Machine learning in concrete science: applications, challenges, and best practices

Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems

(2022) Jared Willard et al.   ACM COMPUTING SURVEYS

Artificial Intelligence and Machine Learning in Glass Science and Technology: 21 Challenges for the 21 st Century

(2021) R. Ravinder et al.   International Journal of Applied Glass Science

Machine Learning Enables Rapid Screening of Reactive Fly Ashes Based on Their Network Topology

(2021) Yu Song et al.   ACS Sustainable Chemistry & Engineering

Machine learning for perovskite materials design and discovery

(2021) Qiuling Tao et al.   npj Computational Materials

Predicting the early-stage creep dynamics of gels from their static structure by machine learning

(2021) Han Liu et al.   ACTA MATERIALIA

A Survey on Bias and Fairness in Machine Learning

(2021) Ninareh Mehrabi et al.   ACM COMPUTING SURVEYS

An engineer's guide to eXplainable Artificial Intelligence and Interpretable Machine Learning: Navigating causality, forced goodness, and the false perception of inference

(2021) M.Z. Naser   AUTOMATION IN CONSTRUCTION

Classification and analysis of deep learning applications in construction: A systematic literature review

(2021) Rana Khallaf et al.   AUTOMATION IN CONSTRUCTION

A machine learning and deep learning based approach to predict the thermal performance of phase change material integrated building envelope

(2021) Dnyandip K. Bhamare et al.   BUILDING AND ENVIRONMENT

Coupling machine learning with thermodynamic modelling to develop a composition-property model for alkali-activated materials

(2021) Xinyuan Ke et al.   COMPOSITES PART B-ENGINEERING

Knowledge-enhanced data-driven models for quantifying the effectiveness of PP fibers in spalling prevention of ultra-high performance concrete

(2021) Jin-Cheng Liu et al.   CONSTRUCTION AND BUILDING MATERIALS

Machine learning prediction of carbonation depth in recycled aggregate concrete incorporating SCMs

(2021) Itzel Nunez et al.   CONSTRUCTION AND BUILDING MATERIALS

Machine learning model for predicting the crack detection and pattern recognition of geopolymer concrete beams

(2021) N Aravind et al.   CONSTRUCTION AND BUILDING MATERIALS

Predicting Mechanical Properties of High-Performance Fiber-Reinforced Cementitious Composites by Integrating Micromechanics and Machine Learning

(2021) Pengwei Guo et al.   Materials

Estimating compressive strength of modern concrete mixtures using computational intelligence: A systematic review

(2021) Itzel Nunez et al.   CONSTRUCTION AND BUILDING MATERIALS

Chemistry-informed machine learning prediction of compressive strength for alkali-activated materials

(2021) Lei V. Zhang et al.   CONSTRUCTION AND BUILDING MATERIALS

Unrestricted permutation forces extrapolation: variable importance requires at least one more model, or there is no free variable importance

(2021) Giles Hooker et al.   STATISTICS AND COMPUTING

Machine learning for high-fidelity prediction of cement hydration kinetics in blended systems

(2021) Rachel Cook et al.   MATERIALS & DESIGN

Validating the validation: reanalyzing a large-scale comparison of deep learning and machine learning models for bioactivity prediction

(2020) Matthew C. Robinson et al.   JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN

Opportunities and Challenges for Machine Learning in Materials Science

(2020) Dane Morgan et al.   Annual Review of Materials Research

Semantic segmentation of the micro-structure of strain-hardening cement-based composites (SHCC) by applying deep learning on micro-computed tomography scans

(2020) Renata Lorenzoni et al.   CEMENT & CONCRETE COMPOSITES

Machine Learning for Materials Scientists: An introductory guide towards best practices

(2020) Anthony Yu-Tung Wang et al.   CHEMISTRY OF MATERIALS

An ensemble machine learning approach for prediction and optimization of modulus of elasticity of recycled aggregate concrete

(2020) Taihao Han et al.   CONSTRUCTION AND BUILDING MATERIALS

Machine learning study of the mechanical properties of concretes containing waste foundry sand

(2020) Ali Behnood et al.   CONSTRUCTION AND BUILDING MATERIALS

Dissociated dislocation-mediated carbon transport and diffusion in austenitic iron

(2020) Ruiwen Xie et al.   ACTA MATERIALIA

Deep convolution neural network-based transfer learning method for civil infrastructure crack detection

(2020) Qiaoning Yang et al.   AUTOMATION IN CONSTRUCTION

Structural health evaluation of the prestressed concrete using advanced acoustic emission (AE) parameters

(2020) Guofeng Ma et al.   CONSTRUCTION AND BUILDING MATERIALS

Random forest-based evaluation technique for internal damage in reinforced concrete featuring multiple nondestructive testing results

(2020) Pang-jo Chun et al.   CONSTRUCTION AND BUILDING MATERIALS

A metaheuristic-optimized multi-output model for predicting multiple properties of pervious concrete

(2020) Junfei Zhang et al.   CONSTRUCTION AND BUILDING MATERIALS

Optimizing fresh properties and compressive strength of self-consolidating concrete

(2020) Walid E. Elemam et al.   CONSTRUCTION AND BUILDING MATERIALS

Hyperspectral imaging features for mortar classification and compressive strength assessment

(2020) Liang Fan et al.   CONSTRUCTION AND BUILDING MATERIALS

Multi-objective optimization of concrete mixture proportions using machine learning and metaheuristic algorithms

(2020) Junfei Zhang et al.   CONSTRUCTION AND BUILDING MATERIALS

Concrete crack detection and quantification using deep learning and structured light

(2020) Song Ee Park et al.   CONSTRUCTION AND BUILDING MATERIALS

Toward intelligent construction: Prediction of mechanical properties of manufactured-sand concrete using tree-based models

(2020) Junfei Zhang et al.   JOURNAL OF CLEANER PRODUCTION

High-throughput design of fiber reinforced cement-based composites using deep learning

(2020) Zheng Tong et al.   CEMENT & CONCRETE COMPOSITES

Combined mechanical and 3D-microstructural analysis of strain-hardening cement-based composites (SHCC) by in-situ X-ray microtomography

(2020) Renata Lorenzoni et al.   CEMENT AND CONCRETE RESEARCH

Prediction of surface chloride concentration of marine concrete using ensemble machine learning

(2020) Rong Cai et al.   CEMENT AND CONCRETE RESEARCH

Deep learning-based automated image segmentation for concrete petrographic analysis

(2020) Yu Song et al.   CEMENT AND CONCRETE RESEARCH

Pavement aggregate shape classification based on extreme gradient boosting

(2020) Lili Pei et al.   CONSTRUCTION AND BUILDING MATERIALS

Evaluation of carbonation progress using AIJ model, FEM analysis, and machine learning algorithms

(2020) Hyungmin Lee et al.   CONSTRUCTION AND BUILDING MATERIALS

Experimental investigation and modelling the deformation properties of demolition wastes subjected to freeze–thaw cycles using ANN and SVR

(2020) Behnam Ghorbani et al.   CONSTRUCTION AND BUILDING MATERIALS

Automated inspection in robotic additive manufacturing using deep learning for layer deformation detection

(2020) Omid Davtalab et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Compressive strength prediction of high-performance concrete using gradient tree boosting machine

(2020) Mosbeh R. Kaloop et al.   CONSTRUCTION AND BUILDING MATERIALS

Deep learning models for bridge deck evaluation using impact echo

(2020) Sattar Dorafshan et al.   CONSTRUCTION AND BUILDING MATERIALS

Machine learning prediction of compressive strength for phase change materials integrated cementitious composites

(2020) Afshin Marani et al.   CONSTRUCTION AND BUILDING MATERIALS

Efficient machine learning models for prediction of concrete strengths

(2020) Hoang Nguyen et al.   CONSTRUCTION AND BUILDING MATERIALS

Machine learning approaches to predict the micromechanical properties of cementitious hydration phases from microstructural chemical maps

(2020) Emily Ford et al.   CONSTRUCTION AND BUILDING MATERIALS

Undersampling Strategy for Machine-learned Deterioration Regression Model in Concrete Bridges

(2020) Yuriko Okazaki et al.   Journal of Advanced Concrete Technology

Elucidating the constitutive relationship of calcium–silicate–hydrate gel using high throughput reactive molecular simulations and machine learning

(2020) Gideon A. Lyngdoh et al.   Scientific Reports

Machine learning potentials for tobermorite minerals

(2020) Keita Kobayashi et al.   COMPUTATIONAL MATERIALS SCIENCE

Using artificial neural network to predict the fracture properties of the interfacial transition zone of concrete at the meso-scale

(2020) Xun Xi et al.   ENGINEERING FRACTURE MECHANICS

Machine Learning in Amyotrophic Lateral Sclerosis: Achievements, Pitfalls, and Future Directions

(2019) Vincent Grollemund et al.   Frontiers in Neuroscience

Computer vision for real-time extrusion quality monitoring and control in robotic construction

(2019) Ali Kazemian et al.   AUTOMATION IN CONSTRUCTION

Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

(2019) Chi Chen et al.   CHEMISTRY OF MATERIALS

Multiple mechanical properties prediction of hydraulic concrete in the form of combined damming by experimental data mining

(2019) Mengxi Zhang et al.   CONSTRUCTION AND BUILDING MATERIALS

A fast adaptive crack detection algorithm based on a double-edge extraction operator of FSM

(2019) Qijun Luo et al.   CONSTRUCTION AND BUILDING MATERIALS

Quick image analysis of concrete pore structure based on deep learning

(2019) Shuangxi Zhou et al.   CONSTRUCTION AND BUILDING MATERIALS

Parametric sensitivity analysis and modelling of mechanical properties of normal- and high-strength recycled aggregate concrete using grey theory, multiple nonlinear regression and artificial neural networks

(2019) Jinjun Xu et al.   CONSTRUCTION AND BUILDING MATERIALS

Unsupervised word embeddings capture latent knowledge from materials science literature

(2019) Vahe Tshitoyan et al.   NATURE

Semi-supervised machine-learning classification of materials synthesis procedures

(2019) Haoyan Huo et al.   npj Computational Materials

Computer vision-based concrete crack detection using U-net fully convolutional networks

(2019) Zhenqing Liu et al.   AUTOMATION IN CONSTRUCTION

Application of thermodynamic modelling to hydrated cements

(2019) Barbara Lothenbach et al.   CEMENT AND CONCRETE RESEARCH

Prediction of concrete coefficient of thermal expansion and other properties using machine learning

(2019) Vanessa Nilsen et al.   CONSTRUCTION AND BUILDING MATERIALS

Parallel approach of a Galerkin-based methodology for predicting the compressive strength of the lightweight aggregate concrete

(2019) Violeta Migallón et al.   CONSTRUCTION AND BUILDING MATERIALS

A novel method for multi-scale carbon fiber distribution characterization in cement-based composites

(2019) Zheng Tong et al.   CONSTRUCTION AND BUILDING MATERIALS

Machine learning can predict setting behavior and strength evolution of hydrating cement systems

(2019) Tandré Oey et al.   JOURNAL OF THE AMERICAN CERAMIC SOCIETY

Recent advances and applications of machine learning in solid-state materials science

(2019) Jonathan Schmidt et al.   npj Computational Materials

A scientometric analysis and critical review of computer vision applications for construction

(2019) Pablo Martinez et al.   AUTOMATION IN CONSTRUCTION

A generalized method to predict the compressive strength of high-performance concrete by improved random forest algorithm

(2019) Qinghua Han et al.   CONSTRUCTION AND BUILDING MATERIALS

Prediction of triaxial behavior of recycled aggregate concrete using multivariable regression and artificial neural network techniques

(2019) Jinjun Xu et al.   CONSTRUCTION AND BUILDING MATERIALS

A new method for CF morphology distribution evaluation and CFRC property prediction using cascade deep learning

(2019) Zheng Tong et al.   CONSTRUCTION AND BUILDING MATERIALS

Machine learning algorithm validation with a limited sample size

(2019) Andrius Vabalas et al.   PLoS One

A robust time-dependent model of alkali-silica reaction at different temperatures

(2019) Hamed Allahyari et al.   CEMENT & CONCRETE COMPOSITES

A comparison of machine learning methods for predicting the compressive strength of field-placed concrete

(2019) M.A. DeRousseau et al.   CONSTRUCTION AND BUILDING MATERIALS

Effect of nano-silica on mechanical properties and durability of self-compacting mortar containing natural zeolite: Experimental investigations and artificial neural network modeling

(2019) Danial Nasr et al.   CONSTRUCTION AND BUILDING MATERIALS

Advanced Quality Control Models for Concrete Admixtures

(2019) Hyungjoo Choi et al.   JOURNAL OF MATERIALS IN CIVIL ENGINEERING

Computational design optimization of concrete mixtures: A review

(2018) M.A. DeRousseau et al.   CEMENT AND CONCRETE RESEARCH

Concrete material science: Past, present, and future innovations

(2018) Henri Van Damme   CEMENT AND CONCRETE RESEARCH

Infrared thermography model for automated detection of delamination in RC bridge decks

(2018) Tarek Omar et al.   CONSTRUCTION AND BUILDING MATERIALS

Measurement of reinforcement corrosion in concrete adopting ultrasonic tests and artificial neural network

(2018) Yidong Xu et al.   CONSTRUCTION AND BUILDING MATERIALS

A machine learning approach for the identification of the Lattice Discrete Particle Model parameters

(2018) Mohammed Alnaggar et al.   ENGINEERING FRACTURE MECHANICS

Rational Condition Assessment of RC Bridge Decks Subjected to Corrosion-Induced Delamination

(2018) Tarek Omar et al.   JOURNAL OF MATERIALS IN CIVIL ENGINEERING

Prediction of shear strength of FRP-reinforced concrete members using a rule-based method

(2018) Asad-Allah Abbasloo et al.   MAGAZINE OF CONCRETE RESEARCH

Can the compressive strength of concrete be estimated from knowledge of the mixture proportions?: New insights from statistical analysis and machine learning methods

(2018) Benjamin A. Young et al.   CEMENT AND CONCRETE RESEARCH

Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concrete

(2018) Sattar Dorafshan et al.   CONSTRUCTION AND BUILDING MATERIALS

Machine learning in human movement biomechanics: Best practices, common pitfalls, and new opportunities

(2018) Eni Halilaj et al.   JOURNAL OF BIOMECHANICS

Image Processing and Machine Learning to investigate fibre distribution on fibre-reinforced shotcrete Round Determinate Panels

(2018) Mirko Manca et al.   CONSTRUCTION AND BUILDING MATERIALS

Avoiding common pitfalls in machine learning omic data science

(2018) Andrew E. Teschendorff   NATURE MATERIALS

Mix design of the green self-consolidating concrete: Incorporating the waste glass powder

(2018) Ali Hendi et al.   CONSTRUCTION AND BUILDING MATERIALS

Five ways to fix statistics

(2017)   NATURE

Towards sustainable concrete

(2017) Paulo J. M. Monteiro et al.   NATURE MATERIALS

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

(2017) Faezehossadat Khademi et al.   Frontiers of Structural and Civil Engineering

Genetic programming for experimental big data mining: A case study on concrete creep formulation

(2016) Amir H. Gandomi et al.   AUTOMATION IN CONSTRUCTION

Recycling combustion ash for sustainable cement production: A critical review with data-mining and time-series predictive models

(2016) Yu Wang et al.   CONSTRUCTION AND BUILDING MATERIALS

Advancing concrete strength prediction using non-destructive testing: Development and verification of a generalizable model

(2016) Kamran Amini et al.   CONSTRUCTION AND BUILDING MATERIALS

Investigation of chloride diffusion in cement mortar via statistical learning theory

(2016) Kuo-Wei Liao et al.   MAGAZINE OF CONCRETE RESEARCH

Prediction of chloride content in concrete using ANN and CART

(2016) Mohammadreza Seify Asghshahr et al.   MAGAZINE OF CONCRETE RESEARCH

Regression and artificial neural network models for strength properties of engineered cementitious composites

(2016) Khandaker M. A. Hossain et al.   NEURAL COMPUTING & APPLICATIONS

Promises, Pitfalls, and Basic Guidelines for Applying Machine Learning Classifiers to Psychiatric Imaging Data, with Autism as an Example

(2016) Pegah Kassraian-Fard et al.   Frontiers in Psychiatry

A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure

(2015) Christian Koch et al.   ADVANCED ENGINEERING INFORMATICS

Statistical mixture design approach for eco-efficient UHPC

(2015) Ehsan Ghafari et al.   CEMENT & CONCRETE COMPOSITES

A comparative assessment of bagging ensemble models for modeling concrete slump flow

(2015) Hacer Yumurtaci Aydogmus et al.   Computers and Concrete

CaPrM: Carbonation prediction model for reinforced concrete using machine learning methods

(2015) Woubishet Zewdu Taffese et al.   CONSTRUCTION AND BUILDING MATERIALS

Explicit formulation of drying and autogenous shrinkage of concretes with binary and ternary blends of silica fume and fly ash

(2015) Kasım Mermerdaş et al.   CONSTRUCTION AND BUILDING MATERIALS

Artificial neural network approach to predict the fracture parameters of the size effect model for concrete

(2015) Y. Yan et al.   FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES

Shear strength prediction of HSC slender beams without web reinforcement

(2015) H. M. Elsanadedy et al.   MATERIALS AND STRUCTURES

Sensitivity analysis of creep models considering correlation

(2015) Bing Han et al.   MATERIALS AND STRUCTURES

Optimization method, choice of form and uncertainty quantification of Model B4 using laboratory and multi-decade bridge databases

(2015) Roman Wendner et al.   MATERIALS AND STRUCTURES

Fracture mode identification in cementitious materials using supervised pattern recognition of acoustic emission features

(2014) Alireza Farhidzadeh et al.   CONSTRUCTION AND BUILDING MATERIALS

Cement and concrete as an engineering material: An historic appraisal and case study analysis

(2014) Colin R. Gagg   ENGINEERING FAILURE ANALYSIS

Numerical modeling of time to corrosion induced cover cracking in reinforced concrete using soft-computing based methods

(2014) Esra Mete Güneyisi et al.   MATERIALS AND STRUCTURES

Scientific method: Statistical errors

(2014) Regina Nuzzo   NATURE

Assessment of fresh properties and compressive strength of self-compacting concrete made with different sand types by mixture design modelling approach

(2013) Tayeb Bouziani   CONSTRUCTION AND BUILDING MATERIALS

Leakage in data mining

(2013) Shachar Kaufman et al.   ACM Transactions on Knowledge Discovery from Data

An Artificial Neural Networks Model for Predicting Permeability Properties of Nano Silica–Rice Husk Ash Ternary Blended Concrete

(2013) Alireza Najigivi et al.   International Journal of Concrete Structures and Materials

Commentary: The Materials Project: A materials genome approach to accelerating materials innovation

(2013) Anubhav Jain et al.   APL Materials

Concrete properties evaluation by statistical fusion of NDT techniques

(2012) Zoubir Mehdi Sbartaï et al.   CONSTRUCTION AND BUILDING MATERIALS

Monitoring biological crusts in civil engineering structures using intensity data from terrestrial laser scanners

(2012) H. González-Jorge et al.   CONSTRUCTION AND BUILDING MATERIALS

Prediction of Elastic Modulus of Concrete Using Support Vector Committee Method

(2012) Javad Sadoghi Yazdi et al.   JOURNAL OF MATERIALS IN CIVIL ENGINEERING

Recent advances in modeling for cementitious materials

(2011) Jorge S. Dolado et al.   CEMENT AND CONCRETE RESEARCH

Modeling and simulation of cement hydration kinetics and microstructure development

(2011) Jeffrey J. Thomas et al.   CEMENT AND CONCRETE RESEARCH

Thermodynamics and cement science

(2011) D. Damidot et al.   CEMENT AND CONCRETE RESEARCH

Modeling with ANN and effect of pumice aggregate and air entrainment on the freeze–thaw durabilities of HSC

(2011) Mehmet Burhan Karakoç et al.   CONSTRUCTION AND BUILDING MATERIALS

µic: A new platform for modelling the hydration of cements

(2009) Shashank Bishnoi et al.   CEMENT AND CONCRETE RESEARCH

Analysis of carbonation behavior in concrete using neural network algorithm and carbonation modeling

(2009) Seung-Jun Kwon et al.   CEMENT AND CONCRETE RESEARCH

Influence of salt on desorption isotherm and hygral state of cement mortar – Modelling using neural networks

(2009) Marcin Koniorczyk et al.   CONSTRUCTION AND BUILDING MATERIALS

Neural networks for predicting compressive strength of structural light weight concrete

(2009) Marai M. Alshihri et al.   CONSTRUCTION AND BUILDING MATERIALS

A Survey on Transfer Learning

(2009) Sinno Jialin Pan et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

A novel aggregate classification technique using moment invariants and cascaded multilayered perceptron network

(2009) Mohammad Subhi Al-Batah et al.   INTERNATIONAL JOURNAL OF MINERAL PROCESSING

Artificial Neural Network for Predicting Creep and Shrinkage of High Performance Concrete

(2008) Jayakumar Karthikeyan et al.   Journal of Advanced Concrete Technology

Evaluating and forecasting the initial and final setting times of self-compacting concretes containing mineral admixtures by neural network

(2008) Erhan Güneyisi et al.   MATERIALS AND STRUCTURES

Innovation in use and research on cementitious material

(2007) Karen L. Scrivener et al.   CEMENT AND CONCRETE RESEARCH

Estimation of chloride permeability of concretes by empirical modeling: Considering effects of cement type, curing condition and age

(2007) Erhan Güneyisi et al.   CONSTRUCTION AND BUILDING MATERIALS

An axiomatic approach to intrinsic dimension of a dataset

(2007) Vladimir Pestov   NEURAL NETWORKS

Suitable features selection for the HMLP and MLP networks to identify the shape of aggregate

(2006) Nor Ashidi Mat Isa et al.   CONSTRUCTION AND BUILDING MATERIALS