Time Step Length Research Articles

Short Communication: Numerically simulated time to steady state is not a reliable measure of landscape response time

Abstract. Quantifying the timescales over which landscapes evolve is critical for understanding past and future environmental change. Computational landscape evolution models are one tool among many that have been used in this pursuit. We compare numerically modeled times to reach steady state for a landscape adjusting to an increase in rock uplift rate. We use three different numerical modeling libraries and explore the impact of time step, grid type, numerical method for solving the erosion equation, and metric for quantifying the time to steady state. We find that modeled time to steady state is impacted by all of these variables. Time to steady state varies inconsistently with time step length, both within a single model and among different models. In some cases, drainage rearrangement extends the time to reach steady state, but this is not consistent in all models or grid types. The two sets of experiments operating on Voronoi grids have the most consistent times to steady state when comparing across time step and metrics. On a raster grid, if we force the drainage network to remain stable, time to steady state varies much less with computational time step. In all cases we find that many measures of modeled time to steady state are longer than that predicted by an analytical equation for bedrock river response time. Our results show that the predicted time to steady state from a numerical model is, in many cases, more reflective of drainage rearrangement and numerical artifacts than the time for an uplift wave to propagate through a fixed drainage network.

Long-Term Optimal Scheduling of Hydro-Photovoltaic Hybrid Systems Considering Short-Term Operation Performance

Integrating photovoltaic power stations into large-capacity hydropower stations is an efficient and promising method for regulating large-scale photovoltaic power generation. However, constrained by the time step length, traditional long-term scheduling of hydro-PV hybrid systems does not adequately consider short-term operational performance indicators, resulting in sub-optimal scheduling plans that fail to coordinate the consumption of photovoltaic power and the utilization of water resources in the basin. To address this, this study established a long-term optimal scheduling model for hydro-PV hybrid systems. This model overcomes the limitation of the time step length in long-term scheduling by incorporating long-term power generation goals and short-term operation performance targets into the long-term optimal scheduling process based on scheduling auxiliary functions. In case studies, the optimised model balanced the long-term power-generation goals and short-term operational performance targets by redistributing energy across different periods. Compared to optimization models that did not consider short-term operation performance, in a typical normal year, the model effectively reduced the electricity curtailment volume (28.54%) and power shortage volume (10.91%) of the hybrid system while increasing on-grid electricity (0.03%). Similar improvements were observed in wet and dry years. These findings provide decision support for hydropower scheduling in the context of large-scale photovoltaic power integration.

Motor interference on lateral pelvis shifting towards the paretic leg during walking and its cortical mechanisms in persons with stroke.

Motor interference, where new skill acquisition disrupts the performance of a previously learned skill, is a critical yet underexplored factor in gait rehabilitation post-stroke. This study investigates the interference effects of two different practice schedules, applying interleaved (ABA condition) and intermittent (A-A condition) pulling force to the pelvis during treadmill walking, on lateral pelvis shifting towards the paretic leg in individuals with stroke. Task A involved applying resistive pelvis force (pulling towards the non-paretic side), and Task B applied assistive force (pulling towards the paretic side) at the stance phase of the paretic leg during walking. Sixteen individuals with chronic stroke were tested for gait pattern changes, including lateral pelvis shifting and spatiotemporal gait parameters, and neurophysiological changes, including muscle activity in the paretic leg and beta band absolute power in the lesioned cortical areas. A-A condition demonstrated increased lateral pelvis shifting towards the paretic side, extended paretic stance time and longer non-paretic step length after force release while ABA condition did not show any changes. These changes in gait pattern after A-A condition were accompanied by increased muscle activities of the ankle plantarflexors, and hip adductors/abductors. A-A condition demonstrated greater changes in beta band power in the sensorimotor regions compared to ABA condition. These findings suggest that while walking practice with external force to the pelvis can improve lateral pelvis shifting towards the paretic leg post-stroke, practicing a new pelvis shifting task in close succession may hinder the performance of a previously obtained lateral pelvis shifting pattern during walking.

Application of an Auditory-Based Feedback Distortion to Modify Gait Symmetry in Healthy Individuals.

Augmenting auditory feedback through an error-augmentation paradigm could facilitate the perception and correction of gait asymmetry in stroke survivors, but how such a paradigm should be tailored to individual asymmetry profiles remains unclear. Before implementing the paradigm in rehabilitation, we need to investigate the instantaneous effects of distorted footstep sound feedback on gait symmetry in healthy young adults. Participants (n = 12) walked on a self-paced treadmill while listening to their footstep sounds, which were distorted unilaterally according to five conditions presented randomly: small delay; small advance; large delay; large advance; or unmodified (control). The primary outcomes were swing time ratio (SWR) and step length ratio (SLR). Secondary outcomes included walking speed, bilateral swing time, step length, and maximum toe height, as well as hip, knee, and ankle angle excursions. SWR (p < 0.001) but not SLR (p ≥ 0.05) was increased in all distorted feedback conditions compared to the control condition. Increased swing time on the perturbed side ipsilateral to feedback distortion was observed in the advanced conditions (p < 0.001), while swing time increased bilaterally in the delayed conditions (p < 0.001) but to a larger extent on the unperturbed side contralateral to feedback distortion. Increases in swing time were accompanied by larger maximum toe height as well as larger hip and knee joint excursions (p < 0.05 to p < 0.001). No differences in any outcomes were observed between small and large feedback distortion magnitudes. Distorted footstep sound feedback successfully elicits adaptation in temporal gait symmetry (SWR), with distinct modulation patterns for advanced vs. delayed footstep sounds. Spatial symmetry (SLR) remains unaltered, likely because auditory feedback primarily conveys temporal information. This research lays the groundwork to implement personalized augmented auditory feedback in neurorehabilitation.

ERoots: A three-dimensional dynamic growth model of rice roots coupled with soil

Root architecture systems (RAS) reflect the spatial structure of roots in soil. To clarify the structure and distribution of rice roots and investigate the coupling between roots and soil, wetland rice was selected as the experimental object, and a three-dimensional (3D) growth model of rice root environment-roots (ERoots) based on the parameter Lindenmayer system (L-system) was proposed. ERoots combines a root morphological structure model with a growth model and defines L-system grammar iteration rules with the unit time and unit step length as parameters. At the same time, the basic growth parameters of rice roots were obtained via destructive detection, and 3D growth visualisation of roots was realised via MATLAB. In the soil coupling process, a soil nutrient simulation map was constructed based on the spatial soil characteristics per unit volume, and an adjustment strategy for roots reaching the growth boundary was designed. The flexibility of the model coupled with soil was reflected in the tropisms of root growth, growth rate and root branching strategy. Finally, combined with soil spatial characteristic simulation, geometric growth boundary and 3D root growth model, the ability of 3D growth visualisation of rice roots was verified under three soil conditions: (1) unconfined root growth, (2) confined spatial root growth, and (3) root growth with tropisms. The results indicated that the ERoots root model basically realised coupling with soil and achieved a satisfactory simulation effect in regard to the rice morphological structure. This study provides a reference for 3D growth modelling and visualisation of other crop roots.

Importance of microphysical settings for climate forcing by stratospheric SO2 injections as modeled by SOCOL-AERv2

Abstract. Solar radiation modification by a sustained deliberate source of SO2 into the stratosphere (strat-SRM) has been proposed as an option for climate intervention. Global interactive aerosol–chemistry–climate models are often used to investigate the potential cooling efficiencies and associated side effects of hypothesized strat-SRM scenarios. A recent model intercomparison study for composition–climate models with interactive stratospheric aerosol suggests that the modeled climate response to a particular assumed injection strategy depends on the type of aerosol microphysical scheme used (e.g., modal or sectional representation) alongside host model resolution and transport. Compared to short-duration volcanic SO2 emissions, the continuous SO2 injections in strat-SRM scenarios may pose a greater challenge to the numerical implementation of microphysical processes such as nucleation, condensation, and coagulation. This study explores how changing the time steps and sequencing of microphysical processes in the sectional aerosol–chemistry–climate model SOCOL-AERv2 (40 mass bins) affects model-predicted climate and ozone layer impacts considering strat-SRM by SO2 injections of 5 and 25 Tg(S) yr−1 at 20 km altitude between 30° S and 30° N. The model experiments consider the year 2040 to be the boundary conditions for ozone-depleting substances and greenhouse gases (GHGs). We focus on the length of the microphysical time step and the call sequence of nucleation and condensation, the two competing sink processes for gaseous H2SO4. Under stratospheric background conditions, we find no effect of the microphysical setup on the simulated aerosol properties. However, at the high sulfur loadings reached in the scenarios injecting 25 Tg(S) yr−1 of SO2 with a default microphysical time step of 6 min, changing the call sequence from the default “condensation first” to “nucleation first” leads to a massive increase in the number densities of particles in the nucleation mode (R&lt;0.01 µm) and a small decrease in coarse-mode particles (R&gt;1 µm). As expected, the influence of the call sequence becomes negligible when the microphysical time step is reduced to a few seconds, with the model solutions converging to a size distribution with a pronounced nucleation mode. While the main features and spatial patterns of climate forcing by SO2 injections are not strongly affected by the microphysical configuration, the absolute numbers vary considerably. For the extreme injection with 25 Tg(S) yr−1, the simulated net global radiative forcing ranges from −2.3 to −5.3 W m−2, depending on the microphysical configuration. Nucleation first shifts the size distribution towards radii better suited for solar scattering (0.3 µm &lt;R&lt; 0.4 µm), enhancing the intervention efficiency. The size distribution shift, however, generates more ultrafine aerosol particles, increasing the surface area density and resulting in 10 DU (Dobson units) less ozone (about 3 % of the total column) in the northern mid-latitudes and 20 DU less ozone (6 %) over the polar caps compared to the condensation first approach. Our results suggest that a reasonably short microphysical time step of 2 min or less must be applied to accurately capture the magnitude of the H2SO4 supersaturation resulting from SO2 injection scenarios or volcanic eruptions. Taken together, these results underscore how structural aspects of model representation of aerosol microphysical processes become important under conditions of elevated stratospheric sulfur in determining atmospheric chemistry and climate impacts.

Time Series Prediction Based on Multi-Scale Feature Extraction

Time series data are prevalent in the real world, particularly playing a crucial role in key domains such as meteorology, electricity, and finance. Comprising observations at historical time points, these data, when subjected to in-depth analysis and modeling, enable researchers to predict future trends and patterns, providing support for decision making. In current research, especially in the analysis of long time series, effectively extracting and integrating long-term dependencies with short-term features remains a significant challenge. Long-term dependencies refer to the correlation between data points spaced far apart in a time series, while short-term features focus on more recent changes. Understanding and combining these two features correctly are crucial for constructing accurate and reliable predictive models. To efficiently extract and integrate long-term dependencies and short-term features in long time series, this paper proposes a pyramid attention structure model based on multi-scale feature extraction, referred to as the MSFformer model. Initially, a coarser-scale construction module is designed to obtain coarse-grained information. A pyramid data structure is constructed through feature convolution, with the bottom layer representing the original data and each subsequent layer containing feature information extracted across different time step lengths. As a result, nodes higher up in the pyramid integrate information from more time points, such as every Monday or the beginning of each month, while nodes lower down retain their individual information. Additionally, a Skip-PAM is introduced, where a node only calculates attention with its neighboring nodes, parent node, and child nodes, effectively reducing the model’s time complexity to some extent. Notably, the child nodes refer to nodes selected from the next layer by skipping specific time steps. In this study, we not only propose an innovative time series prediction model but also validate the effectiveness of these methods through a series of comprehensive experiments. To comprehensively evaluate the performance of the designed model, we conducted comparative experiments with baseline models, ablation experiments, and hyperparameter studies. The experimental results demonstrate that the MSFformer model improves by 35.87% and 42.6% on the MAE and MSE indicators, respectively, compared to traditional Transformer models. These results highlight the outstanding performance of our proposed deep learning model in handling complex time series data, particularly in capturing long-term dependencies and integrating short-term features.

Forced vibrations of a cantilever beam using radial point interpolation methods: A comparison study

Meshless methods are a type of numerical method used to simulate continuum mechanics problems. These methods have been applied to several types of problems, there are a few works using meshless method focused on dynamic problems, but most works study static loading conditions. The current work aims at using two different meshless methods, the Radial Point Interpolation Method (RPIM) and the Natural Neighbours RPIM (NNRPIM), in a dynamic problem, specifically forced vibrations. This problem requires time integration, therefore three different time integration methods have also been tested, namely: the Central Difference Method (CDM), the Wilson method, and the Newmark method. The CDM is an explicit method, while the other two are implicit. A discretization study was performed to assess the ideal nodal discretization before the numerical and time integration methods are validated. For the implicit methods, different time step lengths were also tested. In the final example damping was introduced. The results prove the validity of the two meshless methods by having similar results to the Finite Element Method (FEM) using the three distinct time integration methods, different loading conditions, and damping.

Effects of vertical grid spacing on the climate simulated in the ICON-Sapphire global storm-resolving model

Abstract. Global storm-resolving models (GSRMs) use strongly refined horizontal grids compared with the climate models typically used in the Coupled Model Intercomparison Project (CMIP) but employ comparable vertical grid spacings. Here, we study how changes in the vertical grid spacing and adjustments to the integration time step affect the basic climate quantities simulated by the ICON-Sapphire atmospheric GSRM. Simulations are performed over a 45 d period for five different vertical grids with between 55 and 540 vertical layers and maximum tropospheric vertical grid spacings of between 800 and 50 m, respectively. The effects of changes in the vertical grid spacing are compared with the effects of reducing the horizontal grid spacing from 5 to 2.5 km. For most of the quantities considered, halving the vertical grid spacing has a smaller effect than halving the horizontal grid spacing, but it is not negligible. Each halving of the vertical grid spacing, along with the necessary reductions in time step length, increases cloud liquid water by about 7 %, compared with an approximate 16 % decrease for halving the horizontal grid spacing. The effect is due to both the vertical grid refinement and the time step reduction. There is no tendency toward convergence in the range of grid spacings tested here. The cloud ice amount also increases with a refinement in the vertical grid, but it is hardly affected by the time step length and does show a tendency to converge. While the effect on shortwave radiation is globally dominated by the altered reflection due to the change in the cloud liquid water content, the effect on longwave radiation is more difficult to interpret because changes in the cloud ice concentration and cloud fraction are anticorrelated in some regions. The simulations show that using a maximum tropospheric vertical grid spacing larger than 400 m would increase the truncation error strongly. Computing time investments in a further vertical grid refinement can affect the truncation errors of GSRMs similarly to comparable investments in horizontal refinement, because halving the vertical grid spacing is generally cheaper than halving the horizontal grid spacing. However, convergence of boundary layer cloud properties cannot be expected, even for the smallest maximum tropospheric grid spacing of 50 m used in this study.

Adaptive implicit–explicit method for robust and efficient failure analysis of composite materials

Despite numerous methods devised for the analysis of composite materials, substantial challenges persist in modeling the progressive failure process. Specifically, the damage-induced strain softening may cause convergence difficulty in implicit procedures, whereas lack of accuracy and restriction on time-step length are problems of concern for explicit formulations. Herein, we develop an adaptive implicit–explicit method (A-IEM) to enhance the robustness and efficiency of computational failure models. Initially, implicit algorithms are applied for non-linear analysis, during which critical nodes that hinder the convergence rate are identified through a concurrent monitoring algorithm. Upon fatal non-convergence, explicit constitutive law is locally enforced on the corresponding material points to evaluate the damage progression within current increment, and reversion to implicit scheme is subsequently enabled by A-IEM after resolving the numerical issues. The performance of A-IEM against conventional methods is verified via standard numerical examples and further demonstrated in the failure modeling of composite laminates.

Factors influencing gait performance in older adults in a dual-task paradigm.

The aim of this study was to determine the effect of cognitive interference through a dual-task (DT) paradigm on gait parameters by sex or other predictive variables, such as physical fitness, health status, and cognition. A total of 125 older adults joined in this study (age, 72.42 ± 5.56years old; 28 men and 97 women). The DT paradigm was evaluated through Comfortable Linear Gait (CLG) and Complex Gait Test (CGT). The gait parameters between single task (ST) vs. DT condition in men showed a significant reduction in speed (p < 0.001), cadence (p < 0.001), and step length (p = 0.049) and increased time to execute the CGT (p < 0.001), while women showed a decreased speed (p = 0.014), cadence (p < 0.001), and double support coefficient variation (CV) (p = 0.024) and increased single support time (p < 0.001) and CV step length (p < 0.05). In addition, women increased CGT time (p < 0.001). Furthermore, correlations between DT cost (DTC) cadence vs. Physical Activity for Elderly questionnaire (PASE) (r = - 0.399; p = 0.008), DTC single support vs. 30s Sit to Stand Test (r = - 0.356; 0.016), DTC single support vs. Rey Auditory Verbal Learning Test-Learning curve (r = - 0.335; p = 0.023), DTC double support vs. 30s Sit to Stand Test (r = - 0.590; p < 0.001), DTC CV step length vs. 30s Sit to Stand (r = - 0.545; p = 0.003), and DTC CGT vs. 30s Sit to Stand Test (r = - 0.377; p = 0.048) were found. The results of our study indicate that the gait parameters within the DT condition decreased speed and cadence, while increasing CV step length and CGT time, causing slower gait with shortened steps in men and women.

Effects of Auditory Cue Length and Visual Cue Superimposition on Gait Initiation in Parkinson’s Disease: A Pilot Study

Objectives: Effects of cues on gait disturbance in Parkinson’s disease (PD) depend on features of cue presentation. We investigated the effects of the length of simple auditory cues on cue-triggered gait initiation in PD. Methods: The subjects were 8 PD patients in OFF-state (6 women and two men, aged 50-75 years) and 8 normal controls (NCs) (5 women and three men, aged 55-77 years). For the assessment of gait initiation, the subjects were instructed to take three steps without the strong constraint of a quick start. The auditory cues consisted of long and short beeps, and the visual cue was a red light-emitting diode (LED) line projected across the floor 15 cm in front of the subjects’ toes. The four experimental conditions were: (1) short Beep condition (0.1 sec), (2) long Beep condition (3 sec), (3) short Beep/LED condition and (4) long Beep/LED condition. Results: The gait initiation time was delayed, and the initial step length was short under the Beep conditions in the PD patients compared with those in the NCs. Neither parameter differed between the short Beep and the long Beep conditions. Superimposition of the visual cues improved the gait initiation time under the short Beep condition and the initial step length under the short and long Beep conditions. Conclusion: The duration of single auditory cues does not contribute to the gait initiation time and initial step length in PD. Although large-sized studies are necessary to confirm the results, instantaneous auditory perception may be the primary driving force for the effects of single auditory cues on gait initiation.

The validity of smartphone-based spatiotemporal gait measurements during walking with and without head turns: Comparison with the GAITRite® system

Smartphone accelerometry has potential to provide clinicians with specialized gait analysis not available in most clinical settings. The Gait&Balance Application (G&B App) uses smartphone accelerometry to assess spatiotemporal gait parameters under two conditions: walking looking straight ahead and walking with horizontal head turns. This study investigated the validity of G&B App gait parameters compared with the GAITRite® pressure-sensitive walkway. Healthy young and older adults (age range 21–85 years) attended a single session where a smartphone was secured over the lumbosacral junction. Data were collected concurrently with the app and GAITRite® systems as participants completed the two walking conditions. Spatiotemporal gait parameters for 54 participants were determined from both systems and agreement evaluated with partial Pearson’s correlation coefficients and limits of agreement. The results demonstrated moderate to excellent validity for G&B App measures of step time (rp 0.97, 95 % CI [0.96, 0.98]), walking speed (rp 0.83 [0.78, 0.87]), and step length (rp 0.74, [0.66, 0.80]) when walking looking straight ahead, and results were comparable with head turns. The validity of walking speed and step length measures was influenced by sex and height. G&B App measures of step length variability, step time variability, step length asymmetry, and step time asymmetry had poor validity. The G&B App has potential to provide valid measures of unilateral and bilateral step time, unilateral and bilateral step length, and walking speed, under two walking conditions in healthy young and older adults. Further research should validate this tool in clinical conditions and optimise the algorithm for demographic characteristics.

Study of the convergence of the Meshless Lattice Boltzmann Method in Taylor–Green, annular channel and a porous medium flows

The Meshless Lattice Boltzmann Method (MLBM) is a numerical tool that relieves the standard Lattice Boltzmann Method (LBM) from regular lattices and, at the same time, decouples space and velocity discretizations. In this study, we investigate the numerical convergence of MLBM in three benchmark tests: the Taylor–Green vortex, annular (bent) channel and a porous medium flow. We compare our MLBM results to LBM and to the analytical solution of the Navier–Stokes equation. We investigate the method’s convergence in terms of the discretization parameter, the interpolation order, and the LBM streaming distance refinement. We observe that MLBM outperforms LBM in terms of the error value for the same number of nodes discretizing the domain. We find that LBM errors at a given streaming distance δx and timestep length δt are the asymptotic lower bounds of MLBM errors with the same streaming distance and timestep length. Finally, we suggest an expression for the MLBM error that consists of the LBM error and other terms related to the semi-Lagrangian nature of the discussed method itself.

An Integrated Eye-Tracking and Motion Capture System in Synchronized Gaze and Movement Analysis.

Integrating mobile eye-tracking and motion capture emerges as a promising approach in studying visual-motor coordination, due to its capability of expressing gaze data within the same laboratory-centered coordinate system as body movement data. In this paper, we proposed an integrated eye-tracking and motion capture system, which can record and analyze temporally and spatially synchronized gaze and motion data during dynamic movement. The accuracy of gaze measurement were evaluated on five participants while they were instructed to view fixed vision targets at different distances while standing still or walking towards the targets. Similar accuracy could be achieved in both static and dynamic conditions. To demonstrate the usability of the integrated system, several walking tasks were performed in three different pathways. Results revealed that participants tended to focus their gaze on the upcoming path, especially on the downward path, possibly for better navigation and planning. In a more complex pathway, coupled with more gaze time on the pathway, participants were also found having the longest step time and shortest step length, which led to the lowest walking speed. It was believed that the integration of eye-tracking and motion capture is a feasible and promising methodology quantifying visual-motor coordination in locomotion.

Performance and mechanism study of IA‐AMPS‐HPA as an oilfield scale inhibitor: Experimental and molecular dynamics simulation

AbstractIn this article, itaconic acid (IA), 2‐acrylamide‐2‐methylpropanesulfonic acid (AMPS), and hydroxypropyl acrylate (HPA) served as the reaction's monomers, deionized water served as the reaction's solvent, and ammonium persulfate served as the reaction's initiator, with isopropanol serving as the chain transfer agent, a terpolymer scale inhibitor (IA‐AMPS‐HPA) was synthesized and used to prevent the growth of calcium carbonate (CaCO3) scale in an oilfield environment. On the effectiveness of scale inhibition, the influence of temperature, scale inhibitor concentration, pH, calcium ion concentration, and salt levels are examined. The results indicate that the scale inhibition rate progressively drops with growing temperature and gradually increases with rising scale inhibitor concentration. The scale inhibition rate reaches 97.67% when the temperature is 60°C, and the scale inhibitor concentration is 60 mg/L. When the temperature is 80°C and the concentration of scale inhibitor is 40 mg/L, the inhibitor's ability to block CaCO3 increases as the salt content rises. The scale inhibition rate is more than 85% when the pH is less than 9. Besides, the Ca2+ concentration is less than 300 mg/L, and the scale inhibition rate declines as the Ca2+ concentration rises, reaching a maximum value of 91.67% when the salt content is 33 g/L. With a rise in pH, the scale inhibition rate dropped. Employing a scanning electron microscope, the morphology of scale samples was described and analyzed. Molecular dynamics was utilized to simulate the interaction between IA‐AMPS‐HPA and the crystallization surface of CaCO3 at varying temperatures. The results show that the binding energy decreases as the system temperature rises and that the reaction between polymer molecules and CaCO3 crystals in the system can be observed by increasing the time step length and the water molecule concentration. The simulation results are with following the observed phenomena.

Efficient Runge–Kutta solver for stochastic crack growth analysis

Stochastic crack growth analysis by simulation may easily require a significant amount of computational effort. The Initial Value ordinary differential equations appearing in crack propagation problems may be solved by the Runge–Kutta (RK) family of solvers. However, crack propagation considering uncertainties imposes additional challenges for RK solvers: possibility of vectorized and/or parallelized computation of sample realizations; and adaptation of time discretization for each sample, to handle changes and discontinuities in the derivatives of crack growth curves, caused by changes in loads and in crack propagation rates. Existing adaptive RK methods, with change in time step length during crack growth computation, struggle with these challenges. In this setting, the present paper proposes a modified adaptive RK method which allows for simultaneous crack growth computations with different time-step discretizations, and aims at efficiently dealing with cases where discontinuities are present in the derivative of the crack growth curve. Application of the proposed method to three crack propagation examples, including one related to weld flaws in pipes, indicates that it is as accurate as other adaptive methods from the literature, while requiring only a fraction of the computational time.

Comparison of contact treatment methods for rigid polyhedral discrete element models

Blocky rock and stone structures (such as jointed rocks mass, masonry structures and railway ballast) are often submitted to dynamic effects. Their mechanical behaviour can be simulated with the discrete element method (DEM) using polyhedral elements. DEM models differ in how they compute the contact forces. Several studies have compared different contact constitutive laws, but little information is available in the literature on which contact treatment method (i.e. number of contacts between two elements, contact detection, contact orientation, area and overlap computation) to choose. The inclined slope, the perpendicular impact and the rocking block problems were simulated and applied as benchmark tests in the present study to compare three most popular polyhedral DEM contact treatment models for rigid elements, namely the Eliáš (available in Yade), the Gilbert-Johnson-Keerthi (GJK, widely implemented, here tested with PFC3D) and the Sub-Contact model (available in 3DEC), to see which ones could be precisely calibrated to analytic and experimental solutions. Sensitivity studies were also carried out on the effect of subdivision density of element surfaces and on the admissible timestep length. Experiences showed that while there are serious doubts about the applicability of the Eliáš volumetric model as it is sensitive to both variations in geometry and the results vary randomly with the timestep length, the GJK model is suitable to simulate granular materials because of its computational efficiency and robustness, and the Sub-Contact method is the proper choice to model structures where the contact surfaces are relatively large, as it operates multiple contacts between two elements and gives information about the force distribution on the surface of the elements.

Kinetic and Kinematic Analysis of Gait Termination: A Comparison between Planned and Unplanned Conditions

Purpose: Gait termination (GT) is the transition from steady-state walking to a complete stop, occurring under planned gait termination (PGT) or unplanned gait termination (UGT) conditions. This study aimed to investigate the biomechanical differences between PGT and UGT, which could help develop therapeutic interventions for individuals experiencing difficulty with GT. Methods: Twenty healthy adults performed three walking trials, followed by PGT and UGT trials. Gait termination was analyzed in three phases as follows: Phase 1 (pre-stopping), Phase 2 (initial stopping phase), and Phase 3 (terminal stopping phase). Spatiotemporal, kinematic, and kinetic data during each phase were compared between conditions. Results: The GT time and GT step length were significantly different between the PGT and UGT trials. Ankle range of motion (ROM) demonstrated significant differences in Phase 1, with the PGT having a slightly lower ankle ROM than the UGT. In Phase 2, the hip, knee, and ankle ROM exhibited significant differences between the conditions. Finally, in Phase 3, UGT showed reduced hip ROM but increased knee ROM and kinetic parameters compared to PGT. Conclusion: Our results indicate that the ankle joint primarily contributes to deceleration during the initial preparation for generating braking force during PGT. Conversely, UGT reveals disrupted kinesthetic control due to instability, leading to a preference for a hip and knee strategy to absorb force and control the center of mass for a safe and rapid GT in response to unexpected stimuli. These findings provide valuable insights into the biomechanical mechanisms underlying body stability during GT and may contribute to the development of effective rehabilitation strategies for individuals with gait impairment.

Numerical investigation on wheel-rail adhesion under water-lubricated condition during braking

PurposeThe purpose of this study is to develop a 3D wheel-rail adhesion model under wet condition, which considers the generated surface roughness topography and the traditional braking procedure for high-speed trains.Design/methodology/approachWheel-rail adhesion has an important effect on the braking ability of railway vehicle. Based on the deterministic mixed lubrication approach, the model was solved to get the adhesion characteristics of the train during braking. The elastic deformation was calculated with the discrete convolution and fast Fourier transform method. The simulation results of adhesion coefficient were compared with the experimental values. The wheel-rail adhesion characteristics of train braking at several different initial speeds were investigated. The effects of the time-step length and roughness orientation on the contact load ratio were also discussed.FindingsThe results show that the adhesion coefficient of the numerical model is in good agreement with the experimental results. At the instant of braking, the adhesion coefficient drops to a lower adhesion level, the value of adhesion coefficient is lower than 0.06, especially at a higher speed (200, 300 and 400 km/h).Originality/valueIt can provide a better understanding of the low adhesion phenomenon of train braking under wet condition.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2023-0040/