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Effect of root water uptake on road movement across seasonal changes
(2025-01-01)
Yuliana, Yuliana
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Apriyono, Arwan
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Leung, Anthony Kwan
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Keawsawasvong, Suraparb
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Kamchoom, Viroon
The use of trees as roadside barriers provides benefits like noise and pollution control. On the other hand, the root systems can disrupt soil moisture, leading to uneven subsidence and impacting nearby structures. Knowing the appropriate distance between trees and pavement will allow for maximizing the plant's favourable impact on infrastructure. This study aimed to determine the safe distance between trees and pavement by examining the effects of transpiration on pore water pressure (PWP) and pavement subsidence under seasonal variations. The root water uptake was simplified in a finite element model using multiple hydraulic head boundaries and validated through field observations. A hypoplastic model was employed to simulate the non-linear behaviour and plastic strain accumulation in unsaturated soil. The findings indicate that the summer season exhibited a more noticeable change in negative PWP. Trees significantly reduce PWP, especially during summer seasons, creating higher suction near them due to evapotranspiration. Additionally, pavement edges closest to trees experience the most pronounced subsidence, likely due to a greater soil moisture deficit. Seasonal variations influence subsidence, with drier periods leading to more severe effects. Furthermore, the pavement with the distance 4 meters from the tree highlights a potential risk exceeded the cracking moment at 5th summer period, indicating a high risk of damage.
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Rectangular tunnel heading stability in three dimensions and its predictive machine learning models
(2024-11-01)
Shiau, Jim
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Keawsawasvong, Suraparb
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Lai, Van Qui
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Promwichai, Thanachon
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Kamchoom, Viroon
Tunnel heading stability in two dimensions (2D) has been extensively investigated by numerous scholars in the past decade. One significant limitation of 2D analysis is the absence of actual tunnel geometry modeling with a considerable degree of idealization. Nevertheless, it is possible to study the stability of tunnels in three dimensions (3D) with a rectangular shape using finite element limit analysis (FELA) and a nonlinear programming technique. This paper employs 3D FELA to generate rigorous solutions for stability numbers, failure mechanisms, and safety factors for rectangular-shaped tunnels. To further explore the usefulness of the produced results, multivariate adaptive regression spline (MARS) is used for machine learning of big dataset and development of design equations for practical design applications. The study should be of great benefit to tunnel design practices using the developed equations provided in the paper.
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The impact of biochar amendment on soil water infiltration and evaporation under climate change scenarios
(2024-10-01)
Apriyono, Arwan
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Yuliana, Yuliana
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Chen, Zhongkui
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Keawsawasvong, Suraparb
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Kamchoom‬, Viroon
Biochar is an eco-friendly material that is potentially used in earthworks to prevent stability and serviceability problems under extreme scenarios. This study aims to examine the effects of biochar amended on water infiltration and evaporation under extreme climate. A series of numerical analyzes were conducted to observe the response of pore water pressure (PWP) to extreme climate variation with an application of biochar composition. Moreover, an analysis of variance (ANOVA) has been performed to investigate the effect of biochar on soil water holding capacity at a low suction range. According to the result, biochar amended can maintain the fluctuation of PWP due to wetting and drying processes under extreme climate scenarios. This is due to the fact that the finer particles of biochar may clog large soil pores, reducing the water infiltration rate. Moreover, the addition of biochar can increase water retention capacity at low matric suction ranges, which can prevent flooding during extreme wet conditions. Further to this, the addition of biochar to the soil can maintain PWP fluctuation at the near surface area under extreme climate, preventing soil desiccation cracks.
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Developing effective optimized machine learning approaches for settlement prediction of shallow foundation
(2024-09-15)
Khajehzadeh, Mohammad
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Keawsawasvong, Suraparb
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Kamchoom, Viroon
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Shi, Chao
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Khajehzadeh, Alimorad
The precise assessment of shallow foundation settlement on cohesionless soils is a challenging geotechnical issue, primarily due to the significant uncertainties related to the factors influencing the settlement. This study aims to create an advanced hybrid machine learning methodology for accurately estimating shallow foundations' settlement (Sm). The initial contribution of the current research is developing and validating a robust hybrid optimization methodology based on an artificial electric field and single candidate optimizer (AEFSCO). This approach is thoroughly tested using various benchmark functions. AEFSCO will also be used to optimize three useful machine learning methods: long short-term memory (LSTM), support vector regression (SVR), and multilayer perceptron neural network (MLPNN) by adjusting their hyperparameters for predicting the settlement of shallow foundations. A database consisting of 189 individual case histories, conducted through various investigations, was used for training and testing the models. The database includes five input parameters and one output. These factors encompassed both the geometric characteristics of the foundation and the properties of the sandy soil. The results demonstrate that employing effective optimization strategies to adjust the ML models’ hyperparameters can significantly improve the accuracy of predicted results. The AEFSCO has increased the coefficient of determination (R2) value of the MLPNN model by 9.3 %, the SVR model by 8 %, and the LSTM model by 22 %. Also, the LSTM-AEFSCO model is more accurate than the SVR-AEFSCO and MLPNN-AEFSCO models. This is shown by the fact that R2 went from 0.9494 to 0.9290 to 0.9903, which is an increase of 4.5 % and 6 %.
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Spatiotemporal variations of sand hydraulic conductivity by microbial application methods
(2024-01-01)
Kamchoom, Viroon
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Khattiwong, Thiti
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Treebupachatsakul, Treesukon
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Keawsawasvong, Suraparb
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Leung, Anthony Kwan
The spatiotemporal distributions of microbes in soil by different methods could affect the efficacy of the microbes to reduce the soil hydraulic conductivity. In this study, the specimens of bio-mediated sands were prepared using three different methods, i.e. injecting, mixing, and pouring a given microbial solution onto compacted sand specimens. The hydraulic conductivity was measured by constant-head tests, while any soil microstructural changes due to addition of the microbes were observed by scanning electron microscope (SEM) and mercury intrusion porosimetry (MIP) tests. The amount of dextran concentration produced by microbes in each type of specimen was quantified by a refractometer. Results show that dextran production increased exponentially after 5–7 d of microbial settling with the supply of culture medium. The injection and mixing methods resulted in a similar amount and uniform distribution of dextran in the specimens. The pouring method, however, produced a nonuniform distribution, with a higher concentration near the specimen surface. As the supply of culture medium discontinued, the dextran content near the surface produced by the pouring method decreased dramatically due to high competition for nutrients with foreign colonies. Average dextran concentration was negatively and correlated with hydraulic conductivity of bio-mediated soils exponentially, due to the clogging of large soil pores by dextran. The hydraulic conductivity of the injection and mixing cases did not change significantly when the supply of culture medium was absent.
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Effect of Bacillus subtilis on mechanical and self-healing properties in mortar with different crack widths and curing conditions
(2023-12-01)
Yamasamit, Nattapong
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Sangkeaw, Panisa
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Jitchaijaroen, Wittaya
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Thongchom, Chanachai
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Keawsawasvong, Suraparb
This research aimed to investigate the effectiveness of Bacillus subtilis (B. subtilis) in self-healing cracks in concrete and enhancing concrete strength through microbial induced calcium carbonate precipitation (MICP). The study evaluated the ability of the mortar to cover cracks within 28 days, taking into account the width of the crack, and observed the recovery of strength after self-healing. The use of microencapsulated endospores of B. subtilis was also examined for its impact on the strength of concrete. The compressive, splitting tensile, and flexural strengths of normal mortar were compared to those of biological mortar, and it was found that biological mortar had a higher strength capacity. Microstructure analysis using SEM and EDS showed that bacterial growth increased calcium production, contributing to the improved mechanical properties of the bio-mortar.
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Trapdoor Stability of Drained Cohesive-Frictional Soils Using Terzaghi’s Superposition Method
(2023-04-01)
Shiau, Jim
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Banyong, Rungkhun
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Keawsawasvong, Suraparb
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Kamchoom, Viroon
Most previous trapdoor stability studies were centered on undrained clay in two dimensions in the past few decades. Very few works were reported for cohesive-frictional soils in two- and three-dimensions. This paper sets out to examine the stability of trapdoors in c-ϕ soils under both 2D planar and 3D circular (axisymmetric) conditions using a superposition method that is similar to Terzaghi’s bearing capacity coefficients approach. Using lower bound and upper bound limit analysis with finite elements, the proposed three coefficients (Fc, Fs, and Fγ) are determined with respect to a series of parametric changes of depth ratios and soil internal friction angles. Novel design charts and tables are presented, and several examples are provided to show how to use the three coefficients to evaluate soil stability under planar and circular trapdoors. The numerical results presented in the paper should be of interest to the geotechnical engineering community.
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The impact of tree transpiration on the safety and serviceability of pavement under seasonal variations
(2023-01-01)
Yuliana
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Apriyono, Arwan
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Leung, Anthony Kwan
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Keawsawasvong, Suraparb
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Kamchoom, Viroon
Roadway trees planted as barriers reduce traffic noise and particle pollution in cities. However, tree roots may alter the soil's moisture content, resulting in uneven soil subsidence and maintenance issues for neighbouring structures. This study determined the safe distance between trees and pavement by investigating the effects of transpiration on pore water pressure (PWP) and pavement subsidence under seasonal variations. The root water uptake was simplified in a finite element model using multiple hydraulic head boundaries and validated using field observations. A hypoplastic model was used to model non-linear behaviour and plastic strain accumulation in unsaturated soil. Evergreen trees can reduce PWP by 72% during the dry season and 84% during the wet season, compared to bare soil. The subsidence did not decrease linearly with the distance away from trees under a rigid and impermeable pavement structure. The maximum bending moment was influenced by the distance between trees and pavement with the highest value occurring when trees were located near the pavement (up to five times the bending moments on pavement without trees). Our findings suggest that the pavement is at risk of experiencing structural failure if trees are located within 0.4 times their height away from the pavement.

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