氯盐侵蚀环境下混凝土结构耐久性设计与评估提供参考.     

Service life prediction and environmental exposure conditions of timber claddings in South Chile

ABSTRACT

In this research, a methodology for the service life prediction of external timber claddings is proposed and discussed. The proposed model is based on the visual assessment of 110 timber claddings, subjected to real exposure conditions. The claddings under analysis belong to 80 buildings, with and without heritage characteristics, located in Valdivia and Niebla, South Chile. Timber claddings are a relevant symbol of the local identity of this region, portraying a complexity of ideas and cultural values, inherited by Spanish and German colonizations. The main anomalies that can occur in these claddings are translated into a numerical index, which describes the overall degradation condition of a timber façade. This work also discusses the influence of the local climate and environmental exposure conditions, considering biotic factors (fungi, insects, moulds, algae and bacteria) and abiotic factors (water, solar radiation, amplitude of temperature, physical damage) in the evolution of the degradation condition of timber claddings. The scarcity of funds in Chile to maintain and preserve the constructions and its components needs a more rational approach to decision-making concerning inspection, maintenance and rehabilitation procedures. The expeditious tool proposed in this paper may help in providing the basis for rational decision-making by professionals in practice.     

基于RBF的钢筋混凝土结构剩余使用寿命预测

分析了一般混凝土结构剩余使用寿命预测方法，在吸取等维灰色递补GM（1，1）模型的优点之后，提出了利用RBF网络对既有钢筋混凝土结构的剩余使用寿命进行预测的方法，通过理论分析及应用，证明了其可行性。     

Status,needs and possibilities for service life prediction and estimation of district heating distribution networks

An optimised and proactive maintenance strategy aims to maximise the economical profit, minimise environmental impacts and keep the risk of failure to a low level. Implementation of such a strategy in the context of district heating requires efforts and abilities for predicting future performances and estimating service life of district heating components. A literature review on failures (damages and performance reductions) occurring on district heating pipes, reveals that failures in district heating pipes are mainly leaks due to corrosion or mechanical impacts and reduced thermal insulation performance: leaks being the more serious damage type. A feasible service life estimation method for this type of damage is the Factor Method. Since the application of this method within the context of DH pipes has not been found in other publications, this paper focuses on describing the method and discusses the possibilities on how to apply it in two specific cases with respect to leakage: service life estimation of repaired district heating pipe sections (i.e. maintenance of district heating network) and of district heating pipes in new or extended district heating networks. Particular attention is paid to which modifying factors should be considered and how to quantify them.     

Service life prediction of fly ash concrete using an artificial neural network

Carbonation is one of the most aggressive phenomena affecting reinforced concrete structures and causing their degradation over time. Once reinforcement is altered by carbonation, the structure will no longer fulfill service requirements. For this purpose, the present work estimates the lifetime of fly ash concrete by developing a carbonation depth prediction model that uses an artificial neural network technique. A collection of 300 data points was made from experimental results available in the published literature. Backpropagation training of a three-layer perceptron was selected for the calculation of weights and biases of the network to reach the desired performance. Six parameters affecting carbonation were used as input neurons: binder content, fly ash substitution rate, water/binder ratio, CO₂ concentration, relative humidity, and concrete age. Moreover, experimental validation carried out for the developed model shows that the artificial neural network has strong potential as a feasible tool to accurately predict the carbonation depth of fly ash concrete. Finally, a mathematical formula is proposed that can be used to successfully estimate the service life of fly ash concrete.     

CRTSⅡ型板式无砟轨道板局部锈胀裂耐久性寿命预测

以CRTSⅡ型无砟轨道板局部出现顺筋锈胀裂缝作为耐久性极限状态,在相关模型基础上提出假缝处钢筋锈蚀发展的"两阶段"实用模型,并按照"全年锈蚀深度等效"的原则确定不同区域温湿度谱下的锈蚀速度向标准温湿度谱、标准锈蚀速度进行转化的当量关系,为不同地区自然环境下轨道板结构中钢筋腐蚀速度及其耐久性寿命提供了较为实用的预测方法。以京沪铁路沿线具有代表性的北京、徐州、上海三大城市为例对各类环境下轨道板假缝处的钢筋锈蚀速度和局部锈胀裂耐久性寿命进行了预测,并建议:对通过假缝的上层纵向钢筋采取表面涂刷环氧树脂或沥青漆等措施进行防锈处理以延长无砟轨道结构的耐久性寿命。     

加强科学养护工作延长公路使用寿命

对大同县段公路科学养护方面的主要工作内容作了介绍，从坚持改革、强化管理、加强培训等方面，提出坚持科学养护的几点体会，通过实践证明，所养护的路段路况良好。     

基于区间分析的锈蚀钢筋混凝土结构使用寿命预测

钢筋锈蚀程度具有很大的不确定性,为体现锈蚀不确定性对结构寿命预测结果的影响,将区间分析方法引入锈蚀钢筋混凝土结构的使用寿命预测。首先,对区间分析的基础知识及区间参数问题的求解方法作简单介绍,针对区间运算法则导致运算结果区间扩张的缺陷,优化方法是求解区间参数问题的有效方法;其次,基于钢筋锈蚀过程的确定性预测模型,采用区间数描述结构参数及环境参数,提出结构锈蚀损伤的区间预测方法;再根据选取的使用寿命终结标准,提出结构使用寿命的区间预测方法。工程实例分析表明,该方法分析过程简单,不需要建立不确定参数的概率模型,分析结果以区间形式给出,预测结果较概率方法更直观,易于接受。     

人工神经网络在受腐蚀钢筋混凝土结构工程中的应用

介绍了人工神经网络在土木工程中的应用现状，阐述了人工神经网络在受腐蚀钢筋混凝土结构工程中的应用，介绍了神经网络方法在锈蚀钢筋与混凝土之间粘结特性及受腐蚀钢筋混凝土构件受力性能研究中新近取得的研究成果。研究表明，与传统的回归方法相比，神经网络方法在解决多影响因子复杂非线性问题方面具有显著的优势，在受腐蚀钢筋混凝土结构工程中具有广阔的应用前景。     

应用人工神经网络预测高掺量粉煤灰混凝土的强度

基于人工神经网络原理,建立了反映高掺量粉煤灰混凝土配方与强度之问映射关系的多因素智能分析模型.利用可视化CC 6.0开发了粉煤灰混凝土的强度预测应用软件,解决了高掺量粉煤灰混凝土的模式特征不明确、各组分对混凝土性能影响非线性、随机因素多等问题.该方法进行高掺量粉煤灰混凝土的配制具有优化设计及快速、定量、预测精度高、适应性强、成本低等特点.     

暴露环境下普通混凝土耐久性试验及基于加速系数K法寿命预测研究

针对影响混凝土耐久性的关键因素,进行了混凝土室内冻融试验和现场暴露试验,以单评价指标ωa、ωb和综合评价参数ω评价混凝土耐久性,并采用加速试验法对暴露环境下混凝土的寿命进行预测。其结果表明:加速系数K是关于ω的函数,通过加速法得到0.30、0.35、0.43水灰比的试件分别在51.98、39.13、25.35年达到破坏,水灰比越小,混凝土预测使用寿命越长;室内冻融条件下,ωa整体呈下降趋势,ωb虽有小幅度波动,但整体也是呈下降趋势;现场暴露条件下,在近300 d的暴露时间内,虽然混凝土试件没有达到破坏,但是可以看出其评价参数也在缓慢下降,这是外界腐蚀性离子与当地气候环境综合作用的结果。     

Time-dependent reliability method for service life prediction of reinforced concrete shield metro tunnels

Ageing and deterioration of underground tunnels is inevitable after their long-time in service. This necessitates a rigorous assessment of the probability of failure due to deterioration with a view to predicting remaining safe life. In the light of considerable research undertaken on prediction of service life of the aboveground structures, e.g. bridges, few such studies dealing with the underground structures, e.g. tunnels, have been carried out. The intention of this paper is to present a time-dependent reliability method to assess the tunnel probability failure due to different mechanisms of deterioration. Stochastic models are developed for four common failure modes of tunnel structures as identified by strength and serviceability criteria. Application of the proposed methodology is demonstrated in a case study. It is found in the paper that the reinforcement corrosion is a key factor that affects the probability of deterioration failure and that all deterioration scenarios need to be considered in the assessment of tunnel failures and prediction of their remaining safe life. The proposed method can help the asset managers and practitioners in developing rehabilitation or replacement strategy for existing tunnels with a view for better management of the valuable tunnel asset.