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Data driven models for compressive strength prediction of concrete at high temperatures

Mahmood AKBARI, Vahid JAFARI DELIGANI

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 2,   Pages 311-321 doi: 10.1007/s11709-019-0593-8

Abstract: nearest neighbor models based on collection of 207 laboratory tests, are investigated for compressive strengthprediction of concrete at high temperature.standard and demonstrate the suitability of using the data driven models to predict the compressive strength

Keywords： data driven model     compressive strength     concrete     high temperature    

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Damage propagation and strength prediction of a single-lap interference-fit laminate structure

Peng ZOU, Xiangming CHEN, Hao CHEN, Guanhua XU

Frontiers of Mechanical Engineering 2020, Volume 15, Issue 4,   Pages 558-570 doi: 10.1007/s11465-020-0591-5

Abstract: interference fit of a single-lap laminated structure to reveal the damage propagation mechanism and strengthA typical single-lap statically loading experiment was performed, and a finite element damage prediction

Keywords： single-lap     interference fit     secondary bending moment     damage mechanism     bearing strength    

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Unconfined compressive strength prediction of soils stabilized using artificial neural networks and support

Alireza TABARSA, Nima LATIFI, Abdolreza OSOULI, Younes BAGHERI

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 2,   Pages 520-536 doi: 10.1007/s11709-021-0689-9

Abstract: This study aims to improve the unconfined compressive strength of soils using additives as well as bypredicting the strength behavior of stabilized soils using two artificial-intelligence-based models.To predict the results of unconfined compressive strength tests conducted on soils, a comprehensive laboratoryThe suggested models predicted the unconfined compressive strength of soils accurately and can be introducedThis study demonstrates the better performance of support vector machines in predicting the strength

Keywords： unconfined compressive strength     artificial neural network     support vector machine     predictive models     regression    

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Compressive strength prediction and optimization design of sustainable concrete based on squirrel search

Frontiers of Structural and Civil Engineering   Pages 1310-1325 doi: 10.1007/s11709-023-0997-3

Abstract: The complex relationship between influential factors and concrete compressive strength makes the predictionand estimation of compressive strength difficult.with extreme gradient boosting (XGB) to predict the compressive strength of green concrete based onThe intelligent prediction models were assessed using the root mean square error (RMSE), coefficientThe remaining five prediction methods yield promising results.

Keywords： sustainable concrete     fly ash     slay     extreme gradient boosting technique     squirrel search algorithm     parametric analysis    

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Multiple linear regression, artificial neural network, and fuzzy logic prediction of 28 days compressivestrength of concrete

Faezehossadat KHADEMI,Mahmoud AKBARI,Sayed Mohammadmehdi JAMAL,Mehdi NIKOO

Frontiers of Structural and Civil Engineering 2017, Volume 11, Issue 1,   Pages 90-99 doi: 10.1007/s11709-016-0363-9

Abstract: Evaluating the in situ concrete compressive strength by means of cores cut from hardened concrete isacknowledged as the most ordinary method, however, it is very difficult to predict the compressive strengthtrained, and tested within the Matlab programming environment for predicting the 28 days compressive strengthand resulted in the fact that ANN and ANFIS models enables us to reliably evaluate the compressive strengthprediction are carried out.

Keywords： concrete     28 days compressive strength     multiple linear regression     artificial neural network     ANFIS     sensitivity    

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Empirical models and design codes in prediction of modulus of elasticity of concrete

Behnam VAKHSHOURI, Shami NEJADI

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 1,   Pages 38-48 doi: 10.1007/s11709-018-0479-1

Abstract: It represents the stress-strain relationship in the elastic range and is used in the prediction of concreteincludes: (a) evaluation and comparison of the existing analytical models to estimating the MOE in normal strengthaddition, a wide range of experimental databases and empirical models to estimate the MOE from compressive strength

Keywords： modulus of elasticity     normal strength normal weight concrete     empirical models     design codes     compressivestrength     density    

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Simulation of foamed concrete compressive strength prediction using adaptive neuro-fuzzy inference system

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 1,   Pages 61-79 doi: 10.1007/s11709-020-0684-6

Abstract: Concrete compressive strength prediction is an essential process for material design and sustainabilityANFIS–differential evolution (DE), and ANFIS–genetic algorithm to predict the foamed concrete compressive strengthANFIS–PSO– (C–O) yielded the best accurate prediction of compressive strength with an MP value of 0.96

Keywords： foamed concrete     adaptive neuro fuzzy inference system     nature-inspired algorithms     prediction of compressivestrength    

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Determination of shear strength of steel fiber RC beams: application of data-intelligence models

Abeer A. AL-MUSAWI

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 3,   Pages 667-673 doi: 10.1007/s11709-018-0504-4

Abstract: Accurate prediction of shear strength of structural engineering components can yield a magnificent informationHence, various input attributes are constructed to model the shear strength “as a targeted variable”.ratio ( ), while the shear strength ( ) is the output of the matrix.results obtained indicated that the hybrid predictive model of ANN-PSO can be used efficiently in the predictionof the shear strength of fiber reinforced concrete beams.

Keywords： hybrid intelligence model     shear strength     prediction     steel fiber reinforced concrete    

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Influence of accelerated curing on the compressive strength of polymer-modified concrete

Izhar AHMAD; Kashif Ali KHAN; Tahir AHMAD; Muhammad ALAM; Muhammad Tariq BASHIR

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 5,   Pages 589-599 doi: 10.1007/s11709-022-0789-1

Abstract: Furthermore, in designing concrete structures, compressive strength is the most significant of all parametersWhile 3-d and 7-d compressive strength reflects the strengths at early phases, the ultimate strengthThe compressive strength of EVA-modified concrete was studied by incorporating various concentrationsAn accelerated compressive strength at 3.5 hours was considered as a reference strength on the basisBased on the results of compressive strength test, it was concluded that the strength of EVA-modified

Keywords： compressive strength prediction     polymer-modified concrete     linear regression fit     early age strength    

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Novel hybrid models of ANFIS and metaheuristic optimizations (SCE and ABC) for prediction of compressivestrength of concrete using rebound hammer field test

Dung Quang VU; Fazal E. JALAL; Mudassir IQBAL; Dam Duc NGUYEN; Duong Kien TRONG; Indra PRAKASH; Binh Thai PHAM

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 8,   Pages 1003-1016 doi: 10.1007/s11709-022-0846-9

Abstract: These were used to predict compressive strength (Cs) of concrete relating to thirteen concrete-strengthreflected better convergence of the results and better performance compared to that of ANFIS-SCE in the predictionThus, the ANFIS-ABC model can be used for the quick and accurate estimation of compressive strength of

Keywords： shuffled complex evolution     artificial bee colony     ANFIS     concrete     compressive strength     Vietnam    

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Prediction model for residual strength of stiffened panels with multiple site damage based on artificial

Yang Maosheng,Chen Yueliang,Yu Dazhao

Strategic Study of CAE 2008, Volume 10, Issue 5,   Pages 46-50

Abstract:

A prediction model for residual strength of stiffened panels with multipleThe results show that the residual strength decreases linearly as the half-crack length of lead crack

Keywords： neural network     multiple site damage     stiffened panel     residual strength    

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Evaluating the material strength from fracture angle under uniaxial loading

Jitang FAN

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 2,   Pages 288-293 doi: 10.1007/s11709-018-0480-8

Abstract: The most common experimental methods of measuring material strength are the uniaxial compressive andCompressive strength is higher than tensile strength for a material.In this work, a unified relation of material strength under uniaxial compression and tension is developedThis constitutive relation is quantitatively illustrated by a function for analyzing the material strengthIt is full of interest to give a scientific illustration for designing the high-strength materials and

Keywords： strength     fracture     mechanics    

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The effects of interfacial strength on fractured microcapsule

Luthfi Muhammad MAULUDIN, Chahmi OUCIF

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 2,   Pages 353-363 doi: 10.1007/s11709-018-0469-3

Abstract: The effects of interfacial strength on fractured microcapsule are investigated numerically.attention is given to the effects of cohesive fracture on the microcapsule interface, namely fracture strengthmicrocapsule, the load carrying capacity of self-healing material under tension increases as interfacial strengthIn addition, given the fixed fracture strength of the interface of microcapsule shell, the higher the

Keywords： interfacial strength     cohesive elements     microcapsule     core-shell thickness ratio     fracture properties    

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Effect of loading rate on shear strength parameters of mechanically and biologically treated waste

Frontiers of Environmental Science & Engineering 2022, Volume 16, Issue 12, doi: 10.1007/s11783-022-1595-7

Abstract:

● Mechanical behavior of MBT waste affected by loading rate was investigated.

Keywords： Mechanically and biologically treated waste     Landfill     Triaxial test     Loading rate     Axial strain     Shear strength    

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The strength–dilatancy characteristics embraced in hypoplasticity

Zhongzhi FU, Sihong LIU, Zijian WANG

Frontiers of Structural and Civil Engineering 2013, Volume 7, Issue 2,   Pages 178-187 doi: 10.1007/s11709-013-0191-0

Abstract: The strength-dilatancy characteristics of frictional materials embraced in the hypoplastic model proposedThe flow rule, the failure state surface equation and the strength-dilatancy relationship embraced inThe performance of the two hypoplastic models in reproducing the relationship between the peak strengthNumerical investigations show that the performance in reproducing the strength-dilatancy relationship

Keywords： strength     dilatancy     hypoplasticity     frictional materials    

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Title Author Date Type Operation

Data driven models for compressive strength prediction of concrete at high temperatures

Mahmood AKBARI, Vahid JAFARI DELIGANI

Journal Article

Damage propagation and strength prediction of a single-lap interference-fit laminate structure

Peng ZOU, Xiangming CHEN, Hao CHEN, Guanhua XU

Journal Article

Unconfined compressive strength prediction of soils stabilized using artificial neural networks and support

Alireza TABARSA, Nima LATIFI, Abdolreza OSOULI, Younes BAGHERI

Journal Article

Compressive strength prediction and optimization design of sustainable concrete based on squirrel search

Journal Article

Multiple linear regression, artificial neural network, and fuzzy logic prediction of 28 days compressivestrength of concrete

Faezehossadat KHADEMI,Mahmoud AKBARI,Sayed Mohammadmehdi JAMAL,Mehdi NIKOO

Journal Article

Empirical models and design codes in prediction of modulus of elasticity of concrete

Behnam VAKHSHOURI, Shami NEJADI

Journal Article

Simulation of foamed concrete compressive strength prediction using adaptive neuro-fuzzy inference system

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

Journal Article

Determination of shear strength of steel fiber RC beams: application of data-intelligence models

Abeer A. AL-MUSAWI

Journal Article

Influence of accelerated curing on the compressive strength of polymer-modified concrete

Izhar AHMAD; Kashif Ali KHAN; Tahir AHMAD; Muhammad ALAM; Muhammad Tariq BASHIR

Journal Article

Novel hybrid models of ANFIS and metaheuristic optimizations (SCE and ABC) for prediction of compressivestrength of concrete using rebound hammer field test

Dung Quang VU; Fazal E. JALAL; Mudassir IQBAL; Dam Duc NGUYEN; Duong Kien TRONG; Indra PRAKASH; Binh Thai PHAM

Journal Article

Prediction model for residual strength of stiffened panels with multiple site damage based on artificial

Yang Maosheng,Chen Yueliang,Yu Dazhao

Journal Article

Evaluating the material strength from fracture angle under uniaxial loading

Jitang FAN

Journal Article

The effects of interfacial strength on fractured microcapsule

Luthfi Muhammad MAULUDIN, Chahmi OUCIF

Journal Article

Effect of loading rate on shear strength parameters of mechanically and biologically treated waste

Journal Article

The strength–dilatancy characteristics embraced in hypoplasticity

Zhongzhi FU, Sihong LIU, Zijian WANG

Journal Article