Scale Fluctuations Research Articles

Deciphering the effects of STN DBS on neuropsychiatric fluctuations in Parkinson’s disease

The impact of subthalamic nucleus (STN) deep brain stimulation (DBS) on neuropsychiatric fluctuations in Parkinson´s disease (PD) remains unclear. The Neuropsychiatric Fluctuations Scale (NFS) can help to fill this gap, directly measuring fluctuations between the OFF- and ON-medication conditions. The NFS provides NFS-plus (hyperdopaminergic) and NFS-minus (hypodopaminergic) sub-scores. Based on these, the NFS global scores express the overall magnitude of neuropsychiatric symptoms in both the OFF- and ON-medication states. The total fluctuation score (TFS) represents the difference between ON- vs. OFF-medication NFS global scores, thus assessing fluctuations amplitude. The NFS was used to evaluate changes in neuropsychiatric fluctuations between the OFF- and ON-medication conditions before and 1-year after bilateral STN-DBS in 45 PD patients (32 males; mean age, 61.3 ± 7.2 years; PD duration, 10.2 ± 3.0 years). After surgery, the amplitude of neuropsychiatric fluctuations was significantly reduced (p < 0.001), confirming the efficacy of STN-DBS on these symptoms.

Assessment of a multiphase formulation of one-dimensional turbulence using direct numerical simulation of a decaying turbulent interfacial flow

The interaction between turbulence and surface tension is studied numerically using the one-dimensional-turbulence (ODT) model. ODT is a stochastic model simulating turbulent flow evolution along a notional one-dimensional line of sight by applying instantaneous maps that represent the effects of individual turbulent eddies on property fields. It provides affordable high resolution of interface creation and property gradients within each phase, which are key for capturing the local behavior as well as overall trends, and has been shown to reproduce the main features of an experimentally determined regime diagram for primary jet breakup. Here ODT is used to investigate the interaction of turbulence with an initially planar interface. The notional flat interface is inserted into a periodic box of decaying homogeneous isotropic turbulence, simulated for a variety of turbulent Reynolds and Weber numbers. Unity density and viscosity ratios serve to focus solely on the interaction between fluid inertia and the surface-tension force. Statistical measures of interface surface density and spatial structure along the direction normal to the initial surface are compared to corresponding direct-numerical-simulation (DNS) data. Allowing the origin of the lateral coordinate system to follow the location of the median interface element improves the agreement between ODT and DNS, reflecting the absence of lateral nonvortical displacements in ODT. Beyond the DNS-accessible regime, ODT is shown to obey the predicted parameter dependencies of the Kolmogorov critical scale in both the inertial and dissipative turbulent-cascade subranges. Notably, the probability density function of local fluctuations of the critical scale is found to collapse to a universal curve across both subranges. Published by the American Physical Society 2024

Influence of subgrade spatial variability on strain-alleviating ability of geogrids and rutting life in flexible pavement

This study employs the Random Field Finite Difference Analysis to assess how subgrade spatial variability impacts geogrid reinforcement’s strain-alleviating ability and the reinforced pavement’s rutting life. The geogrid’s abilities to reduce critical strains are evaluated using a strain-alleviating ratio and compared between deterministic and spatially variable scenarios. The analysis involves six geogrid reinforcement arrangements, considering two kinds of geogrid stiffness (G1 and G2) and three typical positions: top (L1), mid-depth (L1-2) and bottom (L2) of the base course. Key findings include: (a) Subgrade spatial variability significantly amplifies mean critical strains and leads to irregular strain and stress distributions, which in turn impacts the strain-alleviating ability of the geogrid reinforcements and potentially changes the optimal geogrid position. (b) The impacts of subgrade spatial variability on the geogrids’ strain-alleviating ability vary with the type of critical strains, the geogrid position, and the coefficient of variation and scale of fluctuation of subgrade modulus. When the geogrid is located at L2 (G_L2), its ability to alleviate critical subgrade strain is significantly compromised. (c) The adverse effect of subgrade spatial variability on the rutting life of G_L2 reinforced pavement is significant and can be mitigated by homogenising a very thin sublayer at the subgrade surface.

Study of Site Investigation Sample Quality and Worst-Case Scale of Fluctuation for Monopiles Based on Conditional Random Fields

Study of Site Investigation Sample Quality and Worst-Case Scale of Fluctuation for Monopiles Based on Conditional Random Fields

A reliability analysis framework coupled with statistical uncertainty characterization for geotechnical engineering

Reliability analysis plays an important role in the risk management of geotechnical engineering. For the random field-based method, it is expected that the uncertainty characterization of geo-material parameters and the realization of random field can be integrated effectively. Moreover, as the increase in measured data size is generally difficult in the field investigation of geotechnical engineering due to limitation of budget and time etc., the statistical uncertainty resulting from sparse data should be paid great attention. Therefore, taking the determination of hyper-parameters for Bayesian-based conditional random field as the breakthrough, this study proposed a reliability analysis framework to achieve the expectation above. In this proposed reliability analysis framework, the present characterization method of statistical uncertainty is improved by setting the lognormal distribution as the prior distribution of scale of fluctuation (SOF). Subsequently, the performance of statistical uncertainty characterization method is tested by a set of unconfined compressive strength (UCS) database about rocks. Then, a case study about the stability analysis of slope is employed to demonstrate the beneficial effect of the proposed reliability analysis framework. It is found that the uncertainty in both the realization of random field and the reliability analysis results can be significantly mitigated by the proposed reliability analysis framework.

Information and entropy in the labor market: Frictional and involuntary unemployment and the neutrality of money

AbstractWe re‐examine the concept of involuntary and frictional unemployment and the neutrality of money in a statistical equilibrium model of the labor market in which boundedly rational workers' and employers' interactions have a non‐zero impact on wages. From this perspective both the degree of involuntary unemployment and the neutrality of money depend on the adjustment of both expectations of the average level of wages and prices and the further adjustment of anticipations of the scale of fluctuations in prices and wage offers. Shocks to the economy can produce new long‐run equilibrium levels of unemployment and short‐run increases in involuntary unemployment arising from unevenness in the adjustment of expectations.

A novel efficient RFEM for reliability analysis and design of multi-line dynamically installed anchor for floating offshore wind turbines

A novel multi-line dynamically installed anchor was previously proposed by the authors to allow for the mooring of multiple floating offshore wind turbine, resulting in a significant reduction in the total number and cost of anchors required for floating wind farms. Considering the spatial variability of soil properties and the uncertainty of environmental loads, the present study performs reliability analysis and design of the multi-line dynamically installed anchor. Firstly, a strategy to repeatedly use fundamental random variables is proposed and validated for reducing the number of random variables used in Karhunen-Loève expansion in the simulation of random field of soil properties when the ratio of the soil domain dimension to the scale of fluctuation is large. Then, the efficiency, accuracy, and robustness of the RFEM (random finite element method) combined with K-MCS (Kriging model and Monte Carlo simulation) based on the proposed strategy are validated through examples of random capacity of foundations. Next, the random capacities and probabilistic VHMT failure envelopes of the multi-line dynamically installed anchor in spatially variable soil are investigated. Finally, the reliability design of multi-line dynamically installed anchors is conducted and compared with that of multi-line pile anchors, in which both the spatial variability of soil and the uncertainty of loads are condidered. The results show that the costs for multi-line dynamically installed anchors are obviously less than those of multi-line pile anchors.

Right anterior insula ASL hypoperfusion as a diagnostic biomarker of prodromal and mild dementia with Lewy bodies: preliminary evidence using a Bayesian approach.

Identifying and validating a biomarker with high specificity in early-stage dementia with Lewy bodies (DLB) using a feasible method is crucial to enhance the current suboptimal diagnostic procedure. Previous research revealed abnormalities, including hypoperfusion in the right anterior insular cortex at group level, in prodromal DLB. Exploring hypoperfusion of the right anterior insula, at an individual-level and assessing its relevance as a potential imaging biomarker in early DLB, has, to our knowledge, not been investigated. Our preliminary study aims to assess the feasibility of the technique and to provide a methodological framework for further investigation. We assessed the feasibility and accuracy of the hypoperfusion of the right anterior insula per arterial spin labelling magnetic resonance imaging (ASL-MRI) as a diagnostic biomarker in early DLB and provided rough estimates of its sensitivity and specificity. Defining the region of interest based on previous research, we established the biomarker as the hypoperfusion of the right anterior insula. Discriminative and analytical performances were assessed in comparison to a control group of treatment-resistant depression patients. Bayesian diagnostic reasoning was employed to assess the biomarker diagnostic usability in early DLB in two scenarios: healthy elderly controls and mild cognitive impairment. Additionally, we updated probabilities by integrating data from the Mayo-clinic cognitive fluctuations scale and real-time quaking-induced conversion (RT-QuIC) α-synuclein data. Lastly, a whole-brain perfusion analysis of DLB patients was conducted to identify further brain regions with discriminative abilities. We successfully replicated the right anterior insular hypoperfusion (RAI-Hypo) in all DLB patients at the individual level. The overall sensitivity of the biomarker was 96%, and the specificity was 92%. Bayesian testing revealed the biomarker's highest performance in early-stage DLB with cognitive fluctuations, showcasing a diagnostic potential associated with a high precision and moderate accuracy. In a cognitively non-impaired population, the RAI-Hypo showed a limited usability and lacked in selectivity to qualify as a screening tool. The exploratory whole-brain analysis revealed perfect discriminative capacities in the bilateral anterior insulae and the left inferior parietal lobule. Further studies are needed to confirm our preliminary results. If performance is maintained in subsequent studies and is compared to a more suitable control population, the proposed biomarker may be eventually sufficient to discriminate early-stage DLB from non-DLB.

Asynchronous abundance fluctuations can drive giant genotype frequency fluctuations.

Large stochastic population abundance fluctuations are ubiquitous across the tree of life1-7, impacting the predictability of population dynamics and influencing eco-evolutionary outcomes. It has generally been thought that these large abundance fluctuations do not strongly impact evolution, as the relative frequencies of alleles in the population will be unaffected if the abundance of all alleles fluctuate in unison. However, we argue that large abundance fluctuations can lead to significant genotype frequency fluctuations if different genotypes within a population experience these fluctuations asynchronously. By serially diluting mixtures of two closely related E. coli strains, we show that such asynchrony can occur, leading to giant frequency fluctuations that far exceed expectations from models of genetic drift. We develop a flexible, effective model that explains the abundance fluctuations as arising from correlated offspring numbers between individuals, and the large frequency fluctuations result from even slight decoupling in offspring numbers between genotypes. This model accurately describes the observed abundance and frequency fluctuation scaling behaviors. Our findings suggest chaotic dynamics underpin these giant fluctuations, causing initially similar trajectories to diverge exponentially; subtle environmental changes can be magnified, leading to batch correlations in identical growth conditions. Furthermore, we present evidence that such decoupling noise is also present in mixed-genotype S. cerevisiae populations. We demonstrate that such decoupling noise can strongly influence evolutionary outcomes, in a manner distinct from genetic drift. Given the generic nature of asynchronous fluctuations, we anticipate that they are widespread in biological populations, significantly affecting evolutionary and ecological dynamics.

Development of a toroidally resolved broadband ECE imaging system for measurement of turbulent fluctuations on the KSTAR.

The two electron cyclotron emission imaging (ECEI) systems installed at adjacent ports (G and H) on the KSTAR tokamak incorporate large-aperture mm-wave optics, broadband electronics, and high speed digitization (up to 1 MSa/s) for 2D and quasi-3D visualization of MHD-scale fluid dynamics. Recently, the ECEI systems have been proved to be capable of visualization of smaller scale fluctuations albeit with a limited spatiotemporal resolution and even capable of measurement of ion cyclotron harmonic waves by direct high-speed sampling of the ECE IF signals. A four-channel prototype subsystem with a higher sampling rate up to 16 GS/s has been integrated into the G-port ECEI system, enabling the measurement of plasma waves in the GHz range in the form of modulated ECE signals and characterization of high-frequency turbulence during the evolution of pedestal. To achieve higher toroidal resolution in the turbulence measurement, the H-port ECEI system is now being upgraded to have a toroidally dual detector array of 2(toroidal) × 12(vertical) × 8(radial) channel configuration and a high-speed subsystem of 2(toroidal) × 4 channel configuration. The new mm-wave optics has been designed via beam propagation simulation, and the measured performance of the fabricated lens indicates a toroidal resolution of 8-10cm depending on the focus position and zoom factor, allowing for the measurement of parallel wavenumber up to k‖ ∼ 0.8cm-1.

System size scaling of triangularity effects on global temperature gradient-driven gyrokinetic simulations

In this work, we explore the triangularity effects on turbulent transport employing global gyrokinetic simulations performed with the ORB5 code. Numerous experiments on the Tokamak á Configuration Variable (TCV) and, more recently, on the DIII-D machine, have demonstrated superior confinement properties in L-mode of negative triangularity (NT) over positive triangularity (PT) configuration. This presents a particularly attractive scenario, as L-mode operation eliminates or significantly mitigates the presence of hazardous edge-localized modes (ELMs). However, a full theoretical understanding of all these observations remains elusive. Specifically, questions remain about how NT improvements can extend to the core where triangularity is very small, and whether these improvements can scale to larger devices. This paper addresses these two questions. Our analysis is divided into two parts: we first demonstrate that the confinement enhancement in NT configurations arises from the interdependent edge-core dynamics, and then we present the results of a system size scan. Crucially, we find that the relative turbulent transport reduction of NT over PT appears not to be contingent on machine dimensions or fluctuation scales and is moreover robust with respect to variations in plasma profiles. This insight underscores the fundamental nature of the NT confinement advantage and paves the way for its potential application in future fusion devices, regardless of their size.

A novel formulation of wind velocity spectrum incorporating rainfall influence

Wind-rain interaction constitutes a common physical phenomenon in nature. Nevertheless, in fluid mechanics and wind engineering, whether and how rainfall influences wind remains an unresolved challenge. This study relies on a substantial dataset obtained through on-site measurement. Initially, three distinct rainfall categories—light rain, moderate rain, and heavy rain—are established based on the magnitude of vertical wind velocity. Notably, significant disparities in the high-frequency constituents of the fluctuating wind velocity spectrum are discerned across various rainfall levels. Subsequently, a rigorous quantitative analysis explores the relationship between the high-frequency cumulative energy proportion of the fluctuating wind velocity spectrum and rainfall intensity, leading to formulations that delineate the high-frequency cumulative energy proportion in the alongwind, acrosswind, and vertical wind directions as explicit functions of rainfall intensity. Moreover, a comprehensive unified expression models the three-dimensional fluctuating wind velocity spectrum. This expression incorporates parameters encompassing the relative scales of fluctuation and mean components, the extent of conversion between high and low-frequency energy, and the scaling laws governing the inertial subrange. Additionally, explicit functional dependencies for these parameters concerning variations in rainfall intensity are provided. The novel formulation of the fluctuating wind velocity spectrum proposed in this study bears substantial scientific significance, as it facilitates a deeper understanding of wind-rain interaction and offers valuable insights for conducting intricate environmental flow field simulations.

Seismic stability and failure mechanisms of gentle and steep slopes considering soil rotated anisotropy and spatial variability

The present study focuses on investigating the effects of soil rotated anisotropy and spatial variability on slope failure in seismic conditions. The random finite element method aided by subset simulation is implemented, which ensures an efficient quantification of both the probability of failure and its associated consequence of failure. Several slope angles of gentle and steep slopes and soil properties that lead to a low probability of failure were selected for parametric studies. The comprehensive parametric studies of seismic slope stability analysis consider various factors such as slope inclinations, seismic coefficients, scales of fluctuation, and orientations of the major principal scale of fluctuation (i.e., the rotation angle of random field). The results underscore the importance of considering the combined effects of soil anisotropy and the orientation of the major principal scale of fluctuation for designing both gentle and steep slopes under seismic conditions and emphasize that care must be given to ensure the worst-case scenario is considered. Visual observations of failure mechanisms of gentle and steep slopes under seismic conditions were also shown to be very helpful in interpreting the variation of probability of failure due to soil spatial variation.

Basal Force Fluctuations and Granular Rheology: Linking Macroscopic Descriptions of Granular Flows to Bed Forces With Implications for Monitoring Signals

AbstractGranular flows are ubiquitous in nature with single flows traversing a wide range of dynamic conditions from initiation to deposition. Many of these flows are responsible for significant hazards and can generate remotely detectable seismic signals. These signals provide a potential for real‐time flow measurements from a safe distance. To fully realize the benefit of seismic measurements, basal‐granular forces must be linked to macroscopic internal flow dynamics across a wide range of flow conditions. We utilize discrete element simulations to observe dry and submerged granular flows under plane‐shear and inclined‐flow configurations, relating bulk kinematics to basal‐force distributions. We find that the power and frequency of force fluctuations scale with non‐dimensional shear rate (I). This scaling tracks three pre‐established regimes that are described by μ(I) rheology: (a) an intermittent particle rearrangement regime, where basal forces are dominated by low frequencies; (b) an intermediate regime where basal forces start to increase in frequency while showing correlations in space and (c) a fully collisional regime where the signal is nearly flat up to a cutoff frequency. We further identify a newly defined fourth regime that marks a “phase change” from the intermediate to collisional regime where increases in basal force fluctuations with increasing shear rates stalls as the granular bed dilates, partially destroying the contact network. This effort suggests that basal forces can be used to interpret complex granular processes in geophysical flows.

Probabilistic assessment of bearing capacity of skirted foundation under combined loadings with a rigid base

Skirted foundations are critical components in offshore applications where combined loads are common in deep‐water environments. Their ultimate capacity under VH (vertical‐horizontal) combined loading is traditionally determined using VH failure envelopes, which are primarily constructed using numerical methods. These methodologies, however, frequently ignore the spatial variability inherent in seabed soils due to geological formations. This paper investigates the effect of spatial variability of undrained shear strength and embedment ratio impact on the capacity of skirted foundations subjected to VH combined loading. For this, OptumG2 software is used to perform Monte Carlo simulation combined with random finite element limit analysis. This paper investigates the stochastic analysis of bearing capacity and failure envelopes, with a particular emphasis on understanding the effect of spatial correlation on undrained shear strength. The study focuses on the horizontal scale of fluctuation and the soil strength heterogeneity index, shedding insight on previously undiscovered areas. Novel findings highlight how a rigid base affects VH failure envelopes and offer insights into evaluating the vertical bearing capacity of skirted foundations. [Correction added on 8 July 2024, after first online publication: The above statement has been updated in this version.]

Gaps Between Consecutive Primes and the Exponential Distribution

Based on the primes less than 4 × 10 18 , Oliveira e Silva et al. (Math. Comp., 83(288):2033–2060, 2014) conjectured an asymptotic formula for the sum of the kth power of the gaps between consecutive primes less than a large number x. We show that the conjecture of Oliveira e Silva holds if and only if the kth moment of the first n gaps is asymptotic to the kth moment of an exponential distribution with mean log n , though the distribution of gaps is not exponential. Asymptotically exponential moments imply that the gaps asymptotically obey Taylor’s law of fluctuation scaling: variance of the first n gaps ∼ (mean of the first n gaps)2. If the distribution of the first n gaps is asymptotically exponential with mean log n , then the expectation of the largest of the first n gaps is asymptotic to ( log n ) 2 . The largest of the first n gaps is asymptotic to ( log n ) 2 if and only if the Cramér-Shanks conjecture holds. Numerical counts of gaps and the maximal gap Gn among the first n gaps test these results. While most values of Gn are better approximated by ( log n ) 2 than by other models, seven exceptional values of n with G n > 2 e − γ ( log n ) 2 suggest that lim sup n → ∞ G n / [ 2 e − γ ( log n ) 2 ] may exceed 1.

A method for estimating dynamic functional network connectivity gradients (dFNG) from ICA captures smooth inter-network modulation.

Dynamic functional network connectivity (dFNC) analysis is a widely used approach for studying brain function and offering insight into how brain networks evolve over time. Typically, dFNC studies utilized fixed spatial maps and evaluate transient changes in coupling among time courses estimated from independent component analysis (ICA). This manuscript presents a complementary approach that relaxes this assumption by spatially reordering the components dynamically at each timepoint to optimize for a smooth gradient in the FNC (i.e., a smooth gradient among ICA connectivity values). Several methods are presented to summarize dynamic FNC gradients (dFNGs) over time, starting with static FNC gradients (sFNGs), then exploring the reordering properties as well as the dynamics of the gradients themselves. We then apply this approach to a dataset of schizophrenia (SZ) patients and healthy controls (HC). Functional dysconnectivity between different brain regions has been reported in schizophrenia, yet the neural mechanisms behind it remain elusive. Using resting state fMRI and ICA on a dataset consisting of 151 schizophrenia patients and 160 age and gender-matched healthy controls, we extracted 53 intrinsic connectivity networks (ICNs) for each subject using a fully automated spatially constrained ICA approach. We develop several summaries of our functional network connectivity gradient analysis, both in a static sense, computed as the Pearson correlation coefficient between full time series, and a dynamic sense, computed using a sliding window approach followed by reordering based on the computed gradient, and evaluate group differences. Static connectivity analysis revealed significantly stronger connectivity between subcortical (SC), auditory (AUD) and visual (VIS) networks in patients, as well as hypoconnectivity in sensorimotor (SM) network relative to controls. sFNG analysis highlighted distinctive clustering patterns in patients and HCs along cognitive control (CC)/ default mode network (DMN), as well as SC/ AUD/ SM/ cerebellar (CB), and VIS gradients. Furthermore, we observed significant differences in the sFNGs between groups in SC and CB domains. dFNG analysis suggested that SZ patients spend significantly more time in a SC/ CB state based on the first gradient, while HCs favor the SM/DMN state. For the second gradient, however, patients exhibited significantly higher activity in CB domains, contrasting with HCs' DMN engagement. The gradient synchrony analysis conveyed more shifts between SM/ SC networks and transmodal CC/ DMN networks in patients. In addition, the dFNG coupling revealed distinct connectivity patterns between SC, SM and CB domains in SZ patients compared to HCs. To recap, our results advance our understanding of brain network modulation by examining smooth connectivity trajectories. This provides a more complete spatiotemporal summary of the data, contributing to the growing body of current literature regarding the functional dysconnectivity in schizophrenia patients. By employing dFNG, we highlight a new perspective to capture large scale fluctuations across the brain while maintaining the convenience of brain networks and low dimensional summary measures.

Anisotropy of Magnetohydrodynamic and Kinetic Scale Fluctuations through Correlation Tensor in Solar Wind at 0.8 au

Space plasma turbulence is inherently characterized by anisotropic fluctuations. The generalized k-th order correlation tensor of magnetic field increments allow us to separate the mixed isotropic and anisotropic structure functions from the purely anisotropic ones. In this work, we quantified the relative importance of anisotropic fluctuations in solar wind turbulence using two Alfvénic data samples gathered by the Solar Orbiter at 0.8 astronomical units. The results based on the joined statistics suggest that the anisotropic fluctuations are ubiquitous in solar wind turbulence and persist at kinetic scales. Using the RTN coordinate system, we show that their presence depends on the anisotropic sector under consideration, e.g., the RN and RT sectors exhibit enhanced anisotropy toward kinetic scales, in contrast with the TN. We then study magnetic field fluctuations parallel and perpendicular to the local mean magnetic field separately. We find that perpendicular fluctuations are representative of the global statistics, resembling the typical picture of magnetohydrodynamic turbulence, whereas parallel fluctuations exhibit a scaling law with slope ∼1 for all the joined isotropic and anisotropic components. These results are in agreement with predictions based on the critical balance phenomenology. This topic is potentially of interest for future space missions measuring kinetic and MHD scales simultaneously in a multi-spacecraft configuration.

Evaluating the Characteristics of Spatial Variability of Soil in Vertical Direction Highly Heterogeneous Region Based on Cone Penetration Test

Abstract Key parameters describing the spatial variability of soil properties based on the random field theory are the scale of fluctuation (SOF) and coefficient of variation (COV). To characterize the spatial variability of soil properties, reducing the impact of these errors and uncertainties is necessary. To accomplish this, for the five main layers of soil, we collected 18 cone penetration test (CPT) data from a highly heterogeneous region in Lianyungang New Airport, Jiangsu Province, China, and used the control variable method to analyze the influence of the estimation method of tendency, its function type and outliers. The results show that, compared with the ordinary least square method (OLSM), the least absolute deviation method (LADM) can more truly reflect the trend component of CPT parameters in the vertical direction, and the influence of other factors on SOF and COV is also studied, such as outliers and estimation functions of trend components. On this basis, a reasonable calculation process of SOF and COV is summarized, which provides a reference for the calculation of SOF and COV in vertical direction in the future. By comparing the SOF calculated by different models, the results show that the squared exponential (SQX) model has the highest SOF in 68.3% of the evaluation, and the single exponential (SNX) model has the lowest SOF in 64.4% of the evaluation. Moreover, we compared the SOF and COV of cone tip resistance (qc) and sleeve friction (fs), which showed that SOF of qc and COV of qc is lower than that of fs in 54.4 and 73.3% of all evaluations, respectively.

Hypoplastic modeling post-failure behavior of sandy slope with porosity spatial variability

Recent probabilistic studies have thoroughly examined how uncertainties in soil shear strength affect slope stability, while the impact of spatial variability in soil porosity on post-failure behaviors of slopes has received less attention. Overlooking the influence of porosity may lead to inaccurate assessments of slope post-failure behaviors. This study presents a random smoothed particle hydrodynamics (RSPH) framework for probabilistic analysis of slope failure with large deformation using a critical state-based hypoplastic constitutive model. The results indicate that the proposed RSPH method provides reasonable estimates for slope post-failure behaviors. Increases in both the coefficient of variation (COV) and the scale of fluctuation (SOF) of porosity give rise to underestimations of the run-out distance and sliding volume. Additionally, slope failure modes are affected by increasing uncertainty of porosity, which may contribute to the occurrence of deep-seated failures.