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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Capabilities of Single Launch NTP and Chemical Spacecrafts for Cis-Lunar Tug Missions

Renewed interest in the region between the Earth and the moon suggests that a tug operating between these two destinations will be most likely required in the near future. This report details a parametric spacecraft model which sizes a nuclear thermal propulsion or chemical propulsion spacecraft and compares their payload transport capabilities for missions to the moon. A spacecraft sized to fit in a single launch vehicle is assumed, and six launch vehicles are investigated. Maximum spacecraft payload mass and minimum mission transit time are compared between nuclear and chemical propulsion spacecrafts. For vehicles sized to the maximum capability of a launch vehicle, payloads of at least five metric tons are possible with either propulsion option; with nuclear thermal propulsion able to provide additional mass or reduced transit time when the spacecraft is sized to the maximum capability of the heaviest-lift launch vehicles. Transit times to the moon with a five-ton payload could be reduced by at least 0.2 days with a nuclear propulsion system.

Cis-lunar tug↗
NASA NTRSDate not supplied

Development and Validation of an Initial Electric Motor Rotor Vibration Model

An overview of the development of a low fidelity prediction tool for electric motor rotor resonant modes and frequencies. These predictions are useful for the prediction of UAM motor noise during the design phase. Finite Element Analysis of motor rotors has led to the development of a parameterized model to predict these modes shapes. This has in turn allowed to a curve-fit based model from parametric sweeps. These curves can predict resonant frequencies and shapes for 1-5kW class motors without running a simulation.

acoustics↗
NASA NTRSDate not supplied

Capabilities of Single Launch NTP and Chemical Spacecrafts for Cis-Lunar Tug Missions

Renewed interest in the region between the Earth and the moon suggests that a tug operating between these two destinations will be most likely required in the near future. This report details a parametric spacecraft model which sizes a nuclear thermal propulsion or chemical propulsion spacecraft and compares their payload transport capabilities for missions to the moon. A spacecraft sized to fit in a single launch vehicle is assumed, and six launch vehicles are investigated. Maximum spacecraft payload mass and minimum mission transit time are compared between nuclear and chemical propulsion spacecrafts. For vehicles sized to the maximum capability of a launch vehicle, payloads of at least five metric tons are possible with either propulsion option; with nuclear thermal propulsion able to provide additional mass or reduced transit time when the spacecraft is sized to the maximum capability of the heaviest-lift launch vehicles. Transit times to the moon with a five-ton payload could be reduced by at least 0.2 days with a nuclear propulsion system.

Cis-lunar tug↗
DOE OSTI2011

Quench dynamics in SRF cavities: can we locate the quench origin with 2nd sound?

A newly developed method of locating quenches in SRF cavities by detecting second-sound waves has been gaining popularity in SRF laboratories. The technique is based on measurements of time delays between the quench as determined by the RF system and arrival of the second-sound wave to the multiple detectors placed around the cavity in superfluid helium. Unlike multi-channel temperature mapping, this approach requires only a few sensors and simple readout electronics; it can be used with SRF cavities of almost arbitrary shape. One of its drawbacks is that being an indirect method it requires one to solve an inverse problem to find the location of a quench. We tried to solve this inverse problem by using a parametric forward model. By analyzing the data we found that the approximation where the second-sound emitter is a near-singular source does not describe the physical system well enough. A time-dependent analysis of the quench process can help us to put forward a more adequate model. We present here our current algorithm to solve the inverse problem and discuss the experimental results.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

Combining Galaxy-Galaxy Lensing and Galaxy Clustering

Combining galaxy-galaxy lensing and galaxy clustering is a promising method for inferring the growth rate of large scale structure, a quantity that will shed light on the mechanism driving the acceleration of the Universe. The Dark Energy Survey (DES) is a prime candidate for such an analysis, with its measurements of both the distribution of galaxies on the sky and the tangential shears of background galaxies induced by these foreground lenses. By constructing an end-to-end analysis that combines large-scale galaxy clustering and small-scale galaxy-galaxy lensing, we also forecast the potential of a combined probes analysis on DES datasets. In particular, we develop a practical approach to a DES combined probes analysis by jointly modeling the assumptions and systematics affecting the different components of the data vector, employing a shared halo model, HOD parametrization, photometric redshift errors, and shear measurement errors. Furthermore, we study the effect of external priors on different subsets of these parameters. We conclude that DES data will provide powerful constraints on the evolution of structure growth in the universe, conservatively/ optimistically constraining the growth function to 8%/4.9% with its first-year data covering 1000 square degrees, and to 4%/2.3% with its full five-year data covering 5000 square degrees.

Park, Youngsoo↗
DOE OSTI2018

Model-Based Air Flow Path Optimization of Heat Pump Clothes Dryer

A heat pump clothes dryer (HPCD) uses a vapor compression system to dry clothes. The condenser heats air, which passes through the drum to evaporate moisture out of the clothes, and the evaporator condenses water out of the air stream. As a result, the HPCD can achieve 50% energy savings compared to a conventional electric resistance dryer. In this work we developed a physics-based, quasi-steady-state HPCD system model with detailed heat exchanger and compressor models. The system model can simulate the inherently transient HPCD drying process, to size components, and to reveal trends in key variables (e.g. compressor discharge temperature, power consumption, required drying time, etc.) The system model was calibrated using experimental data from a prototype HPCD. Air leakages, in and out, along the closed air circulation path of HPCD cause varied effects on the performance. Understanding the location, magnitude, and direction of air leakage of the heat pump clothes dryer is critical for accurately characterizing the performance and developing a high-performance design. The system model was used to reveal the impacts. In addition, model-based parametric optimizations were conducted to design the HPCD charge inventory, flow rate, air path and leak points for optimum performance.

Shen, Bo↗
DOE OSTI2020

Microwave Cavity Simulation Using Ansys HFSS

The design of microwave cavity detectors for axion dark matter research is often accomplished using advanced full-wave electromagnetic simulation software tools. These tools provide a cost-effective approach to evaluate a wide variety of cavity configurations, frequency tuning mechanisms, and conductive or dielectric materials and coatings. One simulation software package used for this application is Ansys High Frequency Structure Simulator (HFSS), which is based upon the well-established finite element method. HFSS includes numerous features useful for microwave cavity design such as parametric geometry modeling, adaptive meshing algorithm, curvilinear mesh elements, driven modal and eigenmode matrix solvers, and optimization algorithms. This paper describes the use of the HFSS software to simulate microwave cavities for axion haloscope detectors, with an example tutorial for a cylindrical cavity. Excellent agreement between the simulated and analytical results is shown for the resonant frequency, quality factor, and form factor.

Ansys HFSS, Cavity simulation, finite element mode↗
DOE OSTI2022

Large-Scale Simulation of Regional Demand Flexibility Implementation and Customer Economic Impact

The Distribution System Operator with Transactive (DSO+T) study conducted a large-scale simulation of over 60,000 customers in a region the size of Texas to demonstrate the effective coordination of distributed energy resources (DERs) in commercial and residential buildings. The integrated simulation included both the bulk (wholesale generation and transmission) and distribution systems. The DERs (including batteries, electric vehicles, air conditioning, and water heaters) participated in a transactive energy retail market that was integrated into an existing competitive wholesale market. The engineering and economic performance of the resulting demand flexibility was evaluated over annual simulations for both moderate and high renewable generation scenarios. A detailed parametric cost model was developed to enable detailed economic analysis of key stakeholders. In addition, fixed and dynamic customer tariffs were designed and applied to the customer population. This allowed the impact on annual customer bills to be analyzed for various building types (residential versus commercial; single- versus multi-family). This paper presents results showing the relative flexibility of batteries, electric vehicles, and building loads throughout the year and under different renewable scenarios. This feeds a detailed breakdown of the impact this flexibility has on the operating costs of the grid and the resulting net economic benefit. Finally, the study showed that practically all customer classes (including non-participating customers) save money under the proposed demand flexibility scheme. The study found overall net annual economic savings of $3.3-5.0B for a region the size of Texas equating to average customer bill savings of 10-16%.

Reeve, Hayden M.↗
DOE OSTI2010

Supersymmetry Without (Too Much) Prejudice

We have recently completed a detailed scan of the 19-dimensional parameter space of the phenomenological MSSM, i.e., the CP-conserving MSSM [Minimal Supersymmtric Standard Model] assuming Minimal Flavor Violation (MFV) with the first two sfermion generations degenerate. We found a large set of parameter space points that satisfied all of the existing experimental and theoretical constraints. This analysis allows us to examine the general features of the MSSM without reference to any particular SUSY breaking scenario or any other assumptions about physics at higher scales. This study opens up new possibilities for SUSY phenomenology both at colliders and in astrophysical observations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Hierarchical model reduction driven by a proper orthogonal decomposition for parametrized advection-diffusion-reaction problems

This work combines the Hierarchical Model (HiMod) reduction technique with a standard Proper Orthogonal Decomposition (POD) to solve parametrized partial differential equations for the modeling of advection-diffusion-reaction phenomena in elongated domains (e.g., pipes). This combination leads to what we define as HiPOD model reduction, which merges the reliability of HiMod reduction with the computational efficiency of POD. Two HiPOD techniques are presented and assessed by an extensive numerical verification.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

The transient performance of a two-phase fluid reservoir

Thermal control of future large, high power spacecraft will require a two-phase fluid central bus. The two-phase fluid reservoir is a critical component in the two-phase fluid bus. It both controls the saturation temperature and provides a space for volumetric changes. A dynamic reservoir simulation model does not currently exist, but it is needed to expedite efforts and reduce risk. During 1989 an effort was made to develop a simulation model of the transient performance of a two-phase fluid reservoir. As a beginning, a preliminary model was developed. It is based upon component mathematical models in lumped parametric form and build upon five component mathematical models for calculating dynamic responses of two-phase fluid reservoirs, primary feedback elements, controller commands, heater actuators, and reservoir heaters. As much as possible, the model took advantage of the available SINDA'85/FLUINT thermal/fluid integrator. Additional calculation logic and computer subroutines were developed to complete implementation of the model. The model is capable of simulating dynamic response of an equilibrium two-phase fluid reservoir. Modification of the model to include the liquid/vapor nonequilibrium is required for applications of the model to simulate performance of reservoir in which the liquid and vapor phases of the reservoir fluid are not in equilibrium. In addition, the model in its present form, needs to be refined in several respects. More empirical data are needed to guide the model development. The model may then be used to conduct a full parametric study of two-phase fluid reservoirs. More complexities in two-phaes flow regions in laboratory and flight conditions may have to be considered eventually if empirical data cannot be simulated satisfactorily. System with other components arrangement also need to be simulated if optimization is ever to be attained. The present model does, however, preliminarily demonstrates that such analyses are quite possible and offers a far less expensive method to understand the transient of a two-phase fluid reservoir system than a totally headware approach.

Chi, Joseph↗
NASA NTRS2022

Are Soybean Models Ready for Climate Change Food Impact Assessments?

An accurate estimation of crop yield under climate change scenarios is essential to quantify our ability to feed a growing population and develop agronomic adaptations to meet future food demand. A coordinated evaluation of yield simulations from process-based eco-physiological models for climate change impact assessment is still missing for soybean, the most widely grown grain legume and the main source of protein in our food chain. In this first soybean multi-model study, we used ten prominent models capable of simulating soybean yield under varying temperature and atmospheric CO 2 concentration [CO 2 ] to quantify the uncertainty in soybean yield simulations in response to these factors. Models were first parametrized with high quality measured data from five contrasting environments. We found considerable variability among models in simulated yield responses to increasing temperature and [CO 2 ]. For example, under a + 3 °C temperature rise in our coolest location in Argentina, some models simulated that yield would reduce as much as 24%, while others simulated yield increases up to 29%. In our warmest location in Brazil, the models simulated a yield reduction ranging from a 38% decrease under + 3 °C temperature rise to no effect on yield. Similarly, when increasing [CO 2 ] from 360 to 540 ppm, the models simulated a yield increase that ranged from 6% to 31%. Model calibration did not reduce variability across models but had an unexpected effect on modifying yield responses to temperature for some of the models. The high uncertainty in model responses indicates the limited applicability of individual models for climate change food projections. However, the ensemble mean of simulations across models was an effective tool to reduce the high uncertainty in soybean yield simulations associated with individual models and their parametrization. Ensemble, ensemble mean yield responses to temperature and [CO 2 ] were similar to those reported from the literature. Our study is the first demonstration of the benefits achieved from using an ensemble of grain legume models for climate change food projections, and highlights that further soybean model development with experiments under elevated [CO 2 ] and temperature is needed to reduce the uncertainty from the individual models.

Agricultural Model Inter-comparison and Improvemen↗
DOE OSTI2021

Assessing boundary condition and parametric uncertainty in numerical-weather-prediction-modeled, long-term offshore wind speed through machine learning and analog ensemble

To accurately plan and manage wind power plants, not only does the time-varying wind resource at the site of interest need to be assessed but also the uncertainty connected to this estimate. Numerical weather prediction (NWP) models at the mesoscale represent a valuable way to characterize the wind resource offshore, given the challenges connected with measuring hub-height wind speed. The boundary condition and parametric uncertainty associated with modeled wind speed is often estimated by running a model ensemble. However, creating an NWP ensemble of long-term wind resource data over a large region represents a computational challenge. Here, we propose two approaches to temporally extrapolate wind speed boundary condition and parametric uncertainty using a more convenient setup in which a mesoscale ensemble is run over a short-term period (1 year), and only a single model covers the desired long-term period (20 year). We quantify hub-height wind speed boundary condition and parametric uncertainty from the short-term model ensemble as its normalized across-ensemble standard deviation. Then, we develop and apply a gradient-boosting model and an analog ensemble approach to temporally extrapolate such uncertainty to the full 20-year period, for which only a single model run is available. As a test case, we consider offshore wind resource characterization in the California Outer Continental Shelf. Both of the proposed approaches provide accurate estimates of the long-term wind speed boundary condition and parametric uncertainty across the region (R 2 >0.75), with the gradient-boosting model slightly outperforming the analog ensemble in terms of bias and centered root-mean-square error. At the three offshore wind energy lease areas in the region, we find a long-term median hourly uncertainty between 10 % and 14 % of the mean hub-height wind speed values. Finally, we assess the physical variability in the uncertainty estimates. In general, we find that the wind speed uncertainty increases closer to land. Also, neutral conditions have smaller uncertainty than the stable and unstable cases, and the modeled wind speed in winter has less boundary condition and parametric sensitivity than summer.

17 WIND ENERGY↗
DOE OSTI2010

Cross sections of neutron-induced reactions

We study the properties of the neutron-nucleus total and reaction cross sections for several nuclei. We have applied an analytical model, the nuclear Ramsauer model, justified it from the nuclear reaction theory approach, and extracted the values of 12 parameters used in the model. The given parametrization has an advantage as phenomenological optical model potentials are limited up to 150-200 MeV. The present model provides good estimates of the total cross sections for several nuclei particularly at high energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2013

Lumped Parameter Modeling for Rapid Vibration Response Prototyping and Test Correlation for Electronic Units

Present preliminary work using lumped parameter models to approximate dynamic response of electronic units to random vibration; Derive a general N-DOF model for application to electronic units; Illustrate parametric influence of model parameters; Implication of coupled dynamics for unit/board design; Demonstrate use of model to infer printed wiring board (PWB) dynamics from external chassis test measurement.

random vibration↗
DOE OSTI2023

Bayesian uncertainty quantification of tristructural isotropic particle fuel silver release: Decomposing model inadequacy plus experimental noise and parametric uncertainties

Tristructural isotropic (TRISO) particle fuel is one of the most promising fuel concepts enabling high temperature and high burnup reactor operation. One dominant source of radioactivity released from the TRISO particles is silver (Ag), which is subject to a high release fraction and long decay life compared to other fission products. Previous modeling efforts using the fuel performance code BISON indicated nonnegligible uncertainties in modeling the diffusion process of fission products in TRISO compared to the Advanced Gas Reactor experiments. The overall uncertainties observed when modeling the fission product diffusion can result from uncertainties in model parameters, noisy experimental measurements, and deficiencies in the developed models. The three types of underlying uncertainties have not yet been properly quantified in open literature. Here, this paper presents the Bayesian uncertainty quantification (UQ) using massively parallelizable Markov chain Monte Carlo samplers. The uncertainties due to model parameters, model inadequacy, and experimental measurement noise are quantified, with the σ term used to represent the sum of the model inadequacy and measurement noise uncertainties. It is worth noting that this is the first time the σ term is inferred for nuclear fuel experiments, as compared to using prescribed values for uncertainty quantification in previous work. The parallelizable Markov chain Monte Carlo samplers efficiently infer the model parameters and the σ term, giving insight into physical parameters like diffusion coefficients and the combined model discrepancy and measurement noise. A subsequent forward uncertainty quantification (UQ) is also performed based on the calibration results to generate more accurate predictions of the Ag release. The model inadequacy plus experimental noise is the most dominant source of uncertainty compared to the parametric uncertainty. All the UQ analyses presented in this work are based on the second series of the irradiation experiments in the Advanced Gas Reactor program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗