Compression Index Research Articles

Improving the Bearing Capacity of Clay Soil Using Plastic Bottle Waste

With the increase in industry and industrial products, quantities of waste have increased worldwide, especially plastic waste, as plastic pollution is considered one of the wastes of the modern era that threatens the environment and living organisms. On this basis, a solution must be found to use this waste and recycle it safely so that it does not threaten the environment. Therefore, this research used plastic waste as an improvement material for clay soil. In this research, two types of tests were conducted, the first of which was a laboratory test, where the undrained shear strength (cohesion), compression index (Cc), and swelling index (Cr) of the improved and unimproved soils were calculated (plastic was added in proportions (0.5, 1, 1.5, 2)%. The second part of the examination was done through physical modeling, where 2% of plastic was used, considered the optimal percentage in this research, and the calculation of the carrying capacity-settlement relationship for both the improved and unimproved soils. Using this percentage of plastic showed an improvement in the relationship between the bearing capacities of soil vs. subsidence, as an increase in the amount of stress was observed from 405 KPa to 459 kPa at 10% of subsidence.

Influence of Cross-Correlation on the Modelled Uncertainty in Stress–Strain Behavior of Soft Clays

Reliability-based design is increasingly being applied to geotechnical problems because it allows the robust consideration of various sources of uncertainty, such as the inherent variability of soil properties. Some soil properties, however, are mutually dependent, and ignoring this cross-correlation may lead to biased estimates of the probability of unsatisfactory performance. Hence, in this study, the Gaussian copula was used to evaluate how the applied cross-correlation or independence between the compressibility properties affects the uncertainty in the stress–strain response of two marine soft clays. Two settlement calculation methods were considered: the compression index and Janbu tangential stiffness methods. The correlation coefficients were defined from the site-specific oedometer data at two extensively studied clay sites, and from a database. The simulated oedometer curves were compared to the observed variability in the site-specific data. The settlements in the clay sublayers were then computed, and different cases were compared by means of boxplots. It is concluded that the Janbu method leads to a significant overestimation of uncertainty in settlement if the cross-correlation between the compressibility parameters is ignored. On contrary, the compression index method seems less sensitive to the assumed correlation structure, and as such, the parameters can be treated as independent in most cases.

Estimating the Climate-Controlled Soil Parameters and the Distorted Mound Shape for Analysis of Stiffened Rafts on Expansive Soils

A stiffened raft is considered one of the efficient foundation systems for lightweight structures resting on expansive soils. Most existing design methods of stiffened rafts require an analysis of the interaction between the raft and the distorted mound shape of the expansive soil. In most design methods, the distorted mound shape is represented in 2D by the edge distance and the maximum differential movement through a nonlinear equation. This study presents a rational method for estimating the climate-controlled soil parameters that are used for estimating the 3D distorted mound shape of the expansive soil from the routine geotechnical tests’ results. These parameters include the equilibrium soil suction, the amplitude of surface suction change, the diffusion coefficient of the soil, the suction compression index, and the active zone depth. The proposed method is explained through its application to calculate the climate-controlled parameters for expansive soils in different locations throughout Saudi Arabia. A parametric study is carried out using a suction diffusion and soil movements program called SUCH to investigate the effect of the climate-controlled soil parameters and raft dimensions on the shape of the distorted mound, maximum differential movement, and edge moisture variation distance. The results of the parametric study are used in a regression analysis to develop an equation for estimating the edge moisture variation distance, which is considered a major barrier to using existing design methods of stiffened rafts as a function of the climate-controlled soil parameters and the aspect ratio of the raft. The findings indicate that the aspect ratio of the raft and the climate-controlled soil parameters have a significant effect on the shape of the distorted mound, its maximum differential movement, and its edge moisture variation distance. Additionally, the proposed equation of the edge moisture variation distance predicts comparable values to that estimated by the program SUCH.

Deep Learning Approach on Prediction of Soil Consolidation Characteristics

Artificial neural network models, crucial for accurate predictions, should be meticulously designed for specific problems using deep learning-based algorithms. In this study, we compare four distinct deep learning-based artificial neural network architectures to evaluate their performance in predicting soil consolidation characteristics. The consolidation features of fine-grained soil have a significant impact on the stability of structures, particularly in terms of long-term stability. Precise prediction of soil consolidation under planned structures is vital for effective foundation design. The compression index (Cc) is an important parameter used in predicting consolidation settlement in soils. Therefore, this study examines the use of deep learning techniques, which are types of artificial neural network algorithms with deep layers, in predicting compression index (Cc) in geotechnical engineering. Four neural network models with different architectures and hyperparameters were modeled and evaluated using performance metrics such as mean absolute percentage error (MAPE), mean squared error (MSE), root mean squared error (RMSE), and coefficient of determination (R2). The dataset contains 916 samples with variables such as natural water content (w), liquid limit (LL), plasticity index (PI), and compression index (Cc). This approach allows the results of soil consolidation tests to be seen more quickly at less cost, although predictively. The findings demonstrate that deep learning models are an effective tool in predicting consolidation of fine-grained soil and offering significant opportunities for applications in geotechnical engineering. This study contributes to a more accurate prediction of soil consolidation, which is critical for the long-term stability of structural designs.

Prediction of the axial compression capacity of stub CFST columns using machine learning techniques.

Concrete-filled steel tubular (CFST) columns have extensive applications in structural engineering due to their exceptional load-bearing capability and ductility. However, existing design code standards often yield different design capacities for the same column properties, introducing uncertainty for engineering designers. Moreover, conventional regression analysis fails to accurately predict the intricate relationship between column properties and compressive strength. To address these issues, this study proposes the use of two machine learning (ML) models-Gaussian process regression (GPR) and symbolic regression (SR). These models accept a variety of input variables, encompassing geometric and material properties of stub CFST columns, to estimate their strength. An experimental database of 1316 specimens was compiled from various research papers, including circular, rectangular, and double-skin stub CFST columns. In addition, a dimensionless output variable, referred to as the strength index, is introduced to enhance model performance. To validate the efficiency of the introduced models, predictions from these models are compared with those from two established standard codes and various ML algorithms, including support vector regression optimized with particle swarm optimization (PSVR), artificial neural networks, XGBoost (XGB), CatBoost (CATB), Random Forest, and LightGBM models. Through performance metrics, the CATB, GPR, PSVR and XGB models emerge as the most accurate and reliable models from the evaluation results. In addition, simple and practical design equations for the different types of CFST columns have been proposed based on the SR model. The developed ML models and proposed equations can predict the compressive strength of stub CFST columns with reliable and accurate results, making them valuable tools for structural engineering. Furthermore, the Shapley additive interpretation (SHAP) technique is employed for feature analysis. The results of the feature analysis reveal that section slenderness ratio and concrete strength parameters negatively impact the compressive strength index.

SETTLEMENT IN THE NOTHERN PART OF BEKASI REGENCY, WEST JAVA PROVINCE, BASED ON CONE PENETRATION TEST DATA

In the nothern part of Bekasi Regency, the soil layers are dominated with alluvial deposit, especially clay and silt deposit. It makes the potential of the settlement in this area is getting higher. In this research, Cone Penetration Test (CPT) have been done to determine the soil layers from the surface till the 20 meters depth and to identify other soil properties, such as unit weight, compression index, swelling index, void ratio, etc. This research aims to analyze the total settlement in the northern part of Bekasi Regency based on CPT data. The total settlement is calculated by using the theory of One-Dimensional Primary Consolidation based on CPT data. The research area shows that the highest result of total settlement calculation is in the northern part of research area which directly adjacent to the Java Sea. It can be happened because the clay layers in northern part is way thicker than the other area.

OPTIMIZATION AND CHARACTERIZATION OF FAST DISSOLVING TABLETS OF CANDESARTAN CILEXETIL PREPARED FROM SPHERICAL AGGLOMERATES

The primary objective of this study was to develop a rapidly dissolving tablet containing an antihypertensive drug, candesartan cilexetil (CAND). The research work focused on improving solubility and in vitro dissolution of drugs using spherical agglomeration technique. Spherical agglomerates of CAND were developed using PVPK-30 as polymer and dichloromethane as bridging liquid. A spherical agglomerate of CAND was used to formulate fast dissolving tablet (FDT) with different superdisintegrants like Crospovidone and Cross carmellose sodium. The prepared powder blend was evaluated for different pre-compression parameters like solubility, compressibility index, Hausner’s ratio and flow property and post-compression parameters including in vitro dissolution study. The solubility of prepared agglomerates was found to be 0.15 to 0.91 mg mL-1, and it was higher than the pure drug (0.00071 mg mL-1). In vitro drug release study of optimized batch of FDT has shown 95.47 % of drug release. From the results, it was revealed that the prepared FDT using the agglomeration technique might be used to enhance the solubility and bioavailability of CAND to augment acute and chronic hypertension therapy.

A Study on Developing a Model for Predicting the Compression Index of the South Coast Clay of Korea Using Statistical Analysis and Machine Learning Techniques

As large cities are continually being developed around coastal areas, structural damage due to the consolidation settlement of soft ground is becoming more of a problem. Estimating consolidation settlement requires calculating an accurate compressive index through consolidation tests. However, these tests are time-consuming, and there is a risk of the test results becoming compromised while preparing and testing the specimens. Therefore, predicting the compression index based on the results of relatively simple physical property tests enables more reliable and accurate predictions of consolidation settlement by calculating the compression index at multiple points. In this context, this study collected geotechnical data from the soft ground of Korea’s south coast. The collected data were used to construct a dataset for developing a compression index prediction model, and significant influencing factors were identified through Pearson correlation analysis. Simple and multiple linear regression analysis was performed using these factors to derive regression equations, and compression index prediction models were developed by applying machine learning algorithms. The results of deriving the significance of the influencing factors from the developed compression index prediction model showed that natural water content was the most significant factor in predicting the compression index. By collecting a significant amount of high-quality data and using the compression index prediction model and the model construction process proposed in this study, more accurate predictions of the compressive index will be possible in the future.

The Effect of PEG 4000 in Co-processed Excipient using Melt Granulation Method on the Physical Characteristics of Chitosan Tablets in Mangrove Crab Shells (Scylla serrata)

Mangrove Crab (Scylla serrata) is an animal that likes to be consumed but its shell waste is underutilized. The shell contains chitosan which has many benefits, one of which can lower cholesterol levels. The combination of 2 or more excipients is called co-processed excipients which are then continued into tablets by direct compression. The aim of the study was to find out whether chitosan could be formalized into coprocessed tablets (lactose, primogel, and PEG 4000 7.5% & 15%) by direct compression method and the effect of differences in the characteristics of coprocessed and chitosan tablets with a ratio of PEG 4000 7.5% and 15 % as binder. The evaluation results showed that chitosan tablets fulfilled the requirements for the uniformity of weight, hardness, disintegration time (F1) tests, while they did not meet the requirements for the uniformity of tablet size, friability and disintegration times (F2) tests and the results of the coprocessing evaluation met specifications both F1 and F2, namely: particle size distribution, moisture content, flow rate, angle of repose (very good), compressibility index (adequate) and Hausner's ratio (very good). The evaluation results were then processed statistically using the SPSS application using the independent t-test method which showed that there was no significant difference in the effect of PEG 4000 7.5% and 15% as a binder on the characteristics of co-processed and chitosan tablets. Chitosan tablets from mangrove crab shells (Scylla serrata) cannot be formalized by direct compression with co-processing.

A super-learner machine learning model for a global prediction of compression index in clays

Settlement of structures is determined by the stiffness of the soil where they are built. Compression index (cc) quantifies the compressibility of the soil and is a key parameter in the design of geotechnical structures. To predict the value of cc in clay soils, a global database of more than 1000 data points was collected and analysed. Liquid limit, plasticity index, natural water content, and initial void ratio were considered as predictor variables. A super-learner machine learning model was developed to predict cc from these variables. The model demonstrated a reasonable predictive performance and was subsequently integrated into an online tool. Additionally, four symbolic regression expressions were obtained to relate cc with some of the input variables when not all data are available, providing simple and practical alternatives for cc, estimation. This study provided two major contributions: (1) the non-local nature of the data expands the scope and generalizability of the findings, and (2) the availability of the proposed algorithm through an online application ensures its accessibility for geotechnical engineers, enhancing the work's practical applicability and intrinsic value.

Simplified solution for large-strain consolidation considering the time-dependent well resistance

In this study, a simplified solution of the large-strain consolidation theory, which considers the time-dependent well resistance, has been presented. This solution is suitable for consolidation issues involving the influence of either the smear zone or the soil column. To confirm the proposed solution's accuracy, it was compared to fully nonlinear consolidation results calculated using the finite element method. Parametric analysis was conducted to examine the impact of the time-dependent well resistance in combination with the soil thickness, the ratio of the compression index to the radial and vertical permeability indices, and the initial void ratio at the soil surface. Finally, the proposed solution’s applicability was confirmed through a comparison of calculated results based on two case studies with both field measurements and numerical simulations.

Pilot test and consolidation theory of marine dredged slurry using the membrane-free horizontal-vacuum method

Laboratory tests and theoretical analyses were conducted to investigate the membrane-free horizontal-vacuum (MFHV) method for inducing seepage consolidation in dredged marine fills. First, six well-designed tests with dredged marine slurry were conducted to simulate the consolidation behaviour with a prefabricated horizontal drain (PHD). The dewatering features under MFHV conditions were studied with respect to the drainage rate, settlement, water content, and permeability. The dewatering rate saltation (DRS) problem was systematically investigated by observing the changes in the supernatant water. The results indicated that the DRS problem existed in the case of the thin slurry layer rather than the thick slurry layer. Furthermore, a modified consolidation model was proposed considering the vacuum boundary and critical gradient. An explicit solution was provided to calculate the average consolidation degree and settlement. The settlement and DRS points obtained from the model tests and analytical solutions were compared. The results showed that the proposed analytical method could reasonably predict the consolidation behaviour of the MFHV method. In addition, a parameter study was conducted to investigate the influence of the critical gradient, void ratio, and compression index on seepage consolidation. Finally, an equation to design the optimum drain space for the MFHV-treated slurry was presented for direct engineering practice.

Effect of incorporating recycled macro fibres on the properties of ultra-high-performance seawater sea-sand concrete

Ultra-high-performance concrete (UHPC) is an ideal material for constructing marine infrastructures, but faces obstacles such as limited local raw materials (i.e., freshwater and river-sand) and corrosion of steel reinforcement. Non-metallic reinforcement is preferable for reinforcing marine UHPC, especially when seawater and sea-sand are used to develop ultra-high-performance seawater sea-sand concrete (USSC). Recently, the authors' group proposed a cost-efficient UHPC reinforced with discrete macro fibres mechanically processed from waste glass fibre-reinforced polymer (GFRP) composites. This present study aimed to explore the potential application of incorporating macro fibres in USSC. A series of tests were conducted to investigate the fundamental properties of macro fibre reinforced USSC with the examined variables including the content (0 %, 2 %, 4 %, and 6 %) and lengths (30 mm and 60 mm) of macro fibres. Comparisons were made between USSC and UHPC with river-sand and freshwater (UTRC), which were both reinforced with macro fibres. The results revealed that incorporating macro fibres in USSC improved the compressive toughness index (CTI) and flexural toughness by up to 84.00 % and 40.15 times respectively, but decreased the workability and compressive strength by up to 42.22 % and 21.45 % respectively. The effect of incorporating macro fibres on the properties of USSC was more prominent than that of its counterpart of UTRC. A theoretical model was then developed for predicting the flexural toughness of various concrete with macro fibres based on the regression analysis on the available test results.

Microcrystalline cellulose: an alternative to increase the resistance of kraft packaging with recycled fiber

The consumption of paper packaging is increasing. On the contrary, the planted areas of Pinus spp. are showing a trend tendency of imbalance between supply and demand. Therefore, many companies are prioritizing the use of recycled fiber (RF). However, its inclusion can influence the quality of the product. This study aimed to evaluate whether the combination of RF with microscale cellulose will enable the production of resistant paper. The first step involved producing bench-scale samples of Kraft paper (with different percentages of virgin and RF) and characterized it physically (grammage, moisture, Gurley porosity, Z-traction, SCT, and Mullen). The second stage involved replicating the first stage with the inclusion of microcrystalline cellulose (MCC) and the elimination of Pinus spp. (LF). All formulations were approved for the physical characterization tests, except for the porosity analysis and grammage for F5. In the first test (MCC=0%), there was a reduction in tensile, compression, and burst index of 13.2, 7.3, and 19.5%, respectively, showing that the higher the percentage of RF, the lower the paper’s strength. In the second test for Formulation 3 (MCC=6%), there was an increase in the tensile, compression, and burst index of 9.5, 2.6, and 2.7%, respectively, when compared with Formulation 2 (LF=MCC=0%). This study demonstrates that the addition of up to 6% MCC strengthens the RFs and decreases the dependence on Pinus spp., making it a promising alternative for the production of sustainable and resistant packaging.

Compressive behavior of polyvinyl alcohol engineered cementitious composites incorporating steel slag as aggregate

Disposal of the steel by-product steel slag (SS) negatively impacts the environment. The use of SS as an aggregate in engineered cementitious composites (ECC) can prevent pollution and mitigate natural aggregate depletion. In this study, river sand (RS) was replaced by SS with maximum size of 4750 µm, and the properties of ECC with varying contents of SS and polyvinyl alcohol (PVA) fiber were investigated. SS changed the hydration product composition and enhanced the bond stress between the fiber and cementitious matrix, increased the bulk specific density and compressive strength, and reduced the porosity. ECC containing only SS and with high PVA fiber content exhibited superior performance. A 25% SS replacement ratio and 2% PVA fiber content improved the compressive strength, ductility index, and toughness index to 47.5 MPa, 1.45, and 2.60, respectively.

Reduced Complexity Learning-Assisted Joint Channel Estimation and Detection of Compressed Sensing-Aided Multi-Dimensional Index Modulation

Reduced Complexity Learning-Assisted Joint Channel Estimation and Detection of Compressed Sensing-Aided Multi-Dimensional Index Modulation

STABILISATION OF GUZAPE LATERITE WITH RICE HUSK ASH AND MARBLE DUST

Guzape Laterite shows cracking surface during dry season and has a high permeability and expand heavily during wet season. Unpleasant features of laterite, such as its expansive nature, present difficulties for building a road without stabilizing the soil. This study looked at the use of leftover waste from industrial and agricultural activities as stabilizing materials to enhance laterite's qualities and remove waste from the surrounding environment. At 2%, 5%, 10%, 15%, 20% and 25% of the rice husk ash combined with a constant marble dust 10% with laterite. To determine the changes in laterite characteristics, geotechnical experiments were carried out. Geotechnical tests such as California bearing ratio, Atterberg limit, unified compressive strength, compaction and free swell index, were examined. The properties of the natural laterite showed high permeability, also the compaction characteristics indicated that the maximum dry density reduced while the optimum moisture content reduced as the percentages of RHA and MD increases. The highest MDD is in the mix of RHA (25%): MD (10%). The consistent increase was noticed for the values of UCS. Atterberg limit showed a reduction in LL for this same mix. Conclusively, the properties of laterite have improved a bit with a certain proportion of discarded agricultural and industrial materials use thereby reducing the nuisance from this waste. Yet, further investigation may yield better options, and it is imperative to assess the environmental impact of RHA.

Using soft soil models in geotechnical engineering: a review paper

Soil is considered a complicated material as, in general, the behavior under loading is non-linear in addition it is anisotropic material and its behavior is time-dependent. Various models were developed in the method of finite element for modeling the behavior of soil under different loading cases, and it must be known that no constitutive model is available that can simulate completely the actual soil behavior under all conditions. This paper attempts to investigate the soft soil model and present a discussion about the advantages and disadvantages for the purpose of giving an overview, and discussing the main finding of the previous studies regarding using the Soft Soil model in the numerical analysis of geotechnical engineering problems and applications. In this research, it was observed from the previous studies that the relation between the modified compression index (λ*) and unloading index (κ*) is from (5 to 10). The Soft Soil model gives a stiffer stress-strain behavior compared to Hardening model. Using this model for compressible soils needs a longer calculation time than other models as the material stiffness matrix was included in each calculation step. It shows satisfactory results in the analysis of the settlement of immediate and consolidation cases of foundation in clayey soil than the model of Mohr-Coulomb.

Investigation of diatomaceous sand using elastic and electromagnetic waves in oedometer tests

The small-strain and electromagnetic behaviors of soils significantly change due to compression. The objective of this study was to investigate the small-strain stiffness and electrical resistivity of diatomaceous sand by modifying the conventional setup of oedometer tests (1D-compression tests). The specimens used were pure sand and sand with 20% diatoms by weight. The vertical displacement was directly observed using a digital gauge at the top of the compression cap during compression. At the end of each loading step, shear waves (S-waves) are measured using a pair of bender elements installed on the top and bottom compression caps. In addition, electrical resistance was measured using a pair of electrodes installed horizontally in the middle of the compression cylinder. The test results show that the compression index increased but the swelling index decreased according with the increase in the amount of the small and crushable diatom particles. The presence of diatom particles weakened the interparticle contacts and softened the soil skeletons. In addition, the electrical resistivity increased with the increase in diatom contents, which increased the surface conduction. Our work suggests that the S-wave velocity and electrical resistivity of diatomaceous sand can be characterized by modifying the conventional oedometer tests.

Розробка оптимальних складів вугільних шихт для трамбування. повідомлення 1. дослідження сировини щодо можливості її використання в трамбованих шихтах

It is shown that the coal used for coking with the tamping technology should be characterised by a low basicity index, the necessary levels of sintering and tamping to achieve cake stability when it is loaded into the coking chamber. Based on this, a comprehensive study of the properties of 15 components of hard coal charges (13 coal concentrates, sludge and flotation concentrate) was carried out in terms of their prospects as a raw material base using the technology of tamping coal charges. The analysis of the obtained results is presented. In particular, the evaluation of the shear strength of coal concentrates showed low values (from 9.6 to 12.6 kPa) of the shear force for all the studied samples. The strength of rammed cakes made from fine additives is significantly higher (σzz of flotation concentrate is 15.8 kPa, and sludge is 14.9 kPa), so an increase in their content in the charge will have a positive effect on the strength of the rammed cake. It has been established that the most accurate of the studied coal quality indicators, the tamping index σzz, is predicted by the Hardgrove rejuvenation coefficient and the thickness of the plastic layer. Prediction by volatile matter yield and free swelling index FSI is possible with medium accuracy, while the vitrinite reflection coefficient, Horn index and maximum compression index of Odibert-Arnoux are inaccurate. The heterogeneity of the samples for all the studied indicators characterising the fluid-plastic properties of coal was revealed. The optimums of the function of the tamping index were calculated, which are achieved at the following quality indicators: Vdaf = 25.7 %; Y = 14.3 mm; HGI = 69.6 units; R0 = 1.17 %; RI = 37.9 units; a = 1.9 %; FSI = 2.6 units. It was established that the optimum ramming properties are achieved at the values of classification indicators corresponding to coking coal. A positive feature of the tamping technology is the possibility of ensuring the specified set of properties by using not expensive and scarce coking coal, but a mixture of cheaper grades of low-baking, petrographically heterogeneous coal.. Keywords: coal, coal concentrates, coking, tamping, technological properties, testing, plastic-viscous properties, Hardgrove threshold. Corresponding author Miroshnychenko D.V., e-mail: dvmir79@gmail.com