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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Theoretical Infrared Spectra for Polycyclic Aromatic Hydrocarbon Neutrals, Cations and Anions

Calculations are carried out using density functional theory (DFT) to determine the harmonic frequencies and intensities of the neutrals and cations of thirteen polycyclic aromatic hydrocarbons (PAHs) up to the size of ovalene. Calculations are also carried out for a few PAH anions. The DFT harmonic frequencies, when uniformly scaled by the factor of 0.958 to account primarily for anharmonicity, agree with the matrix isolation fundamentals to within an average error of about 10 per centimeter. Electron correlation is found to significantly reduce the intensities of many of the cation harmonics, bringing them into much better agreement with the available experimental data. While the theoretical infrared spectra agree well with the experimental data for the neutral systems and for many of the cations, there are notable discrepancies with the experimental matrix isolation data for some PAH cations that are difficult to explain in terms of limitations in the calculations. In agreement with previous theoretical work, the present calculations show that the relative intensities for the astronomical unidentified infrared (UIR) bands agree reasonably well with those for a distribution of polycyclic aromatic hydrocarbon (PAH) cations, but not with a distribution of PAH neutrals. We also observe that the infrared spectra of highly symmetrical cations such as coronene agree much better with astronomical observations than do those of, for example, the polyacenes such as tetracene and pentacene. The total integrated intensities for the neutral species are found to increase linearly with size, while the total integrated intensities are much larger for the cations and scale more nearly quadratically with size. We conclude that emission from moderate-sized highly symmetric PAH cations such as coronene and larger could account for the UIR bands.

Langhoff, Stephen R.↗
NASA NTRS2003

Phase Retrieval Using a Genetic Algorithm on the Systematic Image-Based Optical Alignment Testbed

NASA s Marshall Space Flight Center s Systematic Image-Based Optical Alignment (SIBOA) Testbed was developed to test phase retrieval algorithms and hardware techniques. Individuals working with the facility developed the idea of implementing phase retrieval by breaking the determination of the tip/tilt of each mirror apart from the piston motion (or translation) of each mirror. Presented in this report is an algorithm that determines the optimal phase correction associated only with the piston motion of the mirrors. A description of the Phase Retrieval problem is first presented. The Systematic Image-Based Optical Alignment (SIBOA) Testbeb is then described. A Discrete Fourier Transform (DFT) is necessary to transfer the incoming wavefront (or estimate of phase error) into the spatial frequency domain to compare it with the image. A method for reducing the DFT to seven scalar/matrix multiplications is presented. A genetic algorithm is then used to search for the phase error. The results of this new algorithm on a test problem are presented.

Taylor, Jaime R.↗
NASA NTRS1999

Pulse Phase Thermography for Defect Detection and Visualization

Pulse Phase Thermography (PPT) has been reported as a novel powerful technique of the thermal NDE. It employs application of the Discrete Fourier Transform (DFT) to thermal images obtained following flash heating of the front surface of a specimen. The computed phasegrams are excellent for defect visualization in a wide range of materials. This is in part due to their low sensitivity to uneven heating. This work is an attempt to analyze advantages and limitations of PPT. Results of application of the DFT to simulated temperature decays are presented. The temperature evolution on a surface has been simulated based on an analytical solution of the one-dimensional heat diffusion problem. A more sophisticated study has been done for different sizes of defects using numerical solution of the three-dimensional mathematical model. Capabilities of PPT for in-depth scanning and for monitoring of the material loss are discussed. The recommendations for the practical application of the PPT are presented. Experimental results obtained following these recommendations are reported.

Marinetti, Sergio↗
NASA NTRS2002

622-Mbps Orthogonal Frequency Division Multiplexing (OFDM) Digital Modem Implemented

Future generation space communications systems feature significantly higher data rates and relatively smaller frequency spectrum allocations than systems currently deployed. This requires the application of bandwidth- and power-efficient signal transmission techniques. There are a number of approaches to implementing such techniques, including analog, digital, mixed-signal, single-channel, or multichannel systems. In general, the digital implementations offer more advantages; however, a fully digital implementation is very difficult because of the very high clock speeds required. Multichannel techniques are used to reduce the sampling rate. One such technique, multicarrier modulation, divides the data into a number of low-rate channels that are stacked in frequency. Orthogonal frequency division multiplexing (OFDM), a form of multicarrier modulation, is being proposed for numerous systems, including mobile wireless and digital subscriber link communication systems. In response to this challenge, NASA Glenn Research Center's Communication Technology Division has developed an OFDM digital modem (modulator and demodulator) with an aggregate information throughput of 622 Mbps. The basic OFDM waveform is constructed by dividing an incoming data stream into four channels, each using either 16- ary quadrature amplitude modulation (16-QAM) or 8-phase shift keying (8-PSK). An efficient implementation for an OFDM architecture is being achieved using the combination of a discrete Fourier transform (DFT) at the transmitter to digitally stack the individual carriers, inverse DFT at the receiver to perform the frequency translations, and a polyphase filter to facilitate the pulse shaping.

Kifle, Muli↗
NASA NTRS2006

A dynamic fault tree model of a propulsion system

We present a dynamic fault tree model of the benchmark propulsion system, and solve it using Galileo. Dynamic fault trees (DFT) extend traditional static fault trees with special gates to model spares and other sequence dependencies. Galileo solves DFT models using a judicious combination of automatically generated Markov and Binary Decision Diagram models. Galileo easily handles the complexities exhibited by the benchmark problem. In particular, Galileo is designed to model phased mission systems.

propulsion system↗
NASA NTRS2004

Photoionization of Benzene and Small Polycyclic Aromatic Hydrocarbons in Ultraviolet-Processed Astrophysical Ices: A Computational Study

We employed density functional theory (DFT) calculations to model the photoionization behavior of benzene and small polycyclic aromatic hydrocarbons when they are embedded in a matrix of water ice in order to investigate issues raised by recent experimental work by Gudipati and Allamandola. The ionization energies of benzene, naphthalene, anthracene, and pyrene were found to be lowered by 1.5-2.1 eV in water ice. Low-lying vertical electronic excitation energies were computed with time-dependent DFT for both neutral and ionized species and are found in both cases to be remarkably unaffected by the ice matrix. Chemical behavior in ultraviolet-photoprocessed ices is also discussed, with a focus on electron recombination and pathways leading to phenol and analogous products.

Woon, D. E.↗
NASA NTRS2013

Method and system for dynamic probabilistic risk assessment

The DEFT methodology, system and computer readable medium extends the applicability of the PRA (Probabilistic Risk Assessment) methodology to computer-based systems, by allowing DFT (Dynamic Fault Tree) nodes as pivot nodes in the Event Tree (ET) model. DEFT includes a mathematical model and solution algorithm, supports all common PRA analysis functions and cutsets. Additional capabilities enabled by the DFT include modularization, phased mission analysis, sequence dependencies, and imperfect coverage.

Dugan, Joanne Bechta↗
NASA NTRS2013

Association Mechanisms of Unsaturated C2 Hydrocarbons with Their Cations: Acetylene and Ethylene

The ion-molecule association mechanism of acetylene and ethylene with their cations is investigated by ab initio quantum chemical methods to understand the structures, association energies, and the vibrational and electronic spectra of the products. Stable puckered cyclic isomers are found as the result of first forming less stable linear and bridge isomers. The puckered cyclic complexes are calculated to be strongly bound, by 87, 35 and 56 kcal/mol for acetylene-acetylene cation, ethylene-ethylene cation and acetylene-ethylene cation, respectively. These stable complexes may be intermediates that participate in further association reactions. There are no association barriers, and no significant inter-conversion barriers, so the initial linear and bridge encounter complexes are unlikely to be observable. However, the energy gap between the bridged and cyclic puckered isomers greatly differs from complex to complex: it is 44 kcal/mol in C4H4 +, but only 6 kcal/mol in C4H8 +. The accurate CCSD(T) calculations summarized above are also compared against less computationally expensive MP2 and density functional theory (DFT) calculations for structures, relative energies, and vibrational spectra. Calculated vibrational spectra are compared against available experiments for cyclobutadiene cation. Electronic spectra are also calculated using time-dependent DFT.

ethylene↗
NASA NTRS2015

Discrete Fourier Transform in a Complex Vector Space

An image-based phase retrieval technique has been developed that can be used on board a space based iterative transformation system. Image-based wavefront sensing is computationally demanding due to the floating-point nature of the process. The discrete Fourier transform (DFT) calculation is presented in "diagonal" form. By diagonal we mean that a transformation of basis is introduced by an application of the similarity transform of linear algebra. The current method exploits the diagonal structure of the DFT in a special way, particularly when parts of the calculation do not have to be repeated at each iteration to converge to an acceptable solution in order to focus an image.

Dean, Bruce H.↗
NASA NTRS2016

Simulations of Li+ in Ionic Liquids: Structure, Transport, and Electrochemical Windows

Ionic liquids have been proposed as candidate electrolytes for a number of electrochemical applications. The Li+ solvation structure in these liquids is of central importance to electrolyte properties, like ionic conductivity and electrochemical stability. To this point, we employ simulations at three different size scales to better understand various aspects of the interplay between Li+ solvation structure and dynamics. The smallest systems are Li(Anion)n clusters that are treated with high-accuracy density functional theory (DFT) techniques to provide insight into solvation shell structure through energetics and comparisons to experimental IRRaman spectra. Mid-range sized liquid-phase systems (12-24 ion pairs) are treated with DFT molecular dynamics (MD) to provide temperature-dependent insight into Li+ solvation structure, diffusion, and electrochemical window. The largest systems (144-216 ion pairs) are treated with polarizable MD simulations to evaluate the influence of Li-networks on structure and provide size independent values of transport properties. We perform this procedure on three technologically important ionic liquids and comment on property correlations with solvation structure.

batteries↗
NASA NTRS2019

High-Performance Computing Optimization for Aladyn – Adaptive Neural Network Molecular Dynamics Mini-Application

This report provides a description and performance evaluation of the optimization techniques for high performance computing (HPC) implementation of the open source Computational Materials mini-application Aladyn (https://github.com/nasa/aladyn). Aladyn is a basic molecular dynamics code written in FORTRAN 2003, which is designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory (DFT) method. While achieving orders of magnitude faster computational performance than DFT, the ANN-based approach was still very computationally demanding compared to the conventional approach of using empirically fitted energy functions. After its initial development, Aladyn was evaluated and optimized by experts at the NASA Advanced Supercomputing (NAS) division to exploit modern supercomputer architectures. The code has been optimized for execution on multicore central processing units (CPUs), including Intel® Skylake microarchitecture, and on graphic accelerators, such as Nvidia® V100 graphic processing units (GPUs), using Open Multi-Processing (OpenMP) and Open Accelerators (OpenACC) programming interfaces. The optimization achieved a speedup of 4.7 times the baseline version on CPU performance and an additional 2.4 times on CPU+GPU performance. Atomistic computer simulations are a fundamental tool in materials research to model material properties form physics-based first principles. Atomic interaction, governed by Quantum Mechanics (QM) require sophisticated and highly computationally demanding mathematical models to calculate [1]. Classical methods use approximate functional forms, empirically fitted through a set of variable parameters to emulate atomic energies as direct functions of atomic coordinates [2]. While empirical potentials are computationally much simpler, allowing simulations of large-scale systems of up to a trillion (1012) atoms [3], they are substantially less accurate compared to quantum calculations and applicable only to very specific atomic configurations or predefined crystallographic phases. A recently suggested approach is to use heuristic machine learning methods [4], such as those based on Adaptive Neural Networks (ANNs) to predict atomic energies, after being trained on a sufficiently large database of QM-calculated structures [5,6]. This approach reduces significantly the computational complexity, allowing for simulations of orders of magnitude larger systems compared to QM-based methods without compromising accuracy. Still, compared to classical methods using empirical energy functions, ANN methods remain two- to three orders of magnitude more computationally demanding. Hence, the computational cost of simulations, together with the need for extensive training of ANNs, still makes the practical implementation of ANN-based methods quite challenging. The purpose of the Aladyn mini-application software [7], available as open source at https://github.com/nasa/aladyn, is to be a testbed for exploring possible optimization strategies to develop highly scalable parallel algorithms for ANN-based atomistic simulations. Aladyn is aimed at utilizing the architecture of the high-end modern highperformance computing (HPC) hardware based on multicore central processing units (CPUs) equipped with graphic processing unit (GPU) accelerators. Specifically, the goal is to optimize the performance on a single HPC compute node, before implementing scaling to multi-node parallelization using message passing interface (MPI). At the same time, the open source code of Aladyn can serve as a training model for students and professors in academia.

Yamakov, Vesselin I.↗
NASA NTRS2021

Sulfur Molecules in Space by X-rays: A Computational Study

X-ray astronomy lacks high resolution spectra of interstellar dust analogues and molecules, severely hampering interstellar medium studies based on upcoming X-ray missions. Various theoretical approaches may be used to address this problem, but they must first be shown to reproduce reliable spectra compared to the experiment. In this work, we calculate the sulfur Kedge X-ray absorption spectra of H2S, SO2, and OCS, whose spectra are already known from X-ray experiments and predict the X-ray spectrum of CS, which as far as we are aware has not been measured, thereby hampering its detection by X-ray telescopes. We chose these four molecules as the astrochemistry of sulfur is an unsolved problem and as the four molecules are already known to exist in space. We consider three types of methods for modeling the X-ray spectra: more accurate calculations with the algebraic-diagrammatic construction (ADC) and the CC2, CCSD, and CC3coupled cluster (CC) approaches as well as more affordable ones with transition potential density functional theory (TP-DFT). A comparison of our computational results to previously reported experimental spectra shows that the core−valence separation (CVS)approaches CVS-ADC(2)-x and CVS-CC3 generally yield a good qualitative level of agreement with the experiment, suggesting that they can be used for interpreting measured spectra, while the TP-DFT method is not reliable for these molecules. However, quantitative agreement with the experiment is still outside the reach of the computational methods studied in this work.

Goranka Bilalbegovic↗
NASA NTRSDate not supplied

Does Chirality Influence the Stability of Amino Acid –Cu Complexes in the Salt-Induced Peptide Formation Reaction? Insights from Density Functional Theory Calculations

The polymerization of amino acids into peptides and ultimately proteins is critical to evolution of life. Ribosomally-synthesized proteins are homochiral, composed entirely of L-amino acids. Abiotic syntheses of amino acids, however, produce racemic mixtures(equal amounts of L and D enantiomers), meaning that the pool of monomers available for abiotic protein synthesis would be racemic or nearly so. There are no prebiotically plausible mechanisms known to yield homochiral peptides from racemic pools of amino acids. While some mechanisms capable of producing or amplifying enantiomeric excesses have been observed, these excesses are small or not applicable to all biologically relevant amino acids. As a result, a prebiotically-feasible mechanism to create enantiopure pools of amino acids has not been identified. However, it is not clear that these enantio-enriched or enantiopure pools are necessary to produce homochiral peptides. Steric and electronic effects, or a combination of both, may influence how different enantiomers interact with each other, potentially leading to homochiral peptides from racemic mixtures. Here, we use density functional theory (DFT) calculations to assess the stability of homochiral and heterochiral reactive complexes produced during polymerization via the salt-induced peptide formation (SIPF) reaction. Experimental studies of the SIPF reaction have shown that it enables the formation of peptides under diverse environmental conditions, making it a plausible pathway to peptide formation on early Earth. In the SIPF reaction, NaCl acts as a condensation reagent while a divalent metal cation, primarily Cu2+, facilitates polymerization by complexing and activating amino acids forming a monochlorocuprate complex. To assess if hetero-or homochiral monochlorocuprate complexes were energetically favored, we compared the stability of LL, DD, and LD enantiomers of Cu2+–(alanine)2and Cu2+–(valine) 2 complexes. Gaussian 09 density DFT energy-minimization calculations were made for each Cu –amino acid complex in the cis and trans configuration. Models were energy minimized using the BH and HLYP/6-31++G(d,p) level of theory and free energies were compared to determine the most stable configuration.

A C Fox↗
NASA NTRSDate not supplied

High-precision predictions of properties of chemically disordered crystals

Multiple scattering theory (MST) combined with density functional theory (DFT) allows to predict properties of chemically disordered materials from the first principles. However, such predictions often suffer from the systematic errors, which depend on crystal geometry. Each computed property of a particular crystal structure typically has a relatively small random error and a larger systematic error. Cancellation of systematic errors allows more accurate predictions. We propose a computational methodology based on the subtraction of the systematic errors in MST. To exemplify it, we apply it to the precipitated alloys. Considering precipitation strengthening in Ni superalloys, we compute the relative enthalpies of the competing Ni3(Al,Ti)1 crystal structures with a chemical disorder on the Al+Ti sublattice. Such predicted composition-structure-property dependencies are useful for the guided design of the next-generation alloys with improved strength. Our predictions are validated by comparison with the results of other DFT methods (having a higher computational cost) and with experiment. We acknowledge funding of the guided design of stronger superalloys for airspace by NASA Aeronautics Research Mission Directorate (ARMD) via Transformational Tools and Technologies (TTT) Project.

Computational↗
NASA NTRS2022

High-precision predictions of properties of chemically disordered crystals

Multiple scattering theory (MST) combined with density functional theory (DFT) allows to predict properties of chemically disordered materials from the first principles. However, such predictions often suffer from the systematic errors, which depend on crystal geometry. Each computed property of a particular crystal structure typically has a relatively small random error and a larger systematic error. Cancellation of systematic errors allows more accurate predictions. We propose a computational methodology based on the subtraction of the systematic errors in MST. To exemplify it, we apply it to the precipitated alloys. Considering precipitation strengthening in Ni superalloys, we compute the relative enthalpies of the competing Ni_3(Al_{1-x}Ti_x)_1 crystal structures with a chemical disorder on the Al+Ti sublattice. Such predicted composition-structure-property dependencies are useful for the guided design of the next-generation alloys with improved strength. Our predictions are validated by comparison with the results of other DFT methods (having a higher computational cost) and with experiment.

density functional theory↗
NASA NTRS2023

Cavity Ring-Down Spectroscopy of Anthracene, 9-Methylanthracene, and 2 Methylanthracene in Supersonic Expansion

The S0–S1 absorption spectra of anthracene (C14H10), 9-methylanthracene (C15H12), and 2-methylanthracene (C15H12) are measured in the ultraviolet region between 330 and 375 nm (26,666 to 30,303 cm–1) with cavity ring-down spectroscopy in supersonic free-jet expansions of argon. The associated vibronic band systems and their spectroscopic assignments are discussed and compared to previous studies performed using fluorescence excitation and dispersed fluorescence techniques. Density functional theory (DFT) calculations were carried out to study the structures and evaluate the vibrational transitions of the ground and excited states. Time-dependent DFT calculations of the first electronic excited states and Franck–Condon factor calculations were carried out to assist in the assignment of the experimentally measured vibronic bands. The vibronic spectra obtained in absorption agree well with fluorescence excitation spectra in terms of peak positions but exhibit different relative band intensities. We find a very good match between experimentally obtained vibronic line positions and the peak positions of the quantum chemically calculated Franck–Condon excitation lines.

Salma Bejaoui↗
NASA NTRS2023

An Ensemble Neural Network Model for Predicting Rare-Earth Oxide and Silicate Heat Capacities at High Temperature

In this work, a neural network model was developed to predict the constant pressure heat capacity for materials in the rare-earth oxide—silica material space. Several model architectures were trained and tested on heat capacity data generated from first-principles density functional theory calculations. Hyperparameter optimization was performed, and the optimal model was selected for heat capacity predictions. The optimal model architecture was found to have a root-mean-squared error of 5.12 ± 3.37 J/mol-K. The optimal model architecture was then used in a bagging ensemble model trained using the leave-one-group-out method to provide error estimates for model predictions. The out-of-bag score for the ensemble model was 0.997. The predicted heat capacities agree well with the DFT and experimental results and were computed orders of magnitude faster than DFT simulations. Machine learning shows the potential to provide a suitable surrogate model for thermochemical property predictions for candidate environmental barrier coating materials but refining of input material features and model architectures could further improve accuracy for these models.

environmental barrier coatings↗
NASA NTRSDate not supplied

Metal Hydroxide and Oxyhydroxide Gas Database

In a high temperature combustion situation such as a gas turbine or rocket engine, combustion products include water vapor. This water vapor reacts with oxides in the hot-gas-path to form volatile hydroxides and oxyhydroxides. The oxides may be structural oxide components or protective oxides on alloys or non-oxide ceramics. In either case, this enhanced volatilization leads to degradation of components. Reliable thermochemical data for many metal hydroxides and oxyhydroxides has not been available. We review a database put together at NASA over many years based on experimental and ab initio computations for thermochemical data of Al, Si, Ti, Cr, Mn, Y, Zr, La, Ta, Gd, and Yb hydroxides and oxyhydroxides. Experimental methods for measuring thermodynamic quantities of metal hydroxides and oxyhydroxides are limited since the required high temperatures and high pressures preclude many conventional methods. Nonetheless, transpiration has proven a valuable tool in our laboratories for the Si-O-H, Cr-O-H, and Ti-O-H systems. Data are analyzed with second and third law methods. These data can be leveraged with quantum chemistry to provide reliable free energy functions for the third law calculation and comparison to the derived enthalpies of formation. Both wave function and DFT methods can be utilized for deriving the thermodynamic functions for the various metal hydroxides and oxyhydroxides. We have found that, in general, reasonable molecular geometries and spectroscopic data can be derived with a relatively low level of theory, i.e. DFT with the B3LYP functional. Accurate calculations of the enthalpy of formation require higher levels of theory, such as the Coupled Cluster, Singles, Doubles, and perturbative Triples CCSD(T) approach with complete basis sets (CBS). Also, corrections for hindered rotations and anharmonicity are necessary. For some symmetries, the anharmonic correction has proven to be a challenge and we have found that this is only treated properly by certain codes. The database lists the fHo(298), So(298), and Cp in the form Cp = A + BT + CT2 + D/T + E/T2, where A, B, C, D, and E are the fitting constants. Thus, it can be easily used in any of the common computational thermochemistry codes. To date, the database contains 51 gaseous species of the formula MOx(OH)y.

Metal Hydroxides↗