scholarly journals Elastoplastical Analysis of the Interface between Clay and Concrete Incorporating the Effect of the Normal Stress History

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Zhao Cheng ◽  
Zhao Chunfeng ◽  
Gong Hui
Keyword(s):  
Normal Stress ◽  
Load Transfer ◽  
Shear Behaviour ◽  
Model Parameters ◽  
Stress History ◽  
Hardening Parameter ◽  
Using Data ◽  
Energy Dissipated ◽  
Interaction Problem ◽  
Soil Interface

The behaviour of the soil-structure interface is crucial to the design of a pile foundation. Radial unloading occurs during the process of hole boring and concrete curing, which will affect the load transfer rule of the pile-soil interface. Through large shear tests on the interface between clay and concrete, it can be concluded that the normal stress history significantly influences the shear behaviour of the interface. The numerical simulation of the bored shaft-soil interaction problem requires proper modelling of the interface. By taking the energy accumulated on the interface as a hardening parameter and viewing the shearing process of the interface as the process of the energy dissipated to do work, considering the influence of the normal stress history on the shearing rigidity, a mechanical model of the interface between clay and concrete is proposed. The methods to define the model parameters are also introduced. The model is based on a legible mathematical theory, and all its parameters have definite physical meaning. The model was validated using data from a direct shear test; the validation results indicated that the model can reproduce and predict the mechanical behaviour of the interface between clay and concrete under an arbitrary stress history.

scholarly journals Semi-analytical approach for time-dependent load–settlement response of a jacked pile in clay strata

2017 ◽  
Vol 54 (12) ◽  
pp. 1682-1692 ◽  
Author(s):  
Lin Li ◽  
Jingpei Li ◽  
De’an Sun ◽  
Weibing Gong
Keyword(s):  
Analytical Approach ◽  
Load Transfer ◽  
Time Dependent ◽  
Model Parameters ◽  
Nonlinear Behaviour ◽  
Pile Installation ◽  
Axially Loaded ◽  
Z Curve ◽  
Soil Interface ◽  
Surrounding Soil

Mechanical behaviour of the soil around a jacked pile changes significantly during pile installation and subsequent consolidation. Hence, an axially loaded jacked pile exhibits apparent time-dependent bearing performance after pile installation. This paper presents a semi-analytical approach to predict the time-dependent bearing performance of an axially loaded jacked pile in saturated clay strata. The effects of pile installation and subsequent consolidation on the changes in mechanical properties of the surrounding soil are modeled by the cavity expansion theory and the radial consolidation theory, respectively. An exponential function–based load-transfer (t–z) curve is employed to describe the nonlinear behaviour of the pile–soil interface during pile loading. The evolutions of the three-dimensional strength and shear modulus of the surrounding soil are subsequently incorporated into the two model parameters of the proposed t–z curve to capture the time-dependent pile–soil interaction behaviour. The time-dependent elastic response of the soil outside the pile–soil interface is also considered in the proposed approach. With the proposed load-transfer curve, an incremental algorithm and a corresponding computational code are developed for assessing the time-dependent load–settlement response of a jacked pile. To verify the proposed semi-analytical approach, predictions of the time-dependent load–settlement curves are compared with the measured values from pile tests at two sites. The good agreement shows that the time-dependent bearing performance can be reasonably predicted by the proposed approach.

Predicting the longitudinal modulus of elasticity of Sitka spruce from cellulose orientation and abundance

Holzforschung ◽  
2010 ◽  
Vol 64 (4) ◽  
Author(s):  
J. Paul McLean ◽  
Robert Evans ◽  
John R. Moore
Keyword(s):  
Bulk Density ◽  
Modulus Of Elasticity ◽  
Microfibril Angle ◽  
Sitka Spruce ◽  
Picea Sitchensis ◽  
Model Parameters ◽  
Bending Tests ◽  
Wood Stiffness ◽  
Using Data ◽  
Longitudinal Modulus

Abstract Sitka spruce (Picea sitchensis) is the most widely planted commercial tree species in the United Kingdom and Ireland. Because of the increasing use of this species for construction, the ability to predict wood stiffness is becoming more important. In this paper, a number of models are developed using data on cellulose abundance and orientation obtained from the SilviScan-3 system to predict the longitudinal modulus of elasticity (MOE) of small defect-free specimens. Longitudinal MOE was obtained from both bending tests and a sonic resonance technique. Overall, stronger relationships were found between the various measures of cellulose abundance and orientation and the dynamic MOE obtained from the sonic resonance measurements, rather than with the static MOE obtained from bending tests. There was only a moderate relationship between wood bulk density and dynamic MOE (R2=0.423), but this relationship was improved when density was divided by microfibril angle (R2=0.760). The best model for predicting both static and dynamic MOE involved the product of bulk density and the coefficient of variation in the azimuthal intensity profile (R2=0.725 and 0.862, respectively). The model parameters obtained for Sitka spruce differed from those obtained in earlier studies on Pinus radiata and Eucalyptus delegatensis, indicating that the model might require recalibration before it can be applied to different species.

scholarly journals Resource-Driven Encounters and the Induction of Disease Among Consumers

2016 ◽  
Author(s):  
Rebecca K. Borchering ◽  
Steve E. Bellan ◽  
Jason M. Flynn ◽  
Juliet R.C. Pulliam ◽  
Scott A. McKinley
Keyword(s):  
National Park ◽  
Interaction Model ◽  
Spatially Explicit ◽  
Encounter Rate ◽  
Model Parameters ◽  
Expected Number ◽  
Spatially Explicit Model ◽  
Consumer Population ◽  
Using Data ◽  
The Relationship

AbstractSubmitted Manuscript 2016. Territorial animals share a variety of common resources, which can be a major driver of conspecific encounter rates. We examine how changes in resource availability influence the rate of encounters among individuals in a consumer population by implementing a spatially explicit model for resource visitation behavior by consumers. Using data from 2009 and 2010 in Etosha National Park, we verify our model's prediction that there is a saturation effect in the expected number of jackals that visit a given carcass site as carcasses become abundant. However, this does not directly imply that the overall resource-driven encounter rate among jackals decreases. This is because the increase in available carcasses is accompanied by an increase in the number of jackals that detect and potentially visit carcasses. Using simulations and mathematical analysis of our consumer-resource interaction model, we characterize key features of the relationship between resource-driven encounter rate and model parameters. These results are used to investigate a standing hypothesis that the outbreak of a fatal disease among zebras can potentially lead to an outbreak of an entirely different disease in the jackal population, a process we refer to as indirect induction of disease.

Shear and dewatering behaviour of densified gold tailings in a laboratory simulation of multi-layer deposition

2016 ◽  
Vol 53 (8) ◽  
pp. 1246-1257 ◽  
Author(s):  
Farzad Daliri ◽  
Paul Simms ◽  
Siva Sivathayalan
Keyword(s):  
Sampling Method ◽  
Drainage Water ◽  
Laboratory Simulation ◽  
Shear Behaviour ◽  
Thin Wall ◽  
Stress History ◽  
Bench Scale ◽  
Age Related ◽  
Layer Deposition ◽  
Gold Tailings

Tailings may undergo desiccation stress history under varied climatic and depositional parameters. While tailings substantially dewatered prior to deposition may experience desiccation under the greatest range of climatic variation, even conventionally deposited tailings may desiccate in arid climates at lower rates of rise. Bench-scale research has shown that the stress history imparted by desiccation substantially improves strength in gold tailings. The present study further investigates this phenomenon by simulating multi-layer deposition of high-density tailings using a modular drying box, 0.7 m by 1 m in plan. The box is instrumented for directly measuring evaporation, drainage, water content, vertical volume change, and matric suction. Additional measurements included total suction at the surface as well as observations of crack development. The dewatering behaviour conforms to that predicted by previously published generic modelling, specifically that the presence of partially desiccated tailings initially accelerates, but then decelerates dewatering of fresh tailings. The shear behaviour of samples obtained using buried tubes and by driving thin-wall tubes into the multi-layer simulation are compared with shear behaviour of samples from bench-scale experiments. Shear strength of samples from the multi-layer simulation is independent of the sampling method, and shows higher strength than the bench-scale samples. The higher strength may be due to the greater number of wet–dry cycles or other age-related processes.

scholarly journals Evaluating prior predictions of production and seismic data

2019 ◽  
Vol 23 (6) ◽  
pp. 1331-1347 ◽  
Author(s):  
Miguel Alfonzo ◽  
Dean S. Oliver
Keyword(s):  
Data Assimilation ◽  
Seismic Data ◽  
History Matching ◽  
Simulated Data ◽  
Model Parameters ◽  
Model Diagnostic ◽  
Diagonal Approximation ◽  
Data Coverage ◽  
Reservoir Simulation Model ◽  
Using Data

Abstract It is common in ensemble-based methods of history matching to evaluate the adequacy of the initial ensemble of models through visual comparison between actual observations and data predictions prior to data assimilation. If the model is appropriate, then the observed data should look plausible when compared to the distribution of realizations of simulated data. The principle of data coverage alone is, however, not an effective method for model criticism, as coverage can often be obtained by increasing the variability in a single model parameter. In this paper, we propose a methodology for determining the suitability of a model before data assimilation, particularly aimed for real cases with large numbers of model parameters, large amounts of data, and correlated observation errors. This model diagnostic is based on an approximation of the Mahalanobis distance between the observations and the ensemble of predictions in high-dimensional spaces. We applied our methodology to two different examples: a Gaussian example which shows that our shrinkage estimate of the covariance matrix is a better discriminator of outliers than the pseudo-inverse and a diagonal approximation of this matrix; and an example using data from the Norne field. In this second test, we used actual production, repeat formation tester, and inverted seismic data to evaluate the suitability of the initial reservoir simulation model and seismic model. Despite the good data coverage, our model diagnostic suggested that model improvement was necessary. After modifying the model, it was validated against the observations and is now ready for history matching to production and seismic data. This shows that the proposed methodology for the evaluation of the adequacy of the model is suitable for large realistic problems.

scholarly journals Modelling temperature variations in polar snow using DAISY

1997 ◽  
Vol 43 (143) ◽  
pp. 180-191 ◽  
Author(s):  
Ε. M. Morris ◽  
H. -P. Bader ◽  
P. Weilenmann
Keyword(s):  
Field Experiments ◽  
A Priori ◽  
Model Parameters ◽  
Data Set ◽  
International Geophysical Year ◽  
Snow Model ◽  
Using Data ◽  
Polar Snow ◽  
Parameter Values ◽  
The Antarctic

AbstractA physics-based snow model has been calibrated using data collected at Halley Bay, Antarctica, during the International Geophysical Year. Variations in snow temperature and density are well-simulated using values for the model parameters within the range reported from other polar field experiments. The effect of uncertainty in the parameter values on the accuracy of the predictions is no greater than the effect of instrumental error in the input data. Thus, this model can be used with parameters determined a priori rather than by optimization. The model has been validated using an independent data set from Halley Bay and then used to estimate 10 m temperatures on the Antarctic Peninsula plateau over the last half-century.

scholarly journals Simultaneous state-parameter estimation of rainfall-induced landslide displacement using data assimilation

2019 ◽  
Author(s):  
Jing Wang ◽  
Guigen Nie ◽  
Shengjun Gao ◽  
Changhu Xue
Keyword(s):  
Parameter Estimation ◽  
Data Assimilation ◽  
Prediction Method ◽  
State Parameter ◽  
Joint Estimation ◽  
Model Parameters ◽  
Displacement Estimation ◽  
Landslide Stability ◽  
Landslide Displacement Prediction ◽  
Using Data

Abstract. Landslide displacement prediction has great practical engineering significance to landslide stability evaluation and early warning. The evolution of landslide is a complex dynamic process, applying classical prediction method will result in significant error. Data assimilation method offers a new way to merge multi-source data with the model. However, data assimilation is still deficient in the ability to meet the demand of dynamic landslide system. In this paper, simultaneous state-parameter estimation (SSPE) using particle filter-based data assimilation is applied to predict displacement of the landslide. Landslide SSPE assimilation strategy can make use of time-series displacements and hydrological information for the joint estimation of landslide displacement and model parameters, which can improve the performance considerably. We select Xishan Village, Sichuan province, China as experiment site to test SSPE assimilation strategy. Based on the comparison of actual monitoring data with prediction values, results strongly suggest the effectiveness and feasibility of SSPE assimilation strategy in short-term landslide displacement estimation.

A Sensitivity Study of the Porcine Head Subjected to Bump Impact

2016 ◽  
Author(s):  
Kimberly A. Thompson ◽  
Adam C. Sokolow ◽  
Juliana Ivancik ◽  
Timothy G. Zhang ◽  
William H. Mermagen ◽  
...  
Keyword(s):  
Human Brain ◽  
3D Model ◽  
Porcine Model ◽  
Load Transfer ◽  
Numerical Study ◽  
Sensitivity Study ◽  
Complex Problem ◽  
Model Parameters ◽  
Skin Thickness ◽  
The Impact

Understanding load transfer to the human brain is a complex problem that has been a key subject of recent investigations [4–6]. Because the porcine is a gyrencephalic species, having greater structural and functional similarities to the human brain than other lower species outlined in the literature, it is commonly chosen as a surrogate for human brain studies [7]. Consequently, we have chosen to use a porcine model in this work. To understand stress wave transfer to and through the brain, it is important to fully characterize the nature of the impact (i.e. source, location, and speed) as well as the response of the constituent tissues under such impact. We suspect the material and topology of these tissues play an important role in their response. In this paper, we report on a numerical study assessing the sensitivity of model parameters for a 6-month old Gottingen mini-pig model, under bump loading. In this study, 2D models are used for computational simplicity. While a 3D model is more realistic in nature, a 2D representation is still valuable in that it can provide trends on parameter sensitivity that can help steer the development of the 3D model. In this work, we investigate the variation of skull and skin thickness, evaluate material variability of the skull, and consider the effects of nasal cavities on load transfer. Eighty simulations are computed in LS-DYNA and analyzed in MATLAB. The results of this study will provide useful knowledge on the necessary components and parameters of the porcine model and therefore provide more confidence in the analysis. This is an essential first step as we look toward bridging the gap between correlates of injury in animal and human models.

Fluid Tonicity Affects Peritoneal Characteristics Derived by 3-PORE Model

2019 ◽  
Vol 39 (3) ◽  
pp. 243-251 ◽  
Author(s):  
Joanna Stachowska-Pietka ◽  
Jan Poleszczuk ◽  
Josep Teixido-Planas ◽  
Josep Bonet-Sol ◽  
Maria I. Troya-Saborido ◽  
...  
Keyword(s):  
Model Fitting ◽  
Hydraulic Conductance ◽  
Membrane Properties ◽  
Patient Specific ◽  
Model Parameters ◽  
Peritoneal Membrane ◽  
Substantial Impact ◽  
Pore Model ◽  
Using Data ◽  
The Impact

Background It is typically assumed that within short time-frames, patient-specific peritoneal membrane characteristics are constant and do not depend on the initial fluid tonicity and dwell duration. The aim of this study was to check whether this assumption holds when membrane properties are estimated using the 3-pore model (3PM). Methods Thirty-two stable peritoneal dialysis (PD) patients underwent 3 8-hour peritoneal equilibration tests (PETs) with different glucose-based solutions (1.36%, 2.27%, and 3.86%). Temporary drainage was performed at 1 and 4 hours. Glucose, urea, creatinine, sodium, and phosphate concentrations were measured in dialysate and blood samples. Three-pore model parameters were estimated for each patient and each 8-hour PET separately. In addition, model parameters were estimated using data truncated to the initial 4 hours of peritoneal dwell. Results In all cases, model-estimated parameter values were within previously reported ranges. The peritoneal absorption (PA) and diffusive permeability for all solutes except sodium increased with fluid tonicity, with about 18% increase when switching from glucose 2.27% to 3.86%. Glucose peritoneal reflection coefficient and osmotic conductance (OsmCond), and fraction of hydraulic conductance for ultrasmall pores decreased with fluid tonicity (over 40% when switching from glucose 1.36%). Model fitting to the truncated 4-hour data resulted in little change in the parameters, except for PA, peritoneal hydraulic conductance, and OsmCond, for which higher values for the 4-hour dwell were found. Conclusion Initial fluid tonicity has a substantial impact on the 3PM-estimated characteristics of the peritoneal membrane, whereas the impact of dwell duration was relatively small and possibly influenced by the change in the patient's activity.

scholarly journals Spatial and Seasonal Variations and Inter-Relationship in Fitted Model Parameters for Rainfall Totals across Australia at Various Timescales

Climate ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 4 ◽  
Author(s):  
Md Masud Hasan ◽  
Barry F. W. Croke ◽  
Fazlul Karim
Keyword(s):  
Probabilistic Models ◽  
Dispersion Model ◽  
Synthetic Data ◽  
Daily Rainfall ◽  
Seasonal Rainfall ◽  
Model Parameters ◽  
Exponential Dispersion Model ◽  
Gamma Distributions ◽  
Using Data ◽  
Combined Data

Probabilistic models are useful tools in understanding rainfall characteristics, generating synthetic data and predicting future events. This study describes the results from an analysis on comparing the probabilistic nature of daily, monthly and seasonal rainfall totals using data from 1327 rainfall stations across Australia. The main objective of this research is to develop a relationship between parameters obtained from models fitted to daily, monthly and seasonal rainfall totals. The study also examined the possibility of estimating the parameters for daily data using fitted parameters to monthly rainfall. Three distributions within the Exponential Dispersion Model (EDM) family (Normal, Gamma and Poisson-Gamma) were found to be optimal for modelling the daily, monthly and seasonal rainfall total. Within the EDM family, Poisson-Gamma distributions were found optimal in most cases, whereas the normal distribution was rarely optimal except for the stations from the wet region. Results showed large differences between regional and seasonal ϕ-index values (dispersion parameter), indicating the necessity of fitting separate models for each season. However, strong correlations were found between the parameters of combined data and those derived from individual seasons (0.70–0.81). This indicates the possibility of estimating parameters of individual season from the parameters of combined data. Such relationship has also been noticed for the parameters obtained through monthly and daily models. Findings of this research could be useful in understanding the probabilistic features of daily, monthly and seasonal rainfall and generating daily rainfall from monthly data for rainfall stations elsewhere.

Sign in / Sign up

Export Citation Format

Share Document