Cargando…

Predictive Modelling for Concrete Failure at Anchorages Using Machine Learning Techniques

Anchorage to concrete plays a significant role in various aspects of modern construction. The structural performance of anchors under direct tensile load can lead to failure by concrete cone breakout. Concrete related failure modes are quasi-brittle, and as such, they may develop without prior warni...

Descripción completa

Detalles Bibliográficos
Autores principales:	Spyridis, Panagiotis, Olalusi, Oladimeji B.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2020
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7795158/ https://www.ncbi.nlm.nih.gov/pubmed/33375620 http://dx.doi.org/10.3390/ma14010062

Ejemplares similares

Multilateral Assessment of Anchorage Bond Characteristics in Steel Fibre Reinforced Concrete
por: Spyridis, Panagiotis, et al.
Publicado: (2022)

Analytical Model for Bond Behavior Prediction of CFRP-Concrete Joints with End Anchorage
por: Dong, Kun, et al.
Publicado: (2021)

Splitting tensile strength prediction of Metakaolin concrete using machine learning techniques
por: Li, Qiang, et al.
Publicado: (2023)

Tensile Performance of Headed Anchors in Steel Fiber Reinforced and Conventional Concrete in Uncracked and Cracked State
por: Spyridis, Panagiotis, et al.
Publicado: (2022)

Machine Learning Techniques in Concrete Mix Design
por: Ziolkowski, Patryk, et al.
Publicado: (2019)

Self-Compacting High-Strength Textile-Reinforced Concrete Using Sea Sand and Sea Water
por: Kryzhanovskyi, Vitalii, et al.
Publicado: (2023)

Experimental Findings and Validation on Torsional Behaviour of Fibre-Reinforced Concrete Beams: A Review
por: Awoyera, Paul Oluwaseun, et al.
Publicado: (2022)

Unboxing machine learning models for concrete strength prediction using XAI
por: Elhishi, Sara, et al.
Publicado: (2023)

Smart PZT-Embedded Sensors for Impedance Monitoring in Prestressed Concrete Anchorage
por: Pham, Quang-Quang, et al.
Publicado: (2021)

Modeling of Mechanical Properties of Silica Fume-Based Green Concrete Using Machine Learning Techniques
por: Nafees, Afnan, et al.
Publicado: (2021)

Prediction of the Mechanical Properties of Basalt Fiber Reinforced High-Performance Concrete Using Machine Learning Techniques
por: Hasanzadeh, Ali, et al.
Publicado: (2022)

Predicting Hemodynamic Failure Development in PICU Using Machine Learning Techniques
por: Comoretto, Rosanna I., et al.
Publicado: (2021)

Machine Learning Prediction Models to Evaluate the Strength of Recycled Aggregate Concrete
por: Yuan, Xiongzhou, et al.
Publicado: (2022)

Development of Bonded/Riveted Steel Anchorages of Prestressed CFRP Strips for Concrete Strengthening
por: Piątek, Bartosz, et al.
Publicado: (2020)

GFRP Bars Anchorage Resistance in a GFRP-Reinforced Concrete Bridge Barrier
por: Rostami, Michael, et al.
Publicado: (2019)

Application of Machine Learning Techniques for Predicting Compressive, Splitting Tensile, and Flexural Strengths of Concrete with Metakaolin
por: Shah, Hammad Ahmed, et al.
Publicado: (2022)

Prediction of Healing Performance of Autogenous Healing Concrete Using Machine Learning
por: Huang, Xu, et al.
Publicado: (2021)

Machine Learning Techniques for Evaluating Concrete Strength with Waste Marble Powder
por: Sharma, Nitisha, et al.
Publicado: (2022)

On the Use of Machine Learning Models for Prediction of Compressive Strength of Concrete: Influence of Dimensionality Reduction on the Model Performance
por: Wan, Zhi, et al.
Publicado: (2021)

Performance Assessment of the Post-Tensioned Anchorage Zone Using High-Strength Concrete Considering Confinement Effect
por: Lee, Jun Suk, et al.
Publicado: (2021)

Optimal Localization of Smart Aggregate Sensor for Concrete Damage Monitoring in PSC Anchorage Zone
por: Pham, Quang-Quang, et al.
Publicado: (2021)

Application of Novel Machine Learning Techniques for Predicting the Surface Chloride Concentration in Concrete Containing Waste Material
por: Ahmad, Ayaz, et al.
Publicado: (2021)

Analysis of Shear Model for Steel-Fiber-Reinforced High-Strength Concrete Corbels with Welded-Anchorage Longitudinal Reinforcement
por: Li, Shu-Shan, et al.
Publicado: (2023)

Prediction of Geopolymer Concrete Compressive Strength Using Novel Machine Learning Algorithms
por: Ahmad, Ayaz, et al.
Publicado: (2021)

Prediction of Compressive Strength of Partially Saturated Concrete Using Machine Learning Methods
por: Candelaria, Ma. Doreen Esplana, et al.
Publicado: (2022)

Computation of High-Performance Concrete Compressive Strength Using Standalone and Ensembled Machine Learning Techniques
por: Xu, Yue, et al.
Publicado: (2021)

High-Performance Concrete Strength Prediction Based on Machine Learning
por: Liu, Yanning
Publicado: (2022)

Comparison of Machine Learning Techniques for Prediction of Hospitalization in Heart Failure Patients
por: Lorenzoni, Giulia, et al.
Publicado: (2019)

Predictive modeling for peri-implantitis by using machine learning techniques
por: Mameno, Tomoaki, et al.
Publicado: (2021)

Comprehensive Machine Learning-Based Model for Predicting Compressive Strength of Ready-Mix Concrete
por: Xu, Jiajia, et al.
Publicado: (2021)

Prediction of Mechanical Properties of Fly-Ash/Slag-Based Geopolymer Concrete Using Ensemble and Non-Ensemble Machine-Learning Techniques
por: Amin, Muhammad Nasir, et al.
Publicado: (2022)

Soft computing techniques for predicting the properties of raw rice husk concrete bricks using regression-based machine learning approaches
por: Ganasen, Nakkeeran, et al.
Publicado: (2023)

Predictive models for charitable giving using machine learning techniques
por: Farrokhvar, Leily, et al.
Publicado: (2018)

Predictive models for diabetes mellitus using machine learning techniques
por: Lai, Hang, et al.
Publicado: (2019)

An Innovative Smart Concrete Anchorage with Self-Stress Sensing Capacity of Prestressing Stress of PS Tendon
por: Lee, Seon Yeol, et al.
Publicado: (2021)

Mixture Optimization of Recycled Aggregate Concrete Using Hybrid Machine Learning Model
por: Nunez, Itzel, et al.
Publicado: (2020)

Modeling of Compressive Strength of Self-Compacting Rubberized Concrete Using Machine Learning
por: Kovačević, Miljan, et al.
Publicado: (2021)

Predicting the Mechanical Properties of RCA-Based Concrete Using Supervised Machine Learning Algorithms
por: Shang, Meijun, et al.
Publicado: (2022)

A Predictive Mimicker of Fracture Behavior in Fiber Reinforced Concrete Using Machine Learning
por: Khokhar, Sikandar Ali, et al.
Publicado: (2021)

Compressive Strength of Steel Fiber-Reinforced Concrete Employing Supervised Machine Learning Techniques
por: Li, Yongjian, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_rhiauk4gq9lmt27vqt7rlmm6gh