Compaction Parameters Research Articles

ETUDE COMPARATIVE DES CARACTERISTIQUES DU SOL PAR STABILISATION AU CIMENT ET A LA CHAUX EN CONSTRUCTION ROUTIERE : CAS DU SOL DE BUGANGA A MINOVA/PROVINCE DU SUD KIVU/RDC

This work focused on the comparative study of soil stabilization with cement and lime. The purpose of this study is to carry out a comparative study of the stabilization of soil with cement and lime in order to increase the bearing capacity of the Minova soil to enhance this soil for use in road constructions (base layers and road bed) but also to contribute to the identification of this soil by studying the influence of stabilizers on the characteristics of the Minova soil. To achieve the expected results. Tests for the determination of the parameters of identification, compaction (modified Proctor) and bearing capacity (CBR) on the soil of BUGANGA in its natural state and after stabilization with cement and lime. The results obtained showed that the soil of BUGANGA is made up of 47.25% of the fines, therefore classified as fine soils. As far as the type of soil is concerned, it is a sandy clay with little plasticity characterized by a low bearing capacity (CBR=5.37%) with a medium swelling. Thus, due to its low load-bearing capacity, the BUGANGA soil has been stabilized to increase its bearing capacity. The results obtained showed that the addition of cement and lime increases the bearing capacity of the BUGANGA soil. Hence, by adding different contents of cement and lime, the CBR increased from 5.37%. In various stabilization formulations with lime and cement, BUGANGA soil is suitable for use in pavement beds.

Cutting-edge Bioinformatics strategies for synthesizing Cyclotriazadisulfonamide (CADA) analogs in next-Generation HIV therapies

Cyclotriazadisulfonamide (CADA) is a macrocyclic compound known for its unique mechanism in inhibiting HIV infection by downregulating the CD4 T-cell receptor, a crucial entry point for the virus. Unlike other antiretrovirals, CADA exhibits activity against a wide range of HIV strains, as all HIV variants require CD4 binding for infection. Furthermore, CADA has shown a synergistic effect with clinically approved anti-HIV drugs, offering potential for enhanced therapeutic strategies (Vermeire & Schols, [65]). One proposed mechanism for CADA’s inhibition of the CD4 receptor involves blocking the gates of the Sec61 channel, thereby preventing its translocation. However, CADA suffers from poor solubility and bioavailability. To address this, the study aimed to design CADA analogs with improved binding to the Sec61 channel, enhanced bioavailability, and reduced toxicity. The analogs were designed using SeeSAR, with Avogadro and Meeko used for 3D configuration and pseudoatom placement, respectively. AutoDock Vina version 1.2.4 was employed to predict the binding energies of these analogs. Of the 113 analogs designed, 93 demonstrated a more negative binding energy to the Sec61 channel compared to CADA. Structure-binding energy analyses were done to the top-binding analogs to show favorable structural modifications. Enzyme-ligand interactions were analyzed to elucidate the forces contributing to these binding energies. Additionally, 33 of the 113 analogs were deemed bioavailable using a bioavailability criteria specific for macrocycles. Toxicity predictions using PASS Online and StopTox identified analogs JGL023, JGL024, JGL032, and JGL047 as potential drug candidates. Molecular dynamics simulations using Gromacs-2020.4 revealed that JGL023 and JGL032 exhibited the most favorable binding to the Sec61 channel, as determined by evaluating ligand and residue flexibility, compactness, contact frequency, motion pathways, free energy, and other relevant parameters. Synthetic routes for these four analogs were proposed for future studies. The results of this study offer a new perspective on developing drugs to inhibit HIV entry.

ABAQUS-based research on the parameters of highway subgrade vibratory compaction and vibration wave propagation laws

Vibratory rollers are generally used in the process of highway subgrade compaction. In the paper, the vibratory roller—subgrade finite element model was established to simulate the field construction by using ABAQUS. We used Hilbert–Huang Transform to analyze the compaction in the field test from the time–frequency domain. By changing the parameters of the vibratory roller and the filler, the comprehensive influence of the parameters such as the elastic modulus of the filler, rolling speed, excitation force, vibration frequency and thickness of the filler on the compaction quality of the subgrade was investigated. We studied the propagation pattern of vibration waves in three-dimensional space. The study shows that the signals of different frequency bands in the Hilbert spectrum represent the compaction degrees of fillers in different zones. The peak acceleration generally decreases with the increase of horizontal and vertical distance, but there is an increase at the boundary of the vibration field. There is an optimal combination of the excitation force, vibration frequency and thickness of the filler. The vibration waves propagate in the form of an ellipsoid in three dimensions, and the amplitude decreases with distance.

Effect of multicollinearity in assessing the compaction and strength parameters of lime-treated expansive soil using artificial intelligence techniques

Effect of multicollinearity in assessing the compaction and strength parameters of lime-treated expansive soil using artificial intelligence techniques

Relativistic model for anisotropic compact stars in embedding class-I spacetime

In the present article, we introduce a completely new regular model for static, spherically symmetric celestial fluid spheres in embedding class I spacetime. In this regard, needfully, we propose a new suitable metric potential e λ(r) to generate the present model. The various analyses on energy density, pressure, anisotropic factor, mass, compactness parameter, redshift, and energy condition make sure the model is physically viable on the ground of model stars Vela X-1, Cen X-3, SMC X-4, and LMC X-4. The reported solutions also respect the equilibrium state by satisfying the Tolman–Oppenheimer–Volkoff (TOV) equation and ensure stability by satisfying the causality condition, condition on the adiabatic index, and Harrison–Zeldovich–Novikov condition. The generated M − R graph matches the ranges of masses and radii for the model compact stars. Additionally, this study provides estimates of the moment of inertia based on the I − M graph.

Re-Examination of the Sel’kov Model of Glycolysis and Its Symmetry-Breaking Instability Due to the Impact of Diffusion with Implications for Cancer Imitation Caused by the Warburg Effect

We revisit the seminal model of glycolysis first proposed by Sel’kov more than fifty years ago. We investigate the onset of instabilities in biological systems described by the Sel’kov model in order to determine the conditions of the model parameters that lead to bifurcations. We analyze the glycolysis reaction under the circumstances when the diffusivity of both ATP and ADP reactants are taken into account. We estimate the critical value of the model’s single compact dimensionless parameter, which is responsible for the onset of reaction instability and the system’s symmetry breaking. It appears that it leads to spatial inhomogeneities of reactants, leading to the formation of standing waves instead of a homogeneous distribution of ATP molecules. The consequences of this model and its results are discussed in the context of the Warburg effect, which signifies a transition from oxidative phosphorylation to glycolysis that is correlated with the initiation and progression of cancer. Our analysis may lead to the selection of therapeutic interventions in order to prevent the symmetry-breaking phenomenon described in our work.

Linear Programming with Unitary-Equivariant Constraints

Unitary equivariance is a natural symmetry that occurs in many contexts in physics and mathematics. Optimization problems with such symmetry can often be formulated as semidefinite programs for a dp+q\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$d^{p+q}$$\\end{document}-dimensional matrix variable that commutes with U⊗p⊗U¯⊗q\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$U^{\\otimes p} \\otimes {\\bar{U}}^{\\otimes q}$$\\end{document}, for all U∈U(d)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$U \\in \ extrm{U}(d)$$\\end{document}. Solving such problems naively can be prohibitively expensive even if p+q\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$p+q$$\\end{document} is small but the local dimension d is large. We show that, under additional symmetry assumptions, this problem reduces to a linear program that can be solved in time that does not scale in d, and we provide a general framework to execute this reduction under different types of symmetries. The key ingredient of our method is a compact parametrization of the solution space by linear combinations of walled Brauer algebra diagrams. This parametrization requires the idempotents of a Gelfand–Tsetlin basis, which we obtain by adapting a general method inspired by the Okounkov–Vershik approach. To illustrate potential applications of our framework, we use several examples from quantum information: deciding the principal eigenvalue of a quantum state, quantum majority vote, asymmetric cloning and transformation of a black-box unitary. We also outline a possible route for extending our method to general unitary-equivariant semidefinite programs.

Review and analysis on numerical simulation and compact modeling of InGaZno thin-film transistor for display SENSOR applications

Recent years have seen an increase in the use of Organic Thin Film Transistors (OTFTs), with applications ranging from flexible, low-cost displays to organic memory, RFID tag components, low-cost electronic appliances, and polymer circuits and sensors. Thin-film transistors (TFTs) have developed into a critical business on the grounds levels to their wide scope of utilizations in display; Radio-Frequency ID labels (RFID SENSOR), intelligent computation, and different areas. Reduced models are basic in the turn of events and execution of TFTs on the grounds that they overcome any barrier between the manufacture cycle and circuit plan. The motivation behind this exploration is to assemble a hypothetical structure for nanoscale TFT models made of polysilicon, indistinct silicon, natural, and In-Ga-Zn-O (IGZO) semiconductors. Extraordinary consideration is paid to surface-expected based smaller models of silicon-based TFTs. Surface-potential-based compact models and parameter extraction approaches were presented based on our knowledge of charge transport characteristics and TFT needs in organic and IGZO TFTs.

Predictive Modelling and Functional Group of Clay Soil Treated with Steel Slag and Calcium Carbide Residue

Swell-shrink subgrade soils like clay are rich in sulphate and exhibit a high rate of volume change by swelling and shrinking during wet and dry cycles, respectively, leading to heaves, cracks, and differential settlement of pavement layers. The aim of this study was to establish predictive simulation models and functional group of clay soil treated with steel slag and calcium carbide residue. Physical and geotechnical tests (such as California bearing ratio (CBR), compaction characteristics, and consistency parameters) were carried out on the unstabilised and stabilised clay soil. Using SPSS statistical software (version 23), multiple linear regression analysis was applied to the experimental data that relate CBR to compaction parameters and additive contents (steel slag and calcium carbide residues). The generated models gave a reliable coefficient of determination, R2 , of 0.990, and 0.998, which can be used to successfully predict both unsoaked and soaked CBR of the stabilised clay soil, respectively. Fourier transform infrared spectroscopy (FTIR) analysis was examined on the clay soil, the additives, and the stabilised clay soils. The FTIR analysis showed weak peaks at 1115 and 1103 cm-1 for all the stabilised clay soils, and this revealed that both additives drastically reduced the sulphate content in the clay soil, which consequently reduced the expansion, cracking, and disintegration rates. As a result, the clay soil's chemical bonding was enhanced through physico- chemical mechanisms.

California bearing ratio and compaction parameters prediction using advanced hybrid machine learning methods

California bearing ratio and compaction parameters prediction using advanced hybrid machine learning methods

Machine learning a fixed point action for SU(3) gauge theory with a gauge equivariant convolutional neural network

Fixed point lattice actions are designed to have continuum classical properties unaffected by discretization effects and reduced lattice artifacts at the quantum level. They provide a possible way to extract continuum physics with coarser lattices, thereby allowing one to circumvent problems with critical slowing down and topological freezing toward the continuum limit. A crucial ingredient for practical applications is to find an accurate and compact parametrization of a fixed point action, since many of its properties are only implicitly defined. Here we use machine learning methods to revisit the question of how to parametrize fixed point actions. In particular, we obtain a fixed point action for four-dimensional SU(3) gauge theory using convolutional neural networks with exact gauge invariance. The large operator space allows us to find superior parametrizations compared to previous studies, a necessary first step for future Monte Carlo simulations and scaling studies. Published by the American Physical Society 2024

Analytical Overview of the Methods of Controlling the Parameters of Vibratory Compaction of the Concrete Mixes

Introduction. A historical (retrospective) overview of the evolution and application of the methods of concrete mixture compaction by vibration, as well as an overview of the breakthrough scientific+ advancements in the studied field have been presented. The use of the dry concrete mixes that reduce cement consumption, accelerate the strength gain of concrete, reduce the shrinkage strain and heat emission and increase the strength and durability of products has been proposed. The theoretical and practical issues of vibratory compaction of the concrete mixes, the research on the effect reached by the various vibration modes of the vibrating tables, the issues of choosing an efficient mode of vibration impact during compacting the concrete mixes and optimisation of their parameters have been studied. The vibrating table design, the installation layout of the vibrator’s eccentric weights to obtain a given value of the exciting force and the layout of a vibration module with the directed vibrations have been studied in detail. The criteria of duration of the concrete mixture compaction have been defined, changes of the impact parameters during compacting the concrete mixes have been characterised and technical specifications of the vibrating tables have been defined. In the article considerable attention has been paid to the main parameters of the vibrocompacting machines: frequency, amplitude and acceleration of the working member. Most often, the parameter of intensity is used to assess the efficiency of the vibration impact received by the mixture during the compaction process.Materials and Methods. A mixture that turns into concrete after compaction, setting and hardening was selected for the research. The various methods and parameters of concrete mixture compaction to obtain the high-quality concrete were studied. The impact of the various vibration modes on the process of compaction of concrete mixes was investigated, the criteria for the efficient selection and optimisation of the vibration impact parameters were revealed. The paper presents the criteria for assessing duration of the concrete mixture compaction and describes the changes in the parameters during compaction of the concrete mixes. The technical specifications of the vibrating tables of different types and sizes were also presented. The choice of the vibration compaction mode for the concrete mixture is a complicated task, which includes many parameters.Results. Upon the research, the data on the process of concrete mixture compaction under the impact of vibration forces has been obtained. The process results in the destruction of the structural bonds and weakening the bonds between the particles, which leads to the emergence of a variable stress-strain condition. It has also been found that under such settings, the mineral particles get transferred and a denser packing is formed.Discussion and Conclusion. The resulting denser packing of the concrete mixture particles ensures the undoubted economic advantage due to reduced consumption of a binder without loss of the strength properties of concrete.

Empirical Correlation of Hossaena Town Soil Index Properties with California Bearing Ratio (CBR) Values

California bearing ratio (CBR) is a key input factor in pavement structural design that is used to determine character size, the strength of unbound materials, and subgrade soils. The construction of a straightforward and logical regression model to forecast the CBR of unbound materials as a function of the index properties of the material. This work explains the relationship between compaction parameters and Atterberg limit tests. Laboratory test was conducted to get the independent (percent finer, liquid limit, plastic limit, plastic index, maximum dry density and moisture content), and dependent variables (CBR). A statistical package for social science software (SPSS) used to develop the mathematical model both in single and multiple regression. The viability of using multiple linear regression analysis to relate CBR values to soil index features was investigated. In this study, SPSS is used to examine each independent variable's significance individually. The multiple linear regression analysis was used to create the correlation, which had an eighteen-person sample size and a modest determination coefficient of R2 = 0.821. The CBR has good relation with maximum dry density and optimum moisture content compared to other parameters. This model applicable for small structure in the specified soil type, MH.

Fabrication of High-Performance Asphalt Mixture Using Waterborne Epoxy-Acrylate Resin Modified Emulsified Asphalt (WEREA)

Existing research shows that using waterborne epoxy resin (WER) instead of emulsified asphalt as the binder for cold mix asphalt (CMA) can enhance the rutting resistance, high-temperature performance, fracture performance, and early performance of CMA. In order to eliminate the potential drawbacks such as insufficient strength and low-temperature performance of CMA during application, a novel method was proposed in this study for the preparation of waterborne epoxy-acrylate resin (WER), specifically tailored to modify emulsified asphalt, resulting in waterborne epoxy-acrylate resin emulsified asphalt (WEREA). The modification effect of WER on emulsified asphalt was evaluated through rheological tests and direct tensile tests. A modified design method based on the conventional Marshall design method was proposed to determine the optimal mix proportions, including the key parameters of specimen compaction and curing. The results revealed that the incorporation of WER led to a substantial improvement in the complex shear modulus and a concurrent decrease in the phase angle. When the temperature exceeded 60 °C, the phase angle exhibited a diminishing trend, indicative of a reduced viscosity as temperatures escalated. As the WER content increased, a decrease in the direct tensile strain rate was observed, accompanied by a substantial elevation in direct tensile strength. At various stress levels, the shear strain of WEREA decreases with increased content of WER, indicating that the incorporation of WER can enhance the hardness of emulsified asphalt and improve its deformation resistance. The results from MSCR tests indicate that WER could significantly improve the elasticity and hardness of emulsified asphalt, transitioning it from a viscoelastic material to an elastic material, thereby improving its deformation resistance, resistance to rutting, and high-temperature performance. The results of fatigue life are consistent with those of the amplitude sweep, both reflecting the improvement of resistance to deformation of emulsified asphalt by WER. This indicates that WER has a significant improving effect on the fatigue resistance of emulsified asphalt. Furthermore, the Marshall design tests further confirmed the advantages of WEREA in asphalt mixtures. The optimal preparation for the WEREA mixture was proposed as follows: double-sided compaction for 50 times each, aging at 60 °C for 48 h, optimal moisture content of 5.14%, cement content of 2.5%, and emulsion content of 8.4%. The optimal mix proportions identified through these tests yielded asphalt mixtures with significantly improved stability, reduced flow value, and enhanced rutting resistance compared to the hot-mix asphalt mixture (HMA) of AC-16. These findings suggest that WEREA has the potential to significantly enhance the durability and longevity of asphalt pavements. For future applications, it can be explored for use in producing cold recycled asphalt mixtures. In addition to designing the WEREA mixture according to AC-16 gradation, consideration can also be given to using a gradation with a smaller nominal maximum aggregate size for the application in the surface layer or ultra-thin wearing course.

Study on Characteristics of Soil Profile Stability Indexes in Sakita

This research examines the suitability of soil as infrastructure which can help in the classification and identification of its properties for ideal engineering structures. Sakita, an area in Gesse III as a case study, is a virgin land, allocated for residential buildings. The need to investigate the soil profile in the report area prompted these studies as its physical properties are used for classifying its various engineering applications. These properties indicate qualitative behaviors of soil when subjected to various types of loads. Apart from physical/visual observation made of the soil, trial pits were dug to depths of 0.5m, 1.0m, 1.5m, 2.0m, and 2.5m respectively and disturbed soil samples were taken for tests. The disturbed soil samples obtained were analyzed for grading including mechanical sieve analysis, specific gravity, plastic limit, liquid limit, and bulk density tests. The resistances of the cone against penetration, compaction, consolidation, and permeability properties were also assessed. The detected geotechnical properties varied significantly with depth, except for specific gravity, which did not vary significantly at 0.5 m with depth. Soil samples from all pits consist mainly of poorly sorted gravel and sand with little fineness. They contain a medium- to coarse-grained fraction of sand on average above 85%. The puncture resistance obtained from the cone puncture test ranges from 100 knm2 to 950 knm2. The average safe bearing capacity estimated for the footing using a factor of safety of 3 at a depth of 1 m was not less than 473 km2 anywhere in the study area. The samples from the three locations generally have good compaction parameters, medium to high permeability, and low compressibility. The highest load-bearing capacity is associated with the lateralized basement ceiling. This means that the safety depth for placing infrastructure foundations in the prescribed research area (Sakita) is the depth where it meets the lateralized basement.

Research on a Method for Identification of Peanut Pests and Diseases Based on a Lightweight LSCDNet Model.

Timely and accurate identification of peanut pests and diseases, coupled with effective countermeasures, is pivotal for ensuring high-quality and efficient peanut production. Despite the prevalence of pests and diseases in peanut cultivation, challenges such as minute disease spots, the elusive nature of pests, and intricate environmental conditions often lead to diminished identification accuracy and efficiency. Moreover, continuous monitoring of peanut health in real-world agricultural settings demands solutions that are computationally efficient. Traditional deep learning models often require substantial computational resources, limiting their practical applicability. In response to these challenges, we introduce LSCDNet (Lightweight Sandglass and Coordinate Attention Network), a streamlined model derived from DenseNet. LSCDNet preserves only the transition layers to reduce feature map dimensionality, simplifying the model's complexity. The inclusion of a sandglass block bolsters features extraction capabilities, mitigating potential information loss due to dimensionality reduction. Additionally, the incorporation of coordinate attention addresses issues related to positional information loss during feature extraction. Experimental results showcase that LSCDNet achieved impressive metrics with accuracy, precision, recall, and Fl score of 96.67, 98.05, 95.56, and 96.79%, respectively, while maintaining a compact parameter count of merely 0.59 million. When compared with established models such as MobileNetV1, MobileNetV2, NASNetMobile, DenseNet-121, InceptionV3, and X-ception, LSCDNet outperformed with accuracy gains of 2.65, 4.87, 8.71, 5.04, 6.32, and 8.2%, respectively, accompanied by substantially fewer parameters. Lastly, we deployed the LSCDNet model on Raspberry Pi for practical testing and application and achieved an average recognition accuracy of 85.36%, thereby meeting real-world operational requirements.

Development of machine learning-based standalone GUI application for predicting hydraulic conductivity and compaction parameters of lateritic soils

Hydraulic conductivity and compaction parameters are the key considerations in selecting lateritic soils for engineering construction. Nevertheless, the complexity and high cost of the required tests have driven many contractors and field engineers to skip them, resulting in a succession of engineering structure failures. To overcome this limitation, this study developed machine learning-based standalone GUI application to predict lateritic soils’ hydraulic conductivity (K), maximum dry density (MDD) and optimum moisture content (OMC) from indices including specific gravity, liquid limit, plasticity index, linear shrinkage and fine content. To achieve this goal, the geotechnical properties of three hundred samples, collected using grid sampling method from thirty different lateritic deposits in southwestern Nigeria, were evaluated through laboratory tests. The test results were used to train predictive models using artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and Gaussian process regression (GPR). The models’ performance was compared using coefficient of determination (R2), root mean squared error (RMSE), mean absolute percentage error (MAPE) and mean absolute error (MAE). Based on these performance metrics, ANN demonstrated the best performance (R2 = 0.9835, 0.9797, 0.9999; RMSE = 7.938, 0.252, 2.09E-08; MAPE = 0.288, 1.114, 1.587; MAE = 5.432, 0.169, 1.1E-08) for MDD, OMC and K, respectively, followed by GPR and then ANFIS. Thus, the ANN models were selected and embedded in a standalone GUI application to enhance easy and quick prediction of lateritic soils’ MDD, OMC and K. The validity of the ANN-based standalone GUI application was demonstrated by comparing it favorably to notable regression-based models in the literature.

Static Compaction for Sustainable Geotechnical Solutions: A Comprehensive Study

The objective of this research is to develop an improved uniaxial static compaction method to address the limitations of the traditional Proctor's dynamic approach for soil compaction. This new approach offers reduced labor, enhanced soil density, and increased compactness. The study compares of static soil compaction characteristics with various soil parameters and explores the concept of Equivalent Static Compaction Energy (ESCE). A diverse range of fine-grained soils with varying range of plasticity was investigated, and a significant correlation of compaction parameters attained by static compaction was observed with the corresponding value of static compaction energy, degree of saturation, void ratio, and plastic limit of soil. The research resulted in the creation of constant-energy curves for static compaction, which were compared to dynamic compaction curves from four compaction attempts. From the study, the ESCE corresponding to standard Proctor, reduced standard Proctor, and reduced modified Proctor tests were found to be within the range of 180-340, 155-308, and 532-664 KJ/ m3, respectively. It was also observed for the static compaction method that after reaching the maximum level of compaction, the dry unit weight of the soil specimen remains constant with further increases in compaction energy.

Effects of elevated temperature and treatment duration on selected index and engineering properties of lateritic soils

Lateritic soils are important to various engineering applications, especially in tropical regions, where they serve as key components in road construction, embankments, and other geotechnical structures. This study investigated the combined effects of elevated temperature and heating duration on the index and engineering properties of lateritic soils derived from two distinct parent rocks (charnockite and quartzite) in Ado-Ekiti, Nigeria. Disturbed lateritic soil samples were heated in a furnace at various temperatures (100, 200, 300, and 400 °C) for two designated durations (2 and 3 h). Standard geotechnical tests were conducted to evaluate Atterberg limits, compaction parameters, and unconfined compressive strength. The results showed that elevated temperature led to a decrease in the plastic limit, liquid limit, plasticity index, optimum moisture content (OMC), and UCS for both soils, though the extent varied between the two parent rocks. For instance, at 400 °C for 3 h, the plasticity index decreased by 47.82% for charnockite-derived soil and 55.22% for quartzite-derived soil. At the same temperature for 2 h, it decreased by 38.79% for charnockite-derived soil and 48.92% for quartzite-derived soil. Similarly, UCS decreased by 29.83% for charnockite-derived soil and 25.97% for quartzite-derived soil at 400 °C for 3 h, while at 400 °C for 2 h, UCS decreased by 21.20% for charnockite-derived soil and 23.48% for quartzite-derived soil. Conversely, maximum dry density (MDD) increased with temperature, rising by up to 20.64% for charnockite-derived soil and 14.66% for quartzite-derived soil at 400 °C for 3 h, and by 18.29% for charnockite-derived soil and 12.62% for quartzite-derived soil at 400 °C for 2 h. Longer heating durations (3 h) generally caused more pronounced changes in soil properties compared to shorter durations (2 h). For instance, OMC decreased by 13.41% for charnockite and 14.18% for quartzite at 400 °C for 3 h compared to a 2-h duration. Statistical analyses indicated that temperature had a significant influence on most properties, while the effect of heating duration was less consistent. These findings highlight the need to consider both temperature and heating duration when evaluating the engineering behavior of lateritic soils exposed to elevated temperatures. Practical implications include potential adjustments in construction practices and design parameters for road construction and embankments in regions prone to high temperatures, such as those experiencing frequent forest fires.

A New Porosity Evaluation Method Based on a Statistical Methodology for Granular Material: A Case Study in Construction Sand

Sand porosity is an important compactness parameter that influences the mechanical properties of sand. In order to evaluate the temporal variation in sand porosity, a new method of sand porosity evaluation based on the statistics of target sand particles (which refers to particles within a specific particle size range) is presented. The relationship between sand porosity and the number of target sand particles at the soil surface considering observation depth is derived theoretically, and it is concluded that there is an inverse relationship between the two. Digital image processing and the k-means clustering method were used to distinguish particles in digital images where particles may mask each other, and a criterion for determining the number of particles was proposed, that is, the criterion of min(Dao). The execution process was implemented by self-written codes using Python (2021.3). An experiment on a simple case of Go pieces and sand samples of different porosities was conducted. The results show that the sum of the squared error (SSE) in the k-means method can converge with a small number of iterations. Furthermore, there is a minimum value between the parameter Dao and the set value of a single-particle pixel, and the pixel corresponding to this value is a reasonable value of a single-particle pixel, that is, the min(Dao) criterion is proposed. The k-means method combined with the min(Dao) criterion can analyze the number of particles in different particle size ranges with occlusion between particles. The test results of sand samples with different densities show that the method is reasonable.