Test Data Compression Research Articles

Digital Image Correlation and Numerical Analysis of Mechanical Behavior in Photopolymer Resin Lattice Structures.

Cellular structures are increasingly utilized in modern engineering due to their exceptional mechanical and physical properties. In this study, the deformation and failure mechanisms of two energy-efficient lattice structures-hexagonal honeycomb and re-entrant honeycomb-were investigated. These structures were manufactured using additive stereolithography with light-curable Durable Resin V2. The experimental testing of the topologies under two perpendicular loading directions employed the 3D Digital Image Correlation (DIC) system to capture strain fields and deformation patterns, providing insights into structural behavior and failure mechanisms. The unit cells of the topologies were scaled up to enable precise optical measurements while preserving their structural interaction characteristics. Numerical simulations, conducted using the SAMP-1 material model in LS-DYNA and calibrated with tensile and compression test data, accurately replicated the behavior of the studied topologies and demonstrated good agreement with experimental results. The hexagonal structure, loaded along axis 2, showed the best fit, with deviations within 5%, while the re-entrant honeycomb structure exhibited weaker yet reasonable agreement. By integrating experimental and numerical approaches, the research validates the SAMP-1 model's predictive capabilities for lattice structures and provides a framework for analyzing energy-absorbing lattice topologies.

Research on the confinement mechanism and calculation method of axial load-bearing capacity of steel-reinforced concrete-filled square steel tubular columns

There are significant discrepancies between the experimental results and numerical analysis outcomes for steel-reinforced concrete-filled steel tubular (SRCFST) columns. This is primarily due to the lack of understanding of the confinement mechanisms of SRCFST and the corresponding models for confined concrete. Therefore, based on the confinement mechanisms of square steel tubes and steel reinforcements on concrete, this paper calculates the effective lateral confining stress to determine the strength enhancement factors for concrete in various confined regions. Drawing from the classical Mander model, the key parameters are modified to establish stress–strain models for concrete in different confined regions. By comparing and analyzing axial compression test data for steel tube-reinforced concrete short columns with different parameters, the study identifies the most suitable axial compression bearing capacity calculation formula for these columns. Additionally, the introduction of stress–strain models into finite element analysis, compared with experimental results, demonstrates that the proposed confinement mechanism and the established stress–strain model for steel-reinforced concrete are reasonable and effective. The theoretical calculation results for the ultimate bearing capacity based on this are well aligned with the simulation and experimental values.

Research on rock strength prediction model based on machine learning algorithm

The compressive strength of rocks is one of its mechanical characteristics. It has been a difficult problem to predict rock compressive strength conveniently and efficiently, and to solve the limitations of traditional rock compressive strength tests such as high cost, long time consumption, and reliability assurance. In this study, a data set containing 1774 groups of rock compressive strength test data was constructed through file retrieval, including 9 input parameters: rock type, temperature, confining pressure, dimension of specimen, shape of specimen, and experimental method. Eight supervised learning algorithms were used to learn the rock compressive strength test data, and eight rock compressive strength prediction models considering multiple factors were established to obtain a better method of predicting rock compressive strength. By selecting different features, the optimal feature combination for predicting rock compressive strength was obtained, and the optimal parameters for different models were obtained through the Sparrow Search Algorithm (SSA). Finally, four regression evaluation indicators, including mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R2), were used to evaluate the predictive performance of the established regression models. The results showed that the best-trained model had a MAPE as low as 3.61%, MAE as low as 9.19 MPa, and R2 as high as 0.995. It is noteworthy that AdaBoost was found to be the best model for predicting rock compressive strength. This study presents a significant advancement in the field by demonstrating the effectiveness of machine learning algorithms in this context, which have not been extensively applied to rock compressive strength predictions. The findings suggest that these models can offer substantial improvements over traditional methods, not only in accuracy but also in operational efficiency. This research is important for geotechnical engineering, as accurate rock strength predictions are critical for the design and stability assessments of construction projects, ultimately contributing to safer and more cost-effective engineering solutions.

Assessment of the Numerical Behavior of Remolded and Undisturbed Clayey Soil

Abstract The simulation of soil behavior using finite element analysis depends mainly on the input parameters considered in analysis, moreover, in the case of clayey soil, most of the experimental studies for small models are performed on remolded samples because of difficulty of providing undisturbed soils. This leads to unreal results for numerical analysis as the validation process of numerical results is performed on remolded sample. It was conducted experimental work on remolded clay including load-settlement tests of model footing at three states on undrained cohesion (cu), and then performed unconfined compression tests at the same undrained cohesion. After that, performing numerical modeling of the model footing from the data of unconfined compression tests. It was observed that the value of the modulus of elasticity in clay from unconfined test considering the initial tangent is low for remolded state compared to the findings of the previous research. Moreover, great care must be taken in selecting the elasticity modulus in performing the numerical analysis of the clayey soil, however, for undisturbed clay it is greater than remolded, the difference in the value is up to two times for stiff clay in the case of large scale footing, while it was reaches about four times.

Assessment of Building-Foundation Interac-tion Using the Finite Element Method Based on Soil Compression Test Data

Summary. The article presents a methodology for assessing the interaction between buildings and their soil foundations based on data from soil compression tests widely available in engineering geological survey reports. The primary aim of the study is to develop an approach for accounting for soil compaction within the "Base-Foundation-Structure" system using the finite element method (FEM). This approach enables more accurate modeling of the stress-strain state of structures under pressure ranges typical for modern buildings, such as high-rise residential complexes or industrial facilities. The methodology proposed in the article considers the specific characteristics of soil deformation under loading, particularly the compaction processes that occur due to the reduction of porosity. The dependency of the deformation modulus on soil pressure is described based on experimental data from compression tests extended to higher stress levels using mathematical models. This eliminated the need for expensive and complex tests that are rarely accessible in the context of Ukrainian engineering practice. The study involves modeling the stress-strain state of a real-life object—a 25-story residential building in Kyiv. Two scenarios were analyzed: the traditional approach with a constant deformation modulus and the proposed methodology incorporating a variable deformation modulus. The modeling results demonstrated that considering soil compaction processes significantly reduces peak stress values in foundation structures and ensures a uniform distribution of bending moments in grillages. Special attention is given to assessing the height of the structurally disturbed soil zone beneath the foundation. It was found that this zone could reach up to 9 meters for grillages and 12 meters for pile foundations, depending on the applied load. The results suggest the necessity of embedding piles beyond this zone to ensure structural stability. The proposed approach is universal, as it is based on standard oedometer data and can be adapted to various soil types and structural configurations. The results demonstrate the practical value of the methodology for optimizing foundation design, reducing the material consumption of structures, and improving their reliability. Furthermore, accounting for soil compaction processes enhances the accuracy of engineering calculations and ensures the rational use of material resources in complex geological conditions. The calculation methodology proposed in this study can be integrated into modern software packages such as ABAQUS, significantly simplifying its implementation in engineering practice. This makes it particularly valuable for the design of high-rise buildings, industrial facilities, and other structures subjected to significant foundation loads.

Multiscale simulation study for mechanical characteristics of coral sand influenced by particle breakage

This paper investigates the mechanical response of coral sand under particle breakage using a hierarchical multiscale model combining the discrete element method (DEM) and the finite element method (FEM). This DEM-FEM model links the microscopic interaction mechanisms to macroscopic phenomena such as strain localization and failure. A cohesive contact model was first utilized to simulate compaction bands in the DEM and construct a cohesive assembly with smaller particles distributed around a larger particle to better simulate the grinding and angular breakage of coral sand. A representative volume element (RVE) that includes particle breakage was then constructed and analyzed under periodic boundary conditions. DEM analysis was performed, and the results were compared with triaxial compression test data obtained from the literature, demonstrating that the constructed RVE effectively represents the mechanical properties of coral sand. The constructed RVE was used for hierarchical multiscale simulations, which showed good agreement with existing triaxial testing of coral sand. Finally, by setting a larger cohesive force, the constructed coral sand particles were prevented from breakage, and comparative analysis revealed that particle breakage weakens the mechanical properties of coral sand. Furthermore, different shapes of coral sand particles were constructed, and RVE and hierarchical multiscale simulations of triaxial tests were performed. The results indicated that the triaxial tests of long strip-shaped coral sand particles exhibit higher peak values compared to spherical coral sand particles. Additionally, a double porosity model of coral sand was constructed to analyze the impact of internal porosity on soil mechanical properties. The results showed that the presence of internal porosity significantly weakened the mechanical properties of coral sand. These findings highlight the significant impact of particle breakage and shape on the mechanical behavior of coral sand, offering important insights for engineering applications.

A Modified and Customized Wingsuit Flying Search (MCWFS)-based Approach for the Circular Scan Architecture

The circular scan architecture (CSA) is a widely used scan design technique in digital circuit testing that involves scanning test data through a circuit in a circular pattern. Several optimization approaches have been suggested so far to lessen the Test Data Volume (TDV), but no one has shown satisfactory results. Therefore, this paper proposes a Modified and Customized Wingsuit Flying Search algorithm to decrease the test data volume time. The proposed MCWFS-SBA-CSA introduces some novel features that distinguish it from traditional circular scan approaches. The concept of wingsuit flying is an innovative approach in the field of scan systems. This allows the scan that moves more dynamically and efficiently, enabling it to cover a larger area in a shorter time than traditional circular-scan approaches. After this phase, only scan-chosen inputs are required to obtain the next test pattern from the captured response. Therefore, required less Automatic test equipment (ATE) memory in this research so there is a Decreased cost in system-on-chip (SOC). The proposed method attains fast global searching capacity. The efficiency of the proposed technique attains 26.42%, 32.45%, and 29.34% higher compression ratio (CR), Test Application Time (TAT) reduction of SC-128 attains 29.45%, 34.67%, and 40.22% higher, TDV of SC-256 attains 32.23%, 36.34%, and 39.23% higher than existing methods, such as TDV for Circular Scan Approaches utilizing Modified Shuffled Shepard Optimization (TDV-CSA-MSSO), Effectual Very-large-scale integration Test data compression system for CSA under modified and colony metaheuristic (ETDC-CSA-MACMH), and Test Data Compression Utilizing Tetrad state Skip System (TDC-DC-TSSC) for Digital Circuits, respectively.

Prediction Accuracy of Hyperelastic Material Models for Rubber Bumper under Compressive Load.

Different hyperelastic material models (Mooney-Rivlin, Yeoh, Gent, Arruda-Boyce and Ogden) are able to estimate Treloar's test data series containing uniaxial and biaxial tension and pure shear stress-strain characteristics of rubber. If the rubber behaviour is only determined for the specific load of the product, which, in the case of rubber bumpers, is the compression, the time needed for the laboratory test can be significantly decreased. The stress-strain characteristics of the uniaxial compression test of rubber samples were used to fit hyperelastic material models. Laboratory and numerical tests of a rubber bumper with a given compound and complex geometry were used to determine the accuracy of the material models. Designing rubber products requires special consideration of the numerical discretization process due to the nonlinear behaviours (material nonlinearity, large deformation, connections, etc.). Modelling considerations were presented for the finite element analysis of the rubber bumper. The results showed that if only uniaxial compression test data are available for the curve fitting of the material model, the Yeoh model performs the best in predicting the rubber product material response under compressive load and complex strain state.

Designing a reliable machine learning system for accurately estimating the ultimate condition of FRP-confined concrete

Precisely forecasting how concrete reinforced with fiber-reinforced polymers (FRP) responds under compression is essential for fine-tuning structural designs, ensuring constructions fulfill safety criteria, avoiding overdesigning, and consequently minimizing material expenses and environmental impact. Therefore, this study explores the viability of gradient boosting regression tree (GBRT), random forest (RF), artificial neural network-multilayer perceptron (ANNMLP) and artificial neural network-radial basis function (ANNRBF) in predicting the compressive behavior of fiber-reinforced polymer (FRP)-confined concrete at ultimate. The accuracy of the proposed machine learning approaches was evaluated by comparing them with several empirical models concerning three different measures, including root mean square errors (RMSE), mean absolute errors (MAE), and determination coefficient (R2). In this study, the evaluations were conducted using a substantial collection of axial compression test data involving 765 circular specimens of FRP-confined concrete assembled from published sources. The results indicate that the proposed GBRT algorithm considerably enhances the performance of machine learning models and empirical approaches for predicting strength ratio of confinement (f′cc/f′co) by an average improvement in RMSE as 17.3%, 0.65%, 66.81%, 46.12%, 46.31%, 46.87% and 69.94% compared to RF, ANNMLP, ANNRBF, and four applied empirical models, respectively. It is also found that the proposed ANNMLP algorithm exhibits notable superiority compared to other models in terms of reducing RMSE values as 9.67%, 11.29%, 75.11%, 68.83%, 73.64%, 69.49% and 83.74% compared to GBRT, RF, ANNRBF and four applied empirical models for predicting strain ratio of confinement (εcc/εco), respectively. The superior performance of the GBRT and ANNMLP compared to other methods in predicting the strength and strain ratio confinements is important in evaluating structural integrity, guaranteeing secure functionality, and streamlining engineering plans for effective utilization of FRP confinement in building projects.

A B-spline material point method for deformation failure mechanism of soft–hard interbedded rock

Geological hazards related to soft–hard interbedded rock are frequent in rock engineering. The material point method (MPM) is a mesh-free numerical approach specifically designed for analyzing large deformations. Notably, significant grid-crossing errors frequently arise when material points traverse the underlying grid. To investigate the failure mechanism of soft–hard interbedded rock, an enhanced MPM incorporating B-spline basis functions and Voronoi polygon discretization is developed and subsequently validated through comparisons with uniaxial compression test data and other numerical methods. The numerical results of soft–hard interbedded rock specimens associated with different soft layer dips (SLD) and confining pressures indicate that the SLD has a great effect on compressive strength and crack extension at low confining pressure. Rocks from SLD-30° to SLD-75° correspond to the “sliding failure along discontinuities” failure mode and have lower compressive strength than rocks with other SLD angles. It is also demonstrated that the propagation of cracks leads to a significant alteration in the internal stress state of the rock, and that stress concentrations at the crack tip exacerbate the development of failure surface. Furthermore, the failure mode of soft–hard interbedded rock can be categorized into four types: (1) sliding failure across multiple discontinuities, (2) tensile fracture across multiple discontinuities, (3) sliding failure along discontinuities, (4) tensile-split along discontinuities.

Improved calculations of joints in anisotropic structural materials

Introduction. Contemporary methods for the design and calculation of building structures are often limited to the elastic stage of the material work. In order to analyze the stress-strain state of joints, it is necessary to take into account the properties of the material, as well as its operation under the load, including both elastic and non-linear stages. In this case, anisotropic materials, e.g. wood, represent a particular interest. Therefore, the paper presents a theoretical and practical study of the work, performed by wooden samples.Aim. To perform tests and numerical simulations for analyzing the stress-strain state and improve the calculations of anisotropic structural materials.Materials and methods. Compression tests of wooden samples, made of second-grade pine, were carried out along the fibers with fixed vertical compression stresses and strains. The tests were performed using a hydraulic press with a maximum load of 50 t. Strain gauge equipment was used to record strains and stresses. Based on the data of compression tests, the numerical simulation of the samples in the LIRA-SAPR and ANSYS software packages was performed.Results. According to the test results, the elastic stage of the compressed wood ranges up to 90 kN, followed by a transition to the plastic deformation. The performed numerical simulation of the samples in the LIRA-SAPR and ANSYS software packages demonstrated the convergence of the results. However, the ANSYS software package allows for a more detailed simulation and calculation of joints and structures. The comparison of distributions of vertical compression stresses σy, obtained in tests and ANSYS software package numerical simulation, proved the convergence of the results (discrepancy of less than 5 %). This confirms the effectiveness of using this software package for simulating the joints of anisotropic materials.Conclusions. The results of tests and numerical simulation showed the effectiveness of using the ANSYS software package to calculate complex joints of anisotropic structural materials. The convergence of the results is established for the elastic stage. An additional study is required to simulate the plastic stage.

Enhanced Hoek-Brown (H-B) criterion for rocks exposed to chemical corrosion

Underground constructions often encounter water environments, where water–rock interaction can increase porosity, thereby weakening engineering rocks. Correspondingly, the failure criterion for chemically corroded rocks becomes essential in the stability analysis and design of such structures. This study enhances the applicability of the Hoek-Brown (H-B) criterion for engineering structures operating in chemically corrosive conditions by introducing a kinetic porosity-dependent instantaneous mi (KPIM). A multiscale experimental investigation, including nuclear magnetic resonance (NMR), X-ray diffraction (XRD), scanning electron microscopy (SEM), pH and ion chromatography analysis, and triaxial compression tests, is employed to quantify pore structural changes and their linkage with the strength responses of limestone under coupled chemical-mechanical (C-M) conditions. By employing ion chromatography and NMR analysis, along with incorporating the principles of free-face dissolution theory accounting for both congruent and incongruent dissolution, a kinetic chemical corrosion model is developed. This model aims to calculate the kinetic porosity alterations within rocks exposed to varying H+ concentrations and durations. Subsequently, utilizing the generalized mixture rule (GMR), the kinetic porosity-dependent mi is formulated. Evaluation of the KPIM-enhanced H-B criterion using compression test data from 5 types of rocks demonstrated a high level of consistency between the criterion and the experimental results, with a coefficient of determination greater than 0.96, a mean absolute percentage error less than 4.84%, and a root-mean-square deviation less than 5.95 MPa. Finally, the physical significance of the porosity-dependent instantaneous mi is clarified: it serves as an indicator of a rock’s capacity to leverage the confining pressure effect.

Hot deformation behavior of commercial pure vanadium

The hot deformation behavior of pure vanadium was studied by uniaxial compression tests carried out in vacuum to a true strain of 0.6 in the temperature range of 800 to 1400 °C and strain rate range of 3 × 10−3 to 10 s−1. Strain rate sensitivity was calculated from the compression test data and mapped out in contour plots to determine the optimum regime of hot workability of vanadium. A high strain rate sensitivity of about 0.3 was obtained in the temperature and strain rate range of 1100 to 1400 °C and 3 × 10−3 to 1 s−1 for pure vanadium. Microstructures of the deformed samples showed features of dynamic recrystallization within the high strain rate sensitivity domain. Dynamic abnormal grain growth was observed at 1400 °C and strain rates of 0.1 and 1 s−1. The apparent activation energy of deformation was found to be 244 kJ·mol−1 and the stress exponent was about 3.4. The high values of activation volume suggest the barriers related to the dislocation intersection based process as the main rate controlling mechanism during the hot deformation of vanadium. The 〈100〉 and 〈111〉 fiber texture components evolved during the hot deformation of pure vanadium.

Compaction elastoplastic damage constitutive model of rock under hydro-mechanical coupling: A heuristic modeling method based on internal state variables theory

Based on the internal state variables (ISV) theory, this paper employs a heuristic modeling approach to investigate the compaction elastoplastic damage constitutive model of rocks under hydro-mechanical coupling. The heuristic modeling method demonstrated herein can seamlessly integrate with existing constitutive theories, facilitating a broader spectrum of research on hydro-mechanical coupling constitutive models. Furthermore, a numerical solution was conducted in the principal axes via stress spectrum decomposition, which can well reflect the distinct characteristics of compaction deformation and the influence of water pressure on rock stress distribution. Utilizing the classic Drucker-Prager (D-P) criterion, the modeling method and numerical algorithm were implemented to derive a hydro-mechanical coupling compaction elastic–plastic damage constitutive model. This contribution expands the application domain of the classic D-P criterion within the context of hydro-mechanical coupling environments. The rationality of the model was confirmed through compression test data under various water pressures and confining pressures. Water pressure increases nonlinear compaction deformation by changing the opening degree of microcracks under low confining pressure, which has not been paid enough attention in existing research. This study thoroughly considers the influence of water pressure on compaction deformation. The developed process of “heuristic modeling method-numerical method-model application” is helpful for enriching the constitutive theory of rock under hydro-mechanical coupling.

Application of ANN in Construction: Comprehensive Study on Identifying Optimal Modifier and Dosage for Stabilizing Marine Clay of Qingdao Coastal Region of China

Nowadays, the use of new compound chemical stabilizers to treat marine clay has gained significant attention. However, the complex non-linear relationship between the influencing factors and the unconfined compressive strength of chemically treated marine clay is not clear. In order to study the influence of various factors (dosage, type of stabilizer, curing age) on the unconfined compressive strength of solidified soil during chemical treatment, experiments were performed to determine the unconfined compressive strength of soft marine clay modified with various types of stabilizers. Further, an artificial neural network (ANN) model was used to establish a prediction model based on the unconfined compressive strength test data and to verify the performance. Sensitivity and optimization analyses were further conducted to explore the relative significance of parameters as well as the optimal dosage amount. Research has found that when the content of aluminate cement is 89.5% and the content of curing agent is 30%, the unconfined compressive strength significantly increases after 28 days of solidification, and the change in quicklime content has the greatest effect on the improvement in the unconfined compressive strength. The influence of modifiers on the unconfined compressive strength is in the order: potassium hydroxide > kingsilica > quick lime > bassanite. The values of each factor were obtained when the unconfined compressive strength was the maximum, which provided support for the optimization of the treatment scheme. The analysis of chemical treatment is no longer limited to the linear relationship according to the test results, which proves the feasibility of non-linear relationship analysis based on the artificial neural network.

Design Optimization of a Hybrid-Driven Soft Surgical Robot with Biomimetic Constraints.

The current study investigated the geometry optimization of a hybrid-driven (based on the combination of air pressure and tendon tension) soft robot for use in robot-assisted intra-bronchial intervention. Soft robots, made from compliant materials, have gained popularity for use in surgical interventions due to their dexterity and safety. The current study aimed to design a catheter-like soft robot with an improved performance by minimizing radial expansion during inflation and increasing the force exerted on targeted tissues through geometry optimization. To do so, a finite element analysis (FEA) was employed to optimize the soft robot's geometry, considering a multi-objective goal function that incorporated factors such as chamber pressures, tendon tensions, and the cross-sectional area. To accomplish this, a cylindrical soft robot with three air chambers, three tendons, and a central working channel was considered. Then, the dimensions of the soft robot, including the length of the air chambers, the diameter of the air chambers, and the offsets of the air chambers and tendon routes, were optimized to minimize the goal function in an in-plane bending scenario. To accurately simulate the behavior of the soft robot, Ecoflex 00-50 samples were tested based on ISO 7743, and a hyperplastic model was fitted on the compression test data. The FEA simulations were performed using the response surface optimization (RSO) module in ANSYS software, which iteratively explored the design space based on defined objectives and constraints. Using RSO, 45 points of experiments were generated based on the geometrical and loading constraints. During the simulations, tendon force was applied to the tip of the soft robot, while simultaneously, air pressure was applied inside the chamber. Following the optimization of the geometry, a prototype of the soft robot with the optimized values was fabricated and tested in a phantom model, mimicking simulated surgical conditions. The decreased actuation effort and radial expansion of the soft robot resulting from the optimization process have the potential to increase the performance of the manipulator. This advancement led to improved control over the soft robot while additionally minimizing unnecessary cross-sectional expansion. The study demonstrates the effectiveness of the optimization methodology for refining the soft robot's design and highlights its potential for enhancing surgical interventions.

Analysis of the microstructural connectivity and compressive behavior of particle aggregated silica aerogels

AbstractPorous media such as aerogels can exhibit unique properties including low thermal conductivity, low bulk density, and low sound velocity. However, the limited mechanical properties of aerogels restrict their widespread application. This study focuses on understanding the mechanical behavior of aggregated silica aerogels by investigating their microstructural connectivity and densification mechanisms under uniaxial compression. The interparticle connectivity is generated using the diffusion‐limited cluster–cluster aggregation (DLCA) algorithm, and the particle connections are modeled by beam elements that account for contact interaction. The mechanical response of representative volume elements (RVEs) is analyzed in both linear and nonlinear regimes while applying periodic boundary conditions. The model is correlated with experimental compression test data to validate the simulation results. With increasing compressive strain, load transitions between multiple backbone paths appear in the network structure. Thus, the simulation model provides insight into the compression process. Moreover, the simulation model enables the examination of the influence of various model parameters and facilitates the evaluation of the power–law relationship between the elasticity modulus and porosity of aerogels.

A procedure to analyze a one dimensional compression test

The subsoil of Mexico City (SMC) is highly compressible when loads are applied. This feature is associated with many uncertainties and complex issues during foundation design processes. The compressibility of the SMC has been investigated since the 40s by using oedometer tests in most cases. However, the importance of the results in interpreting compression test data requires a systematic method of determining the end of consolidation (EOC) under a load increment. This paper offers an alternative view to analyze a one-dimensional compression test, decomposing the time-compression curve into two curves, one due to consolidation and another due to volumetric creep, using numerical processing. This approach has several advantages: (1) Data reduction allows us to know the contribution of consolidation and volumetric creep at any time and for each load increment. (2) a systematic method of determining the end-of-consolidation (EOC) under a load increment, and (3) long-term strains (settlements) can be estimated at any time. Finally, an example of the results obtained using the suggested method is presented.

Compression Strength and Critical Impact Speed of Typical Fertilizer Grains

The application of fertilizer is necessary for the growth and yield of crops, especially for paddy rice. Precision application is important for the fertilizer utilization rate and sustainable development of agriculture. However, the crushing of fertilizer grains will reduce the quality of fertilization, for the decrease in the size and mass of the fertilizer particles and the degree of crushing mainly depend on the physical and mechanical properties of the fertilizer grains. In this study, the compression strength and critical impact speed of four typical commonly used fertilizer grains, a compound fertilizer of nitrogen, phosphorus, and potassium (NPK compound fertilizer), organic fertilizer, large granular urea, and small granular urea, were measured and analyzed. The static compression test was carried out using a TMS-Pro texture analyzer and the results show that the four kinds of fertilizer grains are brittle materials, and their elastic moduli are 208 MPa, 233 MPa, 140 MPa, and 107 MPa, respectively; the theoretical impact model of fertilizer granules is established based on the compression test result and Hertz elastic contact theory, the theoretical formula for the critical impact speed of fertilizer grains is derived, and the theoretical critical impact strength and speed are worked out. An image capture system for the impact process of fertilizer grains was developed, and the impact test was conducted. The results show that the critical impact speed of the four kinds of fertilizer grains decreases with the increase in granule size, while the variance analysis shows that the effect is not significant. The comparison of the experimental results with the theoretical values shows that the theoretical formula could be used to predict the trends of the critical impact speed of fertilizer grains. The model was optimized with the MATLAB 2018 function fitting tool based on the test and analysis. The goodness of fit of the formula is 0.824, which is 13.43% greater than that of the original theoretical formula, indicating that the modified formula based on the compression test data might estimate the critical impact speed of the granular fertilizer with brittle material properties more accurately. The results may provide a reference for the parameter design of a precision fertilization machine.

Multivariable Regression 3D Failure Criteria for In-Situ Rock

Wellbore stability problems increase with the exploration and development of oil and gas reservoirs. A new 3D non-linear failure criterion is proposed as a trigonometric function considering the intermediate principal stress (2) on the triaxial compression test data. Mohr-Coulomb and Hoek-Brown are well-known failure criteria, but they do not consider the influence of (2) on rock strength. This new criterion produces a concave surface on the principal stress space (1,2, 3) with the influence of intermediate principal stress. In this study, sensitivity analysis for the variable is also done to understand the significant influence of parameters on the accuracy of the proposed criterion. Further validation of this non-linear criterion on three principal stresses (1,2, 3) was done compared with linear regression and second-degree polynomial regression results. It has been observed that the new non-linear 3D criterion with five material parameters reveals a good fit compared to linear regression and second-degree polynomial regression, which have four and six material parameters, respectively. The new non-linear criterion was further validated by comparison with existing criteria like the Priest, Drucker-Prager, and Mogi-Coulomb. It has been observed that the new 3D non-linear criterion shows a more accurate result than these existing criteria as certain rock types exhibit coefficient of determination (DC) values near one, precisely 0.95 for inada granite, 0.94 for orikabe monzonite, and 0.91 for KTB amphibolite. In contrast, other rock types have DC values ranging from 0.7 to 0.9. The new 3D non-linear criterion also yields lower root means square error (RMSE) values than the Mogi-Coulomb criterion for seven rock types. Specifically, the RMSE values by the new criterion are as follows: KTB amphibolite - 40.03 MPa, Dunham dolomite - 15.16 MPa, Shirahama sandstone - 9.08 MPa, Manazuru andesite - 22.14 MPa, Inada granite - 35.47 MPa, and Coconino sandstone - 19.047 MPa. This new 3D criterion gave precise predictions of the failure of the formation under in-situ stresses and was further helpful for the simulation of the wellbore in the petroleum industry. The variable in the new 3D criterion should be calculated from triaxial compression test data for each formation rock before applying this criterion to the wellbore stability problem and the sand production problem.