Improving Fatigue Evaluations of Structures Using In-Service Behavior Measurement Data

Conservative models and code practices are usually employed for fatigue-damage predictions of existing structures. Direct in-service behavior measurements are able to provide more accurate estimations of remaining-fatigue-life predictions. However, these estimations are often accurate only for measured locations and measured load conditions. Behavior models are necessary for exploiting information given by measurements and predicting the fatigue damage at all critical locations and for other load cases. Model-prediction accuracy can be improved using system identification techniques where the properties of structures are inferred using behavior measurements. Building upon recent developments in system identification where both model and measurement uncertainties are considered, this paper presents a new data-interpretation framework for reducing uncertainties related to prediction of fatigue life. An initial experimental investigation confirms that, compared with traditional engineering approaches, the methodology provides a safe and more realistic estimation of the fatigue reserve capacity. A second application on a full-scale bridge also confirms that using load-test data reduces the uncertainty related to remaining-fatigue-life predictions

Overview of Remaining Useful Life prediction techniques in Through-life Engineering Services

Through-life Engineering Services (TES) are essential in the manufacture and servicing of complex engineering products. TES improves support services by providing prognosis of run-to-failure and time-to-failure on-demand data for better decision making. The concept of Remaining Useful Life (RUL) is utilised to predict life-span of components (of a service system) with the purpose of minimising catastrophic failure events in both manufacturing and service sectors. The purpose of this paper is to identify failure mechanisms and emphasise the failure events prediction approaches that can effectively reduce uncertainties. It will demonstrate the classification of techniques used in RUL prediction for optimisation of products’ future use based on current products in-service with regards to predictability, availability and reliability. It presents a mapping of degradation mechanisms against techniques for knowledge acquisition with the objective of presenting to designers and manufacturers ways to improve the life-span of components

Aging concrete structures: a review of mechanics and concepts

The safe and cost-efficient management of our built infrastructure is a challenging task considering the expected service life of at least 50 years. In spite of time-dependent changes in material properties, deterioration processes and changing demand by society, the structures need to satisfy many technical requirements related to serviceability, durability, sustainability and bearing capacity. This review paper summarizes the challenges associated with the safe design and maintenance of aging concrete structures and gives an overview of some concepts and approaches that are being developed to address these challenges

Handling Concept Drift for Predictions in Business Process Mining

Predictive services nowadays play an important role across all business sectors. However, deployed machine learning models are challenged by changing data streams over time which is described as concept drift. Prediction quality of models can be largely influenced by this phenomenon. Therefore, concept drift is usually handled by retraining of the model. However, current research lacks a recommendation which data should be selected for the retraining of the machine learning model. Therefore, we systematically analyze different data selection strategies in this work. Subsequently, we instantiate our findings on a use case in process mining which is strongly affected by concept drift. We can show that we can improve accuracy from 0.5400 to 0.7010 with concept drift handling. Furthermore, we depict the effects of the different data selection strategies

Report : review of the literature : maintenance and rehabilitation costs for roads (Risk-based Analysis)

Realistic estimates of short- and long-term (strategic) budgets for maintenance and rehabilitation of road assessment management should consider the stochastic characteristics of asset conditions of the road networks so that the overall variability of road asset data conditions is taken into account. The probability theory has been used for assessing life-cycle costs for bridge infrastructures by Kong and Frangopol (2003), Zayed et.al. (2002), Kong and Frangopol (2003), Liu and Frangopol (2004), Noortwijk and Frangopol (2004), Novick (1993). Salem 2003 cited the importance of the collection and analysis of existing data on total costs for all life-cycle phases of existing infrastructure, including bridges, road etc., and the use of realistic methods for calculating the probable useful life of these infrastructures (Salem et. al. 2003). Zayed et. al. (2002) reported conflicting results in life-cycle cost analysis using deterministic and stochastic methods. Frangopol et. al. 2001 suggested that additional research was required to develop better life-cycle models and tools to quantify risks, and benefits associated with infrastructures. It is evident from the review of the literature that there is very limited information on the methodology that uses the stochastic characteristics of asset condition data for assessing budgets/costs for road maintenance and rehabilitation (Abaza 2002, Salem et. al. 2003, Zhao, et. al. 2004). Due to this limited information in the research literature, this report will describe and summarise the methodologies presented by each publication and also suggest a methodology for the current research project funded under the Cooperative Research Centre for Construction Innovation CRC CI project no 2003-029-C

Freeze-Thaw Durability and Long-Term Performance Evaluation of Shotcrete in Cold Regions

This study’s aim was to evaluate the freeze-thaw durability of shotcrete in cold regions and predict its long-term performance. One benchmark mix design from the WSDOT was chosen to prepare samples for performance evaluation. Shotcrete specimens were conditioned in accordance with ASTM C666. The long-term freeze-thaw performance after certain cycles was evaluated using the dynamic modulus of elasticity test (ASTM C215), fracture energy test (RILEM 50-FMC), and X-ray CT microstructure imaging analysis. Probabilistic damage analysis was conducted to establish the relation between the durability life and the damage parameter for different probabilities of reliability using the three-parameter Weibull distribution model. The fracture energy test was found to be a more sensitive test method than the dynamic modulus of elasticity for screening material deterioration over time and for capturing accumulative material damage caused by rapid freeze-thaw action, because of smaller durability factors (degradation ratios) obtained from the fracture energy test. X-ray CT imaging analysis is capable of detecting microcracks that form and pore evolution in the aggregate and interface transition zone of conditioned samples. Moreover, the continuum damage mechanic-based model shows potential in predicting long-term material degradation and the service life of shotcrete

Novel direct method on the life prediction of component under high temperature-creep fatigue conditions

This paper presents a novel direct method, within the Linear Matching Method (LMM) framework, for the direct evaluation of steady state cyclic behaviour of structures subjected to high temperature – creep fatigue conditions. The LMM was originally developed for the evaluation of shakedown and ratchet limits. The latest extension of the LMM makes it capable of predicting the steady state stress strain solutions of component subjected to cyclic thermal and mechanical loads with creep effects. The proposed iterative method directly calculates the creep stress and cyclically enhanced creep strain during the dwell period for the assessment of the creep damage, and also creep enhanced total strain range for the assessment of fatigue damage of each load cycle. To demonstrate the efficiency and applicability of the method to assess the creep fatigue damage, two types of weldments subjected to reverse bending moment at elevated temperature of 550C are simulated by the proposed method considering a Ramberg-Osgood model for plastic strains under saturated cyclic conditions and a power-law model in “time hardening” form for creep strains during the dwell period. Further experimental validation shows that the proposed direct method provides a general purpose technique for the creep fatigue damage assessment with creep fatigue interaction