scholarly journals Probabilistic estimation of flexural loading capacity of existing RC structures based on observational corrosion-induced crack width distribution using machine learning

2021 ◽  
Vol 91 ◽  
pp. 102098
Author(s):  
Mingyang Zhang ◽  
Mitsuyoshi Akiyama ◽  
Mina Shintani ◽  
Jiyu Xin ◽  
Dan M. Frangopol
Keyword(s):  
Machine Learning ◽  
Crack Width ◽  
Loading Capacity ◽  
Rc Structures ◽  
Probabilistic Estimation ◽  
Flexural Loading ◽  
Width Distribution

Influence of Corrosion Distribution on Estimation of Flexural Loading Capacity of Corroded RC Beams

2017 ◽  
Vol 12 (3) ◽  
pp. 478-486
Author(s):  
Takashi Yamamoto ◽  
◽  
Satoshi Takaya ◽  
Toyo Miyagawa ◽  
Keyword(s):  
Estimation Method ◽  
Rc Beam ◽  
Loading Capacity ◽  
Kriging Method ◽  
Flexural Capacity ◽  
Cross Sectional ◽  
Flexural Loading ◽  
Load Carrying ◽  
Steel Bars ◽  
Inspection Data

A load carrying capacity of the reinforced concrete (RC) member is degraded by the corrosion of reinforcing steel bars due to chloride ion ingress. A lot of researches on the effect of corrosion in the longitudinal tensile reinforcing steel bars on the load carrying behavior have been available up to now. Accurate and quantitative estimation of capacity, however, is often difficult, because of the non-uniformity of corrosion in the member. Thus, a relationship between the spatial distribution of corrosion in the reinforcement including its scatter and the flexural loading capacity of RC member with such distribution of corrosion should be clarified so that the flexural capacity of corroded RC member can be estimated accurately. On the other hand, in case of the practical RC member under the corrosive environment, it should be considered that the flexural capacity often have to be derived from not a large number of inspection data on cross sectional areas of corroded reinforcements. So, in this study, a flexural loading test was performed by using RC beam specimens with the corroded tensile reinforcements provided the distribution of sectional areas. An estimation method of the flexural capacity of corroded RC beam was also shown, considering the distribution and its scatter in sectional areas of corroded reinforcements under the limited inspection data. Furthermore, the estimation of the longitudinal distribution of the cross sectional area of corroded reinforcement was performed by the spatial interpolation using Kriging method. Test results showed the yield and maximum load capacity in the corroded RC beam decreased as the corrosion rate increased. The failure mode of rupture in the reinforcement was shown in the large corrosion. The proposed estimation method was able to lead the safe evaluation of those experimental flexural capacities, determining the appropriate longitudinal characteristic value of the cross sectional area of corroded reinforcement. The flexural capacity can be also safely calculated using the characteristic value of diameters estimated by the corrosion crack width on the surface of the concrete, while the ratio of the experimental flexural capacity to the estimated one decreased as the corrosion loss increased. The distribution of bar diameters in the corroded reinforcement was able to be roughly estimated by using Kriging method. However, it was suggested that the measurement points close to the minimum bar diameter should be included to estimate the flexural capacity on the safe side.

scholarly journals Evaluation on crack width required to repair rc structures.

1990 ◽  
pp. 201-209
Author(s):  
Manabu MATSUSHIMA ◽  
Hiroshi SEKI ◽  
Yuichi KANEKO ◽  
Kunihito MATSUI
Keyword(s):  
Crack Width ◽  
Rc Structures

scholarly journals Probabilistic estimation of software development effort techniques using machine learning

2018 ◽  
Vol 7 (2.7) ◽  
pp. 1085
Author(s):  
Dr P. Vidya Sagar ◽  
Dr Nageswara Rao Moparthi ◽  
Venkata Naresh Mandhala
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Artificial Neural Network ◽  
Support Vector Machine ◽  
Support Vector ◽  
Development Effort ◽  
Probabilistic Estimation ◽  
Software Development Effort ◽  
Artificial Neural Network Ann ◽  
High Level

Precisely assessing programming exertion is likely the greatest test confronting for programming engineers. Assessments done at the prop-osition arrange has high level of incorrectness, where prerequisites for the degree are not characterized to the most reduced subtle elements, but rather as the venture advances and necessities are explained, exactness and certainty on appraise increments. It is vital to pick the correct programming exertion estimation systems for the forecast of programming exertion. Artificial Neural Network (ANN) and Support Vector Machine (SVM) have been utilized on guarantee dataset for forecast of programming exertion in this article.  

scholarly journals Machine learning for predicting long-term deflections in reinforce concrete flexural structures

2020 ◽  
Vol 7 (1) ◽  
pp. 95-106 ◽  
Author(s):  
Anh-Duc Pham ◽  
Ngoc-Tri Ngo ◽  
Thi-Kha Nguyen
Keyword(s):  
Machine Learning ◽  
Good Accuracy ◽  
Absolute Error ◽  
Reinforce Concrete ◽  
Performance Comparison ◽  
Percentage Error ◽  
Empirical Methods ◽  
Rc Structures ◽  
Fold Cross Validation

Abstract Prediction of deflections of reinforced concrete (RC) flexural structures is vital to evaluate the workability and safety of structures during its life cycle. Empirical methods are limited to predict a long-term deflection of RC structures because they are difficult to consider all influencing factors. This study presents data-driven machine learning (ML) models to early predict the long-term deflections in RC structures. An experimental dataset was used to build and evaluate single and ensemble ML models. The models were trained and tested using the stratified 10-fold cross-validation algorithm. Analytical results revealed that the ML model is effective in predicting the deflection of RC structures with good accuracy of 0.972 in correlation coefficient (R), 8.190 mm in root mean square error (RMSE), 4.597 mm in mean absolute error (MAE), and 16.749% in mean absolute percentage error (MAPE). In performance comparison against with empirical methods, the prediction accuracy of the ML model improved significantly up to 66.41% in the RMSE and up to 82.04% in the MAE. As a contribution, this study proposed the effective ML model to facilitate designers in early forecasting long-term deflections in RC structures and evaluating their long-term serviceability and safety.

Geopolymer ferrocement panels under flexural loading

2015 ◽  
Vol 22 (3) ◽  
pp. 331-341 ◽  
Author(s):  
Mohana Rajendran ◽  
Nagan Soundarapandian
Keyword(s):  
Experimental Investigation ◽  
Alkaline Solution ◽  
Crack Width ◽  
Ultimate Load ◽  
Wire Mesh ◽  
Flexural Behavior ◽  
Composite Panels ◽  
Environmental Friendly ◽  
Flexural Loading ◽  
Load Carrying

AbstractEfforts are needed to develop innovative and environmental friendly materials in order to reduce greenhouse gas emissions. An experimental investigation on the flexural behavior of thin cementless composite panels reinforced with welded rectangular wire mesh and chicken mesh with varying number of mesh layers as well as varying concentration of alkaline solution is presented. A total of 30 panels have been tested under flexural loading. The size of the panel is 1000 mm (length)×200 mm (width)×25/35 mm (thickness). The parameters studied in this investigation include varying the concentration of NaOH (8, 10, 12, 14 m) and thickness of composite panels. In this work, cement is replaced by geopolymer mix to bind the ferrocement skeletal framework and its flexural behavior is studied. It is concluded that the first crack and ultimate loads increase with the increase in the thickness of the element and the concentration of alkaline solution. From the studies, it is observed that the load-carrying capacities, energy absorption, and deformation at ultimate load are high in the case of geopolymer ferrocement element. Further, it is observed that there is reduction in crack width, and increase in number of cracks in the case of geopolymer ferrocement indicates delay in crack growth.

scholarly journals Crack Width and Load-Carrying Capacity of RC Elements Strengthened with FRP

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Justas Slaitas ◽  
Mykolas Daugevičius ◽  
Juozas Valivonis ◽  
Tatjana Grigorjeva
Keyword(s):  
Crack Propagation ◽  
Carrying Capacity ◽  
Crack Width ◽  
Crack Depth ◽  
Experimental Program ◽  
Mechanics Of Solids ◽  
Crack Model ◽  
Load Carrying Capacity ◽  
Rc Structures ◽  
Load Carrying

The present study focuses on a prediction of crack width and load-carrying capacity of flexural reinforced concrete (RC) elements strengthened with fibre-reinforced polymer (FRP) reinforcements. Most studies on cracking phenomena of FRP-strengthened RC structures are directed to empirical corrections of crack-spacing formula given by design norms. Contrary to the design norms, a crack model presented in this paper is based on fracture mechanics of solids and is applied for direct calculation of flexural crack parameters. At the ultimate stage of crack propagation, the load-carrying capacity of the element is achieved; therefore, it is assumed that the load-carrying capacity can be estimated according to the ultimate crack depth (directly measuring concrete’s compressive zone height). An experimental program is presented to verify the accuracy of the proposed model, taking into account anchorage and initial strain effects. The proposed analytical crack model can be used for more precise predictions of flexural crack propagation and load-carrying capacity.

scholarly journals Applicability of existing crack controlling criteria for structures with large concrete cover thickness: Review.

2020 ◽  
Author(s):  
Chavin Naotunna ◽  
S.M Samindi M.K Samarakoon ◽  
Kjell Fosså
Keyword(s):  
Crack Width ◽  
Concrete Cover ◽  
Design Stage ◽  
Rc Structures ◽  
Model Code ◽  
Design Life ◽  
Service Load ◽  
Model Code 2010 ◽  
Cover Thickness ◽  
Calculation Models

Adverse effects from the cracks in Reinforced Concrete (RC) structures are controlled at the structural design stage. Cracks due to service load are controlled by limiting the ‘calculated crack width’ to a ‘maximum allowable crack width’. With the understanding of social and economic advantages of long design life structures, there is a trend of constructing structures up to 300 years of design life. To enhance durability, such structures require relatively large concrete cover thickness. The existing ‘crack width calculation models’, have to be validated before using on such large cover structures. The predictions of crack width calculation models in Eurocode 2, Model Code 2010, Japanese Code, American Code and British code were compared with the results of recent experiments with large cover specimens. It could identify that the aforementioned models have to be improved to predict the crack widths of large cover structures. The necessary improvements of each model have been identified. Next, a literature survey was conducted to check the applicability of the existing ‘allowable crack width limits’, for the structures with large concrete covers. To effectively use the existing allowable limits on such structures, the necessary improvements and future works have been identified considering the durability, aesthetic and tightness criteria.

scholarly journals Forensic to the Reinforced Concrete (RC) Structures at Library

2020 ◽  
Vol 19 (1) ◽  
pp. 6-14
Author(s):  
Tang Hing Kwong ◽  
Rudy Tawie ◽  
Siti Rozana Romali
Keyword(s):  
Reinforced Concrete ◽  
Crack Width ◽  
Concrete Strength ◽  
Reinforced Concrete Beam ◽  
Steel Reinforcement ◽  
Reinforced Concrete Structure ◽  
Rebound Hammer ◽  
Rc Structures ◽  
Three Samples ◽  
Eurocode 2

This Forensic project has been proposed to investigate the reinforced concrete structure defect at library. There were found 65 points cracks and 20 points spalling in library such as only at reinforced concrete beam and slab part in first floor. The total of cracks which crack width less than 0.25 mm is 63 points and the crack width between 0.25 mm to 5.00 mm is 2 points only. These cracks had categorized as fine cracks because the crack width not more than 5 mm. There was 21 samples Rebound Hammer test was random measured the existing concrete compressive strength of critical structures which six samples at beams, six samples at slabs, six samples at columns and three samples at staircase in library. The Rebound Hammer test shown that average mid-point strength at beam is 33 N/mm2, slab is 25 N/mm², column is 38 N/mm2 and staircase is 37 N/mm2 . Based on the Eurocode 2, the minimum grade concrete required is 25N/mm2 to do the design for reinforced concrete structures, which all the existing concrete strength were achieved the minimum concrete strength. Finally, the Orion software are used to analysis and determine the size of steel reinforcement, the design found the required bar size of steel reinforcement at the middle span or continuous support is 2T16 & 2T25 or 2T20 & 2T25 but the existing steel reinforcement is 2T12 and 2T20 which the existing steel reinforcement could not be sustained the big loading that applied on the library.

scholarly journals Development of Crack Width Prediction Models for RC Beam-Column Joint Subjected to Lateral Cyclic Loading Using Machine Learning

2021 ◽  
Vol 11 (16) ◽  
pp. 7700
Author(s):  
Reventheran Ganasan ◽  
Chee Ghuan Tan ◽  
Zainah Ibrahim ◽  
Fadzli Mohamed Nazri ◽  
Muhammad M. Sherif ◽  
...  
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Cyclic Loading ◽  
Crack Width ◽  
Prediction Models ◽  
Design Parameters ◽  
Rc Beam ◽  
Performance Indices ◽  
Column Joint ◽  
And Performance

In recent years, researchers have investigated the development of artificial neural networks (ANN) and finite element models (FEM) for predicting crack propagation in reinforced concrete (RC) members. However, most of the developed prediction models have been limited to focus on individual isolated RC members without considering the interaction of members in a structure subjected to hazard loads, due to earthquake and wind. This research develops models to predict the evolution of the cracks in the RC beam-column joint (BCJ) region. The RC beam-column joint is subjected to lateral cyclic loading. Four machine learning models are developed using Rapidminer to predict the crack width experienced by seven RC beam-column joints. The design parameters associated with RC beam-column joints and lateral cyclic loadings in terms of drift ratio are used as inputs. Several prediction models are developed, and the highest performing neural networks are selected, refined, and optimized using the various split data ratios, number of inputs, and performance indices. The error in predicting the experimental crack width is used as a performance index.

scholarly journals Mechanical Performance and Chloride Diffusivity of Cracked RC Specimens Exposed to Freeze-Thaw Cycles and Intermittent Immersion in Seawater

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Bei Shen ◽  
Yinghua Ye ◽  
Bo Diao ◽  
Xiaoning Zheng
Keyword(s):  
Crack Width ◽  
Ultimate Load ◽  
Mechanical Performance ◽  
Exposure Period ◽  
Chloride Ingress ◽  
Rc Structures ◽  
Yield Load ◽  
Compression Load ◽  
Freeze Thaw ◽  
Deicing Salts

The effects of crack width on chloride ingress and mechanical behavior of reinforced concrete (RC) specimens were experimentally studied after exposure to 300 cycles of freeze-thaw and seawater immersion (75 times). Cracks were induced prior to exposure by an eccentric compression load which was sustained until the end of the exposure period. The maximum cracks widths induced in the four column specimens were 0, 0.06, 0.11, and 0.15 mm, respectively. Results show that when the crack width was less than 0.06 mm, the effect of cracks on chloride ingress could be neglected. However, when the crack width was more than 0.11 mm, chloride ingress was accelerated. Results of static loading tests show that both yield load and ultimate load of RC columns decreased as crack width increased. When the crack width was 0.15 mm, yield load and ultimate load of RC column specimen decreased by 17.0% and 18.9%, respectively, compared to a specimen without cracks. It was concluded that crack width significantly promoted local chloride ingress and mechanical performance degradation of RC structures in cold coastal regions or exposed to deicing salts.

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