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At least 469 records · Page 26

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NASA NTRS1989

The art of spacecraft design: A multidisciplinary challenge

Actual design turn-around time has become shorter due to the use of optimization techniques which have been introduced into the design process. It seems that what, how and when to use these optimization techniques may be the key factor for future aircraft engineering operations. Another important aspect of this technique is that complex physical phenomena can be modeled by a simple mathematical equation. The new powerful multilevel methodology reduces time-consuming analysis significantly while maintaining the coupling effects. This simultaneous analysis method stems from the implicit function theorem and system sensitivity derivatives of input variables. Use of the Taylor's series expansion and finite differencing technique for sensitivity derivatives in each discipline makes this approach unique for screening dominant variables from nondominant variables. In this study, the current Computational Fluid Dynamics (CFD) aerodynamic and sensitivity derivative/optimization techniques are applied for a simple cone-type forebody of a high-speed vehicle configuration to understand basic aerodynamic/structure interaction in a hypersonic flight condition.

Abdi, F.↗

NASA NTRS1993

Digital mammography, cancer screening: Factors important for image compression

The use of digital mammography for breast cancer screening poses several novel problems such as development of digital sensors, computer assisted diagnosis (CAD) methods for image noise suppression, enhancement, and pattern recognition, compression algorithms for image storage, transmission, and remote diagnosis. X-ray digital mammography using novel direct digital detection schemes or film digitizers results in large data sets and, therefore, image compression methods will play a significant role in the image processing and analysis by CAD techniques. In view of the extensive compression required, the relative merit of 'virtually lossless' versus lossy methods should be determined. A brief overview is presented here of the developments of digital sensors, CAD, and compression methods currently proposed and tested for mammography. The objective of the NCI/NASA Working Group on Digital Mammography is to stimulate the interest of the image processing and compression scientific community for this medical application and identify possible dual use technologies within the NASA centers.

Clarke, Laurence P.↗

NASA NTRS2003

Developing a MATLAB(registered)-Based Tool for Visualization and Transformation

An important step in the structural design and development of spacecraft is the experimental identification of a structure s modal characteristics, such as its natural frequencies and modes of vibration. These characteristics are vital to developing a representative model of any given structure or analyzing the range of input frequencies that can be handled by a particular structure. When setting up such a representative model of a structure, careful measurements using precision equipment (such as accelerometers and instrumented hammers) must be made on many individual points of the structure in question. The coordinate location of each data point is used to construct a wireframe geometric model of the structure. Response measurements obtained from the accelerometers is used to generate the modal shapes of the particular structure. Graphically, this is displayed as a combination of the ways a structure will ideally respond to a specified force input. Two types of models of the tested structure are often used in modal analysis: an analytic model showing expected behavior of the structure, and an experimental model showing measured results due to observed phenomena. To evaluate the results from the experimental model, a comparison of analytic and experimental results must be made between the two models. However, comparisons between these two models become difficult when the two coordinate orientations differ in a manner such that results are displayed in an unclear fashion. Such a problem proposes the need for a tool that not only communicates a graphical image of a structure s wireframe geometry based on various measurement locations (called nodes), but also allows for a type of transformation of the image s coordinate geometry so that a model s coordinate orientation is made to match the orientation of another model. Such a tool should also be designed so that it is able to construct coordinate geometry based on many different listings of node locations and is able to transform the wireframe coordinate orientation to match almost any possible orientation (i.e. it should not be a problem specific application) if it is to be of much value in modal analysis. Also, since universal files are used to store modal parameters and wireframe geometry, the tool must be able to read and extract information from universal files and use these files to exchange model data.The purpose of this project is to develop such a tool as a computer graphical user interface (GUI) capable of performing the following tasks: 1) Browsing for a particular universal file within the computer directory and displaying the name of this file to the screen; 2) Plotting each of the nodes within the universal file in a useful, descriptive, and easily understood figure; 3) Reading the node numbers from the selected file and listing these node numbers to the user for selection in an easily accessible format; 4) Allowing for user selection of a new model orientation defined by three selected nodes; and 5) Allowing the user to specify a directory to which the transformed model s node locations will be saved, and saving the transformed node locations to the specified file.

Anderton, Blake J.↗

NASA NTRS2011

Modeling Vortex Generators in a Navier-Stokes Code

A source-term model that simulates the effects of vortex generators was implemented into the Wind-US Navier-Stokes code. The source term added to the Navier-Stokes equations simulates the lift force that would result from a vane-type vortex generator in the flowfield. The implementation is user-friendly, requiring the user to specify only three quantities for each desired vortex generator: the range of grid points over which the force is to be applied and the planform area and angle of incidence of the physical vane. The model behavior was evaluated for subsonic flow in a rectangular duct with a single vane vortex generator, subsonic flow in an S-duct with 22 corotating vortex generators, and supersonic flow in a rectangular duct with a counter-rotating vortex-generator pair. The model was also used to successfully simulate microramps in supersonic flow by treating each microramp as a pair of vanes with opposite angles of incidence. The validation results indicate that the source-term vortex-generator model provides a useful tool for screening vortex-generator configurations and gives comparable results to solutions computed using gridded vanes.

Dudek, Julianne C.↗

DOE OSTI2020

Screening of Therapeutic Agents for COVID-19 Using Machine Learning and Ensemble Docking Studies

The current pandemic demands a search for therapeutic agents against the novel coronavirus SARS-CoV-2. In this work, we present an efficient computational strategy that combines machine learning (ML)-based models and high-fidelity ensemble docking studies to enable rapid screening of possible therapeutic ligands. Targeting the binding affinity of molecules for either the isolated SARS-CoV-2 S-protein at its host receptor region or the S-protein:human ACE2 interface complex, we screen ligands from drug and biomolecule data sets that can potentially limit and/or disrupt the host-virus interactions. Top scoring one hundred eighty-seven ligands (with 75 approved by the Food and Drug Administration) are further validated by all atom docking studies. Important molecular descriptors ( 2 χ n , topological surface area, and ring count) and promising chemical fragments (oxolane, hydroxy, and imidazole) are identified to guide future experiments. Overall, this work expands our knowledge of small-molecule treatment against COVID-19 and provides a general screening pathway (combining quick ML models with expensive high-fidelity simulations) for targeting several chemical/biochemical problems.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Prediction of Research/Motor Octane Number and Octane Sensitivity Using Artificial Neural Networks

Octane sensitivity (OS), dfined as the research octane number (RON) minus the motor octane number (MON) of a given fuel, has gained interest among researchers due to its apparent ffect on knocking conditions in internal combustion engines. Compounds with a high OS enable higher efficiencies, especially with respect to advanced compression ignition engines. RON/MON must be experimentally tested to determine OS; however, the experimental methods utilized require a substantial amount of time, a significant monetary investment, and specialized equipment. To this end, predictive computational models trained with existing experimental data and molecular properties would allow for the preemptive screening of compounds prior to performing these experiments. The present work proposes two methods for predicting the OS of a given compound: using artficial neural networks (ANNs) trained with quantitative structure-property relationship (QSPR) descriptors to predict RON and MON individually to compute OS from RON/MON predictions (derived octane sensitivity, dOS), and using an ANN trained with QSPR descriptors to directly predict OS. ANNs trained to predict RON and MON achieved test set root-mean-square errors (RMSEs) of 10.499 and 7.551 respectively. dOS calculations were found to have a test set RMSE of 6.432 while predicting OS directly resulted in a test set RMSE of 7.019, showing it is more bene cial to obtain OS from RON/MON predictions than predicting it directly. Furthermore, relationships between individual QSPR descriptors and RON/MON/OS are discussed, highlighting correlations between specfic molecular features and these properties.

09 BIOMASS FUELS↗

NASA NTRS2002

Visions of our Planet's Atmosphere, Land and Oceans: NASA/NOAA Electronic Theater 2002

The NASA/NOAA Electronic Theater presents Earth science observations and visualizations in a historical perspective. Fly in from outer space to the Olympic Medals Plaza, the new Gateway Center, and the University of Utah Stadium Site of the Olympic Opening and Closing Ceremonies in Salt Lake City. Fly in and through the Park City, and Snow Basin sites of the 2002 Winter Olympic Alpine Venues using 1 m IKONOS "Spy Satellite" data. See the four seasons of the Wasatch Front as observed by Landsat 7 at 15m resolution and watch the trees turn color in the Fall, snow come and go in the mountains and the reservoirs freeze and melt. Go back to the early weather satellite images from the 1960s and see them contrasted with the latest US and international global satellite weather movies Including hurricanes & "tornadoes". See the latest visualizations of spectacular images from NASA/NOAA remote sensing missions like Terra, GOES, TRMM, SeaWiFS, Landsat 7 including new 1 - min GOES rapid scan image sequences of Nov 9th 2001 Midwest tornadic thunderstorms and have them explained. See how High-Definition Television (HDTV) is revolutionizing the way we communicate science. (In cooperation with the American Museum of Natural History in NYC) See dust storms in Africa and smoke plumes from fires in Mexico. See visualizations featured on the covers Of Newsweek, TIME, National Geographic, Popular Science & on National & International Network TV. New computer software. tools allow us to roam & zoom through massive global images e.g. Landsat tours of the US, and Africa, showing desert and mountain geology as well as seasonal changes in vegetation. See animations of the polar ice packs and the motion of gigantic Antarctic Icebergs from SeaWinds data. Spectacular new visualizations of the global atmosphere & oceans are shown. See vertexes and currents in the global oceans that bring up the nutrients to feed tin) algae and draw the fish, whales and fisherman. See the how the ocean blooms in response to these currents and El Nino/La Nina climate changes. See the city lights, fishing fleets, gas flares and biomass burning of the Earth at night observed by the "night-vision" DMSP military satellite. The demonstration is interactively driven by a SGI Octane Graphics Supercomputer with two CPUs, 4 Gigabytes of RAM and 0.5 Terabyte of disk using two projectors across a super sized panoramic 48 foot screen. In addition new HDTV technology will be demonstrated from a portable computer server.

Hasler, A. F.↗

NASA NTRS2001

Visions of our Planet's Atmosphere, Land and Oceans: NASA/NOAA Electronic Theater 2002

The NASA/NOAA Electronic Theater presents Earth science observations and visualizations in a historical perspective. Fly in from outer space to the Olympic Medals Plaza, the new Gateway Center, and the University of Utah Stadium Site of the Olympic Opening and Closing Ceremonies in Salt Lake City. Fly in and through the Park City, and Snow Basin sites of the 2002 Winter Olympic Alpine Venues using 1 m IKONOS "Spy Satellite" data. See the four seasons of the Wasatch Front as observed by Landsat 7 at 15m resolution and watch the trees turn color in the Fall, snow come and go in the mountains and the reservoirs freeze and melt. Go back to the early weather satellite images from the 1960s and see them contrasted with the latest US and international global satellite weather movies including hurricanes & "tornadoes". See the latest visualizations of spectacular images from NASA/NOAA remote sensing missions like Terra, GOES, TRMM, SeaWiFS, Landsat 7 including new 1 - min GOES rapid scan image sequences of Nov 9th 2001 Midwest tornadic thunderstorms and have them explained. See how High-Definition Television (HDTV) is revolutionizing the way we communicate science. (In cooperation with the American Museum of Natural History in NYC) See dust storms in Africa and smoke plumes from fires in Mexico. See visualizations featured on the covers of Newsweek, TIME, National Geographic, Popular Science & on National & International Network TV. New computer software tools allow us to roam & zoom through massive global images e.g. Landsat tours of the US, and Africa, showing desert and mountain geology as well as seasonal changes in vegetation. See animations of the polar ice packs and the motion of gigantic Antarctic Icebergs from SeaWinds data. Spectacular new visualizations of the global atmosphere & oceans are shown. See vortexes and currents in the global oceans that bring up the nutrients to feed tiny algae and draw the fish, whales and fisherman. See the how the ocean blooms in response to these currents and El Nino/La Nina climate changes. See the city lights, fishing fleets, gas flares and bio-mass burning of the Earth at night observed by the "night-vision" DMSP military satellite. The demonstration is interactively driven by a SGI Octane Graphics Supercomputer with two CPUs, 4 Gigabytes of RAM and 0.5 Terabyte of disk using two projectors across a super sized panoramic 48 foot screen. In addition new HDTV technology will be demonstrated from a portable computer server.

Hasler, A. F.↗

NASA NTRS1971

Man-machine communication - A transparent switchboard for computers

Device uses pattern of transparent contact touch points that are put on cathode ray tube screen. Touch point system compels more precise and unambiguous communication between man and machine than is possible with any other means, and speeds up operation responses.

Rasmussen, H.↗

DOE OSTI2023

SARS-CoV2 billion-compound docking

Abstract This dataset contains ligand conformations and docking scores for 1.4 billion molecules docked against 6 structural targets from SARS-CoV2, representing 5 unique proteins: MPro, NSP15, PLPro, RDRP, and the Spike protein. Docking was carried out using the AutoDock-GPU platform on the Summit supercomputer and Google Cloud. The docking procedure employed the Solis Wets search method to generate 20 independent ligand binding poses per compound. Each compound geometry was scored using the AutoDock free energy estimate, and rescored using RFScore v3 and DUD-E machine-learned rescoring models. Input protein structures are included, suitable for use by AutoDock-GPU and other docking programs. As the result of an exceptionally large docking campaign, this dataset represents a valuable resource for discovering trends across small molecule and protein binding sites, training AI models, and comparing to inhibitor compounds targeting SARS-CoV-2. The work also gives an example of how to organize and process data from ultra-large docking screens.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Data-Driven and Multiscale Modeling of DNA-Templated Dye Aggregates

Dye aggregates are of interest for excitonic applications, including biomedical imaging, organic photovoltaics, and quantum information systems. Dyes with large transition dipole moments (μ) are necessary to optimize coupling within dye aggregates. Extinction coefficients (ε) can be used to determine the μ of dyes, and so dyes with a large ε (>150,000 M –1 cm –1 ) should be engineered or identified. However, dye properties leading to a large ε are not fully understood, and low-throughput methods of dye screening, such as experimental measurements or density functional theory (DFT) calculations, can be time-consuming. In order to screen large datasets of molecules for desirable properties (i.e., large ε and μ), a computational workflow was established using machine learning (ML), DFT, time-dependent (TD-) DFT, and molecular dynamics (MD). ML models were developed through training and validation on a dataset of 8802 dyes using structural features. A Classifier was developed with an accuracy of 97% and a Regressor was constructed with an R2 of above 0.9, comparing between experiment and ML prediction. Using the Regressor, the ε values of over 18,000 dyes were predicted. The top 100 dyes were further screened using DFT and TD-DFT to identify 15 dyes with a μ relative to a reference dye, pentamethine indocyanine dye Cy5. Two benchmark MD simulations were performed on Cy5 and Cy5.5 dimers, and it was found that MD could accurately capture experimental results. The results of this study exhibit that our computational workflow for identifying dyes with a large μ for excitonic applications is effective and can be used as a tool to develop new dyes for excitonic applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2021

Machine learning to accelerate screening for Marcus reorganization energies

Understanding and predicting the charge transport properties of π-conjugated materials is an important challenge for designing new organic electronic devices, such as solar cells, plastic transistors, light-emitting devices, and chemical sensors. A key component of the hopping mechanism of charge transfer in these materials is the Marcus reorganization energy which serves as an activation barrier to hole or electron transfer. While modern density functional methods have proven to accurately predict trends in intramolecular reorganization energy, such calculations are computationally expensive. In this work, we outline active machine learning methods to predict computed intramolecular reorganization energies of a wide range of polythiophenes and their use toward screening new compounds with low internal reorganization energies. Our models have an overall root mean square error (RMSE) of ±0.113 eV, but a much smaller RMSE of only ±0.036 eV on the new screening set. Since the larger error derives from high-reorganization energy compounds, the new method is highly effective to screen for compounds with potentially efficient charge transport parameters.

14 SOLAR ENERGY↗

DOE OSTI2020

First-principles modeling of chemistry in mixed solvents: Where to go from here?

Mixed solvents (i.e., binary or higher order mixtures of ionic or nonionic liquids) play crucial roles in chemical syntheses, separations, and electrochemical devices because they can be tuned for specific reactions and applications. Apart from fully explicit solvation treatments that can be difficult to parameterize or computationally expensive, there is currently no well-established first-principles regimen for reliably modeling atomic-scale chemistry in mixed solvent environments. We offer our perspective on how this process could be achieved in the near future as mixed solvent systems become more explored using theoretical and computational chemistry. We first outline what makes mixed solvent systems far more complex compared to single-component solvents. An overview of current and promising techniques for modeling mixed solvent environments is provided. We focus on so-called hybrid solvation treatments such as the conductor-like screening model for real solvents and the reference interaction site model, which are far less computationally demanding than explicit simulations. We also propose that cluster-continuum approaches rooted in physically rigorous quasi-chemical theory provide a robust, yet practical, route for studying chemical processes in mixed solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Multipole interaction in spectral line broadening by plasmas

A long-standing ambiguity in spectral line broadening theory related to the electric field divergence in the quadrupole term of the screened Coulomb radiator-plasma interaction is examined. This is accomplished with multipole expansions from a Taylor series as well as a partial wave analysis of the screened Coulomb interaction. Here, it is explicitly shown that the two approaches agree up to the octupole term for an effective radiator size small compared to the plasma screening length. Furthermore, the ambigous corrections are confirmed appearing naturally in both methods. For higher multipoles the agreement is demonstrated numerically with a computer program using exact arithmetic.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRSDate not supplied

Thermal Analysis of an In-Space Heat Shield Exposed to a Rocket Plume During Stage Separation

Thermal analyses were conducted to evaluate the thermal response of various individual materials and multi-layer configurations for an in-space heat shield exposed to a rocket plume during stage separation. Frequently used, readily available thermal protection materials consisting of cork, carbon cloth phenolic (CCP), and silica cloth phenolic (SCP) were selected for an initial screening analysis. SCP was chosen as the primary material for further evaluation using an updated thermal environment calculated using computational fluid dynamics (CFD) results. A multi-layer configuration consisting of SCP providing erosion resistance and a Nomex honeycomb providing thermal protection was then evaluated as a solution for more mass-efficient performance. Pyrolysis depth, bondline temperature, back-side temperature, and a thermal factor of safety were used to define the necessary material thickness profile. Adhesives were included in the analyses with considerations for maximum temperature and application method. One dimensional thermal analyses at several stations along the heat shield surface were performed for the initial screening and follow-on analyses. The methodology used standard processes and computer programs applicable to solid rocket motor internal insulation and nozzle thermal analysis such as Chemical Equilibrium and Applications (CEA), Aerotherm Chemical Equilibrium (ACE), Momentum/Energy Integral Technique (MEIT), and Insulation Thermal Response and Ablation Code (ITRAC). The baseline SCP/Nomex honeycomb multi-layer configuration thermal performance predictions satisfied the objectives with an acceptable mass estimate for the design maturity. The EA9673 film adhesive and SCP resin were the best performing bonding agents considered for the SCP/Nomex honeycomb and Nomex honeycomb/structural substrate interfaces. The baseline mass estimate was lowest when the resin was the bonding agent due to the higher maximum service temperature. These thermal analyses evaluated typical internal and external nozzle materials using a calculated thermal environment and heat loads that were lower than a typical rocket motor internal environment but greater than standard external aeroheating.

Andrew T Hiatt↗

DOE OSTI2022

Probing the Kinetic Origin of Varying Oxidative Stability of Ethyl- vs. Propyl-spaced Amines for Direct Air Capture

Amine-based adsorbents are promising for direct air capture of CO 2 , yet oxidative degradation remains a key unmitigated risk hindering wide-scale deployment. Borrowing wisdom from the basic auto-oxidation scheme, insights are gained into the underlying degradation mechanisms of polyamines by quantum chemical, advanced sampling simulations, adsorbent synthesis, and accelerated degradation experiments. The reaction kinetics of polyamines are contrasted with that of typical aliphatic polymers and they elucidate for the first time the critical role of aminoalkyl hydroperoxide decomposition in the oxidative degradation of amino-oligomers. The experimentally observed variation in oxidative stability of polyamines with different backbone structures is explained by the relationship between the local chemical structure and the free energy barrier of aminoalkyl hydroperoxide decomposition, suggesting that its energetics can be used as a descriptor to screen and design new polyamines with improved stability. In conclusion, the developed computational capability sheds light on radical-induced degradation chemistry of other organic functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

B 2 H 6 splitting on catalytic surfaces and role of BH 3 towards hydrogen spillover

A fundamental understanding of the spillover mechanism is an open and challenging problem and plays an important role in catalysis. In particular, bond-exchange spillover mechanism is considered to be effective for reversible storage and release of hydrogen at near ambient conditions. For this, three critical steps are needed: finding the right support (acceptor), the right catalyst to split H 2 , and ensuring that once H 2 is split, the H atoms can migrate on the surface with the help of secondary catalysts and eventually hydrogenate the entire material. In this paper we address these challenges using density functional theory. Here we show that BH 3 , a secondary catalyst, can be produced by symmetrically splitting its stable precursor, B 2 H 6 , on doped metal-free surfaces such as graphene and h-BN as well as on MOF5. In addition, to reduce computational cost, we develop structural descriptor and predictive model equation to effectively screen potential BH 3 binding sites. Symmetrical splitting of B 2 H 6 on different types of materials can address the hydrogen spillover challenge, making efficient storage of hydrogen possible.

08 HYDROGEN↗

DOE OSTI2026

Computational Discovery of Ultralow Thermal Conductivity in the Energy-Degenerate Polymorphic Crystal Family A 2 M 2 M’Q 4

Crystalline materials, characterized by their well-defined lattices, typically exhibit a unique global thermodynamic minimum for a specific composition. However, in this study, we discover a quaternary chalcogenide family, A 2 M 2 M’Q 4 (A: alkali metals; M: coinage metal; M’: transition or group-IVA metals; Q: chalcogens), that exhibits pervasive energy (near-)degeneracy. For a given composition, multiple structurally distinct polymorphs exist within a formation enthalpy window of only a few milli-electron volts per atom. We quantify this inherent structural flexibility using a dedicated descriptor, σ f : the standard deviation of formation enthalpies among degenerate (meta)stable polymorphs. The consistently low σf observed across the A 2 M 2 M’Q 4 family signifies a characteristically shallow and frustrated potential energy landscape, which drives pronounced lattice anharmonicity, marking these materials as prime candidates for ultralow lattice thermal conductivity (κ L ). Employing an advanced high-throughput computational framework that integrates thermodynamics, lattice dynamics, and thermal conductivity calculations, we screen 1215 A 2 M 2 M’Q 4 compounds, identifying 30 stable candidates with κ L < 0.5 W m –1 K –1 at 300 K. Among them, Rb 2 Ag 2 SnTe 4 and Rb 2 Au 2 HfTe 4 , two representatives from the IVA and TM subgroups, are predicted to show ultralow room-temperature κ L of 0.174 W m –1 K –1 and 0.295 W m –1 K –1 , respectively. A systematic analysis suggests that the nonbonding and antibonding states induced by “dual rattlers” are the origin of low thermal conductivity in these compounds. Our results position the A 2 M 2 M’Q 4 family as a rich source of intrinsic thermal insulators and suggest that polymorphic energy degeneracy may serve as a valuable signpost for identifying crystalline families with potential anharmonicity.

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