Penetration Test Research Articles

Feasibility Analysis of Resource Application of Dry Flue Gas Desulfurization Ash in Asphalt Pavement Materials

To verify the feasibility of applying dry flue gas desulfurization ash (DFGDA) to asphalt pavement materials, the asphalt mastic (filler and asphalt composition) prepared by adding different proportions of DFGDA and LSP (limestone powder) into 70# matrix asphalt was studied experimentally. The asphalt mastics were subjected to the penetration test, the softening point test, and the ductility test. Moreover, the rheological properties of asphalt mastic were evaluated with dynamic shear rheometer (DSR) tests and bending beam rheometer (BBR) tests. An interaction ability index C-value based on the Palierne model was proposed to evaluate the interaction ability between DFGDA and asphalt. The influence of DFGDA asphalt on the interaction ability of matrix asphalt was observed and evaluated using Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). The results showed that with the increasing proportion of DFGDA, the penetration of asphalt mastic gradually decreased, the softening point increased, and the ductility slightly decreased. At the same temperature, the dynamic shear modulus G* of the asphalt mortar significantly increased with increasing DFGDA content. The incorporation of DFGDA negatively affected the low-temperature plastic deformation resistance of asphalt, but the impact was weakened with the growing DFGDA amount and the powder mastic ratio. The combination mode of DFGDA and matrix asphalt depends on the physical blending, and their interaction ability mainly depends on the miscibility between DFGDA and matrix asphalt. In conclusion, DFGDA can be utilized as a novel filler in asphalt pavement materials.

Strength and Durability Properties of High-Volume Fly Ash (HVFA) Binders: A Systematic Review

South Africa is endowed with a wealth of coal-fired power stations that can produce extremely high volumes of fly ash per year exceeding 34 million tonnes. The use of high-volume fly ash (HVFA) binders in the construction sector has the capacity to significantly reduce greenhouse gas emissions associated with traditional cement production and offset the carbon footprint of Eskom. The excessive production of fly ash by Eskom warrants the need for developing ultra-high-volume fly ash binders (UHVFA, fly ash/binder > 60 wt%). Nonetheless, fly ash (FA) replacement of cement is still largely limited to 35% regardless of more ambitious research indicating the potential to surpass 60%. In view of the urgent need for South Africa to offset and reduce its carbon footprint, this work reviews and summarises the literature on the performance of HVFA binders with a focus on two specific areas: (i) strength and (ii) durability. On HVFA binder strength, the focus is drawn on work that analysed the compressive strength, flexural strength, and split tensile strength. This review focuses on the extant literature analysing the durability of HVFA binders using various tests, including sorptivity, resistivity, permeability, tortuosity, rapid chloride penetration tests, resistance to sulphate attack, and microstructural analysis. As the FA content increases towards optima, i.e., 50–80%, the most indicative composite characteristics of the strength and durability properties are UCS (30–90 MPa) and permeability (low). This review reveals the leading methodologies, instrumentation, findings, challenges, and contradictions.

A Machine Learning-Based Approach for Predicting Installation Torque of Helical Piles from SPT Data

Helical piles are advantageous alternatives in constructions subjected to high tractions in their foundations, like transmission towers. Installation torque is a key parameter to define installation equipment and the final depth of the helical pile. This work applies machine learning (ML) techniques to predict helical pile installation torque based on information from 707 installation reports, including Standard Penetration Test (SPT) data. It uses this information to build three datasets to train and test eight machine-learning techniques. Decision tree (DT) was the worst technique for comparing performances, and cubist (CUB) was the best. Pile length was the most important variable, while soil type had little relevance for predictions. Predictions become more accurate for torque values greater than 8 kNm. Results show that CUB predictions are within 0.71,1.59 times the real value with a 95% confidence. Thus, CUB successfully predicted the pile length using SPT data in a case study. One can conclude that the proposed methodology has the potential to aid in the helical pile design and the equipment specification for installation.

Distributed acoustic sensing for seismic surface wave data acquisition in an intertidal environment

The application of distributed acoustic sensing (DAS) for shallow marine seismic investigations is assessed, in particular with respect to the collection of seismic surface wave data in an intertidal setting. Appropriate selection and directional sensitivity of fiber-optic cables is considered and the measured data is validated with respect to conventional seismic data acquisition approaches, using geophones and hydrophones, along with independent borehole and seismic cone penetration test (SCPT) data. In terms of cable selection, a reduction in amplitude and frequency response of an armored cable is observed, when compared with an unarmored cable. For seismic surface wave surveys in an offshore environment where the cable would need to withstand significant stresses, the use of the armored variant with limited loss in frequency response may be acceptable from a practical perspective. The DAS approach also has indicated good consistency with conventional means of surface wave data acquisition, and the inverted [Formula: see text] also is very consistent with downhole SCPT data. Observed differences in phase velocity between high tide (Scholte wave propagation) and low tide (Rayleigh wave propagation) are not thought to be related to the particular type of interface wave due to shallow water depth. These differences are more likely to be related to the development of capillary forces in the partially saturated granular medium at low tide. Overall, this study demonstrates that our novel approach of DAS using seabed fiber-optic cables in the intertidal environment is capable of rapidly providing near-surface S-wave velocity data across considerable spatial scales (multikilometer) at high resolution, which is beneficial for the design of subsea cables routes and landfall locations. The associated reduction in deployment and survey duration, when compared with conventional approaches, is particularly important when working in the marine environment due to potentially short weather windows and expensive downtime.

Prediction of seismic-induced bending moment and lateral displacement in closed and open-ended pipe piles: A genetic programming approach

Ensuring the reliability of pipe pile designs under earthquake loading necessitates an accurate determination of lateral displacement and bending moment, typically achieved through complex numerical modeling to address the intricacies of soil-pile interaction. Despite recent advancements in machine learning techniques, there is a persistent need to establish data-driven models that can predict these parameters without using numerical simulations due to the difficulties in conducting correct numerical simulations and the need for constitutive modelling parameters that are not readily available. This research presents novel lateral displacement and bending moment predictive models for closed and open-ended pipe piles, employing a Genetic Programming (GP) approach. Utilizing a soil dataset extracted from existing literature, comprising 392 data points for both pile types embedded in cohesionless soil and subjected to earthquake loading, the study intentionally limited input parameters to three features to enhance model simplicity: Standard Penetration Test (SPT) corrected blow count (N60), Peak Ground Acceleration (PGA), and pile slenderness ratio (L/D). Model performance was assessed via coefficient of determination (R2), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE), with R2 values ranging from 0.95 to 0.99 for the training set, and from 0.92 to 0.98 for the testing set, which indicate of high accuracy of prediction. Finally, the study concludes with a sensitivity analysis, evaluating the influence of each input parameter across different pile types.

Analytical model of penetration depth and energy dissipation considering impact position

In the research of projectile penetration into reinforced concrete, the discreteness of penetration depth widely exists in the experiments and empirical formulas, and different impact positions are one of the main reasons for this discreteness. However, the existing theoretical models considering impact position require self-programming methods to solve, and analytical solutions for penetration depth have not been provided. Moreover, existing penetration depth formulas have not dealt with the influence of impact position on penetration depth. To incorporate the influence of the impact position in the penetration depth formulas, this study has investigated different impact positions of the projectile penetration. Herein, the Young formula is used as an example, the projectile penetration process is regarded as a uniformly variable motion based on the constant resistance assumption, two methods are used to obtain the penetration constant resistance, and the energy dissipation of the steel bar at three typical impact positions is theoretically modeled. Finally, analytical solutions for the penetration depth at the three positions are proposed and the mechanism of differences at the three typical impact positions is revealed. In addition, finite element models are established for the three impact positions based on published penetration tests. The penetration depth and steel bar energy consumption of the three impact positions are compared and analyzed, and the analytical model is verified. The results suggest that different impact positions can cause different energy consumption of the steel bar, ultimately leading to varying penetration depth. This analytical model, which fully considers the impact positions of the projectile and the arrangement of the steel bars, can be generalized to any penetration resistance theoretical model or penetration depth calculation formula. It can play an important role in further improving and developing the penetration depth calculation formula, and guiding the design of reinforced concrete protection engineering.

Securing the Digital Frontier: Strategies for Cloud Computing Security, Database Protection, and Comprehensive Penetration Testing

This research paper explores the effectiveness of integrated cybersecurity strategies, focusing on the amalgamation of cloud computing security, database protection, and penetration testing into a unified risk management framework. The primary aim is to evaluate how such integration impacts the overall cybersecurity posture of organizations, offering insights into mitigating cyber threats, unauthorized access, and data breaches. Employing a survey-based methodology, the study gathered data from 365 professionals across cloud computing, database administration, and cybersecurity fields. Through descriptive statistics and Partial Least Squares Structural Equation Modeling (PLS-SEM), the research explored the interrelations between various cybersecurity strategies and their collective influence on organizational resilience against cyber threats. The findings underscore the significant benefits of a holistic cybersecurity approach, revealing that penetration testing, robust database security measures, and strict adherence to cloud computing security requirements significantly reduce vulnerabilities and incidents of data breaches. Moreover, the study established that a unified risk management framework substantially enhances an organization's cybersecurity posture, highlighting the critical role of integrated security measures in fostering organizational resilience. The research confirms the hypothesis that incorporating cybersecurity strategies across different domains leads to a synergistic enhancement of security defenses, offering a more robust mechanism against the multifaceted nature of cyber threats. In conclusion, the study advocates for the adoption of a comprehensive, integrated approach to cybersecurity, emphasizing regular penetration testing, stringent database security protocols, and adherence to cloud computing security standards as essential components of a robust cybersecurity framework. This approach not only mitigates the risk of cyber threats but also strengthens organizational resilience, ensuring a secure digital environment for future challenges.

Deep laser melting as controlled fragmentation method for multi-purpose projectiles

A controlled fragmentation method, by deep laser melting, for a multi-purpose projectile (penetrator) is presented, using a full-sized projectile with 1100 mm long, 148 mm diameter, and 17.8 mm wall thickness. Effects on penetration and fragmentation performance, for various laser melting parameters, are explored through penetration and fragmentation field tests. It is shown that it is possible to attain an optimal local microstructure, in the melted regions, that ensures a pre-defined fragmentation pattern upon explosion without compromising on the penetration capabilities.

Correlation between high temperature performance of gussasphalt mixture for steel bridge decks and rheology of asphalt mastic

Rutting is a prevalent issue in the Gussasphalt (GA) mixture layer of steel bridge deck pavements. This study aims to investigate the correlation between the rheology of GA mastic and the high-temperature performance of the GA mixture. To achieve this objective, GA mastic underwent temperature and frequency sweep tests, along with multiple stress creep and recovery tests employing a dynamic shear rheometer. Additionally, indentation tests, uniaxial penetration tests, and Lueer fluidity tests were conducted on the GA mixture. The Grey Relational Analysis method was employed to evaluate the relationship between asphalt mastic rheology and the high-temperature deformation resistance of the GA mixture. The findings reveal that the addition of mineral filler enhances the deformation resistance of both GA mastic and the mixture. The percent difference in non-recoverable creep compliance (Jnr-diff) was minimized when the weight ratio of filler to asphalt binder (F/B) was 2.5. Furthermore, increasing the F/B ratio from 2.0 to 3.5 resulted in a more than twofold increase in the GA mixture’s shear strength. Asphalt type emerged as a significant factor affecting the indentation parameter of the GA mixture, with an F-value reaching 8.82 based on ANOVA analysis. The rheological properties of GA mastic exhibited a significant correlation with the high-temperature performance of the mixture. The highest Grey Relational Grade of 0.87 was observed between the non-recoverable creep compliance at a 3.2 kPa stress level (Jnr3.2) and indentation. In future research, greater emphasis can be placed on exploring the micromechanical properties of the GA mastic-aggregate interface.

Glycerol Triacetate-Based Flame Retardant High-Temperature Electrolyte for the Lithium-Ion Battery.

Rechargeable batteries that can operate at elevated temperatures (>70 °C) with high energy density are long-awaited for industrial applications including mining, grid stabilization, naval, aerospace, and medical devices. However, the safety, cycle life, energy density, and cost of the available high-temperature battery technologies remain an obstacle primarily owing to the limited electrolyte options available. We introduce a flame-retardant electrolyte that can enable stable battery cycling at 100 °C by incorporating triacetin into the electrolyte system. Triacetin has excellent chemical stability with lithium metal, and conventional cathode materials can effectively reduce parasitic reactions and promises a good battery performance at elevated temperatures. Our findings reveal that Li-metal half-cells can be made that have high energy density, high Coulombic efficiency, and good cycle life with triacetin-based electrolytes and three different cathode chemistries. Moreover, the nail penetration test in a commercial-scale pouch battery using this new electrolyte demonstrated suppressed heat generation when the cell was damaged and excellent safety when using the triacetin-based electrolyte.

Formal Analysis and Detection for ROS2 Communication Security Vulnerability

Robotic systems have been widely used in various industries, so the security of communication between robots and their components has become an issue that needs to be focused on. As a framework for developing robotic systems, the security of ROS2 (Robot Operating System 2) can directly affect the security of the upper-level robotic systems. Therefore, it is a worthwhile research topic to detect and analyze the security of ROS2. In this study, we adopted a formal approach to analyze the security of the communication mechanism of ROS2. First, we used a state transition system to model the potential vulnerabilities of ROS2 based on the ROS2 communication mechanism and the basic process of penetration testing. Secondly, we introduced a CIA model based on the established vulnerability model and used linear temporal logic to define its security properties. Then, we designed and implemented a vulnerability detection tool for ROS2 applications based on the vulnerability model and security properties. Finally, we experimentally tested some ROS2-based applications, and the results show that ROS2 has vulnerabilities without additional protection safeguards.

High-velocity projectile penetration test and theoretical calculation of pseudo fluid penetration of calcareous sand

To explore the penetration resistance of calcareous sand media, penetration tests have been conducted in the velocity range of 200–1000 m/s using conical-nosed projectiles with a diameter of 14.5 mm. Further, a pseudo fluid penetration model applicable to the penetration of rigid projectiles in sand media is established according to the approximate flow of compacted sand in the adjacent zone of penetration. The correlation between the impedance function of projectile-target interaction and the internal friction features of pseudo fluid is clarified, and the effects of sand density, cone angle of nose-shaped projectile, and dynamic hardness on the penetration depth are investigated. The results verify the feasibility, wide applicability, and much lower error (with respect to the experimental data) of the proposed model as compared to the Slepyan hydrodynamic model.

An investigation on the jet formation and penetration characteristics of the CuCoCrFeNi high-entropy alloy liner

This study performs a series of mechanical tests, quasi-static and dynamic, on CuCoCrFeNi high-entropy alloys (HEAs) using an experimental setup to explore the performance of Cu-based HEAs in shaped charges. It derives the parameters for the Johnson–Cook constitutive model through fitting. A static penetration test is conducted with a small cone angle and a thin-walled liner. The outcomes are then compared to simulation data generated by AUTODYN software. They indicated that the CuCoCrFeNi HEA liner can produce a shaped-charge jet that achieves both penetration and reaming effects when driven by explosives. In a C45 steel target, the diameter of the penetration hole is 46.43% of the charge diameter. The experimental findings align closely with the simulations, indicating discrepancies of less than 12.13% in the diameters of the penetration holes and ∼2.56% in penetration depths. Hence, the numerical simulation approach and its parameters can be utilized to investigate the penetration characteristics of Cu-based HEA jets, providing a groundwork for future optimization of HEA-shaped charge designs.

A Comprehensive Review of the Evaluation and Application of Engineering Properties of Expansive Soil Based on Piezocone Penetration Test (CPTU)

Expansive soil presents several challenges in civil and geotechnical engineering because of its distinctive physical and mechanical properties, including considerable volumetric fluctuations, non-linear stress–strain behaviour, and high permeability. Owing to soil disturbances and sample size limitations during sampling, important parameters such as the expansive soil expansion force, compressive strength, and shear strength obtained through indoor experiments often cannot accurately reflect the values in situ. In this regard, in situ piezocone penetration testing has the advantages of small disturbances and high efficiency and has been widely used in subways, bridges, highways, and other engineering projects. This paper comprehensively summarizes the research progress of in situ testing technology in the evaluation and application of engineering properties of expansive soils in China and internationally. First, a detailed analysis of the basic theories and physical mechanisms of various in situ testing methods is provided, focusing on their applicability and accuracy in expansive soils. Second, examples of the application of in situ testing technology in expansive soil engineering are summarized. Finally, predictive models and methods based on in situ testing data, especially those that introduce cutting-edge models such as machine learning and advanced data analysis techniques, are discussed.

Small-strain characterization of Shanghai clays by triaxial compression tests

The mechanical properties of the upper Shanghai Layers 2-6 clays at small strain levels have been extensively investigated. Nonetheless, limited data exist on their small-strain characteristics through K 0-consolidated undrained triaxial compression tests, with even less information available for the deeper layers 8 and 10. This study employed a series of K 0-consolidated undrained TC tests on intact samples from both the upper layers 2-6 and the deeper layers 8 and 10 of Shanghai clay. We evaluated the undrained maximum secant stiffness (Eu max) and reference shear strain (γ0.7 ). An increase in over-consolidation ratio (OCR) results in a higher E u max/p’ and a more rapid decay of the G/G max with the increasing shear strain (γ). As the value of γ 0.7 increases with I p and decreases with OCR, a correlation between γ 0.7 and Ip can be established. This study observed significant correlations between the E u max, effective stress (p’), and the maximum deviatoric stress, as well as between E u max and the cone resistance obtained from field cone penetration tests. These correlations offer methods to estimate E u max and γ0.7 values based on parameters that are more readily measurable, which provide critical references for the calculations and design parameters in foundation engineering within the Shanghai region.

Advanced geospatial modeling and statistical evaluation of heterogenous geotechnical facets at multiple depths using the improved formulation of modified Shepard IDW algorithm

A formidable challenge in geology and geotechnics is the significant spatial heterogeneity in the subsoil characteristics in fine-scale grids. To mitigate this problem, geotechnical data is integrated as geotechnical soil maps (GSMs), which uses sophisticated interpolation techniques and provides an advanced understanding and accurate depiction of subsurface variability. This study uses an improved formulation of inverse distance weighting (IDW) algorithm based on modified Shepard method, integrated with the Google Earth Engine platform. The prediction efficiencies of GSMs and traditional IDW algorithm are statistically evaluated and compared, considering heterogeneous geotechnical facets at multiple depths in an unexplored region. Pertinent geotechnical properties including soil type, plasticity index, and standard penetration test were considered to evaluate the algorithm performance based on critical performance metrics. The results demonstrate that the improved formulation of the IDW algorithm is more relevant to field values and tends to align with Tobler's first law of geography by inducing a smooth transition rather than a disruptive trend owing to high geotechnical variability. The prediction accuracy increased by 10 – 20% compared to the traditional IDW algorithm. This study demonstrates and promotes the use of an improved formulation of the modified IDW algorithm considering its better accuracy and relevance to field value

Evaluation of variability of shear wave velocity in India

The shear wave velocity is a significant component in seismic hazard studies. This involves standard practice in seismic hazard analysis through ground motion prediction equations (GMPEs), ground response analyses (GRAs), or the computation of amplification factors. In practice, the shear wave velocity may be obtained through invasive methods, noninvasive methods, transformation models, or correlation-based methods. Currently, the uncertainty component of shear wave velocity has either been overlooked or oversimplified. The aim was to quantify the range of variations in shear wave velocity across India. The database included data of reported shear wave velocities in 20 states collected from various project reports and publications. A brief review of the methods used to obtain the data is given, along with a systematic highlight of the range of uncertainties encountered and their statistics. Base-case profiles for response analyses are recommended, and their statistics are examined. These observations aid computation of amplification factors. The transformation uncertainties of the shear wave velocity and the standard penetration test (SPT) were examined. The outcomes of the research will guide reliable seismic hazard studies across countries. Furthermore, this study paves the way for future development toward addressing uncertainties in shear wave velocity and facilitates the use of reliability-based design procedures.

Slope failure lines analysis to determine landslide potential based on standard penetration test method

Landslide events cause road access to be cut off, such as in the Payung area of Batu City, which connects Malang and Kediri. Analysis and evaluation of landslide disasters need to be carried out in this area to anticipate the next landslides and reduce economic losses. This study aims to determine landslide potential in the Payung Area, Batu City, using the SPT method. The test is carried out at 2 points of the slope on the provincial roads and the slope above the road so that the two measurement points can be correlated. The data needed to analyze slope stability include the internal shear angle, cohesion, and soil unit weight; analysis and modeling of slope stability using Geostudio SLOPE/W software. The results of the slope stability analysis at point 1 show that the average failure line is at a depth of 6.00 m with the smallest Safety Factor (SF) value of 0.710 in scenario 2. While the slope at point 2, the failure line is at a depth of 1.50 m with the smallest FK value of 0.840 in scenario 2. Significant changes in the N-SPT value indicate differences in soil mechanical properties, such as shear angle and cohesion that affect the stability of the slope and cause landslides.

Soil classification based on unsupervised learning using cone penetration test data

Borehole data obtained during geological surveys are the most essential source for understanding soil stratification. It is a prerequisite to know the soil classes up to some depths prior to any construction. However, the direct method to identify the soil classes by drilling boreholes and testing soil samples is costly. A cost-effective alternative is the Cone Penetration Testing (CPT), which is one of the most popular soil investigation methods. This paper explores the intelligent classification of soil layers based on CPT data using three unsupervised machine learning methods: K-means, Gaussian Mixture Process, and BIRCH. The research investigates the classification performance of different models in scenarios with 2 combinations, 3 combinations, 4 combinations, and 5 combinations. The results indicate that the Gaussian Mixture Process method exhibits the best classification performance, followed by the BIRCH method, while K-means performs relatively poorly. Using unsupervised learning for intelligent soil layer classification offers a fast and clear process, but the accuracy still requires further improvement. This study provides a valuable reference for future soil classification studies.

Application of PISA method for monopile design in layered soil

The foundation design for offshore wind turbines (OWTs) is critical to ensuring their structural integrity and long-term stability. Large-diameter monopiles are widely used for OWTs owing to their proven effectiveness. The conventional design approach, derived from the oil and gas industry’s p-y model, has limitations when applied to monopiles for OWTs. Consequently, a novel design method based on the PISA joint industry research project was developed, which extends beyond the traditional lateral soil resistance (p-y curves) and incorporates additional soil reaction components from shaft friction, pile base shear, and base moment. Unlike the simplistic rule-based conventional approaches, the proposed method necessitates site-specific 3D finite element (FE) simulations for precise calibration of soil reaction curves. Although successfully applied in European offshore wind farms, the PISA method’s performance in regions with distinct seabed compositions, such as China, remains to be verified. Therefore, this paper presents a comprehensive case study conducted at the Xiangshan wind farm, a representative site characterized by layered soil. The study employed in-situ investigations (cone penetration test, borehole) and laboratory tests (direct simple shear, bender element) to delineate the seabed soil profile and derive essential soil parameters for accurate foundation design. To facilitate the design, an Abaqus-based design tool was developed, which automated the extraction of soil reaction curves from the 3D FE simulations, calibration of PISA springs, and execution of one-dimensional beam-spring analyses employing Timoshenko beam theory. Comparative analyses were performed on the computed responses of piles, encompassing load-deflection curves, pile deflections, and bending moment profiles. The outcomes from the 3D FE simulations, uncalibrated rule-based PISA model, and calibrated PISA model were compared to validate the PISA method for monopile design in layered soil conditions.