A plate model for compressive strength prediction of delaminated composites

Composite Structures ◽

10.1016/j.compstruct.2018.11.066 ◽

2019 ◽

Vol 210 ◽

pp. 509-517 ◽

Cited By ~ 3

Author(s):

Rizwan S. Choudhry ◽

Andrew T. Rhead ◽

Mark W.D. Nielsen ◽

Richard Butler

Keyword(s):

Compressive Strength ◽

Strength Prediction ◽

Plate Model

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Research on Improved BP Neural Network Gangue Powder Concrete Compressive Strength Prediction Model

2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC) ◽

10.1109/itaic49862.2020.9339112 ◽

2020 ◽

Author(s):

Shengxiang Ma ◽

Xunxian Shi ◽

Chenglong Yu ◽

Wenjing Wang ◽

Yujie Ren ◽

...

Keyword(s):

Neural Network ◽

Compressive Strength ◽

Prediction Model ◽

Bp Neural Network ◽

Strength Prediction ◽

Concrete Compressive Strength

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Simulation of foamed concrete compressive strength prediction using adaptive neuro-fuzzy inference system optimized by nature-inspired algorithms

Frontiers of Structural and Civil Engineering ◽

10.1007/s11709-020-0684-6 ◽

2021 ◽

Author(s):

Ahmad Sharafati ◽

H. Naderpour ◽

Sinan Q. Salih ◽

E. Onyari ◽

Zaher Mundher Yaseen

Keyword(s):

Compressive Strength ◽

Fuzzy Inference System ◽

Fuzzy Inference ◽

Strength Prediction ◽

Concrete Compressive Strength ◽

Inference System ◽

Neuro Fuzzy ◽

Foamed Concrete ◽

Nature Inspired Algorithms

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Concrete compressive strength prediction modeling utilizing deep learning long short-term memory algorithm for a sustainable environment

Environmental Science and Pollution Research ◽

10.1007/s11356-021-12877-y ◽

2021 ◽

Author(s):

Sarmad Dashti Latif

Keyword(s):

Compressive Strength ◽

Deep Learning ◽

Short Term Memory ◽

Strength Prediction ◽

Concrete Compressive Strength ◽

Prediction Modeling ◽

Short Term ◽

Term Memory ◽

Sustainable Environment ◽

Long Short Term Memory

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Cubic meter compressive strength prediction of concrete

Journal of Wuhan University of Technology-Mater Sci Ed ◽

10.1007/s11595-016-1414-8 ◽

2016 ◽

Vol 31 (3) ◽

pp. 590-593

Author(s):

Zhen Gong ◽

Yimin Zhang ◽

Youjian Hu ◽

Yan Yu ◽

Yanbin Yuan ◽

...

Keyword(s):

Compressive Strength ◽

Strength Prediction

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Point-load test and UPV for compressive strength prediction of recycled coarse aggregate concrete via generalized GMDH-class neural network

Construction and Building Materials ◽

10.1016/j.conbuildmat.2020.122143 ◽

2021 ◽

Vol 276 ◽

pp. 122143

Author(s):

Hossein Razzaghi ◽

Rahmat Madandoust ◽

Hassan Aghabarati

Keyword(s):

Neural Network ◽

Compressive Strength ◽

Coarse Aggregate ◽

Point Load ◽

Load Test ◽

Strength Prediction ◽

Aggregate Concrete ◽

Recycled Coarse Aggregate ◽

Point Load Test

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On the Distribution of Delamination in Composite Structures and Compressive Strength Prediction for Laminates with Embedded Delaminations

Applied Composite Materials ◽

10.1007/s10443-010-9154-y ◽

2010 ◽

Vol 18 (3) ◽

pp. 253-269 ◽

Cited By ~ 12

Author(s):

Fu Huimin ◽

Zhang Yongbo

Keyword(s):

Compressive Strength ◽

Composite Structures ◽

Strength Prediction

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Compressive Strength Prediction of Porous Concrete Using Nondestructive Tests

Journal of Civil Engineering and Architecture ◽

10.17265/1934-7359/2011.12.001 ◽

2011 ◽

Vol 5 (12) ◽

Author(s):

Young Sang Cho ◽

Jeom Han Kim ◽

Sung Uk Hong

Keyword(s):

Compressive Strength ◽

Strength Prediction ◽

Porous Concrete ◽

Nondestructive Tests

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GFRP wrapped concrete column compressive strength prediction through neural network

SN Applied Sciences ◽

10.1007/s42452-020-03753-4 ◽

2020 ◽

Vol 2 (12) ◽

Author(s):

P. Sangeetha ◽

M. Shanmugapriya

Keyword(s):

Neural Network ◽

Compressive Strength ◽

Strength Prediction ◽

Concrete Column

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Study on Compressive Strength Prediction for Steam Curing

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/371/1/012019 ◽

2018 ◽

Vol 371 ◽

pp. 012019

Author(s):

N Nakajima ◽

H Koyama ◽

S Hashimoto ◽

S Date

Keyword(s):

Compressive Strength ◽

Strength Prediction ◽

Steam Curing

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Water-Cement-Density Ratio Law for the 28-Day Compressive Strength Prediction of Cement-Based Materials

Advances in Materials Science and Engineering ◽

10.1155/2020/7302173 ◽

2020 ◽

Vol 2020 ◽

pp. 1-8 ◽

Cited By ~ 2

Author(s):

Siqi Li ◽

Jinbo Yang ◽

Peng Zhang

Keyword(s):

Compressive Strength ◽

Apparent Density ◽

Density Ratio ◽

Strength Prediction ◽

Normal Concrete ◽

Present Contribution ◽

Cement Ratio ◽

Water Cement Ratio ◽

Cement Based Materials ◽

Foamed Concrete

In the present contribution, the water-cement-density ratio law for the standard curing 28-day compressive strength of cement-based materials including grout, normal concrete, ceramsite concrete, and foamed concrete is proposed. The standard curing 28-day compressive strength of different grouts, normal concrete, ceramsite concrete, and foamed concrete was tested. Simulations for Abrams’ law, Bolomey’s formula, and water-cement-density ratio law were carried out and compared. The water-cement-density ratio law illustrates better simulations for the prediction of the 28-day compressive strength of cement-based materials. The water-cement-density ratio law includes both the water-cement ratio and relative apparent density of the cement-based material. Relative apparent density of the cement-based material is an important one of all the factors determining the compressive strength of the cement-based material. The water-cement-density ratio law will be beneficial for the precise and generalized prediction of the 28-day standard curing compressive strength of cement-based materials.

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