Effect of Rubber Aggregates on Early-Age Mechanical Properties and Deformation Behaviors of Cement Mortar DOI Creative Commons
Gaowang Zhang, Hao Du, Junmin Li

et al.

Buildings, Journal Year: 2024, Volume and Issue: 14(9), P. 2787 - 2787

Published: Sept. 4, 2024

Rubberized cement-based materials are widely utilized because of their good ductility, impact resistance, and fatigue resistance. This research investigated the effect rubber aggregates content, particle size aggregates, water–cement ratio on early-age mechanical properties deformation behaviors mortar through laboratory tests, strength reduction coefficient fitting models were established according to testing results. The results show that compressive growth rate cement is about 15% slower than flexural strength. existence lowers increase mortar. decreases with increasing content increases age Increasing decreasing aggregate can lower autogenous shrinkage in initial stage, but later stage as increases, a turning point between 30 h 50 h. After 3 days, dry accounts for 70–80% total shrinkage, it higher smaller ratios.

Language: Английский

Optimizing pervious concrete with machine learning: Predicting permeability and compressive strength using artificial neural networks DOI Creative Commons
Yinglong Wu, Ricardo Pieralisi,

F. Gersson B. Sandoval

et al.

Construction and Building Materials, Journal Year: 2024, Volume and Issue: 443, P. 137619 - 137619

Published: Aug. 7, 2024

This study makes a significant contribution to the field of pervious concrete by using machine learning innovatively predict both mechanical and hydraulic performance. Unlike existing methods that rely on labor-intensive trial-and-error experiments, our proposed approach leverages multilayer perceptron network. To develop this approach, we compiled comprehensive dataset comprising 271 sets 3,252 experimental data points. Our methodology involved evaluating 22,246 network configurations, employing Monte Carlo cross-validation over 20 iterations, 4 training algorithms, resulting in total 1,779,680 iterations. results an optimized model integrates diverse mix design parameters, enabling accurate predictions permeability compressive strength even absence data, achieving R² values 0.97 0.98, respectively. Sensitivity analyses validate model's alignment with established principles behavior. By demonstrating efficacy as complementary tool for optimizing designs, research not only addresses current methodological limitations but also lays groundwork more efficient effective approaches field.

Language: Английский

Citations

11

Optimization design and evaluation of polymer-modified hybrid fiber-reinforced cement-based composites DOI
Shuai Li, Lihong Liang, Chengyu Guan

et al.

Construction and Building Materials, Journal Year: 2025, Volume and Issue: 462, P. 139915 - 139915

Published: Jan. 16, 2025

Language: Английский

Citations

1

Utilizing Construction and Demolition Waste in Concrete as a Sustainable Cement Substitute: A Comprehensive Study on Behavior Under Short-term Dynamic and Static Loads via Laboratory and Numerical Analysis DOI
Mohammad Mohtasham Moein, Komeil Rahmati,

Ali Mohtasham Moein

et al.

Journal of Building Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 110778 - 110778

Published: Sept. 1, 2024

Language: Английский

Citations

5

Harnessing expanded polystyrene waste for sustainable construction: NBO-HDLNN approach DOI
M. Seethapathi, T. Vijaya Gowri, P. Rajesh

et al.

International Journal of Pavement Engineering, Journal Year: 2025, Volume and Issue: 26(1)

Published: Feb. 18, 2025

Language: Английский

Citations

0

Machine Learning Models for Predicting Compressive Strength of Eco-Friendly Concrete with Copper Slag Aggregates DOI
Yaser Moodi, Naser Safaeian Hamzehkolaei, Iman Afshoon

et al.

Materials Today Communications, Journal Year: 2025, Volume and Issue: unknown, P. 112572 - 112572

Published: April 1, 2025

Language: Английский

Citations

0

Prediction and optimization of surface waviness of WAAM components using a hybrid Rank-Gaussian PSO algorithm and ANN DOI
Jun Cheng, Wim De Waele

Structures, Journal Year: 2024, Volume and Issue: 69, P. 107247 - 107247

Published: Sept. 14, 2024

Language: Английский

Citations

3

Bending Performance of Reinforced Concrete Beams with Rubber as Form of Fiber from Waste Tires DOI Open Access
Ali Serdar Ecemiş, Emrah Madenci, Memduh Karalar

et al.

Materials, Journal Year: 2024, Volume and Issue: 17(20), P. 4958 - 4958

Published: Oct. 11, 2024

An investigation was conducted to assess the efficacy of using waste rubber as a substitute for portion an aggregate enhance concrete’s sustainability. For purpose accomplishing this objective, total 12 specimens were constructed and then subjected series tests investigate their bending behavior. The samples with following dimensions: 1000 mm length 100 by 150 cross-sectional area. A few factors selected, including impacts longitudinal reinforcement ratio ratio. Based on volume aggregates, replacement rates 0%, 5%, 10%, 15% investigated in study. To beam behavior, stirrup width spacing kept constant at ∅6/10. composed three diameters: ∅6 top (for all beams) ∅8, ∅10, ∅12 bottom. experimental results demonstrated that effects varying amounts tension cracking reinforced concrete beams (RCBs) varied. findings indicate incorporation into reduction both load-carrying capacity level deformation material. Additionally, it shown amount RCB increased, energy absorption ultimate load decreased. There dissipation 53.71%, 51.69%, 40.55% ∅8 when applied replacement, respectively. there reductions 25.35%, 9.31%, 58.15% 38.69%, 57.79%, 62.44% ∅12,

Language: Английский

Citations

3

Numerical Modeling of Steel Fiber Reinforced Recycled Concrete Filled Steel Tube Column Under Cyclic Loading DOI Creative Commons
Mohamed Sakr, Ayman Seleemah,

O.F. Kharoob

et al.

Electronic Journal of Structural Engineering, Journal Year: 2024, Volume and Issue: 24(3), P. 1 - 7

Published: July 25, 2024

A finite element model (FEM) was created with the aim of analyzing behavior steel fiber reinforced recycled concrete (SFRRC)-filled tube columns under combined cyclic loading and monotonic axial load. The FEM considered effect confinement on inner loading. numerical described in detail, a focus modeling materials involved (normal concrete, SFRRC, steel) constitutive - without considering based utilizing damaged plasticity (CDP) model. core interface modeled by surface-to-surface contact. stress-strain model, confined circular tubes, implemented, validated using experimental results from literature. developed various parameters: thickness, volume ratios fibers, besides strengths both tube. showed great similarity to under- cyclic- tested columns. indicated that confining pressure must be CDP good correlation between findings obvious, including failure modes, hysteretic curves load-displacement.

Language: Английский

Citations

1

Optimization of Sound Absorption Performance of 316l Stainless Steel Foam Using the Taguchi Method and Artificial Neural Networks DOI
Kuan‐Yu Chen, Yu‐Chih Tzeng,

You-Sheng Yeh

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

0

Study on Key Parameters and Design Methods for the Density-Mix Proportion of Rubber-Foamed Concrete DOI Creative Commons

Minghui Shi,

Guansheng Yin, Wanqi Zhang

et al.

Buildings, Journal Year: 2024, Volume and Issue: 14(8), P. 2468 - 2468

Published: Aug. 10, 2024

Rubber-foamed concrete demonstrates exceptional toughness, a low elastic modulus, and significant sensitivity to density. It is necessary parameterize the density mix of rubber-foaming meet engineering design requirements. Density-mix methods for foaming rely mainly on empirical knowledge or trial-and-error approaches. In this paper, with numerous parametric tests regression analysis based general principles density-mix designs applicable both foamed rubber-foamed concretes, key parameters, such as volume correction coefficient, rubber size effect water-reducing agent have been proposed in order optimize their respective densities more accurately. The demonstrated an optimal water-to-cement ratio 0.45, corresponding factor 1.027. Incorporating particles agents has cement-paste volume. Controlling fluidity 200 300 mm range crucial when designing varying densities. equation accurately predicts paste’s measured wetting by incorporating corrections, size, water reduction coefficients. By employing foam excess coefficient 1.1 mass 1.25, dry wet error less than 5%. A comprehensive framework optimizing terms provided applications concrete, facilitating researchers ratios additional novel mixture-based foamed-concrete applications.

Language: Английский

Citations

0