Penetration Tests of Multi-Bucket Foundation in Sand for Offshore Wind Turbines

Suction foundations are generally installed with negative pressures to overcome the resistance of soils and complete the penetration,but excessive negative pressures are also avoided to cause seepage damages.In this paper,the model test method was used to analyze the movement characteristics of multi-bucket foundations in the process of sinking in sand,and the common calculation methods of sinking resistances are verified.The critical negative pressure corresponding to the seepage failure of foundation was determined under the action of increasing negative pressure step by step and the characteristics of soil failure were studied.The calculation formula of critical suction in sand was verified in application,and according to the test results,the value of seepage coefficient was modified,which provides an example for the study of suction foundation in sand soils.

FEM-DEM coupled modeling of cone penetration tests in lunar soil

Cone penetration test(CPT)is an appropriate technique for quickly determining the geotechnical properties of lunar soil,which is valuable for in situ lunar exploration.Utilizing a typical coupling method recently developed by the authors,a finite element method(FEM)-discrete element method(DEM)coupled model of CPTs is obtained.A series of CPTs in lunar soil are simulated to qualitatively reveal the flow of particles and the development of resistance throughout the penetration process.In addition,the effects of major factors,such as penetration velocity,penetration depth,cone tip angle,and the low gravity on the Moon surface are investigated.

Efficient Penetration Testing Path Planning Based on Reinforcement Learning with Episodic Memory

Intelligent penetration testing is of great significance for the improvement of the security of information systems,and the critical issue is the planning of penetration test paths.In view of the difficulty for attackers to obtain complete network information in realistic network scenarios,Reinforcement Learning(RL)is a promising solution to discover the optimal penetration path under incomplete information about the target network.Existing RL-based methods are challenged by the sizeable discrete action space,which leads to difficulties in the convergence.Moreover,most methods still rely on experts’knowledge.To address these issues,this paper proposes a penetration path planning method based on reinforcement learning with episodic memory.First,the penetration testing problem is formally described in terms of reinforcement learning.To speed up the training process without specific prior knowledge,the proposed algorithm introduces episodic memory to store experienced advantageous strategies for the first time.Furthermore,the method offers an exploration strategy based on episodic memory to guide the agents in learning.The design makes full use of historical experience to achieve the purpose of reducing blind exploration and improving planning efficiency.Ultimately,comparison experiments are carried out with the existing RL-based methods.The results reveal that the proposed method has better convergence performance.The running time is reduced by more than 20%.

Obtaining 2D Soil Resistance Profiles from the Integration of Electrical Resistivity Data and Standard Penetration Test (SPT) and Light Dynamic Penetrometer (DPL) Resistance Tests—Applications in Mass Movements Studies

In Brazil and various regions globally, the initiation of landslides is frequently associated with rainfall;yet the spatial arrangement of geological structures and stratification considerably influences landslide occurrences. The multifaceted nature of these influences makes the surveillance of mass movements a highly intricate task, requiring an understanding of numerous interdependent variables. Recent years have seen an emergence in scholarly research aimed at integrating geophysical and geotechnical methodologies. The conjoint examination of geophysical and geotechnical data offers an enhanced perspective into subsurface structures. Within this work, a methodology is proposed for the synchronous analysis of electrical resistivity geophysical data and geotechnical data, specifically those extracted from the Light Dynamic Penetrometer (DPL) and Standard Penetration Test (SPT). This study involved a linear fitting process to correlate resistivity with N10/SPT N-values from DPL/SPT soundings, culminating in a 2D profile of N10/SPT N-values predicated on electrical profiles. The findings of this research furnish invaluable insights into slope stability by allowing for a two-dimensional representation of penetration resistance properties. Through the synthesis of geophysical and geotechnical data, this project aims to augment the comprehension of subsurface conditions, with potential implications for refining landslide risk evaluations. This endeavor offers insight into the formulation of more effective and precise slope management protocols and disaster prevention strategies.

Enhancing Mobile Security through Comprehensive Penetration Testing

In today’s era, where mobile devices have become an integral part of our daily lives, ensuring the security of mobile applications has become increasingly crucial. Mobile penetration testing, a specialized subfield within the realm of cybersecurity, plays a vital role in safeguarding mobile ecosystems against the ever-evolving landscape of threats. The ubiquity of mobile devices has made them a prime target for cybercriminals, and the data and functionality accessed through mobile applications make them valuable assets to protect. Mobile penetration testing is designed to identify vulnerabilities, weaknesses, and potential exploits within mobile applications and the devices themselves. Unlike traditional penetration testing, which often focuses on network and server security, mobile penetration testing zeroes in on the unique challenges posed by mobile platforms. Mobile penetration testing, a specialized field within cybersecurity, is an essential tool in the Cybersecurity specialists’ toolkit to protect mobile ecosystems from emerging threats. This article introduces mobile penetration testing, emphasizing its significance, including comprehensive learning labs for Android and iOS platforms, and highlighting how it distinctly differs from traditional penetration testing methodologies.

Study on strength properties and soil behaviour type classification of Huanghe River Delta silts based on variable rate piezocone penetration test

Fine-grained silt is widely distributed in the Huanghe River Delta(HRD)in China,and the sedimentary structure is complex,meaning that the clay content in the silt is variable.The piezocone penetration test(CPTu)is the most widely approved in situ test method.It can be used to invert soil properties and interpret soil behavior.To analyse the strength properties of surface sediments in the HRD,this paper evaluated the friction angle and its inversion formula through the CPTu penetration test and monotonic simple shear test and other soil unit experiments.The evaluation showed that the empirical formula proposed by Kulhawy and Mayne had better prediction and inversion effect.The HRD silts with clay contents of 9.2%,21.4%and 30.3%were selected as samples for the CPTu variable rate penetration test.The results show as follows.(1)The effects of the clay content on the tip resistance and the pore pressure of silt under different penetration rates were summarized.The tip resistance Q_t is strongly dependent on the clay content of the silt,the B_(q)value of the silt tends to 0 and is not significantly affected by the change of the CPTu penetration rate.(2)Five soil behavior type classification charts and three soil behavior type indexes based on CPTu data were evaluated.The results show that the soil behavior type classification chart based on soil behavior type index ISBT,the Robertson 2010 behavior type classification chart are more suitable for the silty soil in the HRD.

Side-Channel Attacks & Data Exfiltration Using Wall Outlet USB Power Adapters

The number and creativity of side channel attacks have increased dramatically in recent years. Of particular interest are attacks leveraging power line communication to 1) gather information on power consumption from the victim and 2) exfiltrate data from compromised machines. Attack strategies of this nature on the greater power grid and building infrastructure levels have been shown to be a serious threat. This project further explores this concept of a novel attack vector by creating a new type of penetration testing tool: an USB power adapter capable of remote monitoring of device power consumption and communicating through powerline communications.

Regressive approach for predicting bearing capacity of bored piles from cone penetration test data

In this study, th e least sq u are su p p o rt v ecto r m achine （LSSVM） alg o rith m w as applied to predicting th ebearing capacity o f b ored piles e m b ed d ed in sand an d m ixed soils. Pile g eo m etry an d cone p e n e tra tio nte s t （CPT） resu lts w ere used as in p u t variables for pred ictio n o f pile bearin g capacity. The d ata u se d w erecollected from th e existing litera tu re an d consisted o f 50 case records. The application o f LSSVM w ascarried o u t by dividing th e d ata into th re e se ts： a train in g se t for learning th e pro b lem an d obtain in g arelationship b e tw e e n in p u t variables an d pile bearin g capacity, and testin g an d validation sets forevaluation o f th e predictive an d g en eralization ability o f th e o b tain ed relationship. The predictions o f pilebearing capacity by LSSVM w ere evaluated by com paring w ith ex p erim en tal d ata an d w ith th o se bytrad itio n al CPT-based m eth o d s and th e gene ex pression pro g ram m in g （GEP） m odel. It w as found th a t th eLSSVM perform s w ell w ith coefficient o f d eterm in atio n , m ean, an d sta n d ard dev iatio n equivalent to 0.99,1.03, an d 0.08, respectively, for th e testin g set, an d 1, 1.04, an d 0.11, respectively, for th e v alidation set. Thelow values o f th e calculated m ean squared e rro r an d m ean ab so lu te e rro r indicated th a t th e LSSVM w asaccurate in p redicting th e pile bearing capacity. The results o f com parison also show ed th a t th e p roposedalg o rith m p red icted th e pile bearin g capacity m ore accurately th a n th e trad itio n al m eth o d s including th eGEP m odel.

An Automated Penetration Semantic Knowledge Mining Algorithm Based on Bayesian Inference

Mining penetration testing semantic knowledge hidden in vast amounts of raw penetration testing data is of vital importance for automated penetration testing.Associative rule mining,a data mining technique,has been studied and explored for a long time.However,few studies have focused on knowledge discovery in the penetration testing area.The experimental result reveals that the long-tail distribution of penetration testing data nullifies the effectiveness of associative rule mining algorithms that are based on frequent pattern.To address this problem,a Bayesian inference based penetration semantic knowledge mining algorithm is proposed.First,a directed bipartite graph model,a kind of Bayesian network,is constructed to formalize penetration testing data.Then,we adopt the maximum likelihood estimate method to optimize the model parameters and decompose a large Bayesian network into smaller networks based on conditional independence of variables for improved solution efficiency.Finally,irrelevant variable elimination is adopted to extract penetration semantic knowledge from the conditional probability distribution of the model.The experimental results show that the proposed method can discover penetration semantic knowledge from raw penetration testing data effectively and efficiently.

Adaptive sampling strategy for characterizing spatial distribution of soil liquefaction potential using cone penetration test

Characterizing spatial distribution of soil liquefaction potential is critical for assessing liquefactionrelated hazards(e.g.building damages caused by liquefaction-induced differential settlement).However,in engineering practice,soil liquefaction potential is usually measured at limited locations in a specific site using in situ tests,e.g.cone penetration tests(CPTs),due to the restrictions of time,cost and access to subsurface space.In these cases,liquefaction potential of soil at untested locations requires to be interpreted from limited measured data points using proper interpolation method,leading to remarkable statistical uncertainty in liquefaction assessment.This underlines an important question of how to optimize the locations of CPT soundings and determine the minimum number of CPTs for achieving a target reliability level of liquefaction assessment.To tackle this issue,this study proposes a smart sampling strategy for determining the minimum number of CPTs and their optimal locations in a selfadaptive and data-driven manner.The proposed sampling strategy leverages on information entropy and Bayesian compressive sampling(BCS).Both simulated and real CPT data are used to demonstrate the proposed method.Illustrative examples indicate that the proposed method can adaptively and sequentially select the required number and optimal locations of CPTs.

Seasonal influence on cone penetration test: An unsaturated soil site example

Interpretation of electric cone penetration test(CPT) based pore water pressure measurement(CPTu) is well established for soils with behavior that follows classical soil mechanics. The literature on the interpretation of these tests performed on unsaturated tropical soils is limited, and little is known about the influence of soil suction on in situ test data. In this context, the CPT data are presented and discussed to illustrate the seasonal variability in an unsaturated tropical soil site. The test data show that soil suction significantly influenced CPT data up to a depth of 4 m at the study site. It shows the importance of considering seasonal variability in unsaturated soil sites caused by soil suction, which was related to water content through a soil-water retention curve(SWRC). It is also important to consider this aspect in the interpretation of CPT data from these soils.

A case study on the soil classification of the Yellow River Delta based on piezocone penetration test

Piezocone penetration test(CPTu),the preferred in-situ tool for submarine investigation,is significant for soil classification and soil depth profile prediction,which can be used to predict soil types and states.However,the accuracy of these methods needs to be validated for local conditions.To distinguish and evaluate the properties of the shallow surface sediments in Chengdao area of the Yellow River Delta,seabed CPTu tests were carried out at ten stations in this area.Nine soil classification methods based on CPTu data are applied for soil classification.The results of classification are compared with the in-situ sampling to determine whether the method can provide sufficient resolution.The methods presented by Robertson(based on soil behavior type index Ic),Olsen and Mitchell are the more consistent and compatible ones compared with other methods.Considering that silt soils have potential to liquefy under storm tide or other adverse conditions,this paper is able to screen soil classification methods suitable for the Chengdao area and help identify the areas where liquefaction or submarine landslide may occur through CPTu investigation.

Structured Query Language Injection Penetration Test Case Generation Based on Formal Description

Aiming to improve the Structured Query Language( SQL) injection penetration test accuracy through the formalismguided test case generation,an attack purpose based attack tree model of SQL injection is proposed,and then under the guidance of this model, the formal descriptions for the SQL injection vulnerability feature and SQL injection attack inputs are established. Moreover,according to new coverage criteria,these models are instantiated and the executable test cases are generated.Experiments show that compared with the random enumerated test case used in other works,the test case generated by our method can detect the SQL injection vulnerability more effectively. Therefore,the false negative is reduced and the test accuracy is improved.

Liquefaction Assessment in Golem Area, Albania, by Means of In-situ Tests

The liquefaction is a very significant phenomenon in clayey silty soils, silty sands and also sands. The high potential of liquefaction is generally recognized when these types of soils are laid under the hydrostatic water table. Low plasticity silts, silty sands and sands are found as recent alluvial deposits in the western coastal part of Albania, especially in the sandy beaches of Adriatic Sea near Durres City. The aim of this study is to evaluate the soil liquefaction potential in the area of Golem. Ten CPTUs （cone penetration test with pore pressure measurements） are carried out for the site investigation of soils. In this paper, results of the CPTU based liquefaction analysis are presented. The data of two CPTUs （10 in total） are analyzed and factor of safety was found by considering different levels of hazard and ground water. The results of liquefaction potential analysis show that the soils in the area of Golem have a high risk of liquefaction.

In Situ Tests--Predicted vs. Observed Settlements： A Comparative Case Study

This paper aims to deal with the comparison of the estimated settlements derived by in situ tests with the observed settlements in site, in order to evaluate the accuracy of settlement prediction by in situ tests, in comparison not only with site observation by topographic means, but also with the values of settlements derived by numerical analysis by means of PLAXIS 2D and 3 D. The site where are carried out the tests and periodically are observed the settlements since the beginning of construction process, is located in the Oil Product Terminal, at the industrial park of Porto Romano, Durres, Albania. The main purpose of this project was the ground improvement by using preloading method in order to prevent liquefaction process and settlements. The data used to conduct this study are taken by the site investigation done after inserting into the soil vertical drains made of columns of free--draining gravel （gravel pile drains） until 14 m depth and center-to-center spacing of 2 m, and wick drains （premanufactured） until 25 m depth and center-to-center spacing of 1.8 m. The observed settlements are periodically measured by topographic equipments. This paper will present the conclusions derived by settlement analyzes from in situ tests and site observations.

Methodology for Obtaining Optimal Sleeve Friction and Friction Ratio Estimates from CPT Data

Cone penetration testing (CPT) is a cost effective and popular tool for geotechnical site characterization. CPT consists of pushing at a constant rate an electronic penetrometer into penetrable soils and recording cone bearing (qc), sleeve friction (fc) and dynamic pore pressure (u) with depth. The measured qc, fs and u values are utilized to estimate soil type and associated soil properties. A popular method to estimate soil type from CPT measurements is the Soil Behavior Type (SBT) chart. The SBT plots cone resistance vs friction ratio, Rf [where: Rf = (fs/qc)100%]. There are distortions in the CPT measurements which can result in erroneous SBT plots. Cone bearing measurements at a specific depth are blurred or averaged due to qc values being strongly influenced by soils within 10 to 30 cone diameters from the cone tip. The qcHMM algorithm was developed to address the qc blurring/averaging limitation. This paper describes the distortions which occur when obtaining sleeve friction measurements which can in association with qc blurring result in significant errors in the calculated Rf values. This paper outlines a novel and highly effective algorithm for obtaining accurate sleeve friction and friction ratio estimates. The fc optimal filter estimation technique is referred to as the OSFE-IFM algorithm. The mathematical details of the OSFE-IFM algorithm are outlined in this paper along with the results from a challenging test bed simulation. The test bed simulation demonstrates that the OSFE-IFM algorithm derives accurate estimates of sleeve friction from measured values. Optimal estimates of cone bearing and sleeve friction result in accurate Rf values and subsequent accurate estimates of soil behavior type.

Technique for Estimating the Cone Bearing Smoothing Parameters

Cone penetration testing (CPT) is an extensively utilized and cost effective tool for geotechnical site characterization. CPT consists of pushing at a constant rate an electronic cone into penetrable soils and recording the resistance to the cone tip (qc value). The measured qc values (after correction for the pore water pressure) are utilized to estimate soil type and associated soil properties based predominantly on empirical correlations. The most common cone tips have associated areas of 10 cm2 and 15 cm2. Investigators also utilized significantly larger cone tips (33 cm2 and 40 cm2) so that gravelly soils can be penetrated. Small cone tips (2 cm2 and 5 cm2) are utilized for shallow soil investigations. The cone tip resistance measured at a particular depth is affected by the values above and below the depth of interest which results in a smoothing or blurring of the true bearing values. Extensive work has been carried out in mathematically modelling the smoothing function which results in the blurred cone bearing measurements. This paper outlines a technique which facilitates estimating the dominant parameters of the cone smoothing function from processing real cone bearing data sets. This cone calibration technique is referred to as the so-called CPSPE algorithm. The mathematical details of the CPSPE algorithm are outlined in this paper along with the results from a challenging test bed simulation.

Comparison of Vs and SPT Soil Liquefaction Assessments of NCEER: Including Hypothesis Testing

Soil liquefaction is one of the complex research topics in geotechnical engineering and engineering geology. Especially after the 1964 Niigata earthquake (Japan) induced many soil liquefaction incidents, a variety of soil liquefaction studies were conducted and reported, including the liquefaction potential assessment methods utilizing the shear wave velocity (Vs) or SPT-N profiles (SPT: standard penetration test). This study used the Vs and SPT methods recommended by the National Center for Earthquake Engineering Research (NCEER) to examine which is more conservative according to the assessment results on 41 liquefiable soil layers at sites in two major cities in Taiwan. Statistical hypothesis testing was used to make the analysis more quantitative and objective. Based on three sets of hypothesis tests, it shows that the hypothesis—the SPT method is more conservative than the Vs method—was not rejected on a 5% level of significance.

Study of LDBPs Shaft Skin Friction for Piles in Cohesiove Soils

The methodology of predicting pile shaft skin ultimate friction has been studied in a systematic way. In the light of that, the analysis of the pile shaft resistance for bored and cast in situ piles in cohesive soils was carried out thoroughly in the basis of field performance data of 10 fully instrumented large diameter bored piles (LDBPs) used as the bridge foundation. The undrained strength index μ in term of cohesive soils was brought forward in allusion to the cohesive soils in the consistence plastic state, and can effectively combine the friction angle and the cohesion of cohesive soils in undrained condition. And that the classical ' α method' was modified much in effect to predict the pile shaft skin friction of LDBPs in cohesive soils. Furthermore, the approach of standard penetration test (SPT) N value used to estimate the pile shaft skin ultimate friction was analyzed, and the calculating formulae were established for LDBPs in clay and silt clay respectively.

Laboratory Test on Long-Term Deterioration of Cement Soil in Seawater Environment

Laboratory tests were conducted to study the effects of curing time, cement ratio and seawater pressure on cement soil deterioration formed at simulative marine soft clay sites. Deterioration depth was determined on the basis of characteristics of penetration resistance and penetration depth curves, and the deterioration depth of cement soil with the cement ratio of 7%, reached 31.8 mm after 720 d. Results of research indicated that deterioration extended quickly under seawater environment and the deterioration depth increased with the prolonging curing time. In addition, the water pressure could speed up deterioration. With the increase of cement content, the strength of cement soil increased obviously. At the same time, the deterioration depth decreased significantly. The concentration of calcium ion in the cement stabilized soil increased with the increase of depth, while that of magnesium ion gradually decreased. The variations were consistent with energy dispersive spectrometer(EDS)analysis results, and the calcium concentration with depth was in a good consistency with strength distribution at long term. The results showed that the deterioration became more serious with the curing time, and it was related to calcium leaching.