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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

(abstract) Characterization of Structural Response for Systems with Loose Joints

This paper describes a technique to locate and characterize loose joints in a large truss structure to generate an accurate structural model. The joint looseness is modeled as a gap in the member that opens and closes depending on the loading. Arbitrarily placed actuators are used to prestress the structure to first linearize the response. Next the actuator displacements are systematically reduced while monitoring the displacement response. The gap locations are determined by comparing the measured displacements with sets of calculated displacements and the sizes are estimated by monitoring the gap member length changes using the appropriate linear force-displacement relationship for the load level. The effect of measurement error in the truss displacements and the actuator length changes are investigated.

truss structures loose joints displacements actuat↗
DOE OSTI2018

A Multi-Step Adaptive Interpolation Approach to Mitigating the Impact of Nonlinearity on Dynamic State Estimation

Accurate estimation of dynamic states (such as synchronous machine rotor angle and speed) is critical for monitoring and controlling transient stability. Extended Kalman filter (EKF)--based approaches have been developed for estimating dynamic states. In order to improve the EKF's performance in estimating dynamic states of a synchronous machine, this paper proposes a multi-step adaptive interpolation (MSAI) approach to achieve balance between estimation accuracy and computational time. This approach consists of three major steps. First, two indexes are calculated to quantify the nonlinearity of the state transition function and measurement function, respectively. Second, based on the nonlinearity indexes, the interpolation factor is determined using a finite state machine model. And finally, to mitigate the negative impact of nonlinearity on the estimation accuracy, pseudo-measurements are added between consecutive measurements through linear interpolation. A simple example is used to validate the proposed nonlinear indexes. The two-area four-machine system and 16-machine 68-bus system are used to evaluate the effectiveness of the proposed MSAI approach. It is shown through the Monte-Carlo method that the estimation accuracy can be improved through interpolation. In addition, a good trade-off between estimation accuracy and computational time can be achieved effectively through the proposed MSAI approach.

Dynamic State Estimation, extended Kalman filter (↗
DOE OSTI2013

Uncertainty quantification for evaluating impacts of caprock and reservoir properties on pressure buildup and ground surface displacement during geological CO2 sequestration

A series of numerical test cases reflecting broad and realistic ranges of geological formation properties was developed to systematically evaluate and compare the impacts of those properties on geomechanical responses to CO2 injection. A coupled hydro-geomechanical subsurface transport simulator, STOMP (Subsurface Transport over Multiple Phases), was adopted to simulate the CO2 migration process and geomechanical behaviors of the surrounding geological formations. A quasi-Monte Carlo sampling method was applied to efficiently sample a high-dimensional parameter space consisting of injection rate and 14 subsurface formation properties, including porosity, permeability, entry pressure, irreducible gas and aqueous saturation, Young’s modulus, and Poisson’s ratio for both reservoir and caprock. Generalized cross-validation and analysis of variance methods were used to quantitatively measure the significance of the 15 input parameters. Reservoir porosity, permeability, and injection rate were found to be among the most significant factors affecting the geomechanical responses to the CO2 injection. We used a quadrature generalized linear model to build a reduced-order model that can estimate the geomechanical response instantly instead of running computationally expensive numerical simulations.

CO2 geological sequestration↗
DOE OSTI2024

Online Model-Free DER Dispatch Via Adaptive Voltage Sensitivity Estimation and Chance Constrained Programming

This paper proposes an online data-driven distributed energy resource management system (DERMS) for distribution system optimal DER dispatch as well as voltage regulation. Here, the key innovation is to leverage the Local Sensitivity Factor (LSF) for transforming the DER control into a computationally efficient linear programming (LP) problem. By taking real-time measurements, the estimation of LSF eliminates the need for an accurate distribution system model as well as full nodal load information, which is difficult to achieve in practice. A robust recursive least squares method is also developed to ensure the robust estimation of LSF, which is initialized using reasonable values from model-derived LSFs. This allows the system to adapt to changing operational conditions effectively. A scenario-based, chance-constrained framework is further employed to ensure voltage remains within acceptable limits in the presence of measurement and estimation uncertainties. Test results on a real-world, 759-node distribution network located in western Colorado, U.S., validate the effectiveness and robustness of the proposed control approach and demonstrate its superior performance as compared to alternative methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Analysis of the LSC microbunching instability in MaRIE linac reference design

In this report we estimate the effect of the microbunching instability in the MaRIE XFEL linac. The reference design for the linac is described in a separate report. The parameters of the L1, L2, and L3 linacs as well as BC1 and BC2 bunch compressors were the same as in the referenced report. The beam dynamics was assumed to be linear along the accelerator (which is a reasonable assumption for estimating the effect of the microbunching instability). The parameters of the bunch also match the parameters described in the referenced report. Additionally, it was assumed that the beam radius is equal to R = 100 m and does not change along linac. This assumption needs to be revisited at later studies. The beam dynamics during acceleration was accounted in the matrix formalism using a Matlab code. The input parameters for the linacs are: RF peak gradient, RF frequency, RF phase, linac length, and initial beam energy. The energy gain and the imposed chirp are calculated based on the RF parameters self-consistently. The bunch compressors are accounted in the matrix formalism as well. Each chicane is characterized by the beam energy and the R56 matrix element. It was confirmed that the linac and beam parameters described previously provide two-stage bunch compression with compression ratios of 10 and 20 resulting in the bunch of 3kA peak current.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

Nuclear Data Uncertainty Quantification for Adjoint-Weighted Quantities via XGPT in Monte Carlo Codes

The Total Monte Carlo method (TMC) is an innovative approach to nuclear data uncertainty propagation. In TMC, a large number of independent ENDF files are randomly generated starting from nuclear models parameters and their uncertainties. These files are then processed with NJOY or similar codes to produce a set of formatted continuous-energy cross sections (i.e., ACE files), and independent Monte Carlo neutron transport simulations are run with these different ACE files as input. Finally the distributions of the considered response functions are obtained directly from the results of the Monte Carlo runs. Despite several improvements of the TMC method, this approach is often considered an inefficient way of propagating nuclear data uncertainties, as it requires several computationally expensive Monte Carlo runs. Covariance-based methods present important advantages for several applications, especially when different sources of uncertainties are to be investigated. For this reason, sensitivity analysis and uncertainty quantification capabilities are being implemented in several Monte Carlo neutron transport codes. On the other hand, the fact that no artificial multi-group covariance matrices are required and that higher moments of the responses distributions can be easily obtained, are definite advantages of the TMC method. In an effort to overcome the limitations of both approaches, a new method, called eXtended Generalized Perturbation Theory (XGPT) is under development. When performing nuclear data uncertainty propagation, such XGPT approach does not require generating discretized (i.e., multigroup) covariance matrices, and allows to estimate higher moments of the response probability distributions, via linear perturbation theory. One of the promising applications of the XGPT method involves its adoption in conjunction with the Proper Orthogonal Decomposition (POD) of nuclear data, to build a Reduced Order Model (ROM) for the approximation of thousands of independent TMC results in a single criticality source simulation. In the present work, this approach is employed for the first time to evaluate the impact of uncertainty in nuclear data on adjoint-weighted quantities. The method has been implemented in an extended version of the Serpent-2.1.24 Monte Carlo code and is demonstrated on two fast spectrum benchmarks, focusing on {sup 208}Pb nuclear data. A new method for propagating nuclear data uncertainties in criticality source Monte Carlo simulations has been developed. This eXtended Generalized Perturbation Theory (XGPT) approach allows to accurately reproduce reference Total Monte Carlo (TMC) uncertainty estimates in a single criticality source simulation. The present work aims to demonstrate that the proposed method can quantify nuclear data uncertainty based on adjoint-weighted quantities. The XGPT approach was applied to evaluate the impact of {sup 208}Pb nuclear data uncertainties on the effective prompt neutron lifetime (l{sub eff}) in two fast spectrum systems. The obtained XGPT results show a good agreement with the reference TMC results, obtained from independent Monte Carlo runs with {sup 208}Pb nuclear data from random TENDL-2013 evaluations. The XGPT method, implemented in a extended version of the Serpent Monte Carlo code and adopted along with the Proper Orthogonal Decomposition (POD) of the nuclear data, is able to provide an accurate reduced order model to approximate thousands TMC results within a single run, ensuring a large saving in computational requirements. The effect of {sup 208}Pb nuclear data uncertainties appears to be rather large. This is consistent with previous studies that adopted the same input random evaluations data from TENDL. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2022

Present-Day and Future PM 2.5 and O 3 -Related Global and Regional Premature Mortality in the EVAv6.0 Health Impact Assessment Model

We used the EVAv6.0 system to estimate the present (2015) and future (2015–2050) global PM 2.5 and O 3 -related premature mortalities, using simulated surface concentrations from the GISS-E2.1-G Earth system model. The PM 2.5 -related global premature mortality is estimated to be 4.3 and 4.4 million by the non-linear and linear models, respectively. Ischemic heart diseases are found to be the leading cause of PM 2.5 -related premature deaths, contributing by 35% globally. Both long-term and short-term O 3 -related premature deaths are estimated to be around 1 million, globally. Overall, PM 2.5 and O 3 -related premature mortality leads to 5.3–5.4 million premature deaths, globally. The global burden of premature deaths is mainly driven by the Asian region, which in 2015 contributes by 75% of the total global premature deaths. An increase from 6.2% to 8% in the PM 2.5 relative risk as recommended by the WHO leads to an increase of PM 2.5 -related premature mortality by 28%, to 5.7 million. Finally, bias correcting the simulated PM 2.5 concentrations in 2015 leads to an increase of up to 73% in the global PM 2.5 -related premature mortality, leading to a total number of global premature deaths of up to 7.7 million, implying the necessity of bias correction to get more robust health burden estimates. PM 2.5 and O 3 -related premature mortality in 2050 decreases by up to 57% and 18%, respectively, due to emission reductions alone. However, the projected increase and aging of the population leads to increases of premature mortality by up to a factor of 2, showing that the population exposed to air pollution is more important than the level of air pollutants, highlighting that the population dynamics should be considered when setting up health assessment systems.

Premature mortality↗
DOE OSTI2016

Fitting and forecasting coupled dark energy in the non-linear regime

We consider cosmological models in which dark matter feels a fifth force mediated by the dark energy scalar field, also known as coupled dark energy. Our interest resides in estimating forecasts for future surveys like Euclid when we take into account non-linear effects, relying on new fitting functions that reproduce the non-linear matter power spectrum obtained from N-body simulations. We obtain fitting functions for models in which the dark matter-dark energy coupling is constant. Their validity is demonstrated for all available simulations in the redshift range 0z=–1.6 and wave modes below 0k=1 h/Mpc. These fitting formulas can be used to test the predictions of the model in the non-linear regime without the need for additional computing-intensive N-body simulations. We then use these fitting functions to perform forecasts on the constraining power that future galaxy-redshift surveys like Euclid will have on the coupling parameter, using the Fisher matrix method for galaxy clustering (GC) and weak lensing (WL). We find that by using information in the non-linear power spectrum, and combining the GC and WL probes, we can constrain the dark matter-dark energy coupling constant squared, β{sup 2}, with precision smaller than 4% and all other cosmological parameters better than 1%, which is a considerable improvement of more than an order of magnitude compared to corresponding linear power spectrum forecasts with the same survey specifications.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Chemical Potential of Metal Atoms in Supported Nanoparticles: Dependence upon Particle Size and Support

Metal nanoparticles supported on oxide surfaces form the basis for many industrial catalysts and promise to play an ever-increasing role in future energy and environmental technologies. The chemical potential (μ) of the metal atoms in these particles depends strongly on particle size and support and is an important factor that determines their catalytic properties, including their binding strengths to adsorbed reaction intermediates and their long-term stability against sintering. We present here a method for estimating this chemical potential as a function of particle size for different metal/oxide combinations. We show that this chemical potential for late transition metals is well approximated for a particle of diameter D by μ( D ) = [(3γ m – E adh )(1 + D o / D )](2 V m / D ), where γ m is the surface energy of the bulk metal, E adh is the adhesion energy at the bulk metal/oxide interface, and D o is ~1.5 nm, and V m is the molar volume of the bulk metal. We further show that E adh increases with (1) increasing heat of formation of the most stable oxide of the metal from metal gas atoms plus O 2 (gas) per mole of metal atoms, (2) decreasing enthalpy of reduction of the oxide to its next lower oxidation state plus O 2 (gas), per mole of oxygen atoms, and (3) increasing density of surface oxygen atoms on the oxide surface. The linear scaling of E adh with these properties allows estimations of E adh for a variety of metal/oxide combinations. Using this E adh estimate in the above equation with known values for γ m allows estimates of metal chemical potential versus particle size for late transition metals on various oxide supports. WE conclude this will improve our ability to understand structure–property relations in catalysis and design better catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2022

Re-Evaluation of Low Cloud Amount Relationships With Lower-Tropospheric Stability and Estimated Inversion Strength

Lower-tropospheric stability (LTS) and estimated inversion strength (EIS) have a widely accepted relationship with low cloud amount and are key observational foundations for understanding and modeling low-level stratiform clouds. Using the updated surface-based and satellite cloud data, we find that low cloud amount is not as strongly correlated with LTS, and not as sensitive to LTS, as established in the past. EIS does not provide a stronger correlation with low cloud amount than LTS over all eight regions (including the midlatitudes). Further analyzing the relationships between LTS and EIS with different types of low clouds, we find that there is a strong correlation of LTS and EIS with stratocumulus only. This explains the weaker correlation of low cloud fraction (including cumulus, stratocumulus, and stratus) to both LTS and EIS. These results also suggest the need to re-evaluate these relationships in Earth system models. Plain Language Summary: Low-level clouds play an important role in the global radiation budget. Low cloud amount has two established linear relationships with lower-tropospheric stability (LTS) and estimated inversion strength (ETS). These two relationships are re-evaluated here using three separate observational cloud and two reanalysis datasets for three distinct but overlapping time periods. The analysis shows that the strength of the LTS and ETS relationships with low cloud amount varies, depending on the cloud data used. They have a strong relationship with stratocumulus cloud amount only.

Lauren Cutler↗
NASA NTRS1995

Prestraining and Its Influence on Subsequent Fatigue Life

An experimental program was conducted to study the damaging effects of tensile and compressive prestrains on the fatigue life of nickel-base, Inconel 718 superalloy at room temperature. To establish baseline fatigue behavior, virgin specimens with a solid uniform gage section were fatigued to failure under fully-reversed strain-control. Additional specimens were prestrained to 2 percent, 5 percent, and 10 percent (engineering strains) in the tensile direction and to 2 percent (engineering strain) in the compressive direction under stroke-control, and were subsequently fatigued to failure under fully-reversed strain-control. Experimental results are compared with estimates of remaining fatigue lives (after prestraining) using three life prediction approaches: (1) the Linear Damage Rule; (2) the Linear Strain and Life Fraction Rule; and (3) the nonlinear Damage Curve Approach. The Smith-Watson-Topper parameter was used to estimate fatigue lives in the presence of mean stresses. Among the cumulative damage rules investigated, best remaining fatigue life predictions were obtained with the nonlinear Damage Curve Approach.

Halford, Gary R.↗
NASA NTRS2003

Biological Effectiveness of Accelerated Particles for the Induction of Chromosome Damage Measured in Metaphase and Interphase Human Lymphocytes

Chromosome aberrations were investigated in human lymphocytes after in vitro exposure to 1H-, 3He-, 12C-, 40Ar-, 28Si-, 56Fe-, or 197Au-ion beams, with LET ranging from approximately 0.4-1393 keV/microm in the dose range of 0.075-3 Gy. Dose-response curves for chromosome exchanges, measured at the first mitosis postirradiation using fluorescence in situ hybridization (FISH) with whole-chromosome probes, were fitted with linear or linear-quadratic functions. The relative biological effectiveness (RBE) was estimated from the initial slope of the dose-response curve for chromosomal damage with respect to low- or high-dose-rate gamma rays. Estimates of RBEmax values for mitotic spreads, which ranged from near 0.7 to 11.1 for total exchanges, increased with LET, reaching a maximum at about 150 keV/microm, and decreased with further increase in LET. RBEs for complex aberrations are undefined due to the lack of an initial slope for gamma rays. Additionally, the effect of mitotic delay on RBE values was investigated by measuring chromosome aberrations in interphase after chemically induced premature chromosome condensation (PCC), and values were up to threefold higher than for metaphase analysis.

NASA Discipline Radiation Health↗
DOE OSTI2023

Monte Carlo goodness-of-fit tests for degree corrected and related stochastic blockmodels

Abstract We construct Bayesian and frequentist finite-sample goodness-of-fit tests for three different variants of the stochastic blockmodel for network data. Since all of the stochastic blockmodel variants are log-linear in form when block assignments are known, the tests for the latent block model versions combine a block membership estimator with the algebraic statistics machinery for testing goodness-of-fit in log-linear models. We describe Markov bases and marginal polytopes of the variants of the stochastic blockmodel and discuss how both facilitate the development of goodness-of-fit tests and understanding of model behaviour. The general testing methodology developed here extends to any finite mixture of log-linear models on discrete data, and as such is the first application of the algebraic statistics machinery for latent-variable models.

Karwa, Vishesh↗
NASA NTRS1986

Polynomial elimination theory and non-linear stability analysis for the Euler equations

Numerical methods are presented that exploit the polynomial properties of discretizations of the Euler equations. It is noted that most finite difference or finite volume discretizations of the steady-state Euler equations produce a polynomial system of equations to be solved. These equations are solved using classical polynomial elimination theory, with some innovative modifications. This paper also presents some preliminary results of a new non-linear stability analysis technique. This technique is applicable to determining the stability of polynomial iterative schemes. Results are presented for applying the elimination technique to a one-dimensional test case. For this test case, the exact solution is computed in three iterations. The non-linear stability analysis is applied to determine the optimal time step for solving Burgers' equation using the MacCormack scheme. The estimated optimal time step is very close to the time step that arises from a linear stability analysis.

Kennon, S. R.↗
NASA NTRS2023

Impact of COVID-19-related Air Traffic Reductions on the Coverage and Radiative Effects of Linear Persistent Contrails over Conterminous United States and Surrounding Oceanic Routes

The radiative effects of the large-scale air traffic slowdown during Apr and May 2020 due to the international response to the COVID-19 pandemic are estimated by comparing the coverage (CC), optical properties, and radiative forcing of persistent linear contrails over the conterminous United States and two surrounding oceanic air corridors during the slowdown period and a similar baseline period during 2018 and 2019 when air traffic was unrestricted. The detected CC during the slowdown period decreased by an area-averaged mean of 41% for the three analysis boxes. The retrieved contrail optical properties were mostly similar for both periods. Total shortwave contrail radiative forcings during the slowdown were 34 and 42% smaller for Terra and Aqua, respectively. The corresponding differences for longwave contrail radiative forcing were 33% for Terra and 40% for Aqua. To account for the impact of any changes in the atmospheric environment between baseline and slowdown periods on detected CC amounts, the contrail formation potential (CFP) was computed from reanalysis data. In addition, a filtered CFP (fCFP) was also developed to account for factors that may affect contrail formation and visibility of persistent contrails in satellite imagery. The CFP and fCFP were combined with air traffic density data to create empirical models that estimated CC during the baseline and slowdown periods and were compared to the detected CC. The models confirm that decreases in CC and radiative forcing during the slowdown period were mostly due to the reduction in air traffic, and partly due to environmental changes.

contrails↗
DOE OSTI2023

Blowing Snow at McMurdo Station, Antarctica During the AWARE Field Campaign: Multi-Instrument Observations of Blowing Snow

In polar regions, blowing snow (BLSN) can play a substantial role in regional thermodynamics and radiation properties. The extent of the impact depends upon the depth of the BLSN layer, a property that is difficult to measure and not well understood. The West Antarctic Radiation Experiment (AWARE) Field Campaign saw the deployment of a large suite of observational instruments to McMurdo Station, Antarctica, allowing for in-depth investigation of BLSN. During the year of the campaign, BLSN occurred ~7.4% of the time. In this study, additional remote sensing observations are used to supplement an existing ceilometer-based BLSN characterization algorithm creating a multi-instrument (MI) depth estimation algorithm to yield layer depths with more certainty. Backscatter coefficient and linear depolarization ratios from the micropulse and high spectral resolution lidar (HSRL) are incorporated along with color ratio derived from HSRL backscatter and Ka-band radar reflectivity observations. This provided estimates of BLSN depth that were less impacted by noise/artifacts in any one set of observations. When applied to the data from AWARE, the MI algorithm yielded an average depth of 168.2 m with ~60% of plumes less than 200 m in depth. Events occurring with precipitation saw the most value in the additional instruments, with the suite of observations allowing for more separation of BLSN particles from fallstreaks.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1983

Seismic velocity structure of the lunar mantle

The recently completed set of seismic arrival times from the Apollo lunar seismic network are inverted to estimate the average seismic velocities in three sections of the lunar mantle: two for the upper mantle and one for the middle mantle. The method used is a variation of the linearized least squares inversion where the inversion is accomplished in steps. The estimated average velocities in the upper mantle decrease from Vp = 7.74 km/sec and Vs = 4.49 km/sec in the section above 270-km depth to Vp = 7.46 km/sec and Vs = 4.25 km/sec in the section between 270- and 500-km depth, confirming the earlier finding of negative gradients based on seismic amplitude variations. The average velocities in the middle mantle between the depths of 500 km and 1000 km of Vp = 8.26 km/sec and Vs = 4.65 km/sec are significantly higher than those in the upper mantle, contradicting earlier estimates based on more limited data. The higher velocities may suggest initial melting of the moon down to at least 1000-km depth.

Nakamura, Y.↗
DOE OSTI2020

Real-Time Modal Analysis of Electric Power Grids - The Need for Dynamic State Estimation

We articulate the reason why dynamic state estimation is needed to push the boundaries of the modal analysis of electric power grids in real-time operation. Then, we demonstrate how to unravel linear and nonlinear modes by using the extended dynamic mode decomposition along with estimates of the synchronous generators’ rotor angles and rotor speed deviations from nominal speed. The estimated modes are associated with electromechanical oscillations that take place continuously in electric power grids because of imbalances between power generation and demand. The numerical simulations are performed on a synthetic, albeit realistic, 2,000-bus network that was designed to resemble the electric power grid of Texas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗