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At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Intercomparison of Model Simulations of the Impact of 1997/98 El Nino on South American Summer Monsoon

The simulations of climatology and response of the South American summer monsoon (SASM) to the 1997/98 El Nino are investigated using six atmospheric general circulation models. Results show all models simulate the large-scale features of the SASM reasonably well. However, both stationary and seasonal components of the surface pressure are overestimated, resulting in an excessively strong SASM in the model climatology. The low-level northwesterly jet over eastern foothills of the Andes is not well resolved because of the coarse resolution of the models. Large rainfall simulation biases are found in association with the Andes and the Atlantic ITCZ, indicating model problems in handling steep mountains and parameterization of convective processes. The simulation of the 1997/98 El Nino impact on SASM is examined based on an ensemble of ten two-year (September 1996 - August 1998) integration. Results show that most models can simulate the large-scale tropospheric warming response over the tropical central Pacific, including the dynamic response of Rossby wave propagation of the Pacific-South America (PSA) pattern that influences remote areas. Deficiencies are found in simulating the regional impacts over South America. Model simulation fails to capture the southeastward expansion of anomalously warm tropospheric air. As a result, the upper tropospheric anomalous high over the subtropical Andes is less pronounced, and the enhancement of subtropical westerly jet is displaced 5deg-10deg equatorward compared to the observed. Over the Amazon basin, the shift of Walker cell induced by El Nino is not well represented, showing anomalous easterlies in both upper and lower troposphere.

Zhou, Jiayu↗
NASA NTRS1974

Glass production differences for equal-diameter impact craters

A thermodynamic model of meteorite impact is used to investigate the possibility that the creation of two impact craters of the same apparent diameter may have been accompanied by dissimilar shock heating regimes. For small craters, the idea may be concisely represented by the question of which event produces more glass, a large slow meteorite or a small fast one, if the resulting craters are of the same diameter. So that the results may be most apparent, the only parameters varied in this study are meteorite size and impact velocity. Identical basaltic material is assumed for meteorite and target. For impact velocities between 10 and 70 km/sec, an available model determines the radius of a spherical meteorite which would produce a crater diameter of 20 cm.

Rehfuss, D. E.↗
NASA NTRS2017

Impact of Archeomagnetic Field Model Data on Modern Era Geomagnetic Forecasts

A series of geomagnetic data assimilation experiments have been carried out to demonstrate the impact of assimilating archeomagnetic data via the CALS3k.4 geomagnetic field model from the period between 10 and 1590 CE. The assimilation continues with the gufm1 model from 1590 to 1990 and CM4 model from 1990 to 2000 as observations, and comparisons between these models and the geomagnetic forecasts are used to determine an optimal maximum degree for the archeomagnetic observations, and to independently estimate errors for these observations. These are compared with an assimilation experiment that uses the uncertainties provided with CALS3k.4. Optimal 20 year forecasts in 1990 are found when the Gauss coefficients up to degree 3 are assimilated. In addition we demonstrate how a forecast and observation bias correction scheme could be used to reduce bias in modern era forecasts. Initial experiments show that this approach can reduce modern era forecast biases by as much as 50 percent.

Tangborn, Andrew↗
DOE OSTI2025

Entropy-based feature selection for capturing impacts in Earth system models with abrupt forcing

This paper presents the development of a new entropy-based feature selection method for identifying and quantifying impacts. Here, impacts are defined as statistically significant differences in spatio-temporal fields when comparing datasets with and without an external forcing in an Earth system model. Temporal feature selection is performed by first computing the cross-fuzzy entropy to quantify similarity of patterns between two datasets and then applying changepoint detection to identify regions of statistically constant entropy. The method is used to capture temperate north surface cooling from a 9-member simulation ensemble of the Mt. Pinatubo volcanic eruption, which injected 10 Tg of SO 2 into the stratosphere. The results estimate a mean difference decrease in near surface air temperature of -0.560 K with a 99% confidence interval between -0.864 K and -0.257 K between April and November of 1992, one year following the eruption. A sensitivity analysis with decreasing SO 2 injection revealed that the impact is statistically significant at 5 Tg but not at 3 Tg. Using identified features, a dependency graph model based on a 9-day lag had significantly fewer nodes than a graph based on monthly means. Furthermore, this demonstrates our method’s ability to perform dimension reduction while still uncovering source-to-impact pathways.

Changepoint detection↗
NASA NTRS2005

A Novel Porosity Model for Use in Hydrocode Simulations

Introduction: Numerical modeling of impact cratering has reached a high degree of sophistication; however, the treatment of porous materials still poses a large problem in hydrocode calculations. Porosity plays only a minor role in the formation of large craters on most planetary objects, but impacts on comets are believed to be highly affected by the presence of porosity, which may be as much as 80%. The upcoming Deep Impact Mission (launched January 2005) will provide more detailed data about the composition of a comet (Tempel 1) by shooting a approx.370 kg projectile onto the surface of its nucleus. The numerical simulations of such impact events requires an appropriate model for how pore space in the comet is crushed out during the violent initial stage of the impact event. Most hydro-codes compute the pressure explicitly using an "equation of state" (EOS) for each material, which relates changes in density and internal energy to changes in pressure. The added complication introduced by porosity is that changes in a material s density are due to both the closing of pore space (compaction) and compression of the matrix. The amount of resistance to volume change and the amount of irreversible work done during these two processes is very different; it is far easier to compact a porous material sample than to compress a non-porous sample of the same material. As an alternative to existing porosity models, like the Pdot(alpha) model [1], we present a novel approach for dealing with the compaction of porosity in hydrocode calculations.

Wuennemann, K.↗
DOE OSTI2020

Ionization Yield in Silicon for eV-Scale Electron-Recoil Processes

The development of single charge resolving, macroscopic silicon detectors has opened a window into rare processes at the O(eV) scale. In order to reconstruct the energy of a given event, or model the charge signal obtained for a given amount of energy absorbed by the electrons in a detector, an accurate charge yield model is needed. In this paper we review existing measurements of charge yield in Silicon, focusing in particular on the region below 1 keV. We highlight a calibration gap between 12-50 eV (referred to as the "UV-gap") and employ a phenomenological model of impact ionization to explore the likely charge yield in this energy regime. Finally, we explore the impact of variations in this model on a test case, that of dark matter scattering off electrons, to illustrate the scientific impact of uncertainties in charge yield.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2008

The US CLIVAR Working Group on Drought: A Multi-Model Assessment of the Impact of SST Anomalies on Regional Drought

The US CLIVAR working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land-atmosphere feedbacks on regional drought. Specific questions that the runs are designed to address include: What are mechanisms that maintain drought across the seasonal cycle and from one year to the next. What is the role of the land? What is the role of the different ocean basins, including the impact of EL Nino/Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), the Atlantic Multi-decadal Oscillation (AMO), and warming trends in the global oceans? The runs were done with several global atmospheric models including NASA/NSIPP-1, NCEP/GFS, GFDL/AM2, and NCAR CCM3 and CAM3. In addition, runs were done with the NCEP CFS (coupled atmosphere-ocean) model by employing a novel adjustment technique to nudge the coupled model towards the imposed SST forcing patterns. This talk provides an overview of the experiments and some initial results.

Schubert, Siegfried↗
NASA NTRS2017

Cross - Scale Intercomparison of Climate Change Impacts Simulated by Regional and Global Hydrological Models in Eleven Large River Basins

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used.

Hydrological models↗
NASA NTRS1982

Venus nightside ionosphere - A model with KeV electron impact ionization

The impact of keV electrons is proposed as the strongest source of ionization in a full-up Venus nightside ionosphere model for the equatorial midnight region. The electron impacts lead to a peak ion density of 100,000/cu cm, which was observed by the PV-OIMS experiment on several occasions. In addition, the observed altitude profiles of CO2(+), O(+), O2(+), H(+), and H2(+) can be reproduced by the model on condition that the available keV electron flux is approximated by a reasonable extrapolation from fluxes observed at lower energies.

Kumar, S.↗
DOE OSTI2023

Simple and Sophisticated Models of Taylor's Cylinder Impact

We present a study based on the simplest possible models for Taylor’s cylinder impact problem, in addition to examination of using convolutional neural networks (CNNs) to map cylinder profiles to strength calibrations. We find that the approximate treatments of Taylor and Hawkyard compare well with hydrodynamic simulations using an equivalent assumption of constant flow stress. The CNN models prove to be well suited to successfully infer parameterizations of the Preston-Tonks-Wallace model of plastic deformation based on the deformed profile of an impacted cylinder

36 MATERIALS SCIENCE↗
DOE OSTI2023

Simple and sophisticated models of Taylor’s cylinder impact

We present a study based on the simplest possible models for Taylor’s cylinder impact problem, in addition to examina-tion of using convolutional neural networks (CNNs) to map cylinder profiles to strength calibrations. We find that the approximate treatments of Taylor and Hawkyard compare well with hydrodynamic simulations using an equivalent assumption of constant flow stress. The CNN models prove to be well suited to successfully infer parameterizations of the Preston-Tonks-Wallace model of plastic deformation based on the deformed profile of an impacted cylinder.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Development of a Representative Molten Chloride Fast Reactor Model to Assess the Impact of Nuclear Data

The SCALE code system was employed to conduct a preliminary investigation of nuclear data impacts for a fast spectrum molten chloride salt reactor. A computationally effective depletion model that is representative of the reactor system was successfully developed and used to conduct fuel depletion simulations. Development of this model draws from the SLICE method that was developed at Oak Ridge National Laboratory to enable generation of fuel compositions for an advanced reactor core at equilibrium operation. Eigenvalue uncertainty calculations using the ENDF/B-VII.1 nuclear data library were performed for the reactor in the fresh fuel state and an irradiated fuel state. It was determined that the primary driver of eigenvalue uncertainty was the uncertainty in the 235U (n, 𝛾) cross section. Uncertainty calculation results from this study were compared to results available for a different fast system, a sodium-cooled fast reactor, to confirm similarities and identify differences with respect to nuclear data impacts between the two fast advanced reactor systems.

Hirji, Rakim [Georgia Institute of Technology]↗
DOE OSTI2020

Synthetic residential load models for smart city energy management simulations

The ability to control tens of thousands of residential electricity customers in a coordinated manner has the potential to enact system-wide electric load changes, such as reduce congestion and peak demand, among other benefits. To quantify the potential benefits of demand-side management and other power system simulation studies (e.g. home energy management, large-scale residential demand response), synthetic load datasets that accurately characterize the system load are required. This study designs a combined top-down and bottom-up approach for modelling individual residential customers and their individual electric assets, each possessing their own characteristics, using time-varying queueing models. The aggregation of all customer loads created by the queueing models represents a known city-sized load curve to be used in simulation studies. The three presented residential queueing load models use only publicly available data. An open-source Python tool to allow researchers to generate residential load data for their studies is also provided. The simulation results presented consider the ComEd region (utility company from Chicago, IL) and demonstrate the characteristics of the three proposed residential queueing load models, the impact of the choice of model parameters, and scalability performance of the Python tool.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Improvements to CTF Closure Models for Modelling of Two-Phase Flow

This report documents the efforts to improve the CTF prediction of void fraction and two-phase pressure drop by improving two-phase closure models. Previous validation activities have revealed that CTF tends to overpredict void fraction and two-phase pressure drop. In response to this, two approaches were taken to improve CTF’s predictive capabilities. Based on findings that the interfacial drag and subcooled boiling models significantly impact void prediction, alternative closure models for these physical effects were found and implemented into the code. An extensive assessment was performed by using the existing and newly added two-phase experimental data, which showed that void prediction, wall temperature, and two-phase pressure-drop results are improved by using the newly implemented models. A second approach for improving CTF modeling accuracy involved the use of a Bayesian calibration process that uses CTF validation data to optimize selected modeling coefficients and closure model multipliers to achieve a more accurate prediction of experimental results. A similar assessment was performed with calibrated models that improved the void and pressure-drop prediction for test cases that were both included and not included in the calibration dataset. Results of this study will be used to change the models used in CTF to achieve more accurate BWR analyses moving forward. This study also identified opportunities for improving additional closure models and other opportunities to use calibration techniques to improve CTF.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Improved solar cell performance and reliability through advanced defect characterization and growth studies

When this project began, CIGS and ACIGS solar cells were still well below the Shockley-Queisser efficiency limit for their bandgaps. Literature review from showed that JSC and FF were ~90% of the ideal values depending on the growth, but that VOC was only around 75% of the ideal value, which provided a clear objective to improve CIGS VOC. In polycrystalline CIGS, semiconductor defects (traps) have been shown by many studies to have detrimental impacts on device performance. Thus, the goal of this project was to investigate the sources and impacts of defects in CIGS, model their impact on device performance to predict efficiency improvements, and develop effective mitigation strategies to reduce the overall trap concentrations of these traps.

14 SOLAR ENERGY↗
NASA NTRS2004

Trajectory and System Analysis For Outer-Planet Solar-Electric Propulsion Missions

Outer-planet mission and systems analyses are performed using three next generation solar-electric ion thruster models. The impact of variations in thruster model, flight time, launch vehicle, propulsion and power systems characteristics is investigated. All presented trajectories have a single Venus gravity assist and maximize the delivered mass to Saturn or Neptune. The effect of revolution ratio - the ratio of Venusian orbital period to the flight time between launch and flyby dates - is also discussed.

Cupples, Michael↗
DOE OSTI2024

A Methodology for Simulating Supercritical CO2 Heat Transfer Experiments Using Machine Learning Models

To support the growth of supercritical carbon dioxide (sCO2) power cycles in the energy industry, this study seeks to train a machine learning model to mirror experimental data to predict new heat transfer data. To do this experimental data was amassed, one preliminary set comprised of 16 test results, and an expanded version comprised of 38 test results. With the goal of predicting experimental apparatus temperatures and pressures, several iterations of models were tested investigating the impact of model hyper-parameters, data inclusion, and data pre-processing on model performance. A total of 15 variations cumulatively of Gaussian Process Regressors, Gradient Boosting Regressors, and Multi-Layer Perceptrons were trained and validated on the preliminary set, and the best algorithm of each class was re-trained on the expanded set. These were compared based on test/train R^2 , test/train mean absolute error (MAE), and validation MAE, to identify the successfulness of these models. It was shown temperatures could be predicted within just a few degrees, showing the potential of this approach. Future research has been identified with approaches to improve pressure and temperature predictions going forward.

Grabowski, Owen↗