scholarly journals Influence of global warming on durability of corroding RC structures: A probabilistic approach

2013 ◽  
Vol 51 ◽  
pp. 259-266 ◽  
Author(s):  
Emilio Bastidas-Arteaga ◽  
Franck Schoefs ◽  
Mark G. Stewart ◽  
Xiaoming Wang
Keyword(s):  
Global Warming ◽  
Probabilistic Approach ◽  
Rc Structures

scholarly journals An efficient mechanical-probabilistic approach for the collapse modelling of RC structures

2019 ◽  
Vol 12 (2) ◽  
pp. 386-397
Author(s):  
K. O. COELHO ◽  
E. D. LEONEL ◽  
J. FLÓREZ-LÓPEZ
Keyword(s):  
Probabilistic Approach ◽  
Damage Model ◽  
Coupled Model ◽  
Simulation Method ◽  
Computationally Efficient ◽  
Rc Structures ◽  
Realistic Representation ◽  
Probabilistic Context ◽  
Numerical Approaches

Abstract The reinforced concrete (RC) structures are widely utilized around the world. However, the modelling of its complex mechanical behaviour by efficient numerical approaches has been presented marginally in the literature. The efficient approaches enable the accurate and the realistic representation of the mechanical phenomena involved and are computationally efficient for analysing complex structures. In the present study, the improved version of the lumped damage model is coupled to the Monte Carlo simulation method to represent the mechanical-probabilistic behaviour of RC structures. In such model, the concrete cracking and reinforcements’ yield are represented accurately. Moreover, this damage approach enables the accurate modelling of failure scenarios, which are based on the damage variable. Furthermore, this coupled model enables the determination of the collapse modelling accounting for uncertainties, which is the main contribution of the present study. One simple supported RC beam and one 2D RC frame are analysed in the probabilistic context. The accurate results are obtained for the probabilistic collapse path as well as its changes as a function of the loading conditions and material properties uncertainties.

Structural Non-Linear Models and Simulation Techniques

2016 ◽  
pp. 540-584
Author(s):  
Jorge M. Delgado ◽  
Antonio Abel R. Henriques ◽  
Raimundo M. Delgado
Keyword(s):  
Computational Models ◽  
Linear Models ◽  
Civil Engineering ◽  
Numerical Models ◽  
Probabilistic Approach ◽  
Latin Hypercube Sampling ◽  
Computational Time ◽  
Rc Structures ◽  
Simulation Techniques ◽  
Non Linear

Advances in computer technology allow nowadays the use of powerful computational models to describe the non-linear structural behavior of reinforced concrete (RC) structures. However their utilization for structural analysis and design is not so easy to be combined with the partial safety factors criteria presented in civil engineering international codes. Trying to minimize this type of difficulties, it is proposed a method for safety verification of RC structures based on a probabilistic approach. This method consists in the application of non-linear structural numerical models and simulation methods. In order to reduce computational time consuming the Latin Hypercube sampling method was adopted, providing a constrained sampling scheme instead of general random sampling like Monte Carlo method. The proposed methodology permits to calculate the probability of failure of RC structures, to evaluate the accuracy of any design criteria and, in particular, the accuracy of simplified structural design rules, like those proposed in civil engineering codes.

Predicting Forest Fire Numbers Using Deterministic-Probabilistic Approach

2020 ◽  
pp. 89-100
Author(s):  
Nikolay Viktorovich Baranovskiy
Keyword(s):  
Global Warming ◽  
Forest Fire ◽  
Forest Fires ◽  
Probabilistic Method ◽  
Probabilistic Approach ◽  
Retrospective Data ◽  
Surface Fires ◽  
Crown Fires ◽  
Vegetation Fires ◽  
Forest Fire Danger

The annual task of forecasting forest fire danger is becoming increasingly relevant, especially in the context of global warming. The forecast of surface fires is most important, as more than 80% of all vegetation fires are surface fires. Practically all crown fires develop from surface fires. This chapter discusses the deterministic-probabilistic method for predicting the number of forest fires in a controlled forest area. This methodology is based on the assumption that the number of registered and projected forest fires is related to the probability of their occurrence. The influence of forest fire retrospective data on the predicted number of forest fires for some sites of the Timiryazevskiy forestry of the Tomsk region was studied. This chapter presents the results of a comparative analysis of forecast data and statistics.

Time-Variant Reliability of RC Structures

2016 ◽  
Vol 847 ◽  
pp. 407-414
Author(s):  
Bruno Palazzo ◽  
Paolo Castaldo ◽  
Alessio Mariniello
Keyword(s):  
Reinforced Concrete ◽  
Probabilistic Approach ◽  
Bending Moment ◽  
Structural Safety ◽  
Time Variability ◽  
Structural Element ◽  
Rc Structures ◽  
Geometrical Properties ◽  
Proposed Model ◽  
Strength And Stiffness

Reinforced concrete structures are generally affected by degradation phenomena, which results in a time variability in strength and stiffness beyond the baseline conditions which are assumed in structural design, in particular when the concrete is exposed to an aggressive environment. Therefore, structural safety should realistically be considered time-variant. This paper provides a probabilistic approach to predict the time-evolution of the mechanical and geometrical properties of a reinforced concrete structural element (i.e., bridge pier) subjected to corrosion-induced deterioration, due to diffusive attack of chlorides, in order to evaluate its service life. The proposed model is based on Monte Carlo simulations in order to evaluate time variant axial force-bending moment resistance domains, with the aim to estimate the time-variant reliability index. Finally, an application to estimate the expected lifetime of a deteriorating reinforced concrete bridge pile is proposed.

Probabilistic Change of Wheat Productivity and Water Use in China for Global Mean Temperature Changes of 1°, 2°, and 3°C

2013 ◽  
Vol 52 (1) ◽  
pp. 114-129 ◽  
Author(s):  
Yujie Liu ◽  
Fulu Tao
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Water Use ◽  
Probabilistic Approach ◽  
Wheat Production ◽  
Positive Effects ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Fertilization Effects ◽  
Global Mean

AbstractImpacts of climate change on agriculture are a major concern worldwide, but uncertainties of climate models and emission scenarios may hamper efforts to adapt to climate change. In this paper, a probabilistic approach is used to estimate the uncertainties and simulate impacts of global warming on wheat production and water use in the main wheat cultivation regions of China, with a global mean temperature (GMT) increase scale relative to 1961–90 values. From output of 20 climate scenarios of the Intergovernmental Panel on Climate Change Data Distribution Centre, median values of projected changes in monthly mean climate variables for representative stations are adapted. These are used to drive the Crop Environment Resource Synthesis (CERES)-Wheat model to simulate wheat production and water use under baseline and global warming scenarios, with and without consideration of carbon dioxide (CO2) fertilization effects. Results show that, because of temperature increase, projected wheat-growing periods for GMT changes of 1°, 2°, and 3°C would shorten, with averaged median values of 3.94%, 6.90%, and 9.67%, respectively. There is a high probability of decreasing (increasing) changes in yield and water-use efficiency under higher temperature scenarios without (with) consideration of CO2 fertilization effects. Elevated CO2 concentration generally compensates for the negative effects of warming temperatures on production. Moreover, positive effects of elevated CO2 concentration on grain yield increase with warming temperatures. The findings could be critical for climate-change-driven agricultural production that ensures global food security.

scholarly journals Effects of climate variations and global warming on the durability of RC structures subjected to carbonation

2014 ◽  
Vol 31 (2) ◽  
pp. 153-164 ◽  
Author(s):  
Thomas de Larrard ◽  
Emilio Bastidas-Arteaga ◽  
Frédéric Duprat ◽  
Franck Schoefs
Keyword(s):  
Global Warming ◽  
Climate Variations ◽  
Rc Structures

scholarly journals Structural Non-Linear Models and Simulation Techniques

2016 ◽  
pp. 369-406
Author(s):  
Jorge M. Delgado ◽  
Antonio Abel R. Henriques ◽  
Raimundo M. Delgado
Keyword(s):  
Computational Models ◽  
Linear Models ◽  
Civil Engineering ◽  
Numerical Models ◽  
Probabilistic Approach ◽  
Latin Hypercube Sampling ◽  
Computational Time ◽  
Rc Structures ◽  
Simulation Techniques ◽  
Non Linear

Advances in computer technology allow nowadays the use of powerful computational models to describe the non-linear structural behavior of reinforced concrete (RC) structures. However their utilization for structural analysis and design is not so easy to be combined with the partial safety factors criteria presented in civil engineering international codes. Trying to minimize this type of difficulties, it is proposed a method for safety verification of RC structures based on a probabilistic approach. This method consists in the application of non-linear structural numerical models and simulation methods. In order to reduce computational time consuming the Latin Hypercube sampling method was adopted, providing a constrained sampling scheme instead of general random sampling like Monte Carlo method. The proposed methodology permits to calculate the probability of failure of RC structures, to evaluate the accuracy of any design criteria and, in particular, the accuracy of simplified structural design rules, like those proposed in civil engineering codes.

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