Search NASA⌕ Search

SEARCH · Search NASA

Results for “Spatial Generative Model”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Effects of head modeling errors on the spatial frequency representation of MEG

Abstract Objectives. We aim to investigate the effects of head model inaccuracies on signal and source reconstruction accuracies for various sensor array distances to the head. This allows for the assessment of the importance of head modeling for next-generation magnetoencephalography (MEG) sensors, optically-pumped magnetometers (OPM). Approach. A 1-shell boundary element method (BEM) spherical head model with 642 vertices of radius 9 cm and conductivity of 0.33 S m −1 was defined. The vertices were then randomly perturbed radially up to 2%, 4%, 6%, 8% and 10% of the radius. For each head perturbation case, the forward signal was calculated for dipolar sources located at 2 cm, 4 cm, 6 cm and 8 cm from the origin (center of the sphere), and for a 324 sensor array located at 10 cm to 15 cm from the origin. Equivalent current dipole (ECD) source localization was performed for each of these forward signals. The signal for each perturbed spherical head case was then analyzed in the spatial frequency domain, and the signal and ECD errors were quantified relative to the unperturbed case. Main results. In the noiseless and high signal-to-noise ratio (SNR) case of approximately ≥6 dB, inaccuracies in our spherical BEM head conductor models lead to increased signal and ECD inaccuracies when sensor arrays are placed closer to the head. This is true especially in the case of deep and superficial sources. In the noisy case however, the higher SNR for closer sensor arrays allows for an improved ECD fit and outweighs the effects of head geometry inaccuracies. Significance. OPMs may be placed directly on the head, as opposed to the more commonly used superconducting quantum interference device sensors which must be placed a few centimeters away from the head. OPMs thus allow for signals of higher spatial resolution to be captured, resulting in potentially more accurate source localizations. Our results suggest that an increased emphasis on accurate head modeling for OPMs may be necessary to fully realize its improved source localization potential.

Yeo, Wan-Jin (ORCID:0000000241417123)↗
NASA NTRSDate not supplied

Sub-City-Scale Air Quality Forecasts Combining Models, Satellites, and Surface Measures

Poor air quality is a global major concern, especially in cities with their higher emissions and large numbers of exposed people. Air quality monitoring has traditionally relied on ground-based measurements from a few accurate but expensive regulatory-grade monitors, leading to limited spatial data coverage. More recently, these have been supplemented with other data sources, including satellite observations of pollutants, atmospheric chemistry model simulations, and low-cost monitors allowing for denser spatial data collection at the expense of lower accuracy compared to regulatory-grade monitors. Each of these air quality data sources have their own benefits and drawbacks, and so there is an opportunity to combine these data together while respecting their relative strengths and weaknesses in order to generate a more comprehensive and detailed picture of local air quality. I will present our current work towards such a combination, with a focus on producing higher spatial resolution estimates and near-term forecasts of Nitrogen Dioxide in urban areas in the United States. Our method combines data from the GEOS Composition Forecasting (GEOS-CF) model system, TROPOMI tropospheric NO2 satellite data products, and ground measurements from the EPA regulatory monitoring network using a combination of simple intuitive relationships and machine learning techniques. I will show the performance of this proposed method in several urban areas in the United States, comparing it with baseline approaches using single data sources separately. Overall, we find that combining these disparate datasets together leads to more accurate air quality forecasts in the target areas than is possible using each data source separately.

Air quality↗
NASA NTRS2006

Simulating Visible/Infrared Imager Radiometer Suite Normalized Difference Vegetation Index Data Using Hyperion and MODIS

The success of MODIS (the Moderate Resolution Imaging Spectrometer) in creating unprecedented, timely, high-quality data for vegetation and other studies has created great anticipation for data from VIIRS (the Visible/Infrared Imager Radiometer Suite). VIIRS will be carried onboard the joint NASA/Department of Defense/National Oceanic and Atmospheric Administration NPP (NPOESS (National Polar-orbiting Operational Environmental Satellite System) Preparatory Project). Because the VIIRS instruments will have lower spatial resolution than the current MODIS instruments 400 m versus 250 m at nadir for the channels used to generate Normalized Difference Vegetation Index data, scientists need the answer to this question: how will the change in resolution affect vegetation studies? By using simulated VIIRS measurements, this question may be answered before the VIIRS instruments are deployed in space. Using simulated VIIRS products, the U.S. Department of Agriculture and other operational agencies can then modify their decision support systems appropriately in preparation for receipt of actual VIIRS data. VIIRS simulations and validations will be based on the ART (Application Research Toolbox), an integrated set of algorithms and models developed in MATLAB(Registerd TradeMark) that enables users to perform a suite of simulations and statistical trade studies on remote sensing systems. Specifically, the ART provides the capability to generate simulated multispectral image products, at various scales, from high spatial hyperspectral and/or multispectral image products. The ART uses acquired ( real ) or synthetic datasets, along with sensor specifications, to create simulated datasets. For existing multispectral sensor systems, the simulated data products are used for comparison, verification, and validation of the simulated system s actual products. VIIRS simulations will be performed using Hyperion and MODIS datasets. The hyperspectral and hyperspatial properties of Hyperion data will be used to produce simulated MODIS and VIIRS products. Hyperion-derived MODIS data will be compared with near-coincident MODIS collects to validate both spectral and spatial synthesis, which will ascertain the accuracy of converting from MODIS to VIIRS. MODIS-derived VIIRS data is needed for global coverage and for the generation of time series for regional and global investigations. These types of simulations will have errors associated with aliasing for some scene types. This study will help quantify these errors and will identify cases where high-quality, MODIS-derived VIIRS data will be available.

Ross, Kenton W.↗
NASA NTRS1999

Low-Frequency Oscillations and Transport Processes Induced by Multiscale Transverse Structures in the Polar Wind Outflow: A Three-Dimensional Simulation

Multiscale transverse structures in the magnetic-field-aligned flows have been frequently observed in the auroral region by FAST and Freja satellites. A number of multiscale processes, such as broadband low-frequency oscillations and various cross-field transport effects are well correlated with these structures. To study these effects, we have used our three-dimensional multifluid model with multiscale transverse inhomogeneities in the initial velocity profile. Self-consistent-frequency mode driven by local transverse gradients in the generation of the low field-aligned ion flow and associated transport processes were simulated. Effects of particle interaction with the self-consistent time-dependent three-dimensional wave potential have been modeled using a distribution of test particles. For typical polar wind conditions it has been found that even large-scale (approximately 50 - 100 km) transverse inhomogeneities in the flow can generate low-frequency oscillations that lead to significant flow modifications, cross-field particle diffusion, and other transport effects. It has also been shown that even small-amplitude (approximately 10 - 20%) short-scale (approximately 10 km) modulations of the original large-scale flow profile significantly increases low-frequency mode generation and associated cross-field transport, not only at the local spatial scales imposed by the modulations but also on global scales. Note that this wave-induced cross-field transport is not included in any of the global numerical models of the ionosphere, ionosphere-thermosphere, or ionosphere-polar wind. The simulation results indicate that the wave-induced cross-field transport not only affects the ion outflow rates but also leads to a significant broadening of particle phase-space distribution and transverse particle diffusion.

Ganguli, Supriya B.↗
DOE OSTI2021

Absolute contrast estimation for soft X-ray photon fluctuation spectroscopy using a variational droplet model

Abstract X-ray photon fluctuation spectroscopy using a two-pulse mode at the Linac Coherent Light Source has great potential for the study of quantum fluctuations in materials as it allows for exploration of low-energy physics. However, the complexity of the data analysis and interpretation still prevent recovering real-time results during an experiment, and can even complicate post-analysis processes. This is particularly true for high-spatial resolution applications using CCDs with small pixels, which can decrease the photon mapping accuracy resulting from the large electron cloud generation at the detector. Droplet algorithms endeavor to restore accurate photon maps, but the results can be altered by their hyper-parameters. We present numerical modeling tools through extensive simulations that mimic previous x-ray photon fluctuation spectroscopy experiments. By modification of a fast droplet algorithm, our results demonstrate how to optimize the precise parameters that lift the intrinsic counting degeneracy impeding accuracy in extracting the speckle contrast. These results allow for an absolute determination of the summed contrast from multi-pulse x-ray speckle diffraction, the modus operandi by which the correlation time for spontaneous fluctuations can be measured.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Downscaling atmospheric chemistry simulations with physically consistent deep learning

Abstract. Recent advances in deep convolutional neural network (CNN)-based super resolution can be used to downscale atmospheric chemistry simulations with substantially higher accuracy than conventional downscaling methods. This work both demonstrates the downscaling capabilities of modern CNN-based single image super resolution and video super-resolution schemes and develops modifications to these schemes to ensure they are appropriate for use with physical science data. The CNN-based video super-resolution schemes in particular incur only 39 % to 54 % of the grid-cell-level error of interpolation schemes and generate outputs with extremely realistic small-scale variability based on multiple perceptual quality metrics while performing a large (8×10) increase in resolution in the spatial dimensions. Methods are introduced to strictly enforce physical conservation laws within CNNs, perform large and asymmetric resolution changes between common model grid resolutions, account for non-uniform grid-cell areas, super-resolve lognormally distributed datasets, and leverage additional inputs such as high-resolution climatologies and model state variables. High-resolution chemistry simulations are critical for modeling regional air quality and for understanding future climate, and CNN-based downscaling has the potential to generate these high-resolution simulations and ensembles at a fraction of the computational cost.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Investigating the Causes and Impacts of Convective Aggregation in a High Resolution Atmospheric GCM

Abstract A ∼50 km resolution atmospheric general circulation model (GCM) is used to investigate the impact of radiative interactions on spatial organization of convection, the model's mean state, and extreme precipitation events in the presence of realistic boundary conditions. Mechanism‐denial experiments are performed in which synoptic‐scale feedbacks between radiation and dynamics are suppressed by overwriting the model‐generated atmospheric radiative cooling rates with its monthly varying climatological values. When synoptic‐scale radiative interactions are disabled, the annual mean circulation and precipitation remain almost unchanged, however tropical convection becomes less aggregated, with an increase in cloud fraction and relative humidity in the free troposphere but a decrease in both variables in the boundary layer. Changes in cloud fraction and relative humidity in the boundary layer exhibit more sensitivity to the presence of radiative interactions than variations in the degree of aggregation. The less aggregated state is associated with a decrease in the frequency of extreme precipitation events, coincident with a decrease in the dynamical contribution to the magnitude of extreme precipitation. At regional scales, the spatial contrast in radiative cooling between dry and moist regions diminishes when radiative interactions are suppressed, reducing the upgradient transport of energy, degree of aggregation, and frequency of extreme precipitation events. However, the mean width of the tropical rain belt remains almost unaffected when radiative interactions are disabled. These results offer insights into how radiation‐circulation coupling affects the spatial organization of convection, distributions of clouds and humidity, and weather extremes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Development of Langmuir and Spatially Resolved OES Diagnostics for Arc Jet Shock and Boundary Layer Measurements Relevant to Atmospheric Re-Entry Environments

The second-generation miniature Arc Jet Research Chamber (mARC) ground testing facility at NASA Ames requires physical characterization of its supersonic plasma flow to verify numerical models and material sample testing. Two types of plasma diagnostics will be utilized: Langmuir probes and optical emission spectroscopy (OES). Several single and triple Langmuir probes have been constructed and will be inserted parallel to the flow via a sweep arm to measure post-shock electron temperature and number density along radial profiles at different axial distances. Due to the high heat flux (200-3000 W/cm2) sweep durations are necessarily short (< 0.1 s). Measuring these properties near the probe surface provide characterization of the post-shock environment. This is an important metric for validating coupled CFD-material codes, and will provide insight into longstanding thermocouple anomalies attributed to charging of heatshield surfaces. An OES system has also been assembled to obtain spatially resolved density and temperature for various flow species. The system consists of a convex lens that forms an image of the plasma onto a 16-channel linear fiber array, which will simultaneously capture the spectra from sixteen different locations. The light emission from the plasma is then focused by a spherical mirror into a spectrometer and recorded with a camera. These measurements non-intrusively provide a new spatially resolved flow characterization capability. This will initially be used to resolve issues with shock radiation interference in pyrometer measurements of material surface temperature. The design of each diagnostic and any initial results will be discussed.

Ethan Main-Loam Leong↗
DOE OSTI2023

Learning-based demand-supply-coupled charging station location problem for electric vehicle demand management

We present a learning-based, demand-supply-coupled optimization model for the charging station location problem (CSLP), aiming to integrate the concept of electric vehicle (EV) charging demand management into the planning of charging infrastructures. In stage one, a gradient boosting-based learning model is developed to predict the charging demand of a charging station based on 15 defined features. Next, in stage two, a demand–supply-coupled CSLP model is developed to optimize the total charging usage rates of both existing and newly selected charging stations. We design a gradient-based stochastic spatial search algorithm to solve the proposed model. A case study with 6-year charging event data from Kansas City Missouri is performed. Results show that the proposed method can generate satisfactory charging demand predictions, and can increase charging usage rates by 14%, outperforming two benchmark approaches. Furthermore, the results of this research are poised to guide agencies in identifying optimal locations for new charging stations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

Laser-produced uranium plasma characterization and Stark broadening measurements

This work reports the spatiotemporal diagnostics of uranium species in plasma plumes produced by nanosecond near-infrared laser pulses in a low-pressure environment. Spatially and temporally resolved emission spectroscopy experiments are combined with the modeling of uranium emission for investigating the dynamics of the plume. The Saha-Eggert equation and Boltzmann plots generated from numerous U I transitions are used to infer temperature. This work also reports the measurements of uranium Stark broadening parameters for U I 499.01 nm and U II 500.82 nm transitions. The Stark widths of select U transitions were measured by comparing their linewidths with the broadening of the O I 777.19 nm line. The electron density was found to be of the order of 10 16 cm -3 , while the temperature was found to be in the range of 3000–9000 K. In addition to enhancing the fundamental understanding of high-Z plasmas in reduced-pressure environments, the knowledge of Stark broadening parameters could improve the modeling capabilities and analytical performance of techniques that rely on emission plasma spectroscopy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

iButton and Tinytag snow/ground interface temperature measurements at Teller 27 and Kougarok 64 from 2022-2023, Seward Peninsula, Alaska

Snow/ground interface temperature measurements were collected at the NGEE Arctic Teller Road Site at mile marker 27 (TL_MM27) and at the Kougarok Road Site at mile marker 64 (KG_MM64) on the Seward Peninsula, Alaska. Data were collected between October 1, 2022 to September 18, 2023 using iButton Link DS1921G-F5# Thermochron miniature temperature sensors (https://www.ibuttonlink.com/products/ds1921g) and Tinytag TGP-4017 internal sensors (https://www.micronmeters.com/product/tgp-4017-internal-sensor-40-to-85-c-40-f-to-185-f) deployed across the Kougarok and Teller sites. These sensors are a cost-efficient way to collect snowpack temperatures at a higher spatial resolution than what is normally achieved. iButton data were collected every 4 hours, while Tinytag data were collected every 30 minutes. In total, data were collected from 196 iButtons and 26 Tinytags. This dataset contains four *.csv files of near-ground surface temperatures at various locations throughout each study site and two *.kml files of sensor locations. Data were collected throughout the snow cover season so that snowpack characteristics could be derived using the temperature data. Sensors were placed both inside and outside of vegetation to better capture the spatial variability of snow properties across each domain.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

iButton snow temperature measurements at Teller 27 and Kougarok 64, Seward Peninsula, Alaska, 2019-2020

Snow temperature measurements were collected at the NGEE Arctic Teller Road Site at mile marker 27 (TL_MM27) and at the Kougarok Road Site at mile marker 64 (KG_MM64) on the Seward Peninsula. Data were collected from October 1, 2021 to August 16, 2022 using iButton Link DS1926-F5# Thermochron miniature temperature sensors (https://www.ibuttonlink.com/products/ds1921g) and Tinytag TGP-4017 internal sensors (https://www.micronmeters.com/product/tgp-4017-internal-sensor-40-to-85-c-40-f-to-185-f) deployed across the Kougarok and Teller sites. These sensors are a cost-efficient way to collect snowpack temperatures at a higher spatial resolution than what is normally achieved. iButton data were collected every 4 hours beginning on October 1, 2021. Tinytag data collection began between October 9, 2021 and October 12, 2021 depending on the specific Tinytag and data were collected every 30 minutes. In total, data were collected from 236 iButtons and 30 Tinytags. This dataset contains four *.csv files of near-ground surface temperatures at various locations throughout each study site and four *.shp files of sensor locations. Data were collected throughout the snow cover season so that snowpack characteristics could be derived using the temperature data. Sensors were placed both inside and outside of vegetation to better capture the spatial variability of snow properties across each domain.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

The Visibility of DCT Quantization Noise: Spatial Frequency Summation

Computational models of the ability to detect image compression artifacts facilitate the optimization of compression parameters, such as the JPEG quantization matrix. For simplicity, some models assume that the visibility of artifacts containing different spatial frequency components is determined by the most visible component, that is, no summation over components. Using the type of noise generated by quantization in the Discrete Cosine Transform (DCT) domain, we find a degree of summation between that of probability summation and contrast energy summation.

Peterson, H. A.↗
NASA NTRS1995

Evolution of Coronal MHD Shocks into Interplanetary MHD Shocks

The energetic particle environment near the Sun, particularly during solar activity, is of major importance to the planning of a solar probe. It is not known if intensive fluxes are generated solely in the impulsive phase of flares or whether they are augmented by, or contained within, the coronal mass ejections and shock waves spatially preceding them. A solar wind model with various ejecta is studied.

sun coronal shocks interplanetary shocks solar pro↗
NASA NTRS2005

Consistent Large-Eddy Simulation of a Temporal Mixing Layer Laden with Evaporating Drops: A Posteriori Modelling - Part 2

Large-eddy simulation (LES) is conducted of a three-dimensional temporal mixing layer whose lower stream is initially laden with liquid drops which may evaporate during the simulation. The gas-phase equations are written in an Eulerian frame for two perfect gas species (carrier gas and vapour emanating from the drops), while the liquid-phase equations are written in a Lagrangian frame. The effect of drop evaporation on the gas phase is considered through mass, species, momentum and energy source terms. The drop evolution is modelled using physical drops, or using computational drops to represent the physical drops. Simulations are performed using various LES models previously assessed on a database obtained from direct numerical simulations (DNS). These LES models are for: (i) the subgrid-scale (SGS) fluxes and (ii) the filtered source terms (FSTs) based on computational drops. The LES, which are compared to filtered-and-coarsened (FC) DNS results at the coarser LES grid, are conducted with 64 times fewer grid points than the DNS, and up to 64 times fewer computational than physical drops. It is found that both constant-coefficient and dynamic Smagorinsky SGS-flux models, though numerically stable, are overly dissipative and damp generated small-resolved-scale (SRS) turbulent structures. Although the global growth and mixing predictions of LES using Smagorinsky models are in good agreement with the FC-DNS, the spatial distributions of the drops differ significantly. In contrast, the constant-coefficient scale-similarity model and the dynamic gradient model perform well in predicting most flow features, with the latter model having the advantage of not requiring a priori calibration of the model coefficient. The ability of the dynamic models to determine the model coefficient during LES is found to be essential since the constant-coefficient gradient model, although more accurate than the Smagorinsky model, is not consistently numerically stable despite using DNS-calibrated coefficients. With accurate SGS-flux models, namely scale-similarity and dynamic gradient, the FST model allows up to a 32-fold reduction in computational drops compared to the number of physical drops, without degradation of accuracy; a 64-fold reduction leads to a slight decrease in accuracy.

two-phase flow↗
NASA NTRS2023

Heliocentric Distance and Solar Activity Dependence of Sustained Quasi-radial Interplanetary Magnetic Field Occurrence

Planets close to their stars experience an interplanetary magnetic field (IMF) that is dominantly quasi-radial. Our solar system serves as a laboratory to study how the occurrence of quasi-radial IMF varies away from the star and under different stellar activities. Furthermore, on time and spatial scales relevant to magnetospheric physics, solar wind variability prevails in the form of structures generated both at the Sun and locally in the interplanetary space. The stationary Parker spiral model only approximates the large-scale structure of the IMF. Deviations from the Parker spiral often result in strongly radial magnetic fields that give rise to kinetic foreshock turbulence, which in turn can impact planetary magnetospheres. The relative significance of this type of interaction can be estimated statistically based on the occurrence rate of cases where the IMF is directed along the radial direction, leading to the entire day-side magnetosphere being downstream of the ion foreshock. We use observations covering radial distances from 0.1 to 10 au and more than 2 solar cycles to quantify the prevalence of radial IMFs throughout the heliosphere. Near Earth's orbit, it is found that the occurrence rates of quasi-radial and southward IMF orientations are similar, and that the Pearson correlation coefficient is ${{ \mathcal R }}_{{xy}}\sim -0.7$ calculated between quasi-radial IMF occurrence rate and solar activity. A negative correlation is demonstrated for radial distances extending to at least Mars but not to Saturn.

Brandon L Burkholder↗
DOE OSTI2022

Particle transport in Markov stochastic mixtures with spatial gradients

Markov geometries are a prototype class of stochastic media that are widely used to model complex disordered systems. In a series of recent works, we have shown that spatially homogeneous (but possibly non-isotropic) Poisson tessellations can be conveniently used in order to generate three-dimensional realizations of Markov media and thus characterize the features of particle transport e.g. in fragmented fuel elements following severe nuclear accidents or Rayleigh-Taylor turbulent mixing for inertial confinement fusion. In this paper we show that Poisson tessellations can be extended to take into account the presence of spatial gradients, which commonly occur in real-world applications due to material stratification. For this purpose, we will provide an explicit construction of spatially-non-homogeneous Poisson tessellations, fully characterize their statistical properties, and finally illustrate the behaviour of particle transport in such random media. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Simulation-based characterization of the variability of earthquake risk to buildings in the near-field

Recent advancements in high performance computing platforms and computational workflow for regional-scale simulations are enabling unprecedented modeling of fault-to-structure earthquake processes. Regional simulations resolving ground motions at frequencies relevant to engineered systems are becoming computationally viable and provide a new capability to improve understanding of the geographical distribution and intensity of risk to buildings and critical infrastructure. As computational capabilities advance, it is essential to move beyond illustrative single rupture realizations for scenario earthquake events towards the development of a full suite of rupture realizations that appropriately characterize the range of risk to building systems. The work described in this article investigates the application of a suite of fault rupture realizations with the objective of assessing near-fault, site-specific seismic demand variability for building structures. A representative high-performance regional-scale computational model is utilized to execute ground motion and building response simulations based on 18 kinematic rupture realizations of an M7 strike-slip scenario earthquake. The fault rupture models for the scenario earthquake are created by systematically perturbing the hypocenter location and stochastically generating rupture parameters (slip, rise time, rake angle) to represent a breadth of ground motion intensities resulting from the spatial and temporal variabilities of an earthquake rupture process. The resulting seismic demand variability for three-story (short period) and forty-story (long period) steel moment-resisting frame buildings is characterized in terms of the median and distribution of peak inter-story drift ratio for a range of near-fault sites. The full suite of 18 fault rupture realizations and approximately 280,000 nonlinear dynamic building simulations indicate that the three-story building undergoes higher median seismic demand and significantly greater variability of demand at a given site than the forty-story building, which has important implications for the level of certainty in predicting building performance during an earthquake. The simulations performed provide deeper insight into the relationship between fault rupture parameterization and building response, which is essential information for developing a representative suite of rupture realizations for specific earthquake scenarios.

58 GEOSCIENCES↗