13474 research outputs found
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Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat
No full textIn response to worsening urban traffic congestion, metro tunnels have emerged as a
solution to ease pressure on road networks. Shield machines, like earth pressure balance
and slurry machines, are pivotal in modern tunnel construction. However, twin tunnel
construction in urban areas commonly faces surface settlement (SS) issues, which
threaten nearby structures. Traditional empirical formulas for SS estimation are limited
to specific soil types and lack consideration of other factors. To overcome these
limitations, this study introduces a comprehensive approach that combines 3D numerical
analysis and machine learning to predict SS during twin tunnel excavation. The 3D
numerical analysis factors in construction stages, tunnel geometry, and operational
parameters while incorporating in-situ and lab test results to establish engineering soil
parameters. Validation against field measurements yields R2 values of 0.94 and 0.96 for
the first and second bored tunnels. While 3D numerical analysis provides accurate SS
estimates, it is time-consuming. To enhance prediction efficiency, validated numerical
models serve as the foundation for data generation. This dataset, alongside key parameters
like cover-to-depth ratio, pillar width, soil stiffness, cohesion, friction angle, and
overburden-to-face pressure ratio, integrates into a machine learning framework using a
theory-guided approach. Conditional Tabular Generative Adversarial Networks
(CTGAN) generate additional data from 20% of the 3D numerical analysis results. The
study primarily focuses on tree-based techniques, including Random Forest (RF),
Adaptive Boost (ADABoost), Gradient Boosting Tree (GBT), Extreme Gradient
Boosting (XGBoost), Light Gradient Boosting (LGBoost), and Categorical Gradient
Boosting (CatBoost). Comparative analyses highlight CatBoost as the most accurate SS
predictor among all machine learning (ML) models. Besides, in comparison with the
CTGAN data generated for the ML analysis, data generated from the finite element model used in the ML analysis has outperform the prediction than the CTGAN of synthetic and
hybrid data. This is due to the data generated from the numerical model possess the
pattern for the ML algorithm ease of prediction. In addition, Coati Optimization
algorithm, Particle Swarm Opimisation (PSO) and Bayesian Optimsiation (BO) are
integrated to identify optimal parameters and minimize settlement during twin tunnel
excavation and GBT with the optimisation algorithm has shown consistent capability
identifying the least SS induced by twin tunnels Keyword
Performance evaluation and prediction analysis of a novel catalytic combustion heating technology in an open cold emergency environment / Qin Mingyuan
No full textProviding comfortable heating solutions for people working, living, and engaging in activities in open, semi-open, and large cold spaces presents numerous challenges, including enhanced resistance to severe weather, the facilitation of efficient heat transfer, and minimizing energy consumption. Traditional indoor heating technologies are often impractical due to their heavy reliance on the power grid. Catalytic combustion technology, with low-temperature operation, high efficiency, and cleanliness, is seen as a solution to above challenges. Therefore, based on disaster-induced cold scenarios, human comfort levels, energy utilization methods, and emergency heating requirements, this study proposes an innovative catalytic combustion emergency heater (HC). Initially, the experimental studies assessed the catalytic and combustion performance of the heater. Compared to commercial catalysts, this heater demonstrated significant enhancements in catalyst activity and particle size uniformity. At an optimal gas flow rate of 1 L/min, the combustion efficiency reached as high as 99%. The emissions of pollutants such as nitrogen oxides and carbon monoxide were below the detection limit of 0.01%. The heater still could successfully cold start at an ambient temperature of -30°C. Subsequently, the heater’s continuous heating performance was evaluated by collecting skin temperature and subjective thermal evaluations. In a wind-chilled environment of -10°C to 15°C, the mean skin temperature was maintained between 30.5°C and 35.6°C, with marked improvements in subjective evaluation of 0.65 units. Comparative analyses were further conducted among the HC, a porous medium infrared heater (HPM), and a quartz tube infrared heater (HQT). Only the HC's infrared spectrum matches the absorption peaks of human skin and clothing, leading to a more significant elevation in skin temperature. Moreover, HC's energy consumption and carbon emissions were just 13% and 34% of HPM's, and 4% and 0.02% of HQT's, respectively. Furthermore, an intermittent heating strategy was developed using the orthogonal testing. By establishing the 'Corrective Power' index for intermittent heating, CPinterm, the optimal strategy was determined to have a heating distance of 40 cm, a heating time of 5 min, and an intermittent time of 5 min. This approach achieves thermal comfort while further reducing energy consumption by 50%. Finally, to enable the heater to be more intelligent, a human-machine interactive heating strategy was established. Five machine learning algorithms were compared to construct predictive models. The results indicated that the Random Forest model ensured the shortest computation time and achieved the highest accuracy of 0.84. This study not only presents a method for maintaining vital signs and comfort through a heat source but also lay the groundwork in modeling details and theoretical basis for future intelligent control devices
Fabrication of metal matrix nanocomposite surface on WE43 using friction stir processing for biomedical implant application / Wu Bo
No full textMagnesium (Mg) alloys are favorable for biomedical implants because of their excellent biocompatibility, biodegradability in physiological environment, similar density and Young’s modulus to natural bone, becoming a new generation biodegradable medical implant material. However, the uncontrollable degradation rate in biological environment and bacterial infection restrains their medical application as implant materials. Hence, surface modification techniques are being used to improve the hardness, bio-corrosion, in-vitro biocompatibility and antibacterial properties of Mg-based alloys. In the present work, as a promising surface modification method due to its cost-effective and pollution-free characteristics, friction stir processing (FSP) was utilized to realize surface modification of Mg alloy WE43 with reinforced particles. Initially, the influence of rotational speed, traverse speed and number of FSP pass on the microstructure, stirring zone morphology and hardness behavior of the WE43 alloy were optimized to develop defect-free surface layer on the WE43 alloy. Further, to improve the degradation rate, WE43 reinforced with single nano-hydroxyapatite (nHA) particles was fabricated. Later, the bioactivity, in-vitro cytocompatibility and in-vitro antibacterial properties of WE43 reinforced with hybrid nanocomposites of nHA doped with nano-silver (nAg) for enhanced biocompatibility and osseointegration in orthopaedic implants were verified. Reinforced nHA and nAg particles were filled in a groove at surface of the WE43 matrix. The experiments were performed for different weight percentages of nHA and nAg particles. Microstructural and phase analysis of FSPed samples were observed by OM, SEM with EDS, EBSD and XRD. Corrosion properties were evaluated by electrochemical corrosion test and immersion test. Wettability test and in-vitro bioactivity behavior were performed on all FSPed WE43/nHA composites. In addition, for FSPed WE43/nHA/nAg composites, in-vitro antibacterial test was investigated against Escherichia coli and Staphylococcus aureus bacteria. In-vitro cytotoxicity test was exposed to mouse calvarial preosteoblasts and evaluated using CCK-8 assay. The results showed that FSP is a feasible method to refine the microstructure and improve the properties of WE43 alloy. The microstructure was refined and defect-free WE43 surface metal matrix composites were developed at 1250 rpm and 30 mm/min. Dynamic recrystallization is responsible for the creation of fine equiaxed grains in the stirring zone. After three passes, the FSPed WE43-3P alloy and WE43/nHA-3P composite have the smallest grain size (2.63 and 1.88 μm), which were reduced by 94.29% and 95.92% compared to base metal, respectively. Additionally, the microhardness of FSPed WE43/nHA-3P composite was 105.59 HV increased by 135%. The reinforced HA and Ag particles underwent fragmentation and redistribution, resulting in improved corrosion resistance and lower degradation rate. The wettability test showed an improvement in contact angle and surface energy for FSPed samples. The atomic ratio of Ca/P after immersion 7d reached 1.61 which indicates superior bioactivity for FSPed WE43/nHA/nAg composite. In-vitro cytotoxicity test and in-vitro antibacterial test proved nAg has an impact on hindering bacterial growth on the surface. These results indicate that the grain refinement by FSP and introduction of nHA and nAg particles play a significant role in degradation rate, in-vitro biocompatibility and antibacterial of WE43 alloy for biomedical applications
Synthesis, characterization and CO2 adsorption performance analysis of MgO functionalized activated carbon from palm kernel Shell / Jayaprina Gopalan
No full textIn recent years, there has been a growing interest in solid adsorbents derived from biomass
for CO2 adsorption due to their carbonaceous properties which allow for modifications to
enhance selectivity towards CO2 in flue gas. Therefore, this study aimed to use innovative
and sustainable approach to develop activated carbon (AC) for CO2 adsorption using palm
kernel shells (PKS) as the precursor. The PKS were subjected to pyrolysis, and then
activated with potassium hydroxide to enhance the porosity and surface area of the
material. The properties of raw PKS adsorbents were further modified using magnesium
oxide (MgO) to enhance the adsorption capacity, selectivity, and the potential for
regeneration. The physicochemical analysis shows that the chemical activation has
increased the surface area of the AC where the PKS-AC had a surface area of 1086 m2/g
which was significantly higher compared to PKS-Char (435 m2/g) and PKS-AC-MgO
(418 m2/g). Although the binding of MgO in PKS-AC-MgO led to a decrease in the
surface area affected by pore blockages, this material demonstrated the most significant
micropore volume (0.29 cm²/g) and pore diameter (2.8 nm) compared to raw PKS. The
functional group analysis confirmed the impregnation of MgO in PKS-AC, as the
transmittance band at 861 cm-1 and 617 cm-1 were assigned to metal oxygen bonding of
Mg-O. Additionally, thermogravimetric analysis showed that all the PKS-adsorbent have
a good thermal and mechanical stability at higher temperatures, up to 500℃.
The CO2 adsorption performance analysis revealed that PKS-AC-MgO has highest
adsorption capacity of 155.35 mg/g at the lowest temperature of 25°C and 5 bars,
compared to PKS-AC (149.63 mg/g) and PKS-Char (138.19 mg/g). On the other hand, PKS-AC-MgO also shows enhanced performance at 50℃ with 117. 5 mg/g of adsorption
capacity. Similarly, at a higher temperature of 75℃, the PKS-AC-MgO adsorbent also
achieved 92.4 mg/g of adsorption capacity which is 48 % higher than the PKS-AC. This
suggested the greater synergistic effect between the PKS-AC and MgO at elevated
temperatures. Isotherm analysis indicated the presence of both physisorption and
chemisorption of CO2 for all the PKS- adsorbents developed in this study. Langmuir
model was best fitted for PKS-AC-MgO with R2 of 0.9916, which described the reaction
due to restriction to monolayer formation. Thermodynamic studies showed a negative
value of Gibbs free energy, enthalpy, and entropy indicating that the adsorption process
of PKS-AC-MgO was spontaneous and favorable at 25°C. The economic analysis showed
also shows that PKS-AC-MgO had a specific cost of $1,977 per tonne, which was 20%
less than commercial AC.
In summary, this study reveals the effectiveness of a novel approach in CO2 adsorption
by utilizing AC impregnated with magnesium oxide developed from palm kernel shells
Strengthening mechanisms in friction stir alloying of AZ61 magnesium alloy and mild steel with Cu-CNT additive / Mohammad Ashraf Ariffin
No full textDissimilar joining between lightweight magnesium (Mg) alloys and steel is essential to produce lighter vehicles, improve fuel efficiency, and reduce carbon emissions. However, the joining of Mg to steel is impractical due to the immiscible properties between these metals. In this experiment, friction stir alloying (FSA) with copper (Cu) and carbon nanotubes (CNT) additives is proposed to solve this problem. The additive, consisting of different wt.% of CNT in Cu powder was first added into the gap between the workpieces and then friction stir welding (FSW) was performed at varied traverse speeds and constant rotational speed. After the joining, microstructure characteristics and mechanical properties of Cu-CNT reinforced Mg-steel joints were investigated. Transmission electron microscopy (TEM) analysis of the Mg-steel joint revealed the formation of an intermetallic compound (IMC) at the interface of the joint. Further analysis by x-ray diffraction (XRD) showed a dominant presence of Mg2Cu IMC, which indicated the interdiffusion of Cu into Mg element to establish the bonding. The presence of CNT inside the Mg matrix which was confirmed by TEM further contributed to the strengthening mechanism of the joint. Tensile and microhardness results revealed a notable enhancement of joint mechanical properties when Cu-CNT additive was added as compared to specimens with only Cu additive, and specimens without additive. The enhanced tensile strength and microhardness of the Cu-CNT reinforced Mg-steel joint was attributed to the dispersion of CNT inside the Mg matrix, which induced dislocations in the surface region, therefore improving the mechanical properties of the joint
Synthesis and characterization of eggshellderived hydroxyapatite by microwave-assisted wet chemical precipitation method / Goh Kian Wei
No full textNowadays, the demand for biomaterials for clinical applications is increasing. Hydroxyapatite (HA) is one of the prevailing biomaterials having a similar chemical composition and crystalline structure for bone regeneration. The high calcium content of biowaste chicken eggshells has been used to synthesize HA with the help of microwave heating. In this research, eggshell-derived HA was successfully synthesized using a simple wet precipitation method assisted by microwave irradiation. Using the microwaveassisted wet precipitation method, HA powders were initially synthesized at various Ph values of 8, 9, 10, 11 and 12 coupled with a lower microwave power (700 W). Optimized HA powders were then determined by calcining at various irradiation times (5, 10, 15, 20, and 30 minutes). Structural characterizations of the derived powders were performed by X-Ray Diffractometer (XRD), Fourier Transform Infrared Spectroscopy (FTIR), Field emission scanning electron microscope (FESEM), and Energy-Dispersive X-Ray Spectroscopy (EDX). The results showed that the pH value and irradiation time were the important parameters in altering the particle size and morphology of HA. The crystallite sizes of eggshell-derived HA powders were calculated using the Scherrer equation and had a similar trend with values obtained from the William-Hall plot. FESEM images showed that a well-formed needle-like HA has an average crystallite size of approximately 10 to 15 nm in width and 60 to 80 nm in length at an optimum pH of 10. In addition, the smallest HA particles of about 22 nm were formed when irradiated for 15 minutes. XRD, FTIR, and EDX analysis revealed that the utilization of biowaste chicken eggshells as a calcium source via microwave-assisted precipitation method was effective in synthesizing stoichiometric HA particles. As compared to the literature, this work clearly confirmed that optimized needle-like HA powder could be obtained at pH 10 with a relatively low microwave power of 700 W for 15 minutes. Furthermore, the dense HA samples were prepared by optimum as-prepared HA powder in a modified domestic microwave oven and were characterized at different sintering temperatures between 900°C and 1200°C. The results revealed that the pure HA phase remains stable up to 1200°C. The sintered HA sample at 1200°C possessed the highest values in bulk and relative density, which were 3.0 g/cm3 and 95.1%, respectively, coupled with the larger grain size of 1.8 μm. Besides, maximum Vickers microhardness and fracture toughness values of 4.1 GPa and 0.90 MPa·m1/2, respectively, were achieved for dense HA samples at 1200°C. These findings demonstrated there is a difference in the sintering behavior of synthetic HA depending on the sintering temperature. Additionally, the modified domestic oven could be successfully used to synthesize HA with excellent mechanical properties
Mechanical response of bioresorbable poly (Glycolide-co-caprolactone) suture under monotonic and non-monotonic loadings / Low Yan Jie
No full textBioresorbable sutures are crucial to alleviate any forces acting on the wound edges and to provide sufficient mechanical support to the injured tissues throughout the wound healing process. Choosing the right suture can improve wound recovery and the quality of life for patients. However, the failure of surgical sutures can occur due to suture breakage, knot breakage, knot untying, and knot slippage, which are related to the stress state in the suture. Therefore, it is necessary to understand the mechanical behavior of sutures to accurately predict their stress state during service. Along these lines, the present work investigates the mechanical responses of non-knotted and knotted poly(glycolide-co-caprolactone) (PGCL) surgical sutures under monotonic and non-monotonic loadings. The first part of this study focuses on the stress-strain response of the PGCL suture under uniaxial monotonic, cyclic, and stress relaxation loadings. Results indicated that the PGCL suture exhibits non-linear stress-strain response and strong inelastic behaviors such as hysteresis, stress-softening, permanent set, and viscoelasticity. Increasing the strain rate from 0.0001 s-1 to 0.1 s-1 resulted in notable improvements: load at break from 22.47 N to 30.44 N, overall stiffness from 3.15 N/mm to 3.92 N/mm, ultimate tensile strength from 288.50 MPa to 383.48 MPa, initial modulus from 232.98 MPa to 367.34 MPa. The gauge length was observed to influence both monotonic and cyclic responses but did not impact the stress relaxation response. In the case of knotted samples, the results showed that the mechanical behavior of all knotted samples depended on the strain rate, regardless of the number of throws. Knots significantly affected the stress-strain response of the suture, resulting in lower load and strain at break. Decreasing the strain rate in knotted samples resulted in increased elongation at break, load at break, ultimate tensile strength, strain at break, and toughness, but decreased overall stiffness and initial modulus. Additionally, an increased number of throws resulted in decreased elongation, load, stiffness, ultimate tensile strength, strain at break, and toughness, indicating the role of stress concentration in the suture due to the presence of a knot. X-ray powder diffraction (XRD) spectra analysis showed that PGCL sutures undergo strain-induced crystallization, which is dependent on the strain level and loading and relaxation durations. The inelastic behaviors observed in PGCL sutures are due to the combined effect of stress relaxation and SIC. A schematic illustration of the conformational change of polymer chains in PGCL sutures was proposed to describe the relationship between stress relaxation and SIC during loading and relaxation processes. The second part of the work focuses on the stress analysis of the PGCL surgical suture using finite element simulation. PGCL suture was assumed to obey linear viscoelastic constitutive behavior, thus can be described by a simple Prony series. The relevant material parameters were subsequently identified from relaxation data, and two sets of Prony series parameters were used to study the phenomenon of creep in surgical sutures, which leads to knot untying and slippage. A single strand solid model was employed to simulate the creep of PGCL suture under different sustained loads, enabling a comparison of creep strain and rate. The results highlighted the significance of these factors, even in non-knotted configurations
Exploring year 11 IGCSE students critical thinking in learning genetics using a virtual biology laboratory / Darishini Sugumar
No full textThis qualitative study investigates the exploration of critical thinking skills among Year 11 IGCSE students in genetic learning using virtual biology laboratory. The study addresses the lack of critical thinking skills observed in genetic learning among IGCSE students in secondary international schools. Six Year 11 IGCSE students from an international school in Ipoh were selected using purposive sampling based on willingness to participate and ICT grades. Data was collected through structured group interviews and field notes from observations. Thematic analysis was employed for data analysis. The Three themes were emerged based on the data analysis contributing to the exploration of critical thinking skills: knowledge construction, evaluating reasoning, and decision-making. Positive perceptions regarding the use of virtual labs were identified, that are usability and comprehensibility which could positively impact critical thinking skills, along with negative perceptions which are limited real world skills and technical issues that offer areas for improvement. Based on the findings, enhancing problem-solving skills through knowledge construction, evaluating reasoning, and decision-making can effectively promote critical thinking skills among Year 11 IGCSE students in genetic learning using virtual biology laboratory. Positive perceptions can be leveraged to enhance critical thinking skills, while negative perceptions offer opportunities for refinement in the use virtual laboratory. The implications include improved problem-solving abilities and application of genetic knowledge
Language learning strategies used by Chinese EFL students / Xiaoshan Sun
No full textThis research aimed to examine the frequency of Language Learning Strategies (LLSs) usage by Chinese English as a Foreign Language (EFL) students and the factors which might impact the selection and utilization of LLSs. The “Strategy Inventory for Language Learning (SILL)”, version 7.0 for ESL/EFL learners (Oxford, 1990) and a background questionnaire were utilized as research instruments to collect the required data. The convenience sampling method was employed to enlist 507 Chinese EFL students from Xi’an International Studies University. The Statistical Package for the Social Sciences (SPSS) version 26.0 was employed to analyze the acquired research data. The findings indicated that Chinese EFL learners utilized overall LLSs at a medium level, and the indirect strategies were deployed more often than direct ones. Additionally, compensatory strategies were employed most frequently, while memory strategies were utilized least commonly. The results also demonstrated that the utilization of overall LLSs was impacted by age, gender, race, major, motivation level, years of study and the interaction between each two factors (some of the 10 influentialfactors), whereas the others of the 10 influencing factors and the interaction of every two of the other factors had no effect on the usage of overall LLSs. Furthermore, the research findings revealed that the employment of some of the six categories of LLSs specified in SILL was affected by some of the 10 influencing factors and the interplay of every two factors (some of the 10 influential factors). However, the application of some of the six types of LLSs was not influenced by the others of the 10 influential factors and the interplay between each two of the other influencing factors. Besides, the current study not only offered some significant implications for EFL teachers, students and other researchers, but also provided some useful and constructive suggestions for future relevant studies
Two step synthesis and activation of hydrothermally pre-treated lignocellulosic residues for removal of heavy metals from single solute system / Shobana Sinniah
No full textApplication of commercial activated carbon derived from nonrenewable fossil fuel sources as adsorbent materials is restricted due to its’ high cost involved in preparation process. This constraint has thus prompted the development of highly cost-effective activated carbons (ACs), resulting in the utilization of Lignocellulosic biomass residues (LSM). These resources are not only renewable, but also abundantly available. The utilization of Lignocellulosic biomass waste residues (LSM) will not only contribute to the resolution of difficulties related with the dumping of such components into the environment but will also aid in the conversion of these materials into value added products; like char and activated carbons (ACs), bio-oil and bio-gas. Synthesized activated carbon (ACs) can be used as versatile low-cost adsorbent materials for water treatment for purifying the heavy metals from wastewater. In this study, surface-engineered activated carbon (ACs) was synthesized from the lingo-cellulosic waste of Durio zibethinus (durian wood) sawdust (DWS) and Adansonia kilima (Baobab) seed powder (BSP) using hydrothermal carbonization (HTC) followed by pyrolysis in the presence of a mild activating agent of K2CO3 for activation in the second step. The first step of carbonization was carried out in presence of water at a lower temperature of 80°C to yield hydrochar. Water is considered as a green catalyst for carbonization, and the resulting hydrochar can be used to produce functional activated carbon (ACs). It was determined that the process input variables of pyrolysis temperature (A1), residence time (B1), and ratio (C1) had the greatest influence on the production of superior quality carbon with the highest removal efficiencies (β1) for Copper (II) cations from waste effluents, carbon yield percentages (β2) and fixed carbon percentages (β3). The analysis of variance (ANOVA) was utilized to generate appropriate mathematical models, which were then subjected to proper statistical analysis to determine their accuracy. Response Surface Methodology (RSM) relying on the Box Behnken design (BBD) was implemented for experimental design. The surface area of the carbonized hydrochar sample (DSWC and BSPC) and the optimized carbon sample (DSWAC and BSPAC) with porous texture were estimated using Brunauer, Emmett, and Teller (BET) adsorption/desorption curves based on the nitrogen (N2) isotherm. With the help of Field Emission Scanning Electron Microscopy (FESEM), it was possible to observe the surface morphological structure. Thermogravimetric analysis (TGA) was performed to ascertain the thermal stability of the synthesized samples. The ultimate method was used to determine the change in carbon content of the samples. Surface functional groups were determined using FTIR analysis. The BET isotherm showed an increase in the sorption capacity of DSWAC and BSPAC for pollutants in a liquid phase system. Hydrochar (BSPC and DSWC) samples were microporous with relatively lower surface area. BET analysis of DSWAC and BSPAC showed that micropores with a specified fraction of mesopores were present in the activated carbon. Increased fixed carbon retention combined with lower levels of moisture and ash residues results in the adsorbent activated carbons (ACs) of (DSWAC and BSPAC) has made them a better adsorbent material for copper (II) cations removal from lab-based waste synthetic water