scholarly journals Elasto-plastic-adhesive DEM model for simulating hillslope debris flows: cross comparison with field experiments

2018 ◽  
Author(s):  
Adel Albaba ◽  
Massimiliano Schwarz ◽  
Corinna Wendeler ◽  
Bernard Loup ◽  
Luuk Dorren
Keyword(s):  
Numerical Model ◽  
Flow Velocity ◽  
Debris Flows ◽  
Field Experiments ◽  
Initial Conditions ◽  
Experimental Tests ◽  
Height Velocity ◽  
Model Parameters ◽  
Fine Content ◽  
Adhesive Model

Abstract. This paper presents a Discrete Element-based elasto-plastic-adhesive model which is adapted and tested for producing hillslope debris flows. The numerical model produces three phases of particle contacts: elastic, plastic and adhesion. The model capabilities of simulating different types of cohesive granular flows were tested with different ranges of flow velocities and heights. The basic model parameters, being the basal friction (ϕb) and normal restitution coefficient (ϵn), were calibrated using field experiments of hillslope debris flows impacting two sensors. Simulations of 50 m3 of material were carried out on a channelized surface that is 41 m long and 8 m wide. The calibration process was based on measurements of flow height, flow velocity and the pressure applied to a sensor. Results of the numerical model matched well those of the field data in terms of pressure and flow velocity while less agreement was observed for flow height. Those discrepancies in results were due in part to the deposition of material in the field test which are not reproducible in the model. A parametric study was conducted to further investigate that effect of model parameters and inclination angle on flow height, velocity and pressure. Results of best-fit model parameters against selected experimental tests suggested that a link might exist between the model parameters ϕb and ϵn and the initial conditions of the tested granular material (bulk density and water and fine contents). The good performance of the model against the full-scale field experiments encourages further investigation by conducting lab-scale experiments with detailed variation of water and fine content to better understand their link to the model's parameters.

scholarly journals Numerical modeling using an elastoplastic-adhesive discrete element code for simulating hillslope debris flows and calibration against field experiments

2019 ◽  
Vol 19 (11) ◽  
pp. 2339-2358
Author(s):  
Adel Albaba ◽  
Massimiliano Schwarz ◽  
Corinna Wendeler ◽  
Bernard Loup ◽  
Luuk Dorren
Keyword(s):  
Numerical Model ◽  
Flow Velocity ◽  
Debris Flows ◽  
Field Experiments ◽  
Initial Conditions ◽  
Experimental Tests ◽  
Discrete Element ◽  
Height Velocity ◽  
Model Parameters ◽  
Fine Content

Abstract. This paper presents a discrete-element-based elastoplastic-adhesive model which is adapted and tested for producing hillslope debris flows. The numerical model produces three phases of particle contacts: elastic, plastic and adhesive. A parametric study was conducted investigating the effect of model parameters and inclination angle on flow height, velocity and pressure, in order to define the most sensitive parameters to calibrate. The model capabilities of simulating different types of cohesive granular flows were tested with different ranges of flow velocities and heights. The basic model parameters, the microscopic basal friction (ϕb) and ratio between stiffness parameters k1/k2, were calibrated using field experiments of hillslope debris flows impacting a pressure-measuring sensor. Simulations of 50 m3 of material were carried out on a channelized surface that is 41 m long and 8 m wide. The calibration process was based on measurements of flow height, flow velocity and the pressure applied to a sensor. Results of the numerical model matched those of the field data in terms of pressure and flow velocity well while less agreement was observed for flow height. Those discrepancies in results were due in part to the deposition of material in the field test, which is not reproducible in the model. Results of best-fit model parameters against selected experimental tests suggested that a link might exist between the model parameters ϕb and k1/k2 and the initial conditions of the tested granular material (bulk density and water and fine contents). The good performance of the model against the full-scale field experiments encourages further investigation by conducting lab-scale experiments with detailed variation in water and fine content to better understand their link to the model's parameters.

scholarly journals Estimation of Coastal Currents Using a Soft Computing Method: A Case Study in Galway Bay, Ireland

2019 ◽  
Vol 7 (5) ◽  
pp. 157 ◽  
Author(s):  
Lei Ren ◽  
Jianming Miao ◽  
Yulong Li ◽  
Xiangxin Luo ◽  
Junxue Li ◽  
...  
Keyword(s):  
Numerical Model ◽  
Soft Computing ◽  
Initial Conditions ◽  
Numerical Models ◽  
Surface Velocity ◽  
Training Dataset ◽  
Model Parameters ◽  
Surface Currents ◽  
Coastal Currents ◽  
Computing Models

In order to obtain forward states of coastal currents, numerical models are a commonly used approach. However, the accurate definition of initial conditions, boundary conditions and other model parameters are challenging. In this paper, a novel application of a soft computing approach, random forests (RF), was adopted to estimate surface currents for three analysis points in Galway Bay, Ireland. Outputs from a numerical model and observations from a high frequency radar system were used as inputs to develop soft computing models. The input variable structure of soft computing models was examined in detail through sensitivity experiments. High correlation of surface currents between predictions from RF models and radar data indicated that the RF algorithm is a most promising means of generating satisfactory surface currents over a long prediction period. Furthermore, training dataset lengths were examined to investigate influences on prediction accuracy. The largest improvement for zonal and meridional surface velocity components over a 59-h forecasting period was 14% and 37% of root mean square error (RMSE) values separately. Results indicate that the combination of RF models with a numerical model can significantly improve forecasting accuracy for surface currents, especially for the meridional surface velocity component.

scholarly journals Particle motion on burned and vegetated hillslopes

2020 ◽  
Vol 117 (41) ◽  
pp. 25335-25343
Author(s):  
Danica L. Roth ◽  
Tyler H. Doane ◽  
Joshua J. Roering ◽  
David J. Furbish ◽  
Aaron Zettler-Mann
Keyword(s):  
Sediment Transport ◽  
Particle Motion ◽  
Debris Flows ◽  
Field Experiments ◽  
Transport Theory ◽  
Surface Characteristics ◽  
Model Parameters ◽  
Mathematical Framework ◽  
Long Distance ◽  
Heavy Tailed

Climate change is causing increasingly widespread, frequent, and intense wildfires across the western United States. Many geomorphic effects of wildfire are relatively well studied, yet sediment transport models remain unable to account for the rapid transport of sediment released from behind incinerated vegetation, which can fuel catastrophic debris flows. This oversight reflects the fundamental inability of local, continuum-based models to capture the long-distance particle motions characteristic of steeplands. Probabilistic, particle-based nonlocal models may address this deficiency, but empirical data are needed to constrain their representation of particle motion in real landscapes. Here we present data from field experiments validating a generalized Lomax model for particle travel distance distributions. The model parameters provide a physically intuitive mathematical framework for describing the transition from light- to heavy-tailed distributions along a continuum of behavior as particle size increases and slopes get steeper and/or smoother. We show that burned slopes are measurably smoother than vegetated slopes, leading to 1) lower rates of experimental particle disentrainment and 2) runaway motion that produces the heavy-tailed travel distances often associated with nonlocal transport. Our results reveal that surface roughness is a key control on steepland sediment transport, particularly after wildfire when smoother surfaces may result in the preferential delivery of coarse material to channel networks that initiate debris flows. By providing a first-order framework relating the statistics of particle motion to measurable surface characteristics, the Lomax model both advances the development of nonlocal sediment transport theory and reveals insights on hillslope transport mechanics.

scholarly journals Discrete-Time Model of Seasonal Plankton Bloom

2020 ◽  
Vol 15 (2) ◽  
pp. 235-250
Author(s):  
G.P. Neverova ◽  
O.L. Zhdanova ◽  
A.I. Abakumov
Keyword(s):  
Dynamic Model ◽  
Discrete Time ◽  
Field Experiments ◽  
Initial Conditions ◽  
Numerical Study ◽  
Classical System ◽  
Zooplankton Community ◽  
Dynamic Mode ◽  
Model Parameters ◽  
Delayed Response

The most interesting results in modeling phytoplankton bloom were obtained based on a modification of the classical system of phytoplankton and zooplankton interaction. The modifications using delayed equations, as well as piecewise continuous functions with a delayed response to intoxication processes, made it possible to obtain adequate phytoplankton dynamics like in nature. This work develops a dynamic model of phytoplankton-zooplankton community consisting of two equations with discrete time. We use recurrent equations, which allows to describe delay in response naturally. The proposed model takes into account the phytoplankton toxicity and zooplankton response associated with phytoplankton toxicity. We use a discrete analogue of the Verhulst model to describe the dynamics of each of the species in the community under autoregulation processes. We use Holling-II type response function taking into account predator saturation to describe decrease in phytoplankton density due to its consumption by zooplankton. Growth and survival rates of zooplankton also depend on its feeding. Zooplankton mortality, caused by an increase in the toxic substances concentration with high density of zooplankton, is included in the limiting processes. An analytical and numerical study of the model proposed is made. The analysis shows that the stability loss of nontrivial fixed point corresponding to the coexistence of phytoplankton and zooplankton can occur through a cascade of period doubling bifurcations and according to the Neimark-Saker scenario leading to the appearance of quasiperiodic fluctuations as well. The proposed dynamic model of the phytoplankton and zooplankton community allows observing long-period oscillations, which is consistent with the results of field experiments. As well, the model have multistability areas, where a variation in initial conditions with the unchanged values of all model parameters can result in a shift of the current dynamic mode.

Simplified simulation of rock avalanches and subsequent debris flows with a single thin-layer model. Application to the Prêcheur river (Martinique, Lesser Antilles)

2021 ◽  
Author(s):  
Marc Peruzzetto ◽  
Clara Levy ◽  
Yannick Thiery ◽  
Gilles Grandjean ◽  
Anne Mangeney ◽  
...  
Keyword(s):  
Debris Flow ◽  
Thin Layer ◽  
Debris Flows ◽  
Initial Conditions ◽  
Rock Avalanche ◽  
Numerical Code ◽  
Lesser Antilles ◽  
Rheological Parameters ◽  
Model Parameters ◽  
High Discharge

<p>This work focuses on the use of thin-layer models for simulating fast gravitational flows for hazard assessment. Such simulations are sometimes difficult to carry out because of the uncertainty on initial conditions and on simulation parameters. In this study, we aggregate various field data to constrain realistic initial conditions and to calibrate the model parameters. By using the SHALTOP numerical code, we choose a simple and empirical rheology to model the flow (no more than two parameters), but we model more finely the geometrical interactions between the flow and the topography. We can thus model both a rock avalanche, and the subsequent remobilization of the deposits as a high discharge debris flow.</p><p>Using the Prêcheur river catchment (Martinique, Lesser Antilles) as a case study, we focus on extreme events with a high potential to impact populations and infrastructures. We use geological and geomorphological data, topographic surveys, seismic recordings and granulometric analysis to define realistic simulation scenarios and determine the main characteristics of documented events. The latter are then reproduced to calibrate rheological parameters. With a single rheological parameter and the Coulomb rheology, we thus model the emplacement and main dynamic characteristics of a recent rock avalanche, as well as the travel duration and flooded area of a documented high discharge debris flow. Then, in a forward prediction simulation, we model a possible 1.9x10<sup>6 </sup>m<sup>3</sup> rock avalanche, and the instantaneous remobilization of the resulting deposits as a high-discharge debris flow. We show that successive collapses allow to better reproduce the dynamics of the rock avalanche, but do not change the geometry of the final deposits, and thus do not influence the initial conditions of the subsequent debris flow simulation. A progressive remobilization of the materials slows down the debris flow and limits overflow, in comparison to instantaneous release. However, we show that high discharge debris flows, such as the one considered for model calibration, are better reproduced with an instantaneous initiation. The range of travel times measured for other significant debris flows in the Pr\^echeur river is consistent with our simulation results, with various rheological parameters and the Coulomb or Voellmy rheology.</p>

State-of-charge estimation based on model-adaptive Kalman filters

2020 ◽  
pp. 095965182096540
Author(s):  
Edoardo Locorotondo ◽  
Giovanni Lutzemberger ◽  
Luca Pugi
Keyword(s):  
Kalman Filter ◽  
Initial Conditions ◽  
Lithium Ion ◽  
Experimental Tests ◽  
State Of Charge ◽  
Model Parameters ◽  
Identification Methods ◽  
State Of Charge Estimation ◽  
Different Levels ◽  
Sampling Times

This article presents a set of algorithms for the estimation of state of charge, specifically deployed for lithium-ion batteries. These algorithms are based on appropriate battery models. These models can be developed having different levels of accuracy, also including the possibility to correctly represent the hysteresis voltage behaviour of the selected lithium cells. In addition, different identification methods of the battery model parameters may also be considered, considering tabulated parameters, calibrated in previous tests, or online parametrization tools. State of charge is then evaluated using non-linear Kalman filter techniques. Effectiveness of identification methods, also with the performance offered by Kalman filter itself, has been accurately evaluated through experimental tests. To verify the robustness of the proposed algorithms, some disturbances were introduced and evaluation was also conducted at different state of charge initial conditions and sampling times.

MODELING COMPLEX FLOW INDUCED BY WATER WAVES PROPAGATION OVER SUBMERGED SQUARE OBSTACLES

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Mona Abdeltawab Gomaa ◽  
Tamer HMA Kasem ◽  
Andreas Schlenkhoff
Keyword(s):  
Numerical Model ◽  
Wave Energy ◽  
Water Waves ◽  
Initial Conditions ◽  
Computational Time ◽  
Model Parameters ◽  
Shore Protection ◽  
Complex Flow ◽  
Time Step ◽  
Wave Energy Dissipation

Submerged breakwaters are efficient structures used for shore protection. Many design features of these structures are captured upon modeling wave propagation over submerged square obstacles. The presence of separation vortices and large free surface deformations complicates the problem. A multiphase turbulent numerical model is developed using ANSYS commercial package. Careful domain discretization is done employing suitable mesh clustering to capture high gradients. Various numerical model parameters are provided, including grid size and time step. Special attention is directed towards clarifying turbulence initial conditions. Stable simulation results are obtained within acceptable computational time. Numerical results are validated quantitatively using subsurface measurements. Comparison along continuous horizontal and vertical velocity profiles is provided. Temporal and spatial model resolutions are illustrated for three test cases. The effect of wave period and height is well focused. The unsteady vortical structure is visualized. The incident wave energy is calculated and validated against theoretical values. The wave energy dissipation characteristics are briefly explained.

scholarly journals Life Prediction Model of Mineral Admixture Cement Based-Materials under Early Age CO2-Erosion

Coatings ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 413
Author(s):  
Saisai Wang ◽  
Jian Chen ◽  
Xiaodong Wen
Keyword(s):  
Prediction Model ◽  
Life Prediction ◽  
Experimental Tests ◽  
Mineral Admixture ◽  
Model Parameters ◽  
Influence Coefficient ◽  
Test Pieces ◽  
Cement Based Materials ◽  
Particle Group ◽  
Life Prediction Model

Most of the existing models of structural life prediction in early carbonized environment are based on accelerated erosion after standard 28 days of cement-based materials, while cement-based materials in actual engineering are often exposed to air too early. These result in large predictions of the life expectancy of mineral-admixture cement-based materials under early CO2-erosion and affecting the safe use of structures. To this end, different types of mineral doped cement-based material test pieces are formed, and early CO2-erosion experimental tests are carried out. On the basis of the analysis of the existing model, the influence coefficient of CO2-erosion of the mineral admixture Km is introduced, the relevant function is given, and the life prediction model of the mineral admixture cement-based material under the early CO2-erosion is established and the model parameters are determined by using the particle group algorithm (PSO). It has good engineering applicability and guiding significance.

scholarly journals Numerical simulation method for predicting a flood hydrograph due to progressive failure of a landslide dam

Landslides ◽  
2021 ◽  
Author(s):  
S. Takayama ◽  
S. Miyata ◽  
M. Fujimoto ◽  
Y. Satofuka
Keyword(s):  
Field Experiments ◽  
Failure Modes ◽  
Initial Conditions ◽  
Progressive Failure ◽  
Landslide Dam ◽  
Failure Model ◽  
Reservoir Water ◽  
Erosion Model ◽  
Flood Hydrograph ◽  
Overtopping Erosion

AbstractReducing the damage due to landslide dam failures requires the prediction of flood hydrographs. Although progressive failure is one of the main failure modes of landslide dams, no prediction method is available. This study develops a method for predicting progressive failure. The proposed method consists of the progressive failure model and overtopping erosion model. The progressive failure model can reproduce the collapse progression from a dam toe to predict the longitudinal dam shape and reservoir water level when the reservoir water overflows. The overtopping erosion model uses these predicted values as the new initial conditions and reproduces the dam erosion processes due to an overtopping flow in order to predict a flood hydrograph after the reservoir water overflows. The progressive failure model includes physical models representing the intermittent collapse of a dam slope, seepage flow in a dam, and surface flow on a dam slope. The intermittent collapse model characterizes the progressive failure model. It considers a stabilization effect whereby collapse deposits support a steep slope. This effect decreases as the collapse deposits are transported downstream. Such a consideration allows the model to express intermittent, not continuous, occurrences of collapses. Field experiments on the progressive failure of a landslide dam were conducted to validate the proposed method. The progressive failure model successfully reproduced the experimental results of the collapse progression from the dam toe. Using the value predicted by the progressive failure model, the overtopping erosion model successfully reproduced the flood hydrograph after the reservoir water started to overflow.

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