Experimental p-y curves for liquefied soils from centrifuge tests

The present study aims to obtain p-y curves(Winkler spring properties for lateral pile-soil interaction)for liquefied soil from 12 comprehensive centrifuge test cases where pile groups were embedded in liquefiable soil.The p-y curve for fully liquefied soil is back-calculated from the dynamic centrifuge test data using a numerical procedure from the recorded soil response and strain records from the instrumented pile.The p-y curves were obtained for two ground conditions:(a)lateral spreading of liquefied soil,and(b)liquefied soil in level ground.These ground conditions are simulated in the model by having collapsing and non-collapsing intermittent boundaries,which are modelled as quay walls.The p-y curves back-calculated from the centrifuge tests are compared with representative reduced API p-y curves for liquefied soils(known as p-multiplier).The response of p-y curves at full liquefaction is presented and critical observations of lateral pile-soil interaction are discussed.Based on the results of these model tests,guidance for the construction of p-y curves for use in engineering practice is also provided.

Dynamic p-y curves for vertical and batter pile groups in liquefied sand

In this study,centrifuge model tests of vertical and batter pile groups in liquefied sand were conducted on a centrifuge shaking table.The dynamic p-y curves for these pile groups before and during sand liquefaction were obtained from calculations based on test data.The results confirm that liquefaction contributes to a reduction in the energy consumption of pile foundations,with the degradation effect being more pronounced for batter pile groups.At shallow depths,the difference in the backbone gradients of the p-y curves after liquefaction for vertical and batter pile groups indicates that the lateral stiffness of a batter pile group is greater than that of a vertical pile group.As shaking intensity increases,the lateral stiffness of a vertical pile group increases with depth during the late stage of sand liquefaction.However,the lateral stiffness of a batter pile group during liquefaction does not vary with depth.The results of this study provide a reference for the seismic design of vertical and batter pile groups in liquefied soil.

A comparative study of data-driven battery capacity estimation based on partial charging curves

With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.

Method for determining the position of landslide slip-surface with a typical inclinometric curves

In the actual monitoring of deep hole displacement,the identification of slip surfaces is primarily based on abrupt changes observed in the inclinometric curve.In conventional identification methods,inclinometric curves exhibiting indications of sliding can be categorized into three types:B-type,D-type,and r-type.The position of the slip surface is typically determined by identifying the depth corresponding to the point of maximum displacement mutation.However,this method is sensitive to the interval of measurement points and the observation scale of the coordinate axes and suffers from unclear sliding surfaces and uncertain values.Based on the variation characteristics of these diagonal curves,we classified the landslide into three components:the sliding body,the sliding interval,and the immobile body.Moreover,three different generalization models were established to analyze the relationships between the curve form and the slip surface location based on different physical indicators such as displacement rate,relative displacement,and acceleration.The results show that the displacement rate curves of an r-type slope exhibit a clustering feature in the sliding interval,and by solving for the depth of discrete points within the step phase,it is possible to determine the location of the slip surface.On the other hand,D-type slopes have inflection points in the relative displacement curve located at the slip surface.The acceleration curves of B-type slopes exhibit clustering characteristics during the sliding interval,while the scattered acceleration data demonstrate wandering characteristics.Consequently,the slip surface location can be revealed by solving the depth corresponding to the maximum acceleration with cubic spline interpolation.The approach proposed in this paper was applied to the monitoring data of a landslide in Yunnan Province,China.The results indicate that our approach can accurately identify the slip surface location and enable computability of its position,thereby enhancing applicability and reliability of the deep-hole displacement monitoring data.

Analytical Determination of Size and Location of Roadside Horizontal Sightline Offsets for Compound Curves

AASHTO’s guideline for geometric design of highways and similar guidelines require that roadside areas on the inside of horizontal curves be cleared of high objects to provide stopping sight distance. The guidelines have analytical models for determining the extent of clearance, known as the horizontal sightline offset or clearance offset, for simple curves. Researchers in the past have developed analytical models for clearance offsets for spiraled and reverse curves. Very few researchers developed analytical models for available sight distances for compound curves. Still missing are models for horizontal sightline offsets and locations of the offsets for compound curves. The objective of this paper is to present development of analytical models and charts for determining horizontal sightline offsets and their locations for compound curves. The paper considers curves whose component arcs are individually shorter than stopping sight distance. The resulting models and the charts have been verified with accurate values determined using graphical methods. The models and the charts will find application in geometric design of highway compound curves.

Using Pearson’s System of Curves to Approximate the Distributions of the Difference between Two Correlated Estimates of Signal-to-Noise Ratios: The Cases of Bivariate Normal and Bivariate Lognormal Distributions

Background: The signal-to-noise ratio (SNR) is recognized as an index of measurements reproducibility. We derive the maximum likelihood estimators of SNR and discuss confidence interval construction on the difference between two correlated SNRs when the readings are from bivariate normal and bivariate lognormal distribution. We use the Pearsons system of curves to approximate the difference between the two estimates and use the bootstrap methods to validate the approximate distributions of the statistic of interest. Methods: The paper uses the delta method to find the first four central moments, and hence the skewness and kurtosis which are important in the determination of the parameters of the Pearsons distribution. Results: The approach is illustrated in two examples;one from veterinary microbiology and food safety data and the other on data from clinical medicine. We derived the four central moments of the target statistics, together with the bootstrap method to evaluate the parameters of Pearsons distribution. The fitted Pearsons curves of Types I and II were recommended based on the available data. The R-codes are also provided to be readily used by the readers.

Message Verification Protocol Based on Bilinear Pairings and Elliptic Curves for Enhanced Security in Vehicular Ad Hoc Networks

Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation sector.However,the exchange of beacons and messages over public channels among vehicles and roadside units renders these networks vulnerable to numerous attacks and privacy violations.To address these challenges,several privacy and security preservation protocols based on blockchain and public key cryptography have been proposed recently.However,most of these schemes are limited by a long execution time and massive communication costs,which make them inefficient for on-board units(OBUs).Additionally,some of them are still susceptible to many attacks.As such,this study presents a novel protocol based on the fusion of elliptic curve cryptography(ECC)and bilinear pairing(BP)operations.The formal security analysis is accomplished using the Burrows–Abadi–Needham(BAN)logic,demonstrating that our scheme is verifiably secure.The proposed scheme’s informal security assessment also shows that it provides salient security features,such as non-repudiation,anonymity,and unlinkability.Moreover,the scheme is shown to be resilient against attacks,such as packet replays,forgeries,message falsifications,and impersonations.From the performance perspective,this protocol yields a 37.88%reduction in communication overheads and a 44.44%improvement in the supported security features.Therefore,the proposed scheme can be deployed in VANETs to provide robust security at low overheads.

Sensitive Information Security Based on Elliptic Curves

The elliptic curve cryptography algorithm represents a major advancement in the field of computer security. This innovative algorithm uses elliptic curves to encrypt and secure data, providing an exceptional level of security while optimizing the efficiency of computer resources. This study focuses on how elliptic curves cryptography helps to protect sensitive data. Text is encrypted using the elliptic curve technique because it provides great security with a smaller key on devices with limited resources, such as mobile phones. The elliptic curves cryptography of this study is better than using a 256-bit RSA key. To achieve equivalent protection by using the elliptic curves cryptography, several Python libraries such as cryptography, pycryptodome, pyQt5, secp256k1, etc. were used. These technologies are used to develop a software based on elliptic curves. If built, the software helps to encrypt and decrypt data such as a text messages and it offers the authentication for the communication.

Review on Service Curves of Typical Scheduling Algorithms

In recent years,various internet architectures,such as Integrated Services(IntServ),Differentiated Services(DiffServ),Time Sensitive Networking(TSN)and Deterministic Networking(DetNet),have been proposed to meet the quality-of-service(QoS)requirements of different network services.Concurrently,network calculus has found widespread application in network modeling and QoS analysis.Network calculus abstracts the details of how nodes or networks process data packets using the concept of service curves.This paper summarizes the service curves for typical scheduling algorithms,including Strict Priority(SP),Round Robin(RR),Cycling Queuing and Forwarding(CQF),Time Aware Shaper(TAS),Credit Based Shaper(CBS),and Asynchronous Traffic Shaper(ATS).It introduces the theory of network calculus and then provides an overview of various scheduling algorithms and their associated service curves.The delay bound analysis for different scheduling algorithms in specific scenarios is also conducted for more insights.

The Effectiveness of the Havriliak-Negami Model in Predicting the Master Curves of the Asphalt Blends with SBS Triblock Copolymer and Organic-Montmorillonite at Different Temperatures and Frequencies

The dynamic viscoelastic properties of asphalt AC-20 and its composites with Organic-Montmorillonite clay (OMMt) and SBS were modeled using the empirical Havriliak-Negami (HN) model, based on linear viscoelastic theory (LVE). The HN parameters, α, β, G0, G∞and τHN were determined by solving the HN equation across various temperatures and frequencies. The HN model successfully predicted the rheological behavior of the asphalt and its blends within the temperature range of 25˚C - 40˚C. However, deviations occurred between 40˚C - 75˚C, where the glass transition temperature Tg of the asphalt components and the SBS polymer are located, rendering the HN model ineffective for predicting the dynamic viscoelastic properties of composites containing OMMt under these conditions. Yet, the prediction error of the HN model dropped to 2.28% - 2.81% for asphalt and its mixtures at 100˚C, a temperature exceeding the Tg values of both polymer and asphalt, where the mixtures exhibited a liquid-like behavior. The exponent α and the relaxation time increased with temperature across all systems. Incorporating OMMt clay into the asphalt blends significantly enhanced the relaxation dynamics of the resulting composites.

Gaussian Distance Weighted Algorithm for Geometric Characteristics of Three-Dimensional Discrete Curves

Discrete curves are composed of a set of ordered discrete points distributed at the intersection of the scanning plane and the surface of the object. In order to accurately calculate the geometric characteristics of any point on the discrete curve, a distance-based Gaussian weighted algorithm is proposed to estimate the geometric characteristics of three-dimensional space discrete curves. According to the definition of discrete derivatives, the algorithm fully considers the relative position difference between a specific point and its neighboring points, introduces the distance weighting idea, and integrates the smoothing strategy. The experiment uses two spatial discrete curves for uniform and non-uniform sampling, and compares them with two commonly used estimation algorithms. The comparative analysis is carried out in terms of sampling density, neighborhood radius and noise resistance. The experimental results show that the Gaussian distance weighted algorithm is effective and provides an efficient algorithm for underground pipeline safety detection.

Magnetic Field Curves and Magnetic Equipotential Surfaces around Crossing Electrical Wires Replacing Classical Magnetic Field Lines

This article is based on a recent model specifically defining magnetic field values around electrical wires. With this model, calculations of field around parallel wires were obtained. Now, this model is extended with the new concept of magnetic equipotential surface to magnetic field curves around crossing wires. Cases of single, double, and triple wires are described. Subsequent article will be conducted for more general scenarios where wires are neither infinite nor parallel.

The Origin of the Flat Rotation Curves in Spiral Galaxies: The Hidden Roles of Glitching SMDEOs and Emission of Gravitational Waves

Supermassive DEOs (SMDEOs) are cosmologically evolved objects made of irreducible incompressible supranuclear dense superfluids: The state we consider to govern the matter inside the cores of massive neutron stars. These cores are practically trapped in false vacua, rendering their detection by outside observers impossible. Based on massive parallel computations and theoretical investigations, we show that SMDEOs at the centres of spiral galaxies that are surrounded by massive rotating torii of normal matter may serve as powerful sources for gravitational waves carrying away roughly 1042 erg/s. Due to the extensive cooling by GWs, the SMDEO-Torus systems undergo glitching, through which both rotational and gravitational energies are abruptly ejected into the ambient media, during which the topologies of the embedding spacetimes change from curved into flatter ones, thereby triggering a burst gravitational energy of order 1059 erg. Also, the effects of glitches found to alter the force balance of objects in the Lagrangian-L1 region between the central SMDEO-Torus system and the bulge, enforcing the enclosed objects to develop violent motions, that may explain the origin of the rotational curve irregularities observed in the innermost part of spiral galaxies. Our study shows that the generated GWs at the centres of galaxies, which traverse billions of objects during their outward propagations throughout the entire galaxy, lose energy due to repeatedly squeezing and stretching the objects. Here, we find that these interactions may serve as damping processes that give rise to the formation of collective forces f∝m(r)/r, that point outward, endowing the objects with the observed flat rotation curves. Our approach predicts a correlation between the baryonic mass and the rotation velocities in galaxies, which is in line with the Tully-Fisher relation. The here-presented self-consistent approach explains nicely the observed rotation curves without invoking dark matter or modifying Newtonian gravitation in the low-field approximation.

Beyond p-y method:A review of artificial intelligence approaches for predicting lateral capacity of drilled shafts in clayey soils

In 2023,pivotal advancements in artificial intelligence(AI)have significantly experienced.With that in mind,traditional methodologies,notably the p-y approach,have struggled to accurately model the complex,nonlinear soil-structure interactions of laterally loaded large-diameter drilled shafts.This study undertakes a rigorous evaluation of machine learning(ML)and deep learning(DL)techniques,offering a comprehensive review of their application in addressing this geotechnical challenge.A thorough review and comparative analysis have been carried out to investigate various AI models such as artificial neural networks(ANNs),relevance vector machines(RVMs),and least squares support vector machines(LSSVMs).It was found that despite ML approaches outperforming classic methods in predicting the lateral behavior of piles,their‘black box'nature and reliance only on a data-driven approach made their results showcase statistical robustness rather than clear geotechnical insights,a fact underscored by the mathematical equations derived from these studies.Furthermore,the research identified a gap in the availability of drilled shaft datasets,limiting the extendibility of current findings to large-diameter piles.An extensive dataset,compiled from a series of lateral loading tests on free-head drilled shaft with varying properties and geometries,was introduced to bridge this gap.The paper concluded with a direction for future research,proposes the integration of physics-informed neural networks(PINNs),combining data-driven models with fundamental geotechnical principles to improve both the interpretability and predictive accuracy of AI applications in geotechnical engineering,marking a novel contribution to the field.

水平受荷桩“p-y+M-θ”分析方法

中国近海海上风电机组开发建设中,大直径单桩基础形式使用占比超70%。现行p-y曲线设计方法主要适用于小直径柔性桩,对大直径单桩侧向及桩底受荷描述能力不足,导致其严重低估刚柔性桩和刚性桩(分别常用于中国和欧洲的近海风电工程)的变形和承载能力,过于保守的设计给海上风电降本带来挑战。为此建立了能以统一的方式预测柔性、刚柔性和刚性单桩水平单调受荷响应的“p-y+M-θ”模型,并将该模型推广到循环荷载下单桩的响应分析。通过与相关试验结果比对发现,“p-y+M-θ”模型能较为准确地预测桩基水平加载响应。力图为水平受荷单桩工程设计提供简洁而可行的响应分析方法。

基于桩侧砂土圆锥型修正应变楔模型的p-y曲线

基于桩侧砂土三维圆锥型应变楔的变形特征,提出砂土中水平受荷桩的非线性p-y曲线。构建圆锥型楔形体前表面应力体系并引入土体应力-应变双曲线模型,进而考虑应变楔的水平受力平衡得到桩侧土反力的表达式。在此基础上,结合弹性地基梁有限差分数值分析,建立了水平受荷桩非线性p-y曲线的理论推导方法。将该理论用于钻孔桩和打入桩模型试验的算例分析,结果表明:相对于API规范的p-y曲线、双曲线型p-y曲线以及传统非圆锥型应变楔模型得到的p-y曲线,本文方法得到的非线性p-y曲线与模型试验结果更为接近。通过比较本文圆锥变形模式与传统非圆锥型应变楔模式的差异以及桩-土参数的影响分析,进一步论证了该方法的优点。

Characterization of the generalized permeability jail in tight reservoirs by analyzing relative-permeability curves and numerical simulation

This study comprehensively characterizes the boundary values of generalized permeability jail in tight reservoirs through relative-permeability curve analysis,numerical simulation,and economic evaluation.A total number of 108 relative-permeability curves of rock samples from tight reservoirs were obtained,and the characteristics of relative-permeability curves were analyzed.The irreducible water saturation(Swi)mainly ranges from 20% to 70%,and the residual gas saturation(Sgr)ranges from 5% to 15% for 55% of the samples.The relative-permeability curves are categorized into six types(Category-Ⅰ to Ⅵ)by analyzing the following characteristics:The relative permeability of gas at Swi,the relative permeability of water at Sgr,and the relative permeability corresponding to the isotonic point.The relative permeability curves were normalized to facilitate numerical simulation and evaluate the impact of different types of curves on production performance.The results of simulation show significant difference in production performance for different types of relative-permeability curves:Category-Ⅰ corresponds to the case with best well performance,whereas Categories-Ⅴ and Ⅵ correspond to the cases with least production volume.The results of economic evaluation show a generalized permeability jail for Categories-Ⅳ,Ⅴ,and Ⅵ,and the permeability jail develops when the relative permeability of gas and water is below 0.06.This study further quantifies the range of micro-pore parameters corresponding to the generalized permeability jail for a tight sandstone reservoir.

基于被动区土弹簧刚度降低过程的基坑围护结构计算增量法及软化p-y曲线

基坑围护结构的计算常采用基于杆系有限元的增量法,被动区土弹簧刚度在基坑开挖作用下发生动态降低导致土抗力软化,目前缺少在非线性地基模型基础上对该问题的研究。通过引入两个刚度变化系数来综合量化被动区土弹簧参数随基坑开挖的动态变化过程,建立了基于该过程的基坑围护结构计算增量法。针对非线性地基模型,提出了细化增量法进行数值计算。采用线弹性、理想弹塑性以及双曲线3种基本土弹簧模型计算得到被动区软化p-y曲线,对比显示,基于双曲线基本模型得到的等效水平抗力系数变化曲线更符合实际规律。工程实例计算显示,基于基本土弹簧为双曲线的计算结果与不同开挖阶段墙的位移监测数据对应更好。参数分析显示,与被动区土体极限抗力pu相关的刚度变化系数对计算结果影响较大,采用此方法应着重关注被动区pu的计算方法及开挖卸荷对pu的影响。

一种适用于板桩与土体相互作用的p-y曲线折减方法

p-y曲线法可充分考虑土体的塑性变形及抗力极限值,但该方法是基于单桩水平静载试验提出的一种桩土弹簧计算方法,无法直接应用于板桩与土体的相互作用。通过引入p-y曲线折减系数,提出一种适用于板桩与土体相互作用的p-y曲线折减方法,将其结果与Plaxis有限元模型计算结果及现场位移观测结果进行对比,并验证该方法的准确性。结果表明,该方法可以充分考虑土弹簧的非线性及土体地基反力极限值,弥补了m法和p-y曲线方法的不足。

黏土中大直径钢管桩p-y曲线法适用性研究

大直径钢管桩作为常用的海上风机基础形式,其水平承载性能是风机基础结构设计中最关键的一环。API规范建议的p-y曲线法是目前计算钢管桩水平承载力最主流的方法,但其对大直径刚性桩及刚柔性桩的适用性有待探讨。通过开展数值模拟方法,研究了不同长径比水平受荷桩的桩身变形规律及桩周土体破坏规律,提出了基于长径比的刚柔性桩判断标准,并通过比较不同长径比下钢管桩水平极限承载力,得到了传统p-y曲线的适用范围。研究结果发现传统p-y曲线模型由于仅考虑了水平向的土阻力,适用于计算长径比≥15的刚柔性桩及柔性桩;而对于长径比<9的刚性短桩,其误差最高可达63%,严重低估了单桩的水平向承载力;对于长径比在9~15之间的刚柔性桩可适当使用API规范进行计算。