KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Search Results

Now showing 1 - 10 of 11

Some of the metrics are blocked by your
consent settings
Integrating machine learning with experimental data to predict tensile strength of cement pastes with binary cementitious systems
(2026-07-01)
Khan, Ameer Murad
;
Hussain, Qudeer
;
Mohamad, Hisham
;
Jirasakjamroonsri, Amornthep
;
Anotaipaiboon, Weerachai
This study demonstrates a concerted experimental and machine learning model to determine the direct tensile strength of cement pastes with the addition of supplementary cementitious materials (SCM) used as binary cementitious systems. Five types of SCM were used as single binary substitutes at levels of 5–25 % each to form a complete experimental database of 135 cement paste mixtures at water-cement ratios of 0.30–0.40, respectively, to provide a systematic and applied evaluation of the individual contribution of each material to tensile performance. Briquette tests were used to measure direct tensile strength at the binder level to isolate behaviour. Ten mix design parameters were used to train six machine learning regressors (Decision Tree, Random Forest, Gradient Boosting, XGBoost, CatBoost and Support Vector Regression) to predict tensile strength. Support Vector Regression and XGBoost had the best predictive accuracy with R<sup>2</sup> that reached 0.88 and lowest RMSE of 3.3. Analysis of feature importance and partial dependence indicated that the dominant predictors were the water-cement ratio, cement content, and dosage of fly ash and silica fume had a small optimal replacement range, which is in line with the experimental data. The existence of a correspondence between the trends of machine learning and the known hydration mechanisms proves the physical plausibility of the models. The most successful model was an interactive web based tool, TensAile-Lab, to be used in support of fast, data-driven mix design decisions. The suggested framework illustrates the use of interpretable machine learning to forecast tensile behavior with high reliability and speed up the creation of optimized, low-carbon cementitious systems.
Some of the metrics are blocked by your
consent settings
Temperature-resilient performance of hemp rope–Confined recycled aggregate concrete in axial compression
(2026-07-01)
Thansirichaisree, Phromphat
;
Ejaz, Ali
;
Chaimahawan, Preeda
;
Hussain, Qudeer
;
Jirasakjamroonsri, Amornthep
This study addresses the growing need for sustainable and cost-effective alternatives to conventional fiber-reinforced polymer (FRP) confinement systems, particularly for recycled aggregate concrete (RAC) subjected to elevated temperatures. The axial compressive behavior of hemp rope-confined RAC cylinders was experimentally investigated under ambient and moderate thermal exposure (150°C). Two strength grades were considered, with confinement applied using one to three layers of hemp rope. The results demonstrate that hemp confinement significantly enhances both compressive strength and axial strain, with improvements increasing with the number of layers, while strain enhancement was consistently more pronounced than strength gain. The stress–strain response exhibited a characteristic two-stage behavior, consisting of an initial unconfined-like region followed by a confinement-activated ascending branch. The elastic modulus of RAC was found to be approximately 21.9% to 29.7% lower than ACI 318-19 predictions, suggesting a reduction factor of about 25% for practical applications. Thermal exposure had a limited effect on normalized strength and strain parameters, although post-peak stiffness showed some sensitivity. Notably, confinement proved even more effective in thermally damaged specimens due to increased lateral deformability. A regression-based analytical model was developed to predict the complete stress–strain response, showing close agreement with experimental results. This study is among the first to evaluate the performance of hemp rope confinement for RAC under elevated temperature conditions and to propose a unified predictive framework. Overall, the findings confirm that hemp rope confinement is an effective, sustainable, and reliable technique for enhancing both the strength and ductility of RAC, with strong potential for structural applications, including post-fire rehabilitation.
Some of the metrics are blocked by your
consent settings
Eco-Friendly Structural Solutions: The Synergy of Waste Rubber and Hemp Fibers in Sustainable Concrete Design
(2026-01-01)
Thansirichaisree, Phromphat
;
Mohamad, Hisham
;
Chaimahawan, Preeda
;
Hussain, Qudeer
;
Jirasakjamroonsri, Amornthep
The growing emphasis on sustainable construction has encouraged the integration of recycled and renewable materials into structural concrete. This study investigates the axial compressive behavior of rectangular columns incorporating waste-tire rubber as a partial replacement of fine aggregate (5% and 10%) and external confinement using low-cost hemp ropes. A total of twelve specimen configurations, including unconfined and hemp-confined columns with up to three wrapping layers, were tested under monotonic axial compression. The results show that rubber inclusion reduces initial stiffness and peak strength by up to 46%, yet significantly enhances deformability. Hemp-rope confinement effectively compensates for strength loss, increasing compressive strength by up to 53% and ultimate strain by over 500%, with more pronounced effects in rubberized mixes. Normalized strength and strain trends demonstrate a strong dependence on confinement ratio, particularly for highly deformable concrete. To generalize these behaviors, Popovics-based models were calibrated using nonlinear regression, yielding high predictive accuracy (R<sup>2</sup> = 0.94–0.98) for key parameters including peak stress, peak strain, post-peak modulus, and elastic modulus. The proposed expressions closely reproduce the experimental stress–strain response and provide practical tools for modeling confined conventional and rubberized concrete.
Some of the metrics are blocked by your
consent settings
Green reinforcement techniques: Using natural hemp and cotton ropes to enhance the structural integrity of short-span RC beams
(2025-09-01)
Thansirichaisree, Phromphat
;
Ejaz, Ali
;
Saingam, Panumas
;
Mohamad, Hisham
;
Hussain, Qudeer
This study evaluates the structural performance of natural fiber ropes—hemp and cotton—as sustainable strengthening materials for short-span reinforced concrete (RC) beams. A total of 15 beams were tested under four-point bending: one unstrengthened control beam and 14 strengthened beams divided into three groups. Group I included three cotton-strengthened beams using two strip configurations (Type A: 50 mm wide, Type B: 100 mm wide) and one full wrap (Type C). Group II comprised nine hemp-strengthened beams reinforced with 1, 2, or 3 layers in various configurations, while Group III included two CFRP-strengthened beams using a single layer of CFRP strips (Types A and B). Beams strengthened with a single cotton or hemp rope layer exhibited inadequate shear resistance, showing concrete crushing or diagonal cracking. In contrast, two-layer hemp confinement led to more vertical cracking, indicating improved ductility. Results showed that cotton- and hemp-strengthened beams improved peak load capacity by 17 %–40 % and 22 %–78 %, respectively, compared to the control beam, while CFRP offered 36 %–51 % gains. Deflection capacity, indicating ductility, increased by 58 %–95 % for cotton, 42 %–155 % for hemp, and 71 %–145 % for CFRP. Full wrap configurations consistently provided the highest enhancements in both load and ductility, while among strip configurations, Type B outperformed Type A. Hemp ropes delivered higher load capacity due to their superior tensile strength, whereas cotton ropes exhibited greater ductility because of their higher fracture strain (13.5 % vs. 3.5 %). Energy dissipation improved with increased rope quantity and tighter strip spacing. The study also found that conventional FRP-based shear prediction models significantly overestimated the contribution of hemp confinement due to its larger diameter (2.1 mm), underscoring the need for revised modeling approaches. These findings demonstrate the technical feasibility, cost-effectiveness, and environmental advantages of using natural fiber ropes as alternative strengthening materials in structural retrofitting.
Some of the metrics are blocked by your
consent settings
Hybrid FRP strengthening of reinforced concrete deep beams: Experimental, theoretical and machine learning-based study
(2025-07-01)
Thansirichaisree, Phromphat
;
Hussain, Qudeer
;
Zhou, Mingliang
;
Ejaz, Ali
;
Talpur, Shabbir Ali
This paper presents experimental findings from testing seventeen reinforced concrete deep beams, categorized into four groups based on the presence and type of openings. A novel and cost-effective hybrid strengthening scheme is proposed comprising glass chopped mat sheets and eco-friendly basalt FRP sheets (GF-BFRP). Group 1 consisted of solid beams without openings, while Group 2 included beams with circular openings, Group 3 with square openings, and Group 4 with rectangular openings of varying dimensions. Each group comprised beams tested in various strengthening configurations using GF-BFRP layers with and without anchor support. Analysis of failure modes revealed initial flexural cracking in control beams, with beams containing openings exhibiting diagonal cracking and reduced shear capacity. Results revealed that beams with openings experienced a significant reduction in shear capacity. Circular, square, and rectangular openings reduced peak capacity by 26.11 %, 30.67 %, and 31.91 %, respectively, while rectangular openings oriented vertically caused the most substantial reduction at 47.46 %. Strengthening using a single GF-BFRP sheet led to debonding, which was mitigated by anchors, enhancing confinement and reducing diagonal cracking. However, strengthened beams did not recover the original strength of the solid beam, which reached a peak load of 245.51 kN. For instance, the C-W1-A beam achieved a peak load of 173.58 kN, which was 4.31 % lower than its control beam due to the extensive anchor installation. Evaluation of predictive models for shear capacity highlighted discrepancies. None of the existing codes provide expressions that account for the shear contributions of externally bonded FRP systems on beams with opening shape and size implicitly defined. To overcome this issue, machine learning approaches were utilized, employing gradient boosting regression and random forest methods. Data on deep beams, both with and without openings (and without strengthening), was collected from eight studies. The models were trained on this dataset, and predictions were made based on the results of this study. While the gradient boosting regression model tended to overestimate the peak capacity of the deep beams, the random forest model provided predictions that were much closer to the experimental results.
Some of the metrics are blocked by your
consent settings
Data-driven prediction of failure loads in low-cost FRP-confined reinforced concrete beams
(2025-07-01)
Talpur, Shabbir Ali
;
Thansirichaisree, Phromphat
;
Anotaipaiboon, Weerachai
;
Mohamad, Hisham
;
Zhou, Mingliang
This study investigates the application of machine learning (ML) models to predict the ultimate failure load of reinforced concrete (RC) beams confined with low-cost fiber-reinforced polymers (FRP), relatively underexplored area. A dataset of 100 samples, including beams designed to fail in flexure and shear, was compiled from literature and experimental testing. Four ML models—XGBoost, Random Forest (RF), Neural Network (NN), and Decision Tree (DT)—were evaluated using k-fold cross-validation with performance metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R². XGBoost outperformed the other models, achieving the highest R² of 0.96 and the lowest RMSE of 12.81, while SHAP analysis identified beam height, bottom rebar strength, and beam width as key predictors. These results highlight the effectiveness of ensemble methods for predicting failure loads in RC beams and provide insights into the most influential features affecting structural performance.
Some of the metrics are blocked by your
consent settings
Hybrid B-CSM Composites Strengthening Approach for Improved Stress–Strain Behavior of Concrete Columns and Development of Analytical Models
(2025-02-01)
Thansirichaisree, Phromphat
;
Mohamad, Hisham
;
Zhou, Mingliang
;
Ejaz, Ali
;
Saingam, Panumas
The brittle behavior of concrete under axial compressive loading has been a persistent issue. This study investigates the effectiveness of a hybrid Basalt-E-glass confinement (B-CSM) in improving the compressive behavior of concrete. The B-CSM confinement demonstrates a considerable improvement in ultimate strength and strain capacity by over 250 and 500%, respectively, making it a favorable solution for enhancing the ductility of concrete structures. Specimens at 18.43 MPa unconfined strength, confined with 3-layer B-CSM, demonstrated a 258% ultimate strength enhancement. For 24.43 MPa specimens, the same confinement resulted in a 207% increase in ultimate strength. Specimens with an initial ultimate strain of 18.43 MPa, when confined with 3-layers, showed a notable 516% increase. Likewise, for 24.43 MPa specimens, the same confinement led to a significant 395% improvement in ultimate strain. The use of B-CSM confinement is also effective in terms of cost compared to synthetic fiber-reinforced polymer jackets, and its availability is widespread. Existing analytical models for fiber-reinforced polymer confinement were evaluated, and it was found that these models could not predict the ultimate strength and strain of B-CSM-confined concrete. Therefore, this study proposes a unique regression-based approach for predicting the various points of the compressive stress vs. strain curve of B-CSM confinement. These points are then used to trace the complete stress vs. strain curve, which matches closely with experimental results. This work contributes to the development of new design recommendations for B-CSM confined concrete structures, which can enhance the performance of concrete structures and potentially reduce construction costs.
Some of the metrics are blocked by your
consent settings
Performance of Environmentally Friendly Concrete Containing Fly-Ash and Waste Face Mask Fibers
(2024-12-01)
Nawaz, Adnan
;
Khan, Ameer Murad
;
Jirasakjamroonsri, Amorntep
;
Saingam, Panumas
;
Ejaz, Ali
This work was carried out to explore the potential use of used face masks in concrete to develop sustainable green concrete. In this experimental study, used face masks were cut up, removing the ear stripes and internal nose steel wire, to prepare elongated fibers. These fibers were incorporated in cement fly ash mixtures as an additive to determine the response of M20-grade concrete. The Class F fly ash (FA) was employed as a fractional substitute of cement up to 25% by weight, whereas the addition of face masks occurred at 0%, 0.125%, and 0.25% by volume of concrete. The testing scheme focused on the mechanical and durability characteristics of the cement FA mixtures carried out after 3, 28, and 60 days of curing. The inclusion of FA and face mask fibers reduced the density of concrete specimens. The compressive, splitting tensile, and flexural strengths of mixes were also reduced at an early age; however, the strength characteristics improved at later ages, compared to the control mix. The combination of both materials in concrete mixtures resulted in lower water absorption, lower bulk water sorption, and lower mass loss values against acid attack at later ages. Similarly, the electrical resistance of concrete substantially enhanced by increasing the percentage of both materials. The experimental results demonstrated that processed face masks can be utilized in cement fly ash mixes without significantly compromising the resultant concrete characteristics.
Some of the metrics are blocked by your
consent settings
Machine learning approach to predict the strength of concrete confined with sustainable natural FRP composites
(2024-07-01)
Ali Talpur, Shabbir
;
Thansirichaisree, Phromphat
;
Poovarodom, Nakhorn
;
Mohamad, Hisham
;
Zhou, Mingliang
Recent earthquakes have highlighted the need to strengthen existing structures with substandard designs. NFRPs provide a sustainable, cost-effective alternative for strengthening, but accurately predicting their performance remains a challenge. This study investigates the use of machine learning algorithms for predicting the compressive strength concrete specimens confined with various NFRPs. Four algorithms were employed: decision tree, random forest, neural network, and gradient boosting regressor. A diverse dataset encompassing various geometries, material properties, and confinement configurations was used to train and evaluate the models. Gradient boosting regressor (GBR) achieved the highest performance, with an average R-squared value of 0.94 and low mean absolute error (MAE) and root mean squared error (RMSE) during training and k-fold cross-validation. Neural network and random forest also demonstrated satisfactory performance, with average R-squared values of 0.88 and 0.86, respectively, during cross-validation. These results suggest that machine learning holds promise for predicting the compressive strength of concrete confined with NFRPs. GBR offers the most accurate predictions, making it a valuable tool for engineers seeking to optimize the design and performance of strengthened structures using sustainable materials.
Some of the metrics are blocked by your
consent settings
Stress-strain behavior of square concrete columns confined with hybrid B-CSM composites and development of novel prediction models
(2024-07-01)
Thansirichaisree, Phromphat
;
Mohamad, Hisham
;
Ejaz, Ali
;
Saingam, Panumas
;
Hussain, Qudeer
This paper presents a comprehensive investigation into the behavior of concrete confined with hybrid Basalt and Chopped Strand Mat (B-CSM) fibers. The newly proposed B-CSM confinement technique substantially enhances the brittle compressive stress-strain behavior, leading to a noteworthy increase in peak strength (approximately 90%) and ultimate strain (approximately 461 %). The efficiency of B-CSM confinement is affected by the strength of plain concrete, with lower-strength specimens indicating a more pronounced enhancement. The performance of existing analytical models for FRP confinement in predicting ultimate strength and strain in B-CSM confined concrete is assessed, highlighting the need for tailored models. Regression-based equations are proposed for characteristic points along the stress-strain curve, enabling accurate prediction of material behavior. The predicted stress-strain curves exhibit a high level of agreement with experimental results. These findings provide valuable insights for the design and application of B-CSM confinement techniques in structural engineering, facilitating improved performance and ductility of concrete structures under compressive loading conditions.

KMITL

Browse

Filters

Settings

Sort By

Results per page

Search Results