Search NASA⌕ Search

SEARCH · Search NASA

Results for “test case”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Global Sensitivity Analysis with Small Sample Sizes: Ordinary Least Squares Approach

A new version of global sensitivity analysis is developed in this paper. This new version coupled with tools from statistics, machine learning, and optimization can devise small sample sizes that allow for the accurate ordering of sensitivity coefficients for the first 10-30 most sensitive chemical reactions in complex chemical-kinetic mechanisms, and is particularly useful for studying the chemistry in realistic devices. A key part of the paper is calibration of these small samples. Because these small sample sizes are developed for use in realistic combustion devices, the calibration is done over the ranges of conditions in such devices, with a test case being the operating conditions of a compression ignition engine studied earlier. Compression ignition engines operate under low-temperature combustion conditions with quite complicated chemistry making this calibration difficult, leading to the possibility of false positives and false negatives in the ordering of the reactions. So an important aspect of the paper is showing how to handle the trade-off between false positives and false negatives using ideas from the multiobjective optimization literature. The combination of the new global sensitivity method and the calibration are sample sizes a factor of approximately 10 times smaller than were available with our previous algorithm.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Facile Background Discrimination in Femtosecond Stimulated Raman Spectroscopy Using a Dual-Frequency Raman Pump Technique

Femtosecond stimulated Raman spectroscopy (FSRS) is a useful technique for uncovering chemical reaction dynamics by acquiring high-resolution Raman spectra with ultrafast time resolution. However, in FSRS, it can be challenging to discern Raman features from signals arising from transient absorption and other four-wave mixing pathways. To overcome this difficulty, we combine the principles of shifted excitation Raman difference spectroscopy with a simple fixed frequency comb to perform dual-frequency Raman pump FSRS. Through the addition of only two mirrors and a slit to the standard FSRS setup, this method provides Raman spectra at two different excitation wavelengths that can be processed by an automated algorithm to reconstruct the Raman spectrum. In this study, we demonstrate the utility of dual-frequency Raman pump FSRS to easily identify Raman signatures by visual inspection for excited-state and ground-state spectra, both on- and off-resonance. We show that previously assigned short-lived vibrations of photoexcited β-carotene are actually not vibrational in nature. We also use crystalline betaine-30 as a challenging test case for this method, as the FSRS spectra contain a number of narrow transient vibronic and non-SRS features. By reliably reducing interference from background signals, the interpretation is substantially more quantitative and enables the future study of new systems, particularly those with small Raman cross-sections or solid-state samples with narrow vibronic features.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Molecular dynamics simulations of hydrogen diffusion in aluminum

In this study, hydrogen diffusion impacts the performance of solid-state hydrogen storage materials and contributes to the embrittlement of structural materials under hydrogen-containing environments. In atomistic simulations, the diffusion energy barriers are usually calculated using molecular statics simulations where a nudged elastic band method is used to constrain a path connecting the two end points of an atomic jump. This approach requires prior knowledge of the “end points”. For alloy and defective systems, the number of possible atomic jumps with respect to local atomic configurations is tremendous. Even when these jumps can be exhaustively studied, it is still unclear how they can be combined to give an overall diffusion behavior seen in experiments. Here we describe the use of molecular dynamics simulations to determine the overall diffusion energy barrier from the Arrhenius equation. This method does not require information about atomic jumps, and it has additional advantages, such as the ability to incorporate finite temperature effects and to determine the pre-exponential factor. As a test case for a generic method, we focus on hydrogen diffusion in bulk aluminum. We find that the challenge of this method is the statistical variation of the results. However, highly converged energy barriers can be achieved by an appropriate set of temperatures, output time intervals (for tracking hydrogen positions), and a long total simulation time. Our results help elucidate the inconsistencies of the experimental diffusion data published in the literature. The robust approach developed here may also open up future molecular dynamics simulations to rapidly study diffusion properties of complex material systems in multidimensional spaces involving composition and defects.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Real-Time Time-Dependent Nuclear–Electronic Orbital Approach: Dynamics beyond the Born–Oppenheimer Approximation

The quantum mechanical treatment of both electrons and nuclei is crucial in nona- diabatic dynamical processes such as proton-coupled electron transfer. The nuclear electronic orbital (NEO) method provides an elegant framework for including nuclear quantum effects beyond the Born-Oppenheimer approximation. To enable the study of nonequilibrium properties, we derive and implement a real-time NEO (RT-NEO) approach based on time-dependent Hatree-Fock or density functional theory, in which both the electronic and nuclear degrees of freedom are propagated in a time-dependent variational framework. Nuclear and electronic spectral features can be resolved from the time-dependent dipole moment computed using the RT-NEO method. The test cases demonstrate the dynamical interplay between the quantum nuclei and the electrons through vibronic coupling. Moreover, vibrational excitation in the RT-NEO approach is demonstrated by applying a resonant driving eld, and electronic excitation is demonstrated by simulating excited state intramolecular proton transfer. This work shows that the RT-NEO approach is a promising tool to study nonadiabatic quantum dynamical processes within a time-dependent variational description for the coupled electronic and nuclear degrees of freedom.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Reproducing Quantum Probability Distributions at the Speed of Classical Dynamics: A New Approach for Developing Force-Field Functors

Modeling nuclear quantum effects is required for accurate molecular dynamics (MD) simulations of molecules. The community has paid special attention to water and other biomolecules that show hydrogen bonding. Standard methods of modeling nuclear quantum effects like Ring Polymer Molecular Dynamics (RPMD) are computationally costlier than running classical trajectories. A force-field functor (FFF) is an alternative method that computes an effective force field that replicates quantum properties of the original force field. In this work, we propose an efficient method of computing FFF using the Wigner–Kirkwood expansion. As a test case, we calculate a range of thermodynamic properties of Neon, obtaining the same level of accuracy as RPMD, but with the shorter runtime of classical simulations. Lastly, by modifying existing MD programs, the proposed method could be used in the future to increase the efficiency and accuracy of MD simulations involving water and proteins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Characterization of Ultrathin Polymer Films Using p-polarized ATR-FTIR and Its Comparison with XPS

Here, we report on the chemical analysis of ultrathin (10 nm) polymer films using attenuated total reflectance (ATR)–FTIR technique based on p-polarized IR light and two types of enhancing substrates, i.e. metallic (Au) and dielectric (Si). We selected low temperature plasma treated ~10 nm-thick polystyrene films as a test case for demonstrating the capability of the p-polarized ATR-FTIR whose performance was further compared with the conventional X-ray photoelectron spectroscopy (XPS) techniques. Although the ATR-FTIR cannot be used for quantitatively determining elemental compositions in polymers at which XPS excels, it allows to be operated under non-vacuum conditions and study hydrogen containing moieties. By correcting the contact condition between polymer surface and ATR prism, the relative concentration of the chemical bonds from different samples can be compared. Since ATR-FTIR and XPS provide complementary information on chemical bonds, their combination provides a powerful approach for studying the composition and bonding of polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ionic Liquid Gating of SrTiO 3 Lamellas Fabricated with a Focused Ion Beam

Here, in this work, we combine two previously incompatible techniques for defining electronic devices: shaping three-dimensional crystals by focused ion beam (FIB), and two-dimensional electrostatic accumulation of charge carriers. The principal challenge for this integration is nanometer-scale surface damage inherent to any FIB-based fabrication. We address this by using a sacrificial protective layer to preserve a selected pristine surface. The test case presented here is accumulation of 2D carriers by ionic liquid gating at the surface of a micron-scale SrTiO 3 lamella. Preservation of surface quality is reflected in superconductivity of the accumulated carriers. This technique opens new avenues for realizing electrostatic charge tuning in materials that are not available as large or exfoliatable single crystals, and for patterning the geometry of the accumulated carriers.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Cell-Format-Dependent Mechanical Damage in Silicon Anodes

Strong binders can be counterproductive for silicon anodes. Here, we show that stresses from cycling Si-based electrodes can cause permanent stretching and wrinkling of the current collector. Furthermore, this deformation damages the electrode coating and accelerates cell aging due to the inactivation of Si domains and facilitation of Li plating. Interestingly, we demonstrate that the formation of wrinkles is size-dependent, being present in pouch cells but absent from coin cells. This size-dependent performance decay indicates that, in extreme cases, testing outcomes are highly dependent on scale and that the validation of battery materials may require testing at larger cell formats.

25 ENERGY STORAGE↗
DOE OSTI2024

Monitoring Redox Processes in Lithium-Ion Batteries by Laboratory-Scale Operando X-ray Emission Spectroscopy

Tracking changes in the chemical state of transition metals in alkali-ion batteries is crucial to understanding the redox chemistry during operation. X-ray absorption spectroscopy (XAS) is often used to follow the chemistry through observed changes in the chemical state and local atomic structure as a function of the state-of-charge (SoC) in batteries. In this study, we utilize an operando X-ray emission spectroscopy (XES) method to observe changes in the chemical state of active elements in batteries during operation. Operando XES and XAS were compared by using a laboratory-scale setup for four different battery systems: LiCoO 2 (LCO), Li[Ni 1/3 Co 1/3 Mn 1/3 ]O 2 (NMC111), Li[Ni 0.8 Co 0.1 Mn 0.1 ]O 2 (NMC811), and LiFePO 4 (LFP) under a constant current charging the battery in 10 h (C/10 charge rate). We show that XES, despite narrower chemical shifts in comparison to XAS, allows us to fingerprint the battery SOC in real time. We further demonstrate that XES can be used to track the change in net spin of the probed atoms by analyzing changes in the emission peak shape. As a test case, the connection between net spin and the local chemical and structural environment was investigated by using XES and XAS in the case of electrochemically delithiated LCO in the range of 2–10% lithium removal.

25 ENERGY STORAGE↗
DOE OSTI2019

Elimination of Response to Relative Humidity Changes in Chemical-Sensitive Field-Effect Transistors

Detecting accurate concentrations of gas in environments with dynamically changing relative humidity conditions has been a challenge in gas sensing technology. Here, we report a method to eliminate effects of humidity response in chemical-sensitive field-effect transistors using microheaters. Using a hydrogen gas sensor with Pt/FOTS active material as a test case, we demonstrate that a sensor response of 3844% to a relative humidity change of 50 to 90% at 25 °C can be reduced to a negligible response of 11.6% by utilizing microheaters. We also show the advantage of this technique in maintaining the same sensitivity in changing ambient temperatures and its application to the nitrogen dioxide gas sensors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Predictive Model for Particle Residence Time Distributions in Riser Reactors. Part 1: Model Development and Validation

Here in this computational study, we model the mixing of biomass pyrolysis vapor with solid catalyst in circulating riser reactors with a focus on the determination of solid catalyst residence time distributions (RTDs). A comprehensive set of 2D and 3D simulations were conducted for a pilot-scale riser using the Eulerian-Eulerian two-fluid modeling framework with and without sub-grid-scale models for the gas-solids interaction. A validation test case was also simulated and compared to experiments, showing agreement in the pressure gradient and RTD mean and spread. For simulation cases, it was found that for accurate RTD prediction, the Johnson and Jackson partial slip solids boundary condition was required for all models and a sub-grid model is useful so that ultra high resolutions grids that are very computationally intensive are not required. Finally, we discovered a 2/3 scaling relation for the RTD mean and spread when comparing resolved 2D simulations to validated unresolved 3D sub-grid-scale model simulations.

09 BIOMASS FUELS↗
DOE OSTI2026

Concerted Proton–Electron Transfer Minimizes Substituent Effects on Adsorbed Phthalocyanine Electrocatalysis

Molecularly modified electrodes (MMEs) are potent electrocatalysts, but few principles exist for their rational design. Electrocatalysis by soluble molecules depends strongly on substituents that tune the catalyst redox potential (E 1/2 ), but it is unclear if this parameter similarly impacts MME catalysis. Herein, we employ the hydrogen evolution reaction (HER) as a test case for comparing carbon-adsorbed cobalt phthalocyanine (CoPc/C) and cobalt hexadecafluoro-phthalocyanine (CoFPc/C). By correlating HER activity and voltammetric data to total Co surface concentration across a wide range of catalyst loadings, we find that only 5–25% of adsorbed Co sites contribute to the Co(II/I) redox wave and that this subpopulation poorly correlates with catalytic activity. Instead, in the low-loading limit, catalytic activity correlates linearly with the majority Co(II/I)-silent Co population, revealing per-site turnover frequency (TOF) values for HER. Despite a 230 mV difference in Co(II/I) redox potentials, CoPc/C and CoFPc/C display TOF values differing by less than a factor of 3 when compared over a wide potential range. Mechanistic studies point to an inner-sphere concerted proton–electron transfer step as rate-determining, suggesting that the Co–H bond dissociation free energy (BDFE) rather than the Co(II/I) E 1/2 is thermodynamically relevant. Computational studies indicate that the fluoro-substituents lead to compensatory changes in Co(II/I) E 1/2 and Co(I) basicity, leaving the Co–H BDFE largely unchanged between CoPc and CoFPc and thereby manifesting in similar catalytic rates. Furthermore, these results highlight the limited effect of E 1/2 -tuning on MME catalytic activity and motivate the development of methods to directly alter active site–substrate BDFE.

Catalysts↗
DOE OSTI2020

Embedding Methods for Quantum Chemistry: Applications from Materials to Life Sciences

Quantum mechanical embedding methods hold the promise to transform not just the way calculations are performed, but to significantly reduce computational costs and improve scaling for macro molecular systems containing hundreds if not thousands of atoms. The field of embedding has grown increasingly broad with many approaches of different intersecting flavors. Here, we lay out the methods into two streams: QM:MM and QM:QM, showcasing the advantages and disadvantages of both. We provide a review of the literature, the underpinning theories including our contributions, and we highlight current applications with select examples spanning both materials and life sciences. Lastly, we conclude with prospects and future outlook on embedding, and our view on the use of universal test case scenarios for cross comparisons of the many available (and future) embedding theories.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Response of Tropical Terrestrial Gross Primary Production to the Super El Niño Event in 2015

The gross primary production (GPP) in tropical terrestrial ecosystems plays a critical role in the global carbon cycle and climate change. The strong 2015–2016 El Niño event offers a unique opportunity to investigate how GPP in the tropical terrestrial ecosystems responds to climatic forcing. This study uses two GPP products and concurrent climate data to investigate the GPP anomalies and their underlying causes. We find that both GPP products show an enhanced GPP in 2015 for the tropical terrestrial ecosystem as a whole relative to the multiyear mean of 2001–2015, and this enhancement is the net result of GPP increase in tropical forests and decrease in nonforests. We show that the increased GPP in tropical forests during the El Nino event is consistent with increased photosynthesis active radiation as a result of a reduction in clouds, while the decreased GPP in nonforests is consistent with increased water stress as a result of a reduction of precipitation and an increase of temperature. These results reveal the strong coupling of ecosystem and climate that is different in forest and nonforest ecosystems and provide a test case for carbon cycle parameterization and carbon-climate feedback simulation in models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The Role of Subsurface Flow on Evapotranspiration: A Global Sensitivity Analysis

Abstract Water resources are impacted by water‐energy balance fluxes at the land surface, most notably evapotranspiration ( ET ), the largest component of surface energy balance. While integrated hydrologic models show promise in quantifying the nonlinear dynamics at this interface, the model results are plagued by parametric uncertainties. Given the high computational demand of running multiple parameter spaces of these models, little is known about how these uncertainties propagate into land surface processes. In this work, we perform a global sensitivity analysis by computing Sobol and AMAE indices using a surrogate model constructed with a polynomial chaos expansion to assess the impacts of the subsurface physical properties on ET . We do so by modeling a semisynthetic test case. Our results show that the effects of vertical hydraulic conductivity, porosity, and the water retention curve parameter Van Genuchten α mainly control ET . However, we note that while evaporation ( E ) shows behavior similar to the ET with high sensitivity to the parameters controlling the flow in the unsaturated zone, transpiration ( T ) is very sensitive to the saturated zone parameters and groundwater flow, especially during periods without rain. Our results also show that heterogeneities in land cover impact the flow in the saturated zone. Furthermore, our work demonstrates that reduced‐order models can be developed to make integrated models more accessible for rigorous sensitivity analyses and calibration purposes.

Maina, Fadji Zaouna↗
DOE OSTI2021

A Benchmark to Test Generalization Capabilities of Deep Learning Methods to Classify Severe Convective Storms in a Changing Climate

Abstract This is a test case study assessing the ability of deep learning methods to generalize to a future climate (end of 21st century) when trained to classify thunderstorms in model output representative of the present‐day climate. A convolutional neural network (CNN) was trained to classify strongly rotating thunderstorms from a current climate created using the Weather Research and Forecasting model at high‐resolution, then evaluated against thunderstorms from a future climate and found to perform with skill and comparatively in both climates. Despite training with labels derived from a threshold value of a severe thunderstorm diagnostic (updraft helicity), which was not used as an input attribute, the CNN learned physical characteristics of organized convection and environments that are not captured by the diagnostic heuristic. Physical features were not prescribed but rather learned from the data, such as the importance of dry air at mid‐levels for intense thunderstorm development when low‐level moisture is present (i.e., convective available potential energy). Explanation techniques also revealed that thunderstorms classified as strongly rotating are associated with learned rotation signatures. Results show that the creation of synthetic data with ground truth is a viable alternative to human‐labeled data and that a CNN is able to generalize a target using learned features that would be difficult to encode due to spatial complexity. Most importantly, results from this study show that deep learning is capable of generalizing to future climate extremes and can exhibit out‐of‐sample robustness with hyperparameter tuning in certain applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Bayesian Poroelastic Aquifer Characterization From InSAR Surface Deformation Data. Part I: Maximum A Posteriori Estimate

Characterizing the properties of groundwater aquifers is essential for predicting aquifer response and managing groundwater resources. In this work, we develop a high-dimensional scalable Bayesian inversion framework governed by a three-dimensional quasi-static linear poroelastic model to characterize lateral permeability variations in groundwater aquifers. In this work, we determine the maximum a posteriori (MAP) point of the posterior permeability distribution from centimeter-level surface deformation measurements obtained from Interferometric Synthetic Aperture Radar (InSAR). The scalability of our method to high parameter dimension is achieved through the use of adjoint-based derivatives, inexact Newton methods to determine the MAP point, and a Mat´ern class sparse prior precision operator. Together, these guarantee that the MAP point is found at a cost, measured in number of forward/adjoint poroelasticity solves, that is independent of the parameter dimension. We apply our methodology to a test case for a municipal well in Mesquite, Nevada, in which InSAR and GPS surface deformation data are available. We solve problems with up to 320,824 state variable degrees of freedom (DOFs) and 16,896 parameter DOFs. A consistent treatment of noise level is employed so that the aquifer characterization result does not depend on the pixel spacing of surface deformation data. Our results show that the use of InSAR data significantly improves characterization of lateral aquifer heterogeneity, and the InSAR-based aquifer characterization recovers complex lateral displacement trends observed by independent daily GPS measurements.

54 ENVIRONMENTAL SCIENCES↗