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Gomasa Ramesh

Assistant Professor

SR University

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Research Interests

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Professors in Structural Engineering

Articles (12)

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2023

Collaborators (6)

Ye Li

Lecturer

University of Southampton

UNITED KINGDOM

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Ilda Tole

University of Bath

UNITED KINGDOM

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Diego Jesus De Souza

Technical University of Denmark

DENMARK

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Wolfgang Kunther

Associate Professor at Technical University of Denmark

Technical University of Denmark

DENMARK

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Visalakshi Talakokula

Professor-in-charge

Mahindra University

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Sri Kalyana Rama Jyosyula

Assistant Professor

Mahindra University

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Gomasa Ramesh

Research Interests

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Articles (12)

Durability monitoring of blended concrete systems under acid and sulphate exposure environment using embedded piezo sensor: an experimental and statistical investigation

Monitoring Crack Initiation and Propagation of Plain Concrete with Natural Mineral Admixture and Fibers Using Piezoelectric Sensor

Non-destructive Detection of Bond Slip Failure in Fiber-Reinforced Concrete Using Piezo Sensors

Piezo Sensor-Based Detection of Damage in Fiber-Infused Epoxy Bamboo Composites

Sulfate attack testing approaches from concrete to cement paste

Strength monitoring and prediction of blended concrete systems from very early to delayed curing age using embedded piezo sensor data: An experimental and machine learning approach

Chloride-induced degradation in blended concrete systems: A comparative study under ideal and combined exposure conditions using embedded piezo sensors

Corrigendum to “Integrating electro-mechanical impedance data with machine learning for damage detection and classification of blended concrete systems” [Constr. Build. Mater. 445 (2024), 137725](S0950061824028678)(10.1016/j.conbuildmat.2024.137725)

EMI-based damage prediction of blended concrete under sulphuric acid exposure using ML and ANN models

Integrating electro-mechanical impedance data with machine learning for damage detection and classification of blended concrete systems

Non-destructive Damage Identification of Blended Concrete Systems Using Embedded Piezo Sensors

A review on health monitoring of concrete structures using embedded piezoelectric sensor

Collaborators (6)

Ye Li

Ilda Tole

Diego Jesus De Souza

Wolfgang Kunther

Visalakshi Talakokula

Sri Kalyana Rama Jyosyula

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