An NGA Empirical Model for Estimating the Horizontal Spectral Values Generated by Shallow Crustal Earthquakes

2008 ◽  
Vol 24 (1) ◽  
pp. 217-242 ◽  
Author(s):  
I. M. Idriss
Keyword(s):  
Empirical Model ◽  
Standard Error ◽  
Strike Slip ◽  
Model Parameters ◽  
Ground Acceleration ◽  
Site Specific ◽  
Crustal Earthquakes ◽  
Average Shear ◽  
Error Terms ◽  
New Generation

An empirical model for estimating the horizontal pseudo absolute spectral accelerations (PSA) generated by shallow crustal earthquakes is presented in this paper. The model was selected to be simple and the model parameters were estimated using the recordings gathered as part of the New Generation Attenuation (NGA) project. These parameters are presented for sites with an average shear wave velocity in the upper 30 m, VS30>900 m/s, and for sites with 450 m/s≤ VS30≤900 m/s. Site-specific dynamic response calculations are recommended for estimating spectral ordinates for sites with VS30≤180 m/s. Parameters for sites with 180 m/s< VS30<450 m/s are not included in this paper. The median values of peak horizontal ground acceleration (PGA) and PSA for short periods are on the order of 15% to 20% lower for strike slip events and 30% to 40% lower for reverse events than those calculated using pre-NGA relationships. The differences decrease significantly at longer periods. The minimum values of the standard error terms (for moment magnitude, M≥7.5) are about 15% to 30% larger and the maximum values of the standard error terms (for M≤5) are about 2% to 12% larger than the pre-NGA values.

An NGA-West2 Empirical Model for Estimating the Horizontal Spectral Values Generated by Shallow Crustal Earthquakes

2014 ◽  
Vol 30 (3) ◽  
pp. 1155-1177 ◽  
Author(s):  
I. M. Idriss
Keyword(s):  
Empirical Model ◽  
Site Response ◽  
Earthquake Ground Motion ◽  
Model Parameters ◽  
Motion Data ◽  
Crustal Earthquakes ◽  
Nonlinear Site Response ◽  
Average Shear ◽  
Recorded Data ◽  
A Site

An empirical model for estimating the horizontal pseudo-absolute spectral accelerations (PSA) generated by shallow crustal earthquakes was published in 2008 using the recorded earthquake ground motion data collected and documented as part of the original Next Generation Attenuation (NGA) project. A significant number of additional recordings were collected over the past three years, and the 2008 model has been revised using the new data and is presented in this paper. The model was again selected to be simple, and the model parameters were estimated using the expanded database. The revised model incorporates V S30 as an independent variable because, with the expanded database, it was found that V S30 was required to be included as an independent parameter to allow for a reasonably unbiased fit to the recorded data. It is noted that V S30 is not being used to account for nonlinear site response, but strictly to allow for a better fit to the data. These parameters are presented for sites with an average shear wave velocity in the upper 30 m, V S30, for sites with V S30 ≥ 450 m/s. Parameters for sites with V S30 < 450 m/s are not included in this paper. For a site with V S30 = 450 m/s, there is an overall increase in PGA averaging about 50% over a distance of about 100 km using the 2013 model in comparison to the 2008 model. On the other hand, for a site with V S30 = 900 m/s, there is an overall decrease of about 10% using the 2013 model in comparison to the 2008 model.

Updated PGA, PGV, and Spectral Acceleration Attenuation Relations for Iran

2012 ◽  
Vol 28 (1) ◽  
pp. 257-276 ◽  
Author(s):  
Hamid Saffari ◽  
Yasuko Kuwata ◽  
Shiro Takada ◽  
Abbas Mahdavian
Keyword(s):  
Response Spectra ◽  
Peak Ground Velocity ◽  
Model Parameters ◽  
Ground Acceleration ◽  
Attenuation Relations ◽  
Data Set ◽  
Site Class ◽  
Source Regions ◽  
Average Shear ◽  
Fault Mechanism

We have developed updated attenuation relations for peak ground acceleration (PGA), peak ground velocity (PGV), and acceleration response spectra with 5% damping on the basis of the data (78 earthquakes and 351 records) pertaining to strong ground motion in Iran. Moment magnitude, distance, fault mechanism, site class, and zone were the model parameters considered. A term for the saturation of the acceleration amplitude was also used in the model in order to improve the estimations in near-source regions. A nonlinear regression analysis was performed to obtain the coefficients. A comparison between the data set used in the current study for Iran and two next generation attenuation (NGA) models showed good correlation between our model and the Campbell-Bozorgnia NGA model. The model described is applicable for moment magnitudes from 5.0 to 7.3, distances from 15 to 135 km, and site classes with an average shear-wave velocity at a subsurface depth of 30 m (AVS30) of more than 175 m/s.

scholarly journals Accommodating Taste and Scale Heterogeneity for Front-Seat Passenger’ Choice of Seat Belt Usage

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 460 ◽  
Author(s):  
Mahdi Rezapour ◽  
Khaled Ksaibati
Keyword(s):  
Mixed Model ◽  
Seat Belt ◽  
Model Fit ◽  
Model Parameters ◽  
Extended Model ◽  
Random Parameters ◽  
Front Seat ◽  
Scale Heterogeneity ◽  
Error Terms ◽  
The Cost

There is growing interest in implementation of the mixed model to account for heterogeneity across population observations. However, it has been argued that the assumption of independent and identically distributed (i.i.d) error terms might not be realistic, and for some observations the scale of the error is greater than others. Consequently, that might result in the error terms’ scale to be varied across those observations. As the standard mixed model could not account for the aforementioned attribute of the observations, extended model, allowing for scale heterogeneity, has been proposed to relax the equal error terms across observations. Thus, in this study we extended the mixed model to the model with heterogeneity in scale, or generalized multinomial logit model (GMNL), to see if accounting for the scale heterogeneity, by adding more flexibility to the distribution, would result in an improvement in the model fit. The study used the choice data related to wearing seat belt across front-seat passengers in Wyoming, with all attributes being individual-specific. The results highlighted that although the effect of the scale parameter was significant, the scale effect was trivial, and accounting for the effect at the cost of added parameters would result in a loss of model fit compared with the standard mixed model. Besides considering the standard mixed and the GMNL, the models with correlated random parameters were considered. The results highlighted that despite having significant correlation across the majority of the random parameters, the goodness of fits favors more parsimonious models with no correlation. The results of this study are specific to the dataset used in this study, and due to the possible fact that the heterogeneity in observations related to the front-seat passengers seat belt use might not be extreme, and do not require extra layer to account for the scale heterogeneity, or accounting for the scale heterogeneity at the cost of added parameters might not be required. Extensive discussion has been made in the content of this paper about the model parameters’ estimations and the mathematical formulation of the methods.

Ground-Motion Prediction Model Based on Neural Networks to Extract Site Properties from Observational Records

2021 ◽  
Author(s):  
Tomohisa Okazaki ◽  
Nobuyuki Morikawa ◽  
Asako Iwaki ◽  
Hiroyuki Fujiwara ◽  
Tomoharu Iwata ◽  
...  
Keyword(s):  
Ground Motion ◽  
Ground Acceleration ◽  
Site Specific ◽  
Motion Data ◽  
Motion Models ◽  
Proposed Model ◽  
Single Station ◽  
Input Variables ◽  
Ground Condition ◽  
Ground Motion Models

ABSTRACT Choosing the method for inputting site conditions is critical in reducing the uncertainty of empirical ground-motion models (GMMs). We apply a neural network (NN) to construct a GMM of peak ground acceleration that extracts site properties from ground-motion data instead of referring to ground condition variables given for each site. A key structure of the model is one-hot representations of the site ID, that is, specifying the collection site of each ground-motion record by preparing input variables corresponding to all observation sites. This representation makes the best use of the flexibility of NN to obtain site-specific properties while avoiding overfitting at sites where a small number of strong motions have been recorded. The proposed model exhibits accurate and robust estimations among several compared models in different aspects, including data-poor sites and strong motions from large earthquakes. This model is expected to derive a single-station sigma that evaluates the residual uncertainty under the specification of estimation sites. The proposed NN structure of one-hot representations would serve as a standard ingredient for constructing site-specific GMMs in general regions.

Smart Mesoporous Nanomaterials With Improved Therapeutic Applications

2018 ◽  
pp. 431-447 ◽  
Author(s):  
Sandhya Sanand ◽  
Anshika Tyagi ◽  
Sandeep Kumar ◽  
Gautam Kaul
Keyword(s):  
Drug Delivery ◽  
Mesoporous Silica Nanoparticles ◽  
Surface Modifications ◽  
Chemotherapeutic Agents ◽  
Point Of View ◽  
Site Specific ◽  
Comprehensive Review ◽  
Post Synthesis ◽  
New Generation ◽  
Toxic Drugs

Nanomaterials have revolutionized the drug delivery and therapeutic industry due to their unique physical characteristics, which render them extremely manipulative at nano-scale. One such category of nanomaterials is mesoporous silica nanoparticles. Due to their small size and rigid honeycomb-like structure, they are highly conducive for packaging of drugs, dyes, antibodies, etc. In addition, they show excellent biocompatibility. These new generation nanomaterials can be further functionalized by incorporating surface modifications, thus increasing their acceptability as carriers for drugs and molecules. In this chapter, a brief and comprehensive review covering various aspects of the recent advancements in synthesis of mesoporous nanomaterials and post-synthesis strategies for functionalization has been presented. Further, it also sheds light on how efficiently these smart nano-carriers are involved in transport and site-specific delivery of highly toxic drugs, like chemotherapeutic agents for cancer treatment, and their biocompatibility evaluation from a biosafety point of view.

Attenuation Function Relationship for Far Field Earthquake Considered by Strike Slip Mechanism

2015 ◽  
Vol 754-755 ◽  
pp. 897-901
Author(s):  
Saffuan Wan Ahmad ◽  
Azlan Adnan ◽  
Rozaimi Mohd Noor ◽  
Khairunisa Muthusamy ◽  
Sk Muiz Sk Razak ◽  
...  
Keyword(s):  
Peak Ground Acceleration ◽  
Strike Slip ◽  
Far Field ◽  
Attenuation Relationship ◽  
Ground Acceleration ◽  
Slip Mechanism ◽  
Earthquake Sources ◽  
Peak Ground Accelerations ◽  
Function Relationship ◽  
The Relationship

An attenuation relationship for far field earthquakes considered by strike slip has been developed. The attenuation relationship function was develop using regression analysis. The database consisting of more than 130 peak ground accelerations from seven earthquake sources recorded by Seismology Station in Malaysia have been used to develop the relationship. This study aims to investigate the new relationship attenuation to gain exact peak ground acceleration at the location on site. Based on this study, the location is a structure located at Terengganu seaside.

scholarly journals An Empirical Model for Estimating Soil Thermal Diffusivity from Texture, Bulk Density, and Degree of Saturation

2018 ◽  
Vol 19 (2) ◽  
pp. 445-457 ◽  
Author(s):  
Xiaoting Xie ◽  
Yili Lu ◽  
Tusheng Ren ◽  
Robert Horton
Keyword(s):  
Thermal Diffusivity ◽  
Bulk Density ◽  
Empirical Model ◽  
Soil Texture ◽  
Degree Of Saturation ◽  
Model Parameters ◽  
Near Surface ◽  
New Model ◽  
Soil Thermal Diffusivity ◽  
Mean Square Errors

Abstract Soil thermal diffusivity κ is an essential parameter for studying surface and subsurface heat transfer and temperature changes. It is well understood that κ mainly varies with soil texture, water content θ, and bulk density ρb, but few models are available to accurately quantify the relationship. In this study, an empirical model is developed for estimating κ from soil particle size distribution, ρb, and degree of water saturation Sr. The model parameters are determined by fitting the proposed equations to heat-pulse κ data for eight soils covering wide ranges of texture, ρb, and Sr. Independent evaluations with published κ data show that the new model describes the κ(Sr) relationship accurately, with root-mean-square errors less than 0.75 × 10−7 m2 s−1. The proposed κ(Sr) model also describes the responses of κ to ρb changes accurately in both laboratory and field conditions. The new model is also used successfully for predicting near-surface soil temperature dynamics using the harmonic method. The results suggest that this model provides useful estimates of κ from Sr, ρb, and soil texture.

scholarly journals PRIME: PSF Reconstruction and Identification for Multiple-source characterization Enhancement – application to Keck NIRC2 imager

2019 ◽  
Vol 487 (4) ◽  
pp. 5450-5462 ◽  
Author(s):  
O Beltramo-Martin ◽  
C M Correia ◽  
S Ragland ◽  
L Jolissaint ◽  
B Neichel ◽  
...  
Keyword(s):  
Adaptive Optics ◽  
Multiple Source ◽  
Parametric Estimation ◽  
Model Parameters ◽  
Source Characterization ◽  
Reconstruction Process ◽  
Spread Function ◽  
Hybrid Concept ◽  
Error Terms ◽  
By Products

ABSTRACT In order to enhance the scientific exploitation of adaptive optics (AO)-assisted observations, we investigate a novel hybrid concept to improve the parametric estimation of point spread function (PSF) called PSF Reconstruction and Identification for Multiple-source characterization Enhancement (PRIME). PRIME uses both focal and pupil-plane measurements to estimate jointly the model parameters related to the atmosphere [$C_n^2(h)$, seeing] and the AO system (e.g. optical gains and residual low-order errors). Photometry and astrometry are provided as by-products. The parametric model in use is flexible enough to be scaled with field location and wavelength, making it a proper choice for optimized on-axis and off-axis data-reduction across the spectrum. Here, we present the methodology and validate PRIME on engineering and binary Keck II telescope NIRC2 images. We also present applications of PSF model parameters retrieval using PRIME: (i) calibrate the PSF model for observations void of stars on the acquired images, i.e. optimize the PSF reconstruction process, (ii) update the AO error breakdown mutually constrained by the telemetry and the images in order to speculate on the origin of the missing error terms and evaluate their magnitude, and (iii) measure photometry and astrometry with an application to the triple system Gl569 images.

A Hybrid Semi-empirical Model for Lean Blow-Out Limit Predictions of Aero-engine Combustors

2014 ◽  
Vol 137 (3) ◽  
Author(s):  
Bin Hu ◽  
Yong Huang ◽  
Jianzhong Xu
Keyword(s):  
Experimental Data ◽  
Numerical Simulation ◽  
Empirical Model ◽  
The Other ◽  
Model Parameters ◽  
Model Parameter ◽  
Other Hand ◽  
Aero Engine ◽  
Semi Empirical

According to the Lefebvre's model and flame volume (FV) concept, an FV model about lean blow-out (LBO) was proposed by authors in early study. On the other hand, due to the model parameter (FV) contained in FV model is obtained based on the experimental data, FV model could only be used in LBO analysis instead of prediction. In view of this, a hybrid FV model is proposed that combines the FV model with numerical simulation in the present study. The model parameters contained in the FV model are all estimated from the simulated nonreacting flows. Comparing with the experimental data for 11 combustors, the maximum and average uncertainties of hybrid FV model are ±16% and ±10%.

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