Zobrazeno 1 - 10
of 124
pro vyhledávání: '"M. Sivaraja"'
Autor:
J. Rajprasad, P. Priya Rachel, S. Arulselvan, D. Arul, G. Ramesh Kumar, H. J. Pallavi, M. Sivaraja, Vinay Kumar Singh, Getachew Gebreamlak
Publikováno v:
Advances in Materials Science and Engineering, Vol 2023 (2023)
The paper proposes a deep hybrid forest regression-based modeling method for measuring the compressive strength (CS) of concrete. Then, the reduced feature vector is used as input to train multiple subforest models (SFM), the predicted values are sel
Externí odkaz:
https://doaj.org/article/71ceb3e27bd9473eac48c9fbd29199b2
Publikováno v:
Brazilian Archives of Biology and Technology, Vol 59, Iss spe2
ABSTRACT This paper presents the experimental results of a reinforced concrete beams (RC) strengthened with internal steel fibers (SF) and external glass fiber reinforced polymer laminates (GFRP). The research work studied the load carrying capacity,
Externí odkaz:
https://doaj.org/article/8dec7deb39ba41e9a934196febdfd130
Autor:
M.M. Saravanan, M. Sivaraja
Publikováno v:
Brazilian Archives of Biology and Technology, Vol 59, Iss spe2
ABSTRACT Construction industry is in need of lump sum quantities of materials which has increased both their demand and price. The use of large quantities of cement leads to increasing CO2 emission and as a consequence, the greenhouse effect. Consump
Externí odkaz:
https://doaj.org/article/7dc6e9dba62346339908ee2902893fca
Autor:
Rampradheep G S, M. Sivaraja
Publikováno v:
Brazilian Archives of Biology and Technology, Vol 59, Iss spe2
ABSTRACT Self-Compacting Concrete (SCC) flows around obstructions by its self-weight to fill entirely and self-consolidate (without any need for vibration), without any part of disconnection and chunking. The eradication of the need for consolidation
Externí odkaz:
https://doaj.org/article/f4d8cdcb07f34d71b373721fc5bfec8d
Autor:
R. Sivakumar, B. R. Senthil Kumar, G. Gopalarama Subramaniyan, M. Sivaraja, M. P. Natarajan, Pravin P. Patil, S. Kaliappan, K. P. Yuvaraj, Kassie Jemberu Abebe
Publikováno v:
Journal of Nanomaterials. 2022:1-9
The aim of this study is to evaluate the wear and micro hardness of a Ti-6Al-4V matrix reinforced with 10% and 15% tungsten carbide particle (WCp) composite manufactured using the squeeze casting process. Optical microscopy is used to determine the m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97ee4e83fb90cff05b6ae0ed21e33407
https://doi.org/10.1155/2022/6381265
https://doi.org/10.1155/2022/6381265
Akademický článek
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Autor:
D. Satishkumar, M. Sivaraja
In a world where the relentless force of natural and man-made disasters threatens societies, the need for effective disaster management has never been more critical. Predicting Natural Disasters With AI and Machine Learning addresses the challenges o
Autor:
D. Satishkumar, M. Sivaraja
In manufacturing, entrenched challenges like costly maintenance, operational inefficiencies, and product defects loom large, casting shadows over industry progress. Despite the promise of Industry 4.0 and the proliferation of data-driven technologies
Autor:
D. Satishkumar, M. Sivaraja
In a world where natural disasters wreak havoc with increasing frequency and severity, the need for accurate prediction and effective management has never been more critical. From earthquakes shattering communities to floods submerging vast regions,
Autor:
D. Satishkumar, M. Sivaraja
In the dynamic world of manufacturing, the industry has grappled with ongoing issues such as expensive machine maintenance, operational inefficiencies, and the production of defective products. The need for informed decision-making to maintain qualit