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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Nucleosynthetic Heterogeneity Controls Vanadium Isotope Variations in Bulk Chondrites

The vanadium (V) isotope composition of early solar system materials have been hypothesized to be sensitive to high energy irradiation that originated from the young Sun. Vanadium has two isotopes with masses 50 and 51 that have (51)V/(50)V ratio of approximately 410. High energy irradiation produces (50)V from various target isotopes of Ti, Cr and Fe, which would result in light V isotope compositions (expressed as delta (51)V in per mille = 1000 x (((51)V/(50)V(sub sample)/(51)V/(50)V(sub AlfaAesar)) - 1)) relative to a presumably chondritic starting composition. Recently published V isotope data for calcium aluminium inclusions (CAIs) has revealed some very negative values relative to chondrites (by almost -4 per mille) that were indeed interpreted to reflect irradiation processes despite the fact that the studied CAIs all exhibited significant initial abundances of (10)Be, while only a few CAIs displayed light V isotope compositions. It is difficult to relate V isotope variations directly to a singular process because V only possesses two isotopes. Therefore, V isotope variations can principally be produced both mass dependent and independent processes. Mass dependent kinetic stable isotope fractionation is common in CAIs for refractory elements due to partial condensation/evaporation processes. The element strontium (Sr) has an almost identical condensation temperature to V and studies of stable Sr isotope compositions in CAIs reveal both heavy and light values relative to chondrites of several permil. These variations are similar in magnitude to those reported for V isotopes in CAIs, which suggests it is possible that some of the V isotope variation in CAIs could be due to kinetic stable isotope fractionation during condensation/evaporation processes.

Nielsen, S. G.↗
NASA NTRS2017

Assimilation of AERONET and MODIS AOT Observations Using Variational and Ensemble Data Assimilation Methods and Its Impact on Aerosol Forecasting Skill

Data assimilation of Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical thickness (AOT) for aerosol forecasting was tested within the Navy Aerosol Analysis Prediction System (NAAPS) framework, using variational and ensemble data assimilation methods. Navy aerosol forecasting currently makes use of a deterministic NAAPS simulation coupled to Navy Variational Data Assimilation System for aerosol optical depth, a two-dimensional variational data assimilation system, for MODIS AOT assimilation. An ensemble version of NAAPS (ENAAPS) coupled to an ensemble adjustment Kalman filter (EAKF) from the Data Assimilation Research Testbed was recently developed, allowing for a range of data assimilation and forecasting experiments to be run with deterministic NAAPS and ENAAPS. The main findings are that the EAKF, with its flow-dependent error covariances, makes better use of sparse observations such as AERONET AOT. Assimilating individual AERONET observations in the two-dimensional variational system can increase the analysis errors when observations are located in high AOT gradient regions. By including AERONET with MODIS AOT assimilation, the magnitudes of peak aerosol events (AOT> 1) were better captured with improved temporal variability, especially in India and Asia where aerosol prediction is a challenge. Assimilating AERONET AOT with MODIS had little impact on the 24 h forecast skill compared to MODIS assimilation only, but differences were found downwind of AERONET sites. The 24 h forecast skill was approximately the same for forecasts initialized with analyses from AERONET AOT assimilation alone compared to MODIS assimilation, particularly in regions where the AERONET network is dense; including the United States and Europe, indicating that AERONET could serve as a backup observation network for over-land synoptic-scale aerosol events.

Rubin, Juli I.↗
NASA NTRS2018

Intraseasonal Variations of Nonmigrating Tides Observed Near the Mesopause

Nonmigrating tides excited in the tropical troposphere by latent heat release from deep convection are known to be responsible for introducing the longitudinal structures in the upper atmosphere and the ionosphere. This study presents for the first time an extensive analysis of the prominent wave-3 and wave-4 longitudinal structures using nearly 14 years of temperature observations by the Microwave Limb Sounder instrument operated on the Aura satellite from 2004 to 2017. The observations reveal significant intraseasonal (~30-60 days) periodic variations in the amplitudes of these wave structures at ~97-km altitude near the mesopause. Some large wave amplitudes accompany strong activity of the Madden-Julian Oscillation. Rainfall data from the Tropical Rainfall Measuring Mission are used as a proxy of latent heating to investigate the source of these variations. Intraseasonal signatures in the wave structures are observed to coincide with the rainfall variations, indicating that the tropospheric 30- to 60- day oscillation is an important driver of the same periodic changes in the upper atmosphere. Given that not all intraseasonal oscillations in the lower atmosphere have corresponding signatures in the longitudinal wave structures, the atmospheric conditions and other influences are important. This study provides evidence on the connection between intraseasonal variations of tides in the upper atmosphere and the changes in the forcing by latent heat release in the troposphere.

Liu, Guiping↗
NASA NTRS2019

Quantifying the Storm Time Thermospheric Neutral Density Variations Using Model and Observations

Accurate determination of thermospheric neutral density holds crucial importance for satellited rag calculations. The problem is twofold and involves the correct estimation of the quiet time climatology and storm time variations. In this work, neutral density estimations from two empirical and threephysics based models of the ionosphere thermosphere are compared with the neutral densities along the Challenging MicroSatellite Payload satellite track for six geomagnetic storms. Storm time variations are extracted from neutral density by (1) subtracting the mean difference between model and observation (bias),(2) setting climatological variations to zero, and (3) multiplying model data with the quiet time ratio between the model and observation. Several metrics are employed to evaluate the model performances. We find that the removal of bias or climatology reveals actual performance of the model in simulating the storm time variations. When bias is removed, depending on event and model, storm time errors in neutral density can decrease by an amount of 113% or can increase by an amount of 12% with respect to error in models with quiet time bias. It is shown that using only average and maximum values of neutral density to determine the model performances can be misleading since a model can estimate the averages fairly well but may not capture the maximum value or vice versa. Since each of the metrics used for determining model performances provides different aspects of the error, among these, we suggest employing mean absolute error, prediction efficiency, and normalized root mean square error together as a standard set ofmetrics for the neutral density.

Eyiguler, E. Ceren Kalafatoglu↗
NASA NTRSDate not supplied

Impact of Powder Supply Variation on Mechanical Properties for Additive Manufacture of Alloy 718

The Additive Manufacturing Structural Integrity Initiative (AMSII) examined how a number of different Alloy 718 powder lots can create variation in microstructure and mechanical properties in parts fabricated using Laser Powder Bed Fusion. Being a common alloy, Alloy 718 powder can be found in a variety of compositions, fabrication techniques, and powder size distribution. Sixteen virgin powders, and three recycled powders were used to build samples for microstructure analysis, fatigue and tensile testing. The major impacts of the different powders manifested in variations in the microstructure, such as minor phases and grain size variation. There were corresponding variations in mechanical properties. A down-selection of powders were chosen for additional analysis, and a powder recyclability study was completed to look at the effect of reused powder.

Alloy 718↗
NASA NTRS2022

Canopy height and climate dryness parsimoniously explain spatial variation of unstressed stomatal conductance

The spatio-temporal variation of stomatal conductance directly regulates photosynthesis, water partitioning, and biosphere-atmosphere interactions. While many studies have focused on stomatal response to stresses, the spatial variation of unstressed stomatal conductance remains poorly determined, and is usually characterized in land surface models (LSMs) simply based on plant functional type (PFT). Here, we derived unstressed stomatal conductance at the ecosystem-scale using observations from 115 global FLUXNET sites. When aggregated by PFTs, the across-PFT pattern was highly consistent with the parameterizations of LSMs. However, PFTs alone captured only 17% of the variation in unstressed stomatal conductance across sites. Within the same PFT, unstressed stomatal conductance was negatively related to climate dryness and canopy height, which explained 45% of the total spatial variation. Our results highlight the importance of plant environment interactions in shaping stomatal traits. The trait-environment relationship established here provides an empirical approach for improved parameterizations of stomatal conductance in LSMs.

Yanlan Liu↗
NASA NTRS2023

An Assessment of Stratospheric Water Vapor Trends and Variations Above the Boulder Region

This study analyzes time series of stratospheric water vapor (SWV) data at 30 hPa, based on frost-point hygrometer (FPH) measurements at Boulder, CO (40°N, 255°E), and on sets of HALOE scans above that region for 1993 through 2005; their differing trends agree with previously published findings. Yet, there is an apparent switch over in 2002 from positive to negative trends in the HALOE time series, and that change follows the episodic decrease of tropical, lower stratospheric SWV in early 2001. The HALOE data points only resolve medium to large scale spatial variations, as they are based on an average of four or more limb scans within a latitude/longitude sector near Boulder. The FPH time series do not indicate a similar change of trend in 2002, although its time series points have variations about the mean that are twice as large as those from HALOE. The FPH soundings are sensitive to variations from all spatial scales, however, including the effects of a local vertical mixing of the air due to gravity waves. The vertical gradient SWV mixing ratio with altitude is positive at 30 hPa. There is also a positive trend in methane and its conversion to water vapor during this time that may explain a slightly larger SWV trend from the local FPH data than from the HALOE data. The Nimbus 7 LIMS experiment provides daily SWV plots at medium to large scales during the dynamically active, winter and springtime periods, for assessing the effects of meridional transport of SWV from its source regions. There is transport of high SWV from polar regions and of lower SWV from the subtropics at those times. SWV variations and trends from both the FPH and HALOE time series are reasonable and in accord with the spatial scales that they observed.

Ellis Remsberg↗
NASA NTRSDate not supplied

Variation in Predicted Orbital Lifetime Due to Launch Year

We present trends in predicted orbital lifetimes of CubeSats based not only on orbital parameters, but also launch year and the Area-to-Mass (AtM) ratio of the CubeSat. Determining the orbital lifetime variation of CubeSats in low-Earth orbit (LEO) is an important aspect of mission planning because of two competing factors: (1) the maximum orbital lifetime for orbital debris mitigation requirements, and (2) the minimum orbit duration necessary to accomplish the spacecraft mission requirements. The orbital lifetime is a function of orbital parameters, the AtM ratio of the CubeSat, and date of orbit insertion. Solar flux varies with time, peaking and declining across the 11-year solar cycle and affecting the amount of atmospheric drag on the CubeSat. This results in large variations in orbital lifetime dependent on the mission's launch date. We calculated the variation of orbital lifetime for multiple commonly used 1U to 6U CubeSat mission types across the two upcoming solar cycles. For any given AtM ratio and altitude combination in this analysis, the predicted orbital lifetime varies up to a factor of five due to orbit insertion occurring in a different year. Some examples of orbital lifetime spreads are 5 months to 2 years, and 1.5 to 7.5 years. While orbital lifetimes correlate to the solar cycle, the phasing of the maximum values varies based on a given AtM ratio and altitude combination. Different combinations of these two factors will result in the maximum predicted orbital lifetime occurring at different launch years throughout the solar cycle. Therefore, there is not a specific year within a solar cycle which can be used to calculate the maximum predicted orbital lifetime for all CubeSats. Since CubeSats are typically flown as a rideshare payload on a launch vehicle, mission planners must account for launch date variation in their orbital lifetime predictions. We recommend calculating orbital lifetime for a range of dates to allow for risk planning due to launch date slips, and other mission planning best practices.

CubeSat↗
DOE OSTI2021

Variational Information Planning for Sequential Decision Making

We consider the setting of sequential decision making where, at each stage, potential actions are evaluated based on expected reduction in posterior uncertainty, given by mutual information (MI). As MI typically lacks a closed form, we propose an approach which maintains variational approximations of, both, the posterior and MI utility. Our planning objective extends an established variational bound on MI to the setting of sequential planning. The result, variational information planning (VIP), is an efficient method for sequential decision making. We further establish convexity of the variational planning objective and, under conditional exponential family approximations, we show that the optimal MI bound arises from a relaxation of the well-known exponential family moment matching property. Here, we demonstrate VIP for sensor selection, experiment design, and active learning, where it meets or exceeds methods requiring more computation, or those specialized to the task.

Pacheco, Jason↗
DOE OSTI2026

An Introduction to Variational Calculus

Variational Calculus is an advanced topic in mathematics. This document exists to compile the basics of Variational Calculus in a readable and digestible manner for application by engineers. This document is a living document and will be updated as time moves forward. It is the hope that by reading this document, the basics of Variational Calculus can be readily applied to any system/function of interest. This does not serve as a replacement for textbooks or other learned sources but should act as a companion piece to better serve the reader in times of confusion and distress.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A variational multiscale immersed meshfree method for heterogeneous materials

Abstract We introduce an immersed meshfree formulation for modeling heterogeneous materials with flexible non-body-fitted discretizations, approximations, and quadrature rules. The interfacial compatibility condition is imposed by a volumetric constraint, which avoids a tedious contour integral for complex material geometry. The proposed immersed approach is formulated under a variational multiscale based formulation, termed the variational multiscale immersed method (VMIM). Under this framework, the solution approximation on either the foreground or the background can be decoupled into coarse-scale and fine-scale in the variational equations, where the fine-scale approximation represents a correction to the residual of the coarse-scale equations. The resulting fine-scale solution leads to a residual-based stabilization in the VMIM discrete equations. The employment of reproducing kernel (RK) approximation for the coarse- and fine-scale variables allows arbitrary order of continuity in the approximation, which is particularly advantageous for modeling heterogeneous materials. The effectiveness of VMIM is demonstrated with several numerical examples, showing accuracy, stability, and discretization efficiency of the proposed method.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Elucidating the effect of preheating temperature on melt pool morphology variation in Inconel 718 laser powder bed fusion via simulation and experiment

In laser powder bed fusion (L-PBF) additive manufacturing, the mechanical performance, microstructure and defects of fabricated parts are closely associated with the melt pool morphology, e.g., its dimension and shape through the building process. Past studies have largely focused on how the process parameters such as laser power and scan speed affect melt pool characteristics. In this study, the melt pool morphology variation as a function of preheating temperature in the conduction, transition, and keyhole regimes and the underlying mechanisms in each regime are investigated through ex-situ sample characterization and computation thermal fluid dynamics (CtFD) simulation. Single tracks with different combinations of laser power and scan speed are deposited on an Inconel 718 bare plate preheated to a temperature range of 100–500 °C in the experiment. Significant changes are observed in melt pool morphology as a function of preheating temperature from optical measurements of melt track cross sections. The depth of melt pool in the three regimes increases monotonically with preheating temperature, e.g., at 500 °C, the experimental melt pool depth is increased by 49% in conduction regime, 34% in transition regime and 33% in keyhole regime, respectively, while the variation of melt pool width in each regime does not all follow an increasing trend but depends on the melt pool regimes. Melt pool width variation in the conduction and transition regimes is found to depend on the enhanced heat conduction directly related to temperature dependent thermal properties. Through validated CtFD simulations, it is found that in the keyhole regime the evaporation mass, recoil pressure, and laser drilling effect is enhanced with higher preheating temperature, which gives rise to a deeper melt pool. The simulations also reveal that preheating temperature significantly elongates the melt track length due to the increased flow rate and strong recoil pressure that accelerates the backward flow.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Variational encoder geostatistical analysis (VEGAS) with an application to large scale riverine bathymetry

Estimation of riverbed profiles, also known as bathymetry, plays a vital role in many applications, such as safe and efficient inland navigation, prediction of bank erosion, land subsidence, and flood risk management. The high cost and complex logistics of direct bathymetry surveys, i.e, depth imaging, have encouraged the use of indirect measurements such as surface flow velocities. However, estimating high-resolution bathymetry from indirect measurements is an inverse problem that can be computationally challenging. Here, we propose a reduced-order model (ROM) based approach that utilizes a variational autoencoder (VAE), a type of deep neural network with a narrow layer in the middle, to compress bathymetry and flow velocity information and accelerate bathymetry inverse problems from flow velocity measurements. In our application, the shallow-water equations (SWE) with appropriate boundary conditions (BCs), e.g., the discharge and/or the free surface elevation, constitute the forward problem, to predict flow velocity. Then, ROMs of the SWEs are constructed on a nonlinear manifold of low dimensionality through a variational encoder and the bathymetry inversion problem is derived on the low-dimensional latent space in a Hierarchical Bayesian setting. Further, the reformulation allows variational inference with a small number (e.g., $\mathscr{O}$ (100) of ROM runs and efficient uncertainty quantification. We have tested our inversion approach on a one-mile reach of the Savannah River, GA, USA. Once the neural network is trained (offline stage), the proposed technique can perform the inversion operation orders of magnitude faster than traditional inversion methods that are commonly based on linear projections, such as principal component analysis (PCA), or the principal component geostatistical approach (PCGA). Furthermore, tests show that the algorithm can estimate the bathymetry with good accuracy even with sparse flow velocity measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A variational phase-field framework for thermal softening and dynamic ductile fracture

A variational phase field model for dynamic ductile fracture is presented. Here, the model is designed for elasto-viscoplastic materials subjected to rapid deformations in which the effects of heat generation and material softening are dominant. The variational framework allows for the consistent inclusion of plastic dissipation in the heat equation as well as thermal softening. It employs a coalescence function to degrade fracture energy during regimes of high plastic flow. A variationally consistent form of the Johnson–Cook model is developed for use with the framework. Results from various benchmark problems in dynamic ductile fracture are presented to demonstrate capabilities. In particular, the ability of the model to regularize shear band formation and subsequent damage evolution in two- and three-dimensional problems is demonstrated. Importantly, these phenomena are naturally captured through the underlying physics without the need for phenomenological criteria such as stability thresholds for the onset of shear band formation.

42 ENGINEERING↗
DOE OSTI2024

Investigation of inter-subject variation in ultrafine particle deposition across human nasal airways: A study involving children, adults, and the elderly

Occupational and environmental exposure to toxic nanoparticles, driven by the rapid expansion of nanotechnology, raises significant respiratory health concern. Numerous studies have explored airflow and particle dynamics in adult nasal airways, but understanding the impact of age-related anatomical changes in children and the elderly remains limited. This study systematically investigates age-related anatomical variations and associated influence on nasal airflow dynamics and ultrafine particle deposition characteristics. Using Computational Fluid-Particle Dynamics (CFPD) method, simulation was conducted under diverse inhalation conditions spanning a wide age range, including: two children (5 years old), two young adults (in their twenties), and two elderly (over 77 years old). Our results reveal distinctive variations across age groups in anatomical dimensions, which affect distribution of wall shear stress where the elderly and children display unique patterns distinct from the young adults. While total deposition efficiency differs significantly between children and adults, filtration efficiency in the subregion with most deposition, main respiratory, remains consistent. However, inter-subject differences are observed in the vestibular and olfactory regions,emphasizing nuanced impact of age-related anatomical variations. Overall and subregional empirical equations for deposition efficiency were developed by incorporating the combined diffusion parameter, Sc a Δ b , corroborating the use of geometrical characteristic parameters for each specific subject in predicting nasal deposition efficiency across age groups. Our findings contribute to predictive nanoparticle exposure analysis in nasal airways across different age groups, thereby enhancing respiratory healthcare for individuals across the life span.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Variational quantum state eigensolver

Extracting eigenvalues and eigenvectors of exponentially large matrices will be an important application of near-term quantum computers. The variational quantum eigensolver (VQE) treats the case when the matrix is a Hamiltonian. Here, we address the case when the matrix is a density matrix ρ. We introduce the variational quantum state eigensolver (VQSE), which is analogous to VQE in that it variationally learns the largest eigenvalues of ρ as well as a gate sequence V that prepares the corresponding eigenvectors. VQSE exploits the connection between diagonalization and majorization to define a cost function C=Tr(ρ~H) where H is a non-degenerate Hamiltonian. Due to Schur-concavity, C is minimized when ρ~=VρV† is diagonal in the eigenbasis of H. VQSE only requires a single copy of ρ (only n qubits) per iteration of the VQSE algorithm, making it amenable for near-term implementation. We heuristically demonstrate two applications of VQSE: (1) Principal component analysis, and (2) Error mitigation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

A Facile Approach to High Precision Detection of Cell-to-Cell Variation for Li-ion Batteries

Abstract Over the past decade, it has been repeatedly demonstrated that homogeneity in electrochemical performance of lithium-ion cells plays a major role in determining the life and safety of lithium-ion battery modules or packs. Generally, the homogeneity of a battery pack is evaluated by characterizing the cells individually in terms of capacity, mass, impedance. Particularly, high quality electrochemical data heavily relies on the availability of high precision current source to minimize the discrepancy induced by the channel-to-channel variation. Here, a facile and precise measurement method is reported for screening cell-to-cell variations, in which voltage is the only indicator parameter independent of high precision current source. In detail, by connecting the cells in series (CiS), the measurement error of electrochemical data caused by stability and discrepancy of current sources among different charge/discharge equipment can be effectively avoided. The findings of this work showed that the cell-to-cell variations can be simply and sensitively detected with CiS configuration. For example, the relative standard deviation, which is the evaluation criterion of battery homogeneity, was 2.14% based on CiS while it was 0.43% based on individual measurements. The simple and precise CiS measurement is promising for evaluation of cell quality or module integration quality. In addition, this work can also provide a solid foundation for the development of detection algorithms for battery management systems to rapidly monitor battery homogeneity.

25 ENERGY STORAGE↗
DOE OSTI2020

A non-orthogonal variational quantum eigensolver

Variational algorithms for strongly correlated chemical and materials systems are one of the most promising applications of near-term quantum computers. We present an extension to the variational quantum eigensolver that approximates the ground state of a system by solving a generalized eigenvalue problem in a subspace spanned by a collection of parametrized quantum states. This allows for the systematic improvement of a logical wavefunction ansatz without a significant increase in circuit complexity. To minimize the circuit complexity of this approach, we propose a strategy for efficiently measuring the Hamiltonian and overlap matrix elements between states parametrized by circuits that commute with the total particle number operator. This strategy doubles the size of the state preparation circuits but not their depth, while adding a small number of additional two-qubit gates relative to standard variational quantum eigensolver. We also propose a classical Monte Carlo scheme to estimate the uncertainty in the ground state energy caused by a finite number of measurements of the matrix elements. We explain how this Monte Carlo procedure can be extended to adaptively schedule the required measurements, reducing the number of circuit executions necessary for a given accuracy. We apply these ideas to two model strongly correlated systems, a square configuration of H4 and the π-system of hexatriene (C6H8).

97 MATHEMATICS AND COMPUTING↗