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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.

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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Cloud Adjustments From Large-Scale Smoke–Circulation Interactions Strongly Modulate the Southeastern Atlantic Stratocumulus-to-Cumulus Transition

Smoke from southern Africa blankets the southeastern Atlantic Ocean from June to October, producing strong and competing aerosol radiative effects. Smoke effects on the transition between overcast stratocumulus and scattered cumulus clouds are investigated along a Lagrangian (air-mass-following) trajectory in regional climate and large eddy simulation models. Results are compared with observations from three recent field campaigns that took place in August 2017: ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES), CLouds and Aerosol Radiative Impacts and Forcing: Year 2017 (CLARIFY), and Layered Atlantic Smoke Interactions with Clouds (LASIC). The case study is set up around the joint ORACLES–CLARIFY flight that took place near Ascension Island on 18 August 2017. Smoke sampled upstream on an ORACLES flight on 15 August 2017 likely entrained into the marine boundary layer later sampled during the joint flight. The case is first simulated with the WRF-CAM5 regional climate model in three distinct setups: (1) FireOn, in which smoke emissions and any resulting smoke–cloud–radiation interactions are included; (2) FireOff, in which no smoke emissions are included; (3) RadOff, in which smoke emissions and their microphysical effects are included but aerosol does not interact directly with radiation. Over the course of the Lagrangian trajectory, differences in free tropospheric thermodynamic properties between FireOn and FireOff are nearly identical to those between FireOn and RadOff, showing that aerosol–radiation interactions are primarily responsible for the free tropospheric effects. These effects are non-intuitive: in addition to the expected heating within the core of the smoke plume, there is also a “banding” effect of cooler temperature (∼1–2 K) and greatly enhanced moisture (>2 g kg−1) at the plume top. This banding effect is caused by a vertical displacement of the former continental boundary layer in the free troposphere in the FireOn simulation resulting from anomalous diabatic heating due to smoke absorption of sunlight that manifests primarily as a few hundred meters per day reduction in large-scale subsidence over the ocean. A large eddy simulation (LES) is then forced with free tropospheric fields taken from the outputs for the WRF-CAM5 FireOn and FireOff runs. Cases are run by selectively perturbing one variable (e.g., aerosol number concentration, temperature, moisture, vertical velocity) at a time to better understand the contributions from different indirect (microphysical), “large-scale” semi-direct (above-cloud thermodynamic and subsidence changes), and “local” semi-direct (below-cloud smoke absorption) effects. Despite a more than 5-fold increase in cloud droplet number concentration when including smoke aerosol concentrations, minimal differences in cloud fraction evolution are simulated by the LES when comparing the base case with a perturbed aerosol case with identical thermodynamic and dynamic forcings. A factor of 2 decrease in background free tropospheric aerosol concentrations from the FireOff simulation shifts the cloud evolution from a classical entrainment-driven “deepening–warming” transition to trade cumulus to a precipitation-driven “drizzle-depletion” transition to open cells, however. The thermodynamic and dynamic changes caused by the WRF-simulated large-scale adjustments to smoke diabatic heating strongly influence cloud evolution in terms of both the rate of deepening (especially for changes in the inversion temperature jump and in subsidence) and in cloud fraction on the final day of the simulation (especially for the moisture “banding” effect). Such large-scale semi-direct effects would not have been possible to simulate using a small-domain LES model alone.

southeast Atlantic Ocean↗
DOE OSTI2023

Influence of Blood Rheology and Turbulence Models in the Numerical Simulation of Aneurysms

An aneurysm is a vascular malformation that can be classified according to its location (cerebral, aortic) or shape (saccular, fusiform, and mycotic). Recently, the study of blood flow interaction with aneurysms has gained attention from physicians and engineers. Shear stresses, oscillatory shear index (OSI), gradient oscillatory number (GON), and residence time have been used as variables to describe the hemodynamics as well as the origin and evolution of aneurysms. However, the causes and hemodynamic conditions that promote their growth are still under debate. The present work presents numerical simulations of three types of aneurysms: two aortic and one cerebral. Simulation results showed that the blood rheology is not relevant for aortic aneurysms. However, for the cerebral aneurysm case, blood rheology could play a relevant role in the hemodynamics. The evaluated turbulence models showed equivalent results in both cases. Lastly, a simulation considering the fluid–structure interaction (FSI) showed that this phenomenon is the dominant factor for aneurysm simulation.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

An atmospheric energy analysis of the impact of satellite lidar winds and TIROS temperatures in global simulations

A study of the effects on forecast accuracy of adding wind-profiler data is conducted. An observing system simulation test is employed that assumes a sufficient concentration of aerosols to provide global wind profiles (a best case scenario). The simulated data for the series of five day forecasts are produced from a twenty day integration utilizing the ECMWF model, which is also employed to produce the verification forecast for the five day period.

Keller, Linda M.↗
NASA NTRS2023

Evaluation of Limiter Functions for Supersonic Applications

Limiters commonly used in the simulations of flows with discontinuities are compared with the new limiter function proposed by Nishikawa using idealized test cases in two dimensions as well as complex three-dimensional problems. The Nishikawa limiter is observed to be consistently the least dissipative in idealized test cases as well as complex practical problems, for both steady and time-dependent problems. In the case of steady simulations, its iterative convergence characteristics are either similar or better than other limiter functions. The nearfield sonic boom signature of a low-boom demonstrator is computed to demonstrate the utility of the Nishikawa limiter function for realistic supersonic aircraft configurations.

Computational fluid dynamics↗
NASA NTRSDate not supplied

Evaluation of Limiter Functions for Supersonic Applications

Limiters commonly used in the simulations of flows with discontinuities are compared with the new limiter function proposed by Nishikawa using idealized test cases in two dimensions as well as complex three-dimensional problems. The Nishikawa limiter is observed to be consistently the least dissipative in idealized test cases as well as complex practical problems, for both steady and time-dependent problems. In the case of steady simulations, its iterative convergence characteristics are either similar or better than other limiter functions. The nearfield sonic boom signature of a low-boom demonstrator is computed to demonstrate the utility of the Nishikawa limiter function for realistic supersonic aircraft configurations.

Computational fluid dynamics↗
NASA NTRS1997

Hierarchical Simulation to Assess Hardware and Software Dependability

This thesis presents a method for conducting hierarchical simulations to assess system hardware and software dependability. The method is intended to model embedded microprocessor systems. A key contribution of the thesis is the idea of using fault dictionaries to propagate fault effects upward from the level of abstraction where a fault model is assumed to the system level where the ultimate impact of the fault is observed. A second important contribution is the analysis of the software behavior under faults as well as the hardware behavior. The simulation method is demonstrated and validated in four case studies analyzing Myrinet, a commercial, high-speed networking system. One key result from the case studies shows that the simulation method predicts the same fault impact 87.5% of the time as is obtained by similar fault injections into a real Myrinet system. Reasons for the remaining discrepancy are examined in the thesis. A second key result shows the reduction in the number of simulations needed due to the fault dictionary method. In one case study, 500 faults were injected at the chip level, but only 255 propagated to the system level. Of these 255 faults, 110 shared identical fault dictionary entries at the system level and so did not need to be resimulated. The necessary number of system-level simulations was therefore reduced from 500 to 145. Finally, the case studies show how the simulation method can be used to improve the dependability of the target system. The simulation analysis was used to add recovery to the target software for the most common fault propagation mechanisms that would cause the software to hang. After the modification, the number of hangs was reduced by 60% for fault injections into the real system.

Ries, Gregory Lawrence↗
NASA NTRS2005

Building the Case for SNAP: Creation of Multi-Band, Simulated Images With Shapelets

Dark energy has simultaneously been the most elusive and most important phenomenon in the shaping of the universe. A case for a proposed space-telescope called SNAP (SuperNova Acceleration Probe) is being built, a crucial component of which is image simulations. One method for this is "Shapelets," developed at Caltech. Shapelets form an orthonormal basis and are uniquely able to represent realistic space images and create new images based on real ones. Previously, simulations were created using the Hubble Deep Field (HDF) as a basis Set in one band. In this project, image simulations are created.using the 4 bands of the Hubble Ultra Deep Field (UDF) as a basis set. This provides a better basis for simulations because (1) the survey is deeper, (2) they have a higher resolution, and (3) this is a step closer to simulating the 9 bands of SNAP. Image simulations are achieved by detecting sources in the UDF, decomposing them into shapelets, tweaking their parameters in realistic ways, and recomposing them into new images. Morphological tests were also run to verify the realism of the simulations. They have a wide variety of uses, including the ability to create weak gravitational lensing simulations.

Ferry, Matthew A.↗
DOE OSTI2022

Predictive Contaminant Transport Simulation with the P2R Model for the Composite Analysis Recharge Sensitivity Case

The Plateau-to-River (P2R) model is a groundwater flow and contaminant fate and transport (F&T) simulation model used to support remedial activities conducted by the Central Plateau Cleanup Company (CPCCo) at the Hanford Site in south-central Washington State. The overall objective of the saturated zone modeling effort is to provide a basis for making informed remedial action decisions based on descriptions of current and expected future contaminant concentrations in groundwater at decision points within and downgradient of the Central Plateau of the Hanford Site. Specifically, the purpose of this environmental calculation file (ECF) is to describe a recharge sensitivity case of the CA base case. The recharge sensitivity case implements a change in the activity contribution from the vadose zone in the A Trenches Area model (for tritium [H-3] and iodine-129 [I-129]), BC Cribs and Trenches model (for I-129 and technetium-99 [Tc-99]), or the Plutonium Uranium Extraction (PUREX) Area model (for H-3 and I-129). All other simulated inventories are identical to the CA base case. The simulation of fate and transport of contaminants reported in this case will support dose predictions as part of the updated Hanford Site CA.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1987

Wind measurements for non-uniform wind fields from spaceborne scatterometers

Radar backscattering coefficient measurements by spaceborne scatterometers are presently simulated for the case of nonuniform wind fields, by means of a detailed numerical integration of the radar equation. The winds thus estimated are then compared with a nominal field which is defined as the average wind vector over the wind cell. The simulation results obtained for the NASA scatterometer are presented for cases of random wind fields whose spectra are consistent with the Seasat scatterometer sea surface wind spectrum. When the nonuniformity is small, system noise dominates the wind error; wind error degradation is therefore small for both perfect and imperfect coregistration cases. When it is relatively large, however, the wind error degradation persistently increases for both perfect and imperfect coregistrations.

Chi, Chong-Yung↗
NASA NTRS2010

Improving Computational Efficiency of Prediction in Model-Based Prognostics Using the Unscented Transform

Model-based prognostics captures system knowledge in the form of physics-based models of components, and how they fail, in order to obtain accurate predictions of end of life (EOL). EOL is predicted based on the estimated current state distribution of a component and expected profiles of future usage. In general, this requires simulations of the component using the underlying models. In this paper, we develop a simulation-based prediction methodology that achieves computational efficiency by performing only the minimal number of simulations needed in order to accurately approximate the mean and variance of the complete EOL distribution. This is performed through the use of the unscented transform, which predicts the means and covariances of a distribution passed through a nonlinear transformation. In this case, the EOL simulation acts as that nonlinear transformation. In this paper, we review the unscented transform, and describe how this concept is applied to efficient EOL prediction. As a case study, we develop a physics-based model of a solenoid valve, and perform simulation experiments to demonstrate improved computational efficiency without sacrificing prediction accuracy.

Daigle, Matthew John↗
DOE OSTI2022

Ocean Energy Sandia TEAMER WEC Simulation Results

Computational fluid simulations for wave energy converters and supporting materials from Ocean Energy's WEC Buoy TEAMER project in collaboration with Sandia National Laboratories. Each file includes images and video of simulation along with the simulation files for the case. The videos and images include air and water simulations of the buoy in 2D and 3D views. Data spreadsheets of the simulation outputs are also included in the files. The data are represented as different cases in which the wave height(Hs) and peak period(Tp) were different.

16 TIDAL AND WAVE POWER↗
NASA NTRS1991

Simulator evaluation of system identification with on-line control law update for the controls and astrophysics experiment in space

A procedure for optimizing the performance of large flexible spacecraft that require active vibration suppression to achieve required performance is presented. The procedure is to conduct on-orbit testing and system identification followed by a control system design. It is applied via simulation to a spacecraft configuration currently being considered for flight test by NASA - the Controls, Astrophysics, and Structures Experiment in Space (CASES). The system simulator is based on a NASTRAN finite element structural model. A finite number of modes is used to represent the structural dynamics. The system simulator also includes models of the electronics, actuators, sensors, the digital controller, and the internal and external disturbances. Nonlinearities caused by quantization are included in the study to examine tolerance of the procedure to modelling errors. Disturbance and sensor noise is modelled as a Gaussian process. For system identification, the system is excited using sinusoidal inputs at the resonant frequencies of the structure using each actuator. Mode shapes, frequencies, and damping ratios are identified from the unforced response sensor data after each excitation. Then, the excitation data is used to identify the actuator influence coefficients. The results of the individual parameter identification analyses are assembled into an aggregate system model. The control design is accomplished based only on the identified model using multi-input/output linear quadratic Gaussian theory. Its performance is evaluated based on time-to-damp as compared with the uncontrolled structure.

Montgomery, Raymond C.↗
DOE OSTI2024

DEVELOPMENT OF PLASMA SIMULATION TOOL FOR THE ACCEL-ERATING CAVITIES

Plasma processing of superconducting radio frequency (SRF) cavities has shown an improvement in accelerating gradient by reducing the radiation due to field emission and multipacting. Plasma processing is a common tech-nique where the free oxygen produced by the plasma breaks down and removes hydrocarbons from surfaces. This increases the work function and reduces the second-ary emission coefficient. The hydrocarbon fragments of H2, CO, CO2, and H2O are removed from the system with the process gas which is flowing through the system. Here, we present COMSOL for the first time to simulate the plasma processing of an SRF cavity. In this work, we use Jefferson Lab's C75 SRF cavities design as our case study. Using simulation, we predict the condition of plasma ignition inside the SRF cavity. The simulation provides information about the optimal rf coupling to the cavity, mode for plasma ignition, choice of gas concen-tration, power, and pressure.

Senevirathne, I.↗
NASA NTRS2005

Cycle-averaged dynamics of a periodically driven, closed-loop circulation model

Time-varying elastance models have been used extensively in the past to simulate the pulsatile nature of cardiovascular waveforms. Frequently, however, one is interested in dynamics that occur over longer time scales, in which case a detailed simulation of each cardiac contraction becomes computationally burdensome. In this paper, we apply circuit-averaging techniques to a periodically driven, closed-loop, three-compartment recirculation model. The resultant cycle-averaged model is linear and time invariant, and greatly reduces the computational burden. It is also amenable to systematic order reduction methods that lead to further efficiencies. Despite its simplicity, the averaged model captures the dynamics relevant to the representation of a range of cardiovascular reflex mechanisms. c2004 Elsevier Ltd. All rights reserved.

Non-NASA Center↗
NASA NTRS2008

Spectrally Resolved Flux Derived from Collocated AIRS and CERES Observations and its Application in Model Validation: Clear-Sky Over the Tropic Oceans - Part I

Spectrally resolved outgoing IR flux, the integrand of the outgoing longwave radiation (OLR), has its unique value in evaluating model simulations. Here we describe an algorithm of deriving such clear-sky outgoing spectral flux through the whole IR region from the collocated Atmospheric Infrared Sounder (AIRS) and the Clouds & the Earth's Radiant Energy System (CERES) measurements over the tropical oceans. Based on the scene types and corresponding angular distribution models (ADMs) used in the CERES Single Satellite Footprint (SSF) dataset, spectrally-dependent ADMs are developed and used to estimate the spectral flux at each AIRS channel. A multivariate linear prediction scheme is then used to estimate spectral fluxes at frequencies not covered by the AIRS instrument. The whole algorithm is validated using synthetic spectra as well as the CERES OLR measurements. Using the GFDL AM2 model simulation as a case study, the application of the derived clear-sky outgoing spectral flux in model evaluation is illustrated. By comparing the observed and simulated spectral flux in 2004, compensating errors in the simulated OLR from different absorption bands can be revealed, so does the errors from frequencies within a given absorption band. Discrepancies between the simulated and observed spatial distributions and seasonal evolutions of the spectral fluxes at different spectral ranges are further discussed. The methodology described in this study can be applied to other surface types as well as cloudy-sky observations and corresponding model evaluations.

Huang, Xianglei↗
NASA NTRS2012

Status of the Correlation Process of the V-HAB Simulation with Ground Tests and ISS Telemetry Data

The Virtual Habitat (V-HAB) is a dynamic Life Support System (LSS) simulation, created to investigate future human spaceflight missions. V-HAB provides the capability to optimize LSS during early design phases. Furthermore, it allows simulation of worst case scenarios which cannot be tested in reality. In a nutshell, the tool allows the testing of LSS robustness by means of computer simulations. V-HAB is a modular simulation consisting of a: 1. Closed Environment Module 2. Crew Module 3. Biological Module 4. Physio-Chemical Module The focus of the paper will be the correlation and validation of V-HAB against ground test and flight data. The ECLSS technologies (CDRA, CCAA, OGA, etc.) are correlated one by one against available ground test data, which is briefly described in this paper. The technology models in V-HAB are merged to simulate the ISS ECLSS. This simulation is correlated against telemetry data from the ISS, including the water recovery system and the air revitalization system. Finally, an analysis of the results is included in this paper.

Ploetner, Peter↗
DOE OSTI2022

Predictive Contaminant Transport Simulation with P2R Model for the Composite Analysis Limited Source Sensitivity Case.

The Plateau to River (P2R) is a groundwater flow and contaminant fate and transport (F&T) simulation model used to support remedial activities conducted by the Central Plateau Cleanup Company at the Hanford Site in Washington State. Figure 1 illustrates the P2R Model extents, discretization, and boundary conditions. The P2R Model is utilized in the Composite Analysis (CA) for the Hanford Site as the computational engine for computing F&T predictions as described in CP-60406, Hanford Site Composite Analysis Technical Approach Description: Groundwater. The model simulates contaminants of concern within the saturated zone of the uppermost aquifer beneath the Central Plateau and downgradient to the Columbia River. CP-57037, Model Package Report for the Plateau to River Model Version 8.3 documents the current version of the P2R Model including a description of the conceptual site model, model development and calibration, and limitations to the model application. Simulations conducted to support the dose calculations required by the CA are documented in ECF-HANFORD-19-0119, Predictive Flow Simulation with the P2R Model for the Composite Analysis Base Case and ECF-HANFORD-19-0120, Contaminant Transport Simulation with the P2R Model for the Composite Analysis Base Case.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Dynamic machine learning-based optimization algorithm to improve boiler efficiency

With decreasing computational costs, improvement in algorithms, and the aggregation of large industrial and commercial datasets, machine learning is becoming a ubiquitous tool for process and business innovations. Machine learning is still lacking applications in the field of dynamic optimization for real-time control. This work presents a novel framework for performing constrained dynamic optimization using a recurrent neural network model combined with a metaheuristic optimizer. The framework is designed to augment an existing control system and is purely data-driven, like most industrial Model Predictive Control applications. Several recurrent neural network models are compared as well as several metaheuristic optimizers. Hyperparameters and optimizer parameters are tuned with parameter sweeps, and the resulting values are reported. Further, the best parameters for each optimizer and model combination are demonstrated in closed-loop control of a dynamic simulation, and several recommendations are made for generalizing this framework to other systems. Up to 0.953% improvement is realized over the non-optimized case for a simulated coal-fired boiler. While this is not a large improvement in percentage, the total economic impact is $991,000 per year, and this study builds a foundation for future machine learning with dynamic optimization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗