scholarly journals Simulation of soil liquefaction due to earthquake loading

2019 ◽  
Vol 97 ◽  
pp. 03025 ◽  
Author(s):  
Armen Ter-Martirosyan ◽  
Ahmad Othman
Keyword(s):  
Los Angeles ◽  
Real Data ◽  
Soil Mass ◽  
Soil Liquefaction ◽  
Elastic Behavior ◽  
Main Step ◽  
Soil Behavior ◽  
The Difference ◽  
Strength And Stiffness ◽  
Seismic Impact

Liquefaction is a phenomenon in which the strength and stiffness of a soil are reduced as a result of seismic or other dynamic effects. Liquefaction was the main reason of the huge damages caused by many earthquakes around the world. The modeling of soil behavior is the main step in the process of predicting the soil liquefaction. Currently, a large number of soil models are presented. However, only some of them can simulate this process. One of these models which can be used is model UBC3D-PLM. In this paper, the possibilities of this model are considered by modeling the seismic impact on a building with its different heights on the PLAXIS software package. The real data of Upland earthquake 1990 near Los Angeles city was used. Results of the simulation showed the difference in the behavior of the soil mass under the influence of an earthquake compared with the elastic behavior, as well as the need to use the UBC3D-PLM model to estimate the seismic impact.

scholarly journals SIMULATION OF SOIL LIQUEFACTION DUE TO EARTHQUAKE LOADING USING THE UBC3D-PLM MODEL

2019 ◽  
Vol 7 (3) ◽  
pp. 39-44
Author(s):  
Armen Ter-martirosyan ◽  
Osman Ahmad
Keyword(s):  
Los Angeles ◽  
Process Model ◽  
Soil Mass ◽  
Seismic Effect ◽  
Soil Liquefaction ◽  
Elastic Behavior ◽  
Soil Behavior ◽  
Basic Step ◽  
Seismic Impact ◽  
The Impact

Liquefaction is a phenomenon in which the stiffness and strength of a soil are reduced as a result of seismic effect or other dynamic effects. Liquefaction was the basic reason of the big damages caused by many earthquakes around the world. The basic step in the processes of predicting the soil liquefaction is the modeling of soil behavior. At the present time, numerous soil models are presented. Nevertheless, only some of them can simulate this process. Model UBC3D-PLM is one of these models which can be used. In this paper, the possibilities of this model are considered by modeling on the PLAXIS software package the seismic impact on a building with its different heights. The actual data of Upland earthquake 1990 near Los Angeles city was used. Results of this simulation showed us the difference in the behavior of the soil mass under the impact of an earthquake compared with the elastic behavior, as well as showed us the necessary to use the UBC3D-PLM model to estimate the seismic impact.

scholarly journals Estimating Differential Latent Variable Graphical Models with Applications to Brain Connectivity

Biometrika ◽  
2020 ◽  
Author(s):  
S Na ◽  
M Kolar ◽  
O Koyejo
Keyword(s):  
Graphical Models ◽  
Latent Variable ◽  
Graphical Model ◽  
Brain Connectivity ◽  
Statistical Error ◽  
Real Data ◽  
Low Rank ◽  
Conditional Dependence ◽  
Gradient Descent Algorithm ◽  
The Difference

Abstract Differential graphical models are designed to represent the difference between the conditional dependence structures of two groups, thus are of particular interest for scientific investigation. Motivated by modern applications, this manuscript considers an extended setting where each group is generated by a latent variable Gaussian graphical model. Due to the existence of latent factors, the differential network is decomposed into sparse and low-rank components, both of which are symmetric indefinite matrices. We estimate these two components simultaneously using a two-stage procedure: (i) an initialization stage, which computes a simple, consistent estimator, and (ii) a convergence stage, implemented using a projected alternating gradient descent algorithm applied to a nonconvex objective, initialized using the output of the first stage. We prove that given the initialization, the estimator converges linearly with a nontrivial, minimax optimal statistical error. Experiments on synthetic and real data illustrate that the proposed nonconvex procedure outperforms existing methods.

scholarly journals A Robust Rerank Approach for Feature Selection and Its Application to Pooling-Based GWA Studies

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Jia-Rou Liu ◽  
Po-Hsiu Kuo ◽  
Hung Hung
Keyword(s):  
Characteristic Curve ◽  
Real Data ◽  
Tuning Parameter ◽  
Practical Implementation ◽  
Tuning Parameters ◽  
Genome Wide ◽  
Feature Based ◽  
The Difference ◽  
Gwa Studies ◽  
Selection Of

Large-p-small-ndatasets are commonly encountered in modern biomedical studies. To detect the difference between two groups, conventional methods would fail to apply due to the instability in estimating variances int-test and a high proportion of tied values in AUC (area under the receiver operating characteristic curve) estimates. The significance analysis of microarrays (SAM) may also not be satisfactory, since its performance is sensitive to the tuning parameter, and its selection is not straightforward. In this work, we propose a robust rerank approach to overcome the above-mentioned diffculties. In particular, we obtain a rank-based statistic for each feature based on the concept of “rank-over-variable.” Techniques of “random subset” and “rerank” are then iteratively applied to rank features, and the leading features will be selected for further studies. The proposed re-rank approach is especially applicable for large-p-small-ndatasets. Moreover, it is insensitive to the selection of tuning parameters, which is an appealing property for practical implementation. Simulation studies and real data analysis of pooling-based genome wide association (GWA) studies demonstrate the usefulness of our method.

scholarly journals Soil-gas survey of liquefaction and collapsed caves during the Emilia seismic sequence

2012 ◽  
Vol 55 (4) ◽  
Author(s):  
Alessandra Sciarra ◽  
Barbara Cantucci ◽  
Mauro Buttinelli ◽  
Gianfranco Galli ◽  
Manuela Nazzari ◽  
...  
Keyword(s):  
Soil Liquefaction ◽  
Early Pleistocene ◽  
Seismic Sequence ◽  
Alluvial Deposits ◽  
Epicentral Area ◽  
Emilia Romagna Region ◽  
External Part ◽  
Strength And Stiffness ◽  
Soil Measurements ◽  
Soil Gas Survey

<p>The epicentral area of the Emilia seismic sequence is located in the Emilia-Romagna Region (northern Italy), 45 km from the city of Modena (Figure 1). This area is sited within thrust-related folds of the Ferrara Arc, which represent the most external part of the northern Apennines. This sector is considered as having been active during late Pliocene to early Pleistocene times [Scrocca et al. 2007] and encompasses also the Mirandola and Ferrara seismogenic sources [e.g., Burrato et al. 2003, Boccaletti et al. 2004, Basili et al. 2008]. The main sedimentary infilling of the Po Plain is represented by Pliocene–Pleistocene alluvial deposits (alternating fluvial sands and clays) that overlie a foredeep clastic sequence, with a total average thickness of 2 km to 4 km [e.g., Carminati et al. 2010]. Soon after the mainshock, several liquefaction phenomena coupled to ground fractures were observed in the epicentral area (e.g., San Carlo, Ferrara). Soil liquefaction is a phenomenon in which the strength and stiffness of a soil is reduced by earthquake shaking or other rapid loading. […] Collapsed caves reported in the literature and/or local press [e.g., Febo 1999, Martelli 2002] in the epicentral area were previously investigated by our research group in 2008, with several soil measurements of CO2 and CH4 fluxes. Immediately after the May 20, 2012, mainshock and during the Emilia seismic sequence, the collapsed caves were sampled again to determine any variations in these CO2 and CH4 fluxes. In this survey, newly formed collapsed caves were also found and measured (especially in the northern part of investigated area). […]</p>

scholarly journals Empirical Study of Omnichannel Purchasing Pattern with Real Customer Data from Health and Lifestyle Company

2019 ◽  
Vol 11 (24) ◽  
pp. 7185 ◽  
Author(s):  
Jongsoo Kang ◽  
Marko Majer ◽  
Hyun-Jung Kim
Keyword(s):  
High Performance ◽  
Statistical Significance ◽  
Real Data ◽  
Usage Pattern ◽  
Customer Data ◽  
Customer Group ◽  
Trading Period ◽  
Online Channel ◽  
The Difference ◽  
Offline Channels

This study examines the effect of omnichannel usage pattern on customers’ purchasing amount by determining statistical significance of different purchasing amount occurred for online and offline channel usage pattern with empirical analysis. The data is collected from a health and lifestyle company operated by Major Pharmaceutical company in Korea, which sells health supplement and skincare products through their owned online and offline channels. The channel usage pattern of customers is categorized into four groups: Customer using online channel only, customer using offline channel only, customer first joined membership through online and use both on/offline channels and customers joined membership through offline channel and use both on/offline. Then, the trading period, total number of purchasing, average purchasing amount per transaction and total purchasing amount during trading period among the above four groups were analyzed. The result demonstrated the number of purchasing, average purchasing amount and total purchasing amount for the omnichannel customer groups who cross used on and offline showed statistical significance. However, the difference in purchasing amount between the group of customers who joined online membership and use offline channel and another customer group that joined offline membership and use online channel was not statistically significant. This study overcame the limitation of conventional studies used survey based data, by the application of empirical data from the real customers in on/offline channels, and provides meaningful insights based on empirical real data that group of customers with higher purchasing experience in both on/offline channels shows high performance.

scholarly journals Bayesian Inference for the Difference of Two Proportion Parameters in Over-Reported Two-Sample Binomial Data Using the Doubly Sample

Stats ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 111-120 ◽  
Author(s):  
Dewi Rahardja
Keyword(s):  
Bayesian Inference ◽  
Closed Form ◽  
Bayesian Approach ◽  
Interval Estimation ◽  
Real Data ◽  
Simulation Studies ◽  
Posterior Distributions ◽  
Binomial Data ◽  
The Difference ◽  
Data Subject

We construct a point and interval estimation using a Bayesian approach for the difference of two population proportion parameters based on two independent samples of binomial data subject to one type of misclassification. Specifically, we derive an easy-to-implement closed-form algorithm for drawing from the posterior distributions. For illustration, we applied our algorithm to a real data example. Finally, we conduct simulation studies to demonstrate the efficiency of our algorithm for Bayesian inference.

Continuous Autoregressive Moving Average Models

2021 ◽  
pp. 118-141
Author(s):  
Yakup Ari
Keyword(s):  
Time Series ◽  
Parameter Estimation ◽  
Differential Equations ◽  
Stochastic Differential Equations ◽  
Discrete Time ◽  
Moving Average ◽  
Likelihood Estimation ◽  
Real Data ◽  
Autoregressive Moving Average ◽  
The Difference

The financial time series have a high frequency and the difference between their observations is not regular. Therefore, continuous models can be used instead of discrete-time series models. The purpose of this chapter is to define Lévy-driven continuous autoregressive moving average (CARMA) models and their applications. The CARMA model is an explicit solution to stochastic differential equations, and also, it is analogue to the discrete ARMA models. In order to form a basis for CARMA processes, the structures of discrete-time processes models are examined. Then stochastic differential equations, Lévy processes, compound Poisson processes, and variance gamma processes are defined. Finally, the parameter estimation of CARMA(2,1) is discussed as an example. The most common method for the parameter estimation of the CARMA process is the pseudo maximum likelihood estimation (PMLE) method by mapping the ARMA coefficients to the corresponding estimates of the CARMA coefficients. Furthermore, a simulation study and a real data application are given as examples.

Stratified Ranked Set Sampling With Missing Observations for Estimating the Difference

2022 ◽  
pp. 209-232
Author(s):  
Carlos N. Bouza-Herrera
Keyword(s):  
Random Sampling ◽  
Real Data ◽  
Simple Random Sampling ◽  
Ranked Set Sampling ◽  
Missing Observations ◽  
Seminal Paper ◽  
Sample Error ◽  
The Difference ◽  
Stratified Ranked Set Sampling ◽  
Stratified Model

The authors develop the estimation of the difference of means of a pair of variables X and Y when we deal with missing observations. A seminal paper in this line is due to Bouza and Prabhu-Ajgaonkar when the sample and the subsamples are selected using simple random sampling. In this this chapter, the authors consider the use of ranked set-sampling for estimating the difference when we deal with a stratified population. The sample error is deduced. Numerical comparisons with the classic stratified model are developed using simulated and real data.

Relative Performance of Kobe and Northridge WSMF Buildings

2006 ◽  
Vol 22 (4) ◽  
pp. 1081-1101 ◽  
Author(s):  
Bruce F. Maison ◽  
Kazuhiko Kasai ◽  
Yoji Ooki
Keyword(s):  
Los Angeles ◽  
The United States ◽  
Office Building ◽  
Superior Performance ◽  
Moment Frame ◽  
Moment Connections ◽  
Steel Moment Frame ◽  
Welded Steel ◽  
The Difference ◽  
Seismic Behaviors

Seismic behaviors of a five-story welded steel moment-frame (WSMF) office building in Kobe, Japan, and a six-story WSMF office building in Northridge, California, are compared. Both experienced earthquake damage (1995 Kobe and 1994 Northridge earthquakes, respectively). Computer models of the buildings are formulated, having the ability to simulate damage in terms of fractured moment connections. Analyses are conducted to assess building response during the earthquakes. The calibrated models are then analyzed using a suite of earthquake records to compare building performance under consistent demands. The Kobe building is found to be more rugged than the Northridge building. Analysis suggests it would experience much less damage than the Northridge building from shaking equivalent to 2,500-year earthquake for a generic Los Angeles site. Superior performance of the Kobe building is attributed to its relatively greater stiffness and strength. The results provide insight into the difference in seismic fragility expected for this class of mid-rise WSMF buildings in Japan and the United States.

scholarly journals FACTORS INFLUENCING REINFORCEMENT OF NR AND EPDM RUBBERS WITH SHORT ARAMID FIBERS

2011 ◽  
Vol 84 (2) ◽  
pp. 187-199 ◽  
Author(s):  
M. Shirazi ◽  
J. W. M. Noordermeer
Keyword(s):  
Low Cost ◽  
High Strength ◽  
Short Fiber ◽  
Elastic Behavior ◽  
Aramid Fibers ◽  
Resorcinol Formaldehyde ◽  
Fiber Coating ◽  
Dog Bone ◽  
Strength And Stiffness ◽  
Microscopy Techniques

Abstract Among short fiber reinforced composites, those with rubbery matrices have gained great importance due to the advantages they have in processing and low cost, coupled with high strength. These composites combine the elastic behavior of rubbers with strength and stiffness of fibers. Aramid fibers have been chosen because of their significantly higher modulus and strength, compared to other commercial fibers. Compounds based on NR and EPDM are prepared. Short aramid fibers with different kinds of surface treatments, standard finish, and resorcinol formaldehyde latex (RFL)-coating result in different rubber–fiber interfaces. The reinforcing effect of these short aramid fibers is characterized by mechanical and viscoelastic experiments, and by studying the fracture surfaces with electron microscopy techniques. Related to the fiber coating and rubber curing system, sulfur- or peroxide-based, different reinforcement mechanisms are observed, where the combination of peroxide-cured EPDM with RFL-treated fibers is the only case showing clear signs of chemical adhesion. In all other combinations there are only indications of mechanical interactions of the fibers with the rubber matrices, due to bending/buckling of fibers, dog-bone shaped fiber ends, and surface roughness due to the RFL-coating.

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