scholarly journals Probabilistic Corrosion Initiation Model for Coastal Concrete Structures

2020 ◽  
Vol 1 (3) ◽  
pp. 328-344
Author(s):  
Changkyu Kim ◽  
Do-Eun Choe ◽  
Pedro Castro-Borges ◽  
Homero Castaneda
Keyword(s):  
Experimental Data ◽  
Environmental Conditions ◽  
Bayesian Model ◽  
Structural Reliability ◽  
Electrochemical Corrosion ◽  
Corrosion Process ◽  
Sensitivity Analyses ◽  
Theoretical Understanding ◽  
Rc Structures ◽  
Corrosion Initiation

Corrosion of the reinforced concrete (RC) structures has been affecting the major infrastructures in U.S. and in other continents, causing the recent several bridge collapses and incidents. While the theoretical understanding is well-established, the reliable prediction of the corrosion process in the RC structural systems has hardly been successful due to the inherent uncertainties existed in the electrochemical corrosion process and the associated material and environmental conditions. The paper proposes a computational framework to develop evidence-based probabilistic corrosion initiation models for the reinforcing steels in the RC structures, which predicts the corrosion initiation time and quantifies the inherent variances considering various acting parameters. The framework includes: probabilistic modeling with Bayesian updating based on the sets of previously generated experimental data; Bayesian model/parameter selection considering various parameters, such as material properties and environmental conditions; corrosion reliability analyses to predict the probabilities of the corrosion initiation at given time t, structural configurations, and environmental conditions; and sensitivity analyses to measure and to rank the influences of each acting parameter and its uncertainty to the probabilities of the corrosion initiation. Total of 284 sets of experimental data exposed to the coastal atmospheric environments are used for the modeling. The goal of the Bayesian model selection presented in this paper is to obtain the most accurate and unbiased model using the simplest form of expression. The developed example corrosion model is currently limited to the initiation of diffusion-induced corrosion. The model can be updated, improved, or modified upon future available sets of data. The research contributes to the decision making to improve the corrosion reliability, corrosion control, and further the structural reliability of corroding structures.

Reliability-Based Assessment of the Effect of Climatic Conditions and CO2 Emissions on the Corrosion of RC Structures Subjected to Carbonation

2012 ◽  
Vol 503-504 ◽  
pp. 780-784 ◽  
Author(s):  
Jun Li Liu ◽  
Zhi Fang
Keyword(s):  
Co2 Emissions ◽  
Co2 Emission ◽  
Structural Reliability ◽  
Concrete Structures ◽  
Co2 Concentration ◽  
Climatic Conditions ◽  
Emission Scenarios ◽  
Carbonation Depth ◽  
Rc Structures ◽  
Corrosion Initiation

carbonation rate of concrete structures are influenced by CO2 emissions and climate conditions. Carbonation depth prediction model was proposed and CO2 emission scenarios influence on concrete structures' carbonation damage was studied. As there are significant uncertainty and variability of CO2 emissions, deterioration mechanisms, material properties, dimensions and environments, the time-dependent structural reliability analysis was employed to predict the probability of corrosion initiation from 2000 to 2100, considering several IPCC future atmospheric CO2 emission scenarios. Results show:(1)carbonation depth in A1F1 and A1B scenarios is 36% higher than that invariant CO2 concentration, and A1B scenarios is 21%; (2)The corrosion initiation probability of RC structures in A1F1 and A1B scenarios are 84% and 67% higher than that invariant CO2 concentration , respectively.

scholarly journals Bayesian Assessment of the Effects of Cyclic Loads on the Chloride Ingress Process into Reinforced Concrete

2020 ◽  
Vol 10 (6) ◽  
pp. 2040 ◽  
Author(s):  
Henriette Marlaine Imounga ◽  
Emilio Bastidas-Arteaga ◽  
Rostand Moutou Pitti ◽  
Serge Ekomy Ango ◽  
Xiao-Hui Wang
Keyword(s):  
Experimental Data ◽  
Reinforced Concrete ◽  
Bayesian Networks ◽  
Chloride Ion ◽  
Chloride Ions ◽  
Chloride Diffusion ◽  
Chloride Ingress ◽  
Rc Structures ◽  
Corrosion Initiation ◽  
Static And Cyclic Loading

Chloride-induced corrosion and load induced concrete cracking affect the serviceability and safety of reinforced concrete (RC) structures. Once these phenomena occur simultaneously, the prediction of RC structures’ lifetimes becomes a major challenge. The objective of this paper is to propose a methodology to evaluate the effect of loading and cracking on the mechanism of chloride ion penetration in concrete. The proposed methodology will be based on Bayesian networks. Bayesian networks are useful to update the lifetime assessment based on experimental data as well as to characterize the uncertainties of the input parameters of a chlorination model including a chloride diffusion acceleration factor. The proposed methodology is illustrated with experimental data coming from tests on RC beams subjected to static and cyclic loading before being in contact with a solution containing chloride ions. The characterized parameters are then used to evaluate the effect of these two loading conditions (static and cyclic) on the corrosion initiation time and the corrosion initiation probability. The results obtained indicate that the proposed methodology is capable of integrating loading and chlorination test data for the determination of the probabilistic parameters of a model in a comprehensive way.

scholarly journals Degradation Monitoring in Reinforced Concrete with 3D Localization of Rebar Corrosion and Related Concrete Cracking

2021 ◽  
Vol 11 (15) ◽  
pp. 6772
Author(s):  
Charlotte Van Steen ◽  
Els Verstrynge
Keyword(s):  
Reinforced Concrete ◽  
Degradation Mechanism ◽  
Heterogeneous Material ◽  
Corrosion Damage ◽  
Corrosion Process ◽  
Internal Damage ◽  
Rc Structures ◽  
Degradation Monitoring ◽  
Rebar Corrosion ◽  
Width Measurements

Corrosion of the reinforcement is a major degradation mechanism affecting durability and safety of reinforced concrete (RC) structures. As the corrosion process starts internally, it can take years before visual damage can be noticed on the surface, resulting in an overall degraded condition and leading to large financial costs for maintenance and repair. The acoustic emission (AE) technique enables the continuous monitoring of the progress of internal cracking in a non-invasive way. However, as RC is a heterogeneous material, reliable damage detection and localization remains challenging. This paper presents extensive experimental research aiming at localizing internal damage in RC during the corrosion process. Results of corrosion damage monitoring with AE are presented and validated on three sample scales: small mortar samples (scale 1), RC prisms (scale 2), and RC beams (scale 3). For each scale, the corrosion process was accelerated by imposing a direct current. It is found that the AE technique can detect damage earlier than visual inspection. However, dedicated filtering is necessary to reliably localize AE events. Therefore, AE signals were filtered by a newly developed post-processing protocol which significantly improves the localization results. On the smallest scale, results were confirmed with 3D micro-CT imaging, whereas on scales 2 and 3, results were compared with surface crack width measurements and resulting rebar corrosion levels.

Microemulsion Phase Behavior Observations, Thermodynamic Essentials, Mathematical Simulation

1981 ◽  
Vol 21 (06) ◽  
pp. 747-762 ◽  
Author(s):  
Karl E. Bennett ◽  
Craig H.K. Phelps ◽  
H. Ted Davis ◽  
L.E. Scriven
Keyword(s):  
Experimental Data ◽  
Phase Behavior ◽  
Experimental Studies ◽  
Mathematical Framework ◽  
Alkyl Aryl Sulfonate ◽  
Phase Volume ◽  
Displacement Efficiency ◽  
Alkyl Aryl ◽  
Theoretical Understanding ◽  
Tie Lines

Abstract The phase behavior of microemulsions of brine, hydrocarbon, alcohol, and a pure alkyl aryl sulfonate-sodium 4-(1-heptylnonyl) benzenesulfonate (SHBS or Texas 1) was investigated as a function of the concentration of salt (NaCl, MgCl2, or CaCl2), the hydrocarbon (n-alkanes, octane to hexadecane), the alcohol (butyl and amyl isomers), the concentration of surfactant, and temperature. The phase behavior mimics that of similar systems with the commercial surfactant Witco TRS 10–80. The phase volumes follow published trends, though with exceptions.A mathematical framework is presented for modeling phase behavior in a manner consistent with the thermodynamically required critical tie lines and plait point progressions from the critical endpoints. Hand's scheme for modeling binodals and Pope and Nelson's approach to modeling the evolution of the surfactant-rich third phase are extended to satisfy these requirements.An examination of model-generated progressions of ternary phase diagrams enhances understanding of the experimental data and reveals correlations of relative phase volumes (volume uptakes) with location of the mixing point (overall composition) relative to the height of the three-phase region and the locations of the critical tie lines (critical endpoints and conjugate phases). The correlations account, on thermodynamic grounds, for cases in which the surfactant is present in more than one phase or the phase volumes change discontinuously, both cases being observed in the experimental study. Introduction The phase behavior of a surfactant-based micellar formulation is one of the major factors governing the displacement efficiency of any chemical flooding process employing that formulation. Knowledge of phase behavior is, thus, important for the interpretation of laboratory core floods, the design of flooding processes, and the evaluation of field tests. Phase behavior is connected intimately with other determinants of the flooding process, such as interfacial tension and viscosity. Since the number of equilibrium phases and their volumes and appearances are easier to measure and observe than phase compositions, viscosities, and interfacial tensions, there is great interest in understanding the phase-volume/phase-property relationships. Commercial surfactants, such as Witco TRS 10-80, are sulfonates of crude or partially refined oil. While they seem to be the most economically practicable surfactants for micellar flooding, their behavior, particularly with crude oils and reservoir brines, can be difficult to interpret, the phases varying with time and from batch to batch. Phase behavior studies with a small number of components, in conjunction with a theoretical understanding of phase behavior progressions, can aid in understanding more complex behavior. In particular, one can begin to appreciate which seemingly abnormal experimental observations (e.g., surfactant present in more than one phase or a discontinuity in phase volume trends) are merely features of certain regions of any phase diagram and which are peculiar to the specific crude oil or commercial surfactant used in the study.We report here experimental studies of the phase behavior of microemulsions of a pure sulfonate surfactant (Texas 1), a single normal alkane hydrocarbon, a simple brine, and a small amount of a suitable alcohol as cosurfactant or cosolvent. The controlled variables are hydrocarbon chain length, alcohol, salinity, salt type (NaCl, MgCl2, or CaCl2), surfactant purity, surfactant concentration, and temperature. Many of these experimental data were presented earlier. SPEJ P. 747^

scholarly journals Simulation of olive pits pyrolysis in a rotary kiln plant

2011 ◽  
Vol 15 (1) ◽  
pp. 145-158 ◽  
Author(s):  
Enzo Benanti ◽  
Cesare Freda ◽  
Vincenzo Lorefice ◽  
Giacobbe Braccio ◽  
Vinod Sharma
Keyword(s):  
Experimental Data ◽  
Temperature Profile ◽  
Rotary Kiln ◽  
Southern Italy ◽  
Flow Reactor ◽  
Plug Flow ◽  
Sensitivity Analyses ◽  
Pyrolysis Process ◽  
Simulation Results ◽  
Main Component

This work deals with the simulation of an olive pits fed rotary kiln pyrolysis plant installed in Southern Italy. The pyrolysis process was simulated by commercial software CHEMCAD. The main component of the plant, the pyrolyzer, was modelled by a Plug Flow Reactor in accordance to the kinetic laws. Products distribution and the temperature profile was calculated along reactor's axis. Simulation results have been found to fit well the experimental data of pyrolysis. Moreover, sensitivity analyses were executed to investigate the effect of biomass moisture on the pyrolysis process.

Wavelet Transform Modulus Maxima Decay Lines

2015 ◽  
pp. 48-68
Author(s):  
Andreas Kyprianou ◽  
Andreas Tjirkallis
Keyword(s):  
Experimental Data ◽  
Wavelet Transform ◽  
Damage Detection ◽  
Environmental Conditions ◽  
Simulated Data ◽  
Random Excitation ◽  
Operating Conditions ◽  
Structural Behaviour ◽  
Operational Conditions ◽  
Three Degree Of Freedom

An important task in structural health monitoring (SHM) is that of damage detection under varying environmental and operational conditions. Structures, under varying environmental conditions, change their mass, elasticity and damping properties whereas changing operational conditions cause changes to excitations. A damage detection methodology implemented in these circumstances faces serious challenges since changes to structural behaviour imparted by environmental or operational conditions could be wrongly attributed to damage. The part of a damage detection decision algorithm that removes environmental and operational effects is called normalization. In this chapter a normalization methodology that is based on the similarity between continuous wavelet transform maxima decay lines is presented. This methodology is implemented on both simulated and experimental data. Simulated data were obtained from a three degree of freedom system. Varying environmental conditions were simulated by temperature dependent stiffness parameters and operating conditions by changing the colour of random excitation. Experimental data were obtained from damaged cantilever beams that were subjected to random excitations of different colour and varying temperatures.

Bayesian Model for Evaluating Real-World Adaptation Progress of a Cyber-Physical System

2021 ◽  
pp. 324-343
Author(s):  
Arif Sari ◽  
Joshua Chibuike Sopuru
Keyword(s):  
Work Environment ◽  
Real World ◽  
Environmental Conditions ◽  
Physical System ◽  
Bayesian Model ◽  
Cyber Physical Systems ◽  
Cyber Physical System ◽  
Industrial Activities ◽  
Physical Systems

Cyber-physical systems, also known as CPS, have come to stay. There is no doubt, CPS would one day outnumber humans in industries. How do we evaluate the adaptation progress of these systems considering changing environmental conditions? A failed implementation of a CPS can result to a loss. Since CPSs are designed to automate industrial activities, which are centred on the use of several technologies, collaboration with humans may sometimes be inevitable. CPSs are needed to automate several processes and thus help firms compete favourably within an industry. This chapter focuses on the adaptation of CPS in diverse work environment. Considering the ecosystem of the CPS, the authors present a Bayesian model evaluating the progress of adaptation of a CPS given some known conditions.

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