SEARCH · Engineering Papers
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.
Farnsworth Unit (FWU) CO2EOR Eclipse compositional model: Hydrostratigraphic Region 1 model uses the HS1 relative permeability curves assigned heterogeneously by hydrostratigraphic unit. The model with capillary pressure applies the HS1 curves heterogeneously by hydrostratigraphic unit.
Farnsworth Unit (FWU) CO2EOR Eclipse compositional model: Hydrostratigraphic Region 3 model uses the HS3 relative permeability curves assigned heterogeneously by hydrostratigraphic unit. The model with capillary pressure applies the HS3 curves heterogeneously by hydrostratigraphic unit.
Coronal plasma in active regions is typically measured to be at temperatures near ~1-3 MK. Is the majority of the coronal plasma in hydrostatic equilibrium, maintained at these temperatures through a form of quasi-steady heating, or is this simply a measure of the average temperature of widely varying, impulsively heated coronal plasma? Addressing this question is complicated by the fact that the corona is optically thin: many thousands of flux tubes which are heated completely independently are contributing to the total emission along a given line of sight. There is a large body of work focused on the heating of isolated features - coronal loops - which are impulsively heated, however it is the diffuse emission between loops which often comprises the majority of active region emission. Therefore in this study we move beyond isolated features and analyze all of the emission in an entire active region from all contributing flux tubes. We investigate light curves systematically using SDO/AIA observations. We also model the active region corona as a line-of-sight integration of many thousands of completely independently heated flux tubes. The emission from these flux tubes may be time dependent, quasi-steady, or a mix of both, depending on the cadence of heat release. We demonstrate that despite the superposition of randomly heated flux tubes, different distributions of nanoflare cadences produce distinct signatures in light curves observed with multi-wavelength and high time cadence data, such as those from SDO/AIA. We conclude that the majority of the active region plasma is not maintained in hydrostatic equilibrium, rather it is undergoing dynamic heating and cooling cycles. The observed emission is consistent with heating through impulsive nanoflares, whose energy is a function of location within the active region.
Regional hydrologic planning models built upon remote sensing capabilities and suited for ungaged watersheds are developed. The effectiveness of such models is determined along with which parameters impact most the minimization of errors associated with the prediction of peak flow events (floods). Emphasis is placed on peak flood prediction because of its significance to users for the purpose of planning, sizing, and designing waterworks.
The structural mapping of tectonic landforms on Mars has provided a great deal of information regarding the planet's tectonic history. The present paper has the objective to test models of regional and global fracturing by evaluating the spatial distribution and orientation of the ancient heavily cratered terrain (HCT) structural landforms. Attention is given to background information concerning earlier studies, landform selection and analysis, rose diagrams, tests for Tharsis generation, and a calculation of thermal stress in the early Martian lithosphere. The contribution of classical Tharsis-centered tectonism to the production of HCT structural landforms was found to be very small. Few structural landforms investigated are either perpendicular to calculated principal stress trajectories or radial to Tharsis.
Models are constructed for three stars in order to determine their properties and elemental abundances through comparisons of model predictions and observations. By comparing predicted line fluxes with those observed, it is noted that oxygen is apparently enhanced by a factor of 2 in W3A, and of 4 in G75.84 + 0.40A and G29.9 - 0.0. The first two cases are based on the premise that the O(++)-emitting regions are as clumped as those of S(++). The H II regions all need more than one main sequence star or one unusually large star to provide the observed radio luminosity.
The calculation of engineering flows undergoing laminar-turbulent transition presents special problems. Mean-flow quantities obey neither the fully laminar nor the fully turbulent correlations. In addition, local maxima in skin friction, wall temperature, and heat transfer often occur near the end of the transition region. Traditionally, modeling this region has been important for the design of turbine blades, where the transition region is long in relation to the chord length of the blade. More recently, the need for better transition-region models has been recognized by designers of hypersonic vehicles where the high Mach number, the low Reynolds number, and the low-disturbance flight environment emphasize the importance of the transition region. Needless to say, a model that might work well for the transitional flows typically found in gas turbines will not necessarily work well for the external surface of a hypersonic vehicle. In Section 2 of this report, some of the important flow features that control the transition region will be discussed. In Section 3, different approaches to the modeling problem will be summarized and cataloged. Fully turbulent flow models will be discussed in detail in Section 4; models specifically designed for transitional flow, in Section 5; and the evaluation of models, in Section 6.
The IUE observations of the RS CVn binary system II Pegasi obtained during the period 1981 October 1-7 were used to derive the emission measure distributions and to calculate transmission region models of the quiescent and plage (active) regions of II Peg. Active region models were calculated assuming area coverages of 10%, 6%, 3% and 1% of the visible hemisphere. These models are used to provide lower limits to the electron pressure in the quiescent and plage regions, which are compared with the available density diagnostics. The amount of mechanical energy deposition required to account for the observed radiative losses is very large.
Model representation of carbon uptake and storage is essential for accurate projection of the response of the arctic-boreal zone to a rapidly changing climate. Land model estimates of LAI and aboveground biomass that can have a marked influence on model projections of carbon uptake and storage vary substantially in the arctic and boreal zone, making it challenging to correctly evaluate model estimates of Gross Primary Productivity (GPP). To understand and correct bias of LAI and aboveground biomass in the Community Land Model (CLM), we assimilated the 8-day Moderate Resolution Imaging Spectroradiometer (MODIS) LAI observation and a machine learning product of annual aboveground biomass into CLM using an Ensemble Adjustment Kalman Filter (EAKF) in an experimental region including Alaska and Western Canada. Assimilating LAI and aboveground biomass reduced these model estimates by 58% and 72%, respectively. The change of aboveground biomass was consistent with independent estimates of canopy top height at both regional and site levels. The International Land Model Benchmarking system assessment showed that data assimilation significantly improved CLM's performance in simulating the carbon and hydrological cycles, as well as in representing the functional relationships between LAI and other variables. Here, to further reduce the remaining bias in GPP after LAI bias correction, we re-parameterized CLM to account for low temperature suppression of photosynthesis. The LAI bias corrected model that included the new parameterization showed the best agreement with model benchmarks. Combining data assimilation with model parameterization provides a useful framework to assess photosynthetic processes in LSMs.
Model representation of carbon uptake and storage is essential for accurate projection of the response of the arctic‐boreal zone to a rapidly changing climate. Land model estimates of LAI and aboveground biomass that can have a marked influence on model projections of carbon uptake and storage vary substantially in the arctic and boreal zone, making it challenging to correctly evaluate model estimates of Gross Primary Productivity (GPP). To understand and correct bias of LAI and aboveground biomass in the Community Land Model (CLM), we assimilated the 8‐day Moderate Resolution Imaging Spectroradiometer (MODIS) LAI observation and a machine learning product of annual aboveground biomass into CLM using an Ensemble Adjustment Kalman Filter (EAKF) in an experimental region including Alaska and Western Canada. Assimilating LAI and aboveground biomass reduced these model estimates by 58% and 72%, respectively. The change of aboveground biomass was consistent with independent estimates of canopy top height at both regional and site levels. The International Land Model Benchmarking system assessment showed that data assimilation significantly improved CLM's performance in simulating the carbon and hydrological cycles, as well as in representing the functional relationships between LAI and other variables. To further reduce the remaining bias in GPP after LAI bias correction, we re‐parameterized CLM to account for low temperature suppression of photosynthesis. The LAI bias corrected model that included the new parameterization showed the best agreement with model benchmarks. Combining data assimilation with model parameterization provides a useful framework to assess photosynthetic processes in LSMs.
Abstract. The Energy Exascale Earth System Model (E3SM) Land Model (ELM) is a state-of-the-art land surface model that simulates the intricate interactions between the terrestrial land surface and other components of the Earth system. Originating from the Community Land Model (CLM) version 4.5, ELM has been under active development, with added new features and functionality, including plant hydraulics, radiation–topography interaction, subsurface multiphase flow, and more explicit land use and management practices. This study integrates ELM v2.1 with the Weather Research and Forecasting (WRF; WRF-ELM) model through a modified Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) framework, enabling affordable high-resolution regional modeling by leveraging ELM's innovative features alongside WRF's diverse atmospheric parameterization options. This framework includes a top-level driver for variable communication between WRF and ELM and Earth System Modeling Framework (ESMF) caps for the WRF atmospheric component and ELM workflow control, encompassing initialization, execution, and finalization. Importantly, this LILAC–ESMF framework demonstrates a more modular approach compared to previous coupling efforts between WRF and land surface models. It maintains the integrity of ELM's source code structure and facilitates the transfer of future developments in ELM to WRF-ELM. To test the ability of the coupled model to capture land–atmosphere interactions over regions with a variety of land uses and land covers, we conducted high-resolution (4 km) WRF-ELM ensemble simulations over the Great Lakes region (GLR) in the summer of 2018 and systematically compared the results against observations, reanalysis data, and WRF-CTSM (WRF coupled with the Community Terrestrial Systems Model). In general, the coupled WRF-ELM model has reasonably captured the spatial distribution of surface state variables and fluxes across the GLR, particularly over the natural vegetation areas. The evaluation results provide a baseline reference for further improvements in ELM in the regional application of high-resolution weather and climate predictions. Our work serves as an example to the model development community for expanding an advanced land surface model's capability to represent fully-coupled land–atmosphere interactions at fine spatial scales. The development and release of WRF-ELM marks a significant advancement for the ELM user community, providing opportunities for fine-scale regional representation, parameter calibration in coupled mode, and examination of new schemes with atmospheric feedback.
Abstract. Convection-permitting regional climate models (RCMs) have recently become tractable for applications at multi-decadal timescales. These types of models have tremendous utility for water resource studies, but better characterization of precipitation biases is needed, particularly for water-resource-critical mountain regions, where precipitation is highly variable in space, observations are sparse, and the societal water need is great. This study examines 34 years (1987–2020) of RCM precipitation from the Weather Research and Forecasting model (WRF; v3.8.1), using the Climate Forecast System Reanalysis (CFS; CFSv2) initial and lateral boundary conditions and a 1 km × 1 km innermost grid spacing. The RCM is centered over the Upper Colorado River basin, with a focus on the high-elevation, 750 km2 East River watershed (ERW), where a variety of high-impact scientific activities are currently ongoing. Precipitation is compared against point observations (Natural Resources Conservation Service Snow Telemetry or SNOTEL), gridded climate datasets (Newman, Livneh, and PRISM), and Bayesian reconstructions of watershed mean precipitation conditioned on streamflow and high-resolution snow remote-sensing products. We find that the cool-season precipitation percent error between WRF and 23 SNOTEL gauges has a low overall bias (x^ = 0.25 %, s = 13.63 %) and that WRF has a higher percent error during the warm season (x^ = 10.37 %, s = 12.79 %). Warm-season bias manifests as a high number of low-precipitation days, though the low-resolution or SNOTEL gauges limit some of the conclusions that can be drawn. Regional comparisons between WRF precipitation accumulation and three different gridded datasets show differences on the order of ± 20 %, particularly at the highest elevations and in keeping with findings from other studies. We find that WRF agrees slightly better with the Bayesian reconstruction of precipitation in the ERW compared to the gridded precipitation datasets, particularly when changing SNOTEL densities are taken into account. The conclusions are that the RCM reasonably captures orographic precipitation in this region and demonstrates that leveraging additional hydrologic information (streamflow and snow remote-sensing data) improves the ability to characterize biases in RCM precipitation fields. Error characteristics reported in this study are essential for leveraging the RCM model outputs for studies of past and future climates and water resource applications. The methods developed in this study can be applied to other watersheds and model configurations. Hourly 1 km × 1 km precipitation and other meteorological outputs from this dataset are publicly available and suitable for a wide variety of applications.
The Feynman-alpha method is a neutron noise technique that is used to estimate the prompt neutron period of fissile assemblies. The method and quantity are of widespread interest including in applications such as nuclear criticality safety, safeguards and nonproliferation, and stockpile stewardship; the prompt neutron period may also be used to infer the k eff multiplication factor. The Feynman-alpha method is predicated on time-correlated neutron detections that deviate from a Poisson random variable due to multiplication. Traditionally, such measurements are diagnosed with one-region point kinetics, but two-region models are required when the fissile assembly is reflected. This paper presents a derivation of the two-region point kinetics Feynman-alpha equations based on a double integration of the Rossi-alpha equations, develops novel propagation of measurement uncertainty, and validates the theory. Validation is achieved with organic scintillator measurements of weapons-grade plutonium reflected by various amounts of copper to achieve k eff values of 0.83–0.94 and prompt periods of 5–75 ns. The results demonstrate that Feynman-alpha measurements should use the two-region model instead of the one-region model. The simplified one-region model deviates from the validated two-region models by as much as 10% in the estimate of the prompt neutron period, and the two-region model reduces to the one-region model for small amounts of reflector. The Feynman-alpha estimates of the prompt neutron period are compared to those of the Rossi-alpha approach. The comparative results demonstrate that the Feynman-alpha method is more precise than the Rossi-alpha method and more accurate for k eff < 0.92, whereas the Rossi-alpha method is generally more accurate for higher multiplications. Here, the uncertainty propagation developed in this work should be used for all Feynman-alpha measurements and will therein improve fitting accuracy and appropriate precision estimates.
A detailed set of H II region models that use the same physics and self-consistent input have been computed and are used to examine where in parameter space the effects of heavy element opacity is important. The models are briefly described, and tabular data for the input parameters and resulting properties of the models are presented. It is found that the opacities of C, Ne, O, and to a lesser extent N play a vital role over a large region of parameter space, while S and Ar opacities are negligible. The variation of the average electron temperature T(e) of the models with metal abundance, density, and T(eff) is investigated. It is concluded that by far the most important determinator of T(e) is metal abundance; an almost 7000 K difference is expected over the factor of 10 change from up to down abundances.
Research efforts in FY 1990 included studies employing regional scale numerical models as aids in evaluating potential contributions of specific satellite observing systems (current and future) to numerical prediction. One study involves Observing System Simulation Experiments (OSSEs) which mimic operational initialization/forecast cycles but incorporate simulated Advanced Microwave Sounding Unit (AMSU) radiances as input data. The objective of this and related studies is to anticipate the potential value of data from these satellite systems, and develop applications of remotely sensed data for the benefit of short range forecasts. Techniques are also being used that rely on numerical model-based synthetic satellite radiances to interpret the information content of various types of remotely sensed image and sounding products. With this approach, evolution of simulated channel radiance image features can be directly interpreted in terms of the atmospheric dynamical processes depicted by a model. Progress is being made in a study using the internal consistency of a regional prediction model to simplify the assessment of forced diabatic heating and moisture initialization in reducing model spinup times. Techniques for model initialization are being examined, with focus on implications for potential applications of remote microwave observations, including AMSU and Special Sensor Microwave Imager (SSM/I), in shortening model spinup time for regional prediction.
Dynamical downscaling is a crucial process for providing regional climate information for broad uses, using coarser-resolution global models to drive higher-resolution regional climate simulations. The pool of global climate models (GCMs) providing the fields needed for dynamical downscaling has increased from the previous generations of the Coupled Model Intercomparison Project (CMIP). However, with limited computational resources, the need for prioritizing the GCMs for subsequent downscaling studies remains. GCM selection for dynamical downscaling should focus on evaluating processes relevant for providing boundary conditions to the regional models and be inspired by regional uses such as the response of extremes to changes in the boundary conditions. This leads to the need for metrics representing processes of relevance to diverse stakeholders and subregions of a domain. Procedures to account for metric redundancy and the statistical distinguishability of GCM rankings are required. Further, procedures for selecting realizations from ensembles of top-performing GCM simulations can be used to span the range of climate change signals in multiple ways. As a result, distinct weighting of metrics and prioritization of particular realizations may depend on user needs. We provide high-level guidelines for such region-specific evaluations and address how CMIP7 might enable dynamical downscaling of a representative sample of high-quality models across representative shared socioeconomic pathways (SSPs).
Models of circumstellar dust shells around ultracompact (UC) H II regions were constructed that accurately fit the observed IR flux distributions. The models assume spherically symmetric dust shells illuminated by stars whose bolometric luminosity is inferred from the integrated FIR flux densities. Assuming ionization by a single zero age main sequence (ZAMS) star, the relations of Panagia were used to infer the stellar radius and effective temperature for a given luminosity. The grain mixture in the dust shell consists of bare graphite and silicate grains with the optical properties of Draine and Lee and the size distribution of Mathis et al. The computer code of Wolfire et al was used to solve the radiative transfer equations through a spherical dust shell. The model provides monochromatic luminosities, dust temperatures, and opacities through the shell. Aside from the stellar and dust properties, the only other input parameters to the model are the distance to the shell, the form of its density distribution, and its outer radius. Predictions of the model are compared with observations of a typical UC H II region and the run of dust temperature with radius and the optical depth with frequency are discussed.
In 2006 the LWS TR&T Program funded us to develop a strategic capability model of slowly evolving coronal active regions. In this poster we report on the overall design, and status of our new modeling suite. Our design features two coronal field models, a non-linear force free field model and a global 3D MHD code. The suite includes supporting tools and a user friendly GUI which will enable users to query the web for relevant magnetograms, download them, process them to synthesize a sequence of photospheric magnetograms and associated photospheric flow field which can then be applied to drive the coronal model innner boundary, run the coronal models and finally visualize the results.