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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 181 records · Page 10

Biocompatible Electrostatic Layered Systems for Viral Elimination in the Nose/Throat

An anti-viral coating for the nose & throat is needed to quickly address the spread of COVID-19 infections and to aid future pandemics. Current nasal delivery systems are typically a 1-spray homogenous solution, which is convenient but may not be as efficient or durable as a multi-spray solution that contains a binding layer to anchor the anti-viral components. Many of the current nasal solutions being investigated to aid in pandemic response have solution-based mechanisms of action and are quickly cleared from the nose/mouth limiting their efficacy lifetime. A multi-spray approach utilizing strong intermolecular forces between polymeric materials and anti-viral agents to provide a robust biocompatible coating is expected to have increased physical and chemical properties to combat viral infection. This work evaluated which tailored biocompatible materials are needed to generate a layered system to combat viral infection. This layered system takes advantage of electrostatic interactions to bind anti-viral components, shown in Figure 1. Proof of concept success was demonstrated through cell toxicity studies and anti-viral assays on both the individual layer components and the complete layered system. Project work began with chemical modifications of Xantham Gum to hydrolyzing xanthan gum to give a negatively charged polymer with varying degrees of ionic character and investigate bonding efficiencies. However, this was abandoned in favor of comparing COTS available materials listed in Table 1 (Results section). Concentration and adhesion studies were performed on layers created using the listed polymeric materials and anti-viral agents. Finally, biocompatibility of materials, layers, and coating system were confirmed through cytotoxicity studies and the efficacy of the anti-viral properties tested with phi6 bacteriophage as a SARS-CoV2 surrogate.

36 MATERIALS SCIENCE↗

Simulation techniques for estimating error in the classification of normal patterns

Methods of efficiently generating and classifying samples with specified multivariate normal distributions were discussed. Conservative confidence tables for sample sizes are given for selective sampling. Simulation results are compared with classified training data. Techniques for comparing error and separability measure for two normal patterns are investigated and used to display the relationship between the error and the Chernoff bound.

Whitsitt, S. J.↗

RF performance of a proposed L-band antenna system

Scale model work to determine efficiencies and bandwidth were made on a smooth wall dual mode feedhorn to study the feasibility of its use at L-Band for the Venus Balloon Project. Measured feedhorn patterns were made and scattered from a symmetrical subreflector. A perturbation technique was then used to predict efficiencies due to scanning effects. A correction for the asymmetrical subreflector was also made. Tables of results and patterns are included.

Withington, J. R.↗

Progress on the National Solar Radiation Data Base (NSRDB): A new DNI computation

This study introduces a new technique to compute direct normal irradiance (DNI) for improving the National Solar Radiation Data Base (NSRDB). A finite-surface integration algorithm is developed to compute solar radiation in differential solid angles and efficiently infer its contribution to a surface perpendicular to the solar direction. A lookup table of cloud bi-directional transmittance distribution function (BTDF) is developed by use of the discrete ordinates radiative transfer (DISORT) model for possible solar and observing directions and various cloud optical and microphysical properties. In each solar incident direction, DNI is given by the cloud BTDFs from approximately 200 differential solid angles. The simulated DNI is calibrated and evaluated using surface observations at the National Renewable Energy Laboratory's (NREL's) Solar Energy Research Laboratory (SRRL) and the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) facility.

54 ENVIRONMENTAL SCIENCES↗

The DaveMLTranslator: An Interface for DAVE-ML Aerodynamic Models

It can take weeks or months to incorporate a new aerodynamic model into a vehicle simulation and validate the performance of the model. The Dynamic Aerospace Vehicle Exchange Markup Language (DAVE-ML) has been proposed as a means to reduce the time required to accomplish this task by defining a standard format for typical components of a flight dynamic model. The purpose of this paper is to describe an object-oriented C++ implementation of a class that interfaces a vehicle subsystem model specified in DAVE-ML and a vehicle simulation. Using the DaveMLTranslator class, aerodynamic or other subsystem models can be automatically imported and verified at run-time, significantly reducing the elapsed time between receipt of a DAVE-ML model and its integration into a simulation environment. The translator performs variable initializations, data table lookups, and mathematical calculations for the aerodynamic build-up, and executes any embedded static check-cases for verification. The implementation is efficient, enabling real-time execution. Simple interface code for the model inputs and outputs is the only requirement to integrate the DaveMLTranslator as a vehicle aerodynamic model. The translator makes use of existing table-lookup utilities from the Langley Standard Real-Time Simulation in C++ (LaSRS++). The design and operation of the translator class is described and comparisons with existing, conventional, C++ aerodynamic models of the same vehicle are given.

Hill, Melissa A.↗

On-the-Fly Treatment of Temperature Dependent Cross Sections in the Unresolved Resonance Regions in RMC Code

Monte Carlo method can provide high fidelity neutronics analysis of different nuclear reactors, owing to its advantages of the flexible geometry modeling and the use of continuous-energy nuclear cross sections. It can also be coupled with thermal-hydraulics codes to consider the feedback. For thermal reactors such as PWR and HTGR, two main temperature effects should be considered. The first is the effect of thermal motion of target nuclei in resolved resonance energy regions, which is known as Doppler effect. The second is the thermal scattering and bound effect in thermal energy regions. The traditional approach of pre-generated cross sections has difficulty in memory footprint for detailed temperature modelling in multi-physics calculations. Recently, on-the-fly (OTF) technique has been proposed in order to reduce the memory consumption for both resolved resonance energy and thermal energy. For fast reactors calculations, the temperature dependence of cross sections in the unresolved resonance energy regions is also important. However, less attention was paid to the unresolved resonance regions compared with resolved resonance energy and thermal energy. In this paper, the on-the-fly temperature treatment of cross sections in unresolved resonance regions was proposed and developed in RMC codes. The results show that the on-the-fly treatment has high efficiency and satisfactory fidelity. The on-the-fly treatment of unresolved resonance region was also combined with the target motion sampling (TMS) method for resolved resonance energy. The formats of libraries were changed, in which the probability tables were separated from the cross sections. Then the interpolation of probability table was performed on-the-fly during the transport routine. The results show that the on-the-fly treatment has high efficiency and satisfactory fidelity. The on-the-fly treatment of unresolved resonance region was also combined with the target motion sampling (TMS) method for resolved resonance energy, showing that TMS method is effective and accurate for cross sections treatment in resolved resonance energy regions. The memory saving of the on-the-fly treatment is also considerable. For the high-fidelity 'transport-burnup-thermal-hydraulics' coupling calculation, the memory requirement is 60 Mb. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

RELAP-7 Progress Report. FY-2015 Optimization Activities Summary

This report summarily documents the optimization activities on RELAP-7 for FY-2015. It includes the migration from the analytical stiffened gas equation of state for both the vapor and liquid phases to accurate and efficient property evaluations for both equilibrium and metastable (nonequilibrium) states using the Spline-Based Table Look-up (SBTL) method with the IAPWS-95 properties for steam and water. It also includes the initiation of realistic closure models based, where appropriate, on the U.S. Nuclear Regulatory Commission’s TRACE code. It also describes an improved entropy viscosity numerical stabilization method for the nonequilibrium two-phase flow model of RELAP-7. For ease of presentation to the reader, the nonequilibrium two-phase flow model used in RELAP-7 is briefly presented, though for detailed explanation the reader is referred to RELAP-7 Theory Manual [R.A. Berry, J.W. Peterson, H. Zhang, R.C. Martineau, H. Zhao, L. Zou, D. Andrs, “RELAP-7 Theory Manual,” Idaho National Laboratory INL/EXT-14-31366(rev. 1), February 2014].

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A remote sensing algorithm for vertically resolved cloud condensation nuclei number concentrations from airborne and spaceborne lidar observations

Cloud condensation nuclei (CCN) are mediators of aerosol–cloud interactions (ACIs), contributing to the largest uncertainties in the understandings of global climate change. We present a novel remote-sensing-based algorithm that quantifies the vertically resolved CCN number concentrations (N CCN ) using aerosol optical properties measured by a multiwavelength lidar. The algorithm considers five distinct aerosol subtypes with bimodal size distributions. The inversion used the lookup tables developed in this study, based on the observations from the Aerosol Robotic Network, to efficiently retrieve optimal particle size distributions from lidar measurements. The method derives dry aerosol optical properties by implementing hygroscopic enhancement factors in lidar measurements. The retrieved optically equivalent particle size distributions and aerosol-type-dependent particle composition are utilized to calculate critical diameters using κ-Köhler theory and N CCN at six supersaturations ranging from 0.07 % to 1.0 %. Sensitivity analyses indicate that uncertainties in extinction coefficients and relative humidity greatly influence the retrieval error in N CCN . The potential of this algorithm is further evaluated by retrieving N CCN using airborne lidar from the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign and is validated against simultaneous measurements from the CCN counter. The independent validation with robust correlation demonstrates promising results. Furthermore, the N CCN has been retrieved for the first time using a proposed algorithm from spaceborne lidar – Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) – measurements. The application of this new capability demonstrates the potential for constructing a 3D CCN climatology at a global scale, which helps to better quantify ACI effects and thus reduce the uncertainty in aerosol climate forcing.

54 ENVIRONMENTAL SCIENCES↗

RINA: An interactive system for the rapid interpretation of NASTRAN results

RINA is a general post-processor system which performs data reduction, post processing and post analysis of NASTRAN results. RINA can be run in either batch or time-sharing mode. The system, which is an expansion of the NASDAT program, performs the following tasks: (1) scan of extreme values for displacements, forces, stresses and margins of safety, (2) computations of envelopes for displacements, forces, stresses and margins of safety, (3) computations of allowables and margins of safety; and (4) generation of NASTRAN tables needed for reanalysis computations. Usage of all these options provides the analyst with an efficient tool for the study and interpretation of NASTRAN analysis results and their presentation for project documentation.

Raibstone, A. I.↗

Liquid solar collector

Report documents evaluation test on commercial flat-plate solar collector that uses water as working fluid. Performance was measured before and after 34-day exposure to natural environment. Tables in metric and English units present data on air and water temperatures, waterflow, insolation, efficiency, and windspeed and direction.

Source record↗

Flight Dynamic Model Exchange using XML

The AIAA Modeling and Simulation Technical Committee has worked for several years to develop a standard by which the information needed to develop physics-based models of aircraft can be specified. The purpose of this standard is to provide a well-defined set of information, definitions, data tables and axis systems so that cooperating organizations can transfer a model from one simulation facility to another with maximum efficiency. This paper proposes using an application of the eXtensible Markup Language (XML) to implement the AIAA simulation standard. The motivation and justification for using a standard such as XML is discussed. Necessary data elements to be supported are outlined. An example of an aerodynamic model as an XML file is given. This example includes definition of independent and dependent variables for function tables, definition of key variables used to define the model, and axis systems used. The final steps necessary for implementation of the standard are presented. Software to take an XML-defined model and import/export it to/from a given simulation facility is discussed, but not demonstrated. That would be the next step in final implementation of standards for physics-based aircraft dynamic models.

Jackson, E. Bruce↗

Phenomena Identification and Ranking Table (PIRT) for heat pipes

Heat pipes are advanced passive thermal management devices that utilize phase change and capillary action to achieve efficient heat transfer. However, due to the complexity of the phenomena coupled in heat pipes, including capillary, phase change, turbulence, and compressibility effects, there are high uncertainties in the predictability of their operational regimes and performance. This PIRT exercise, conducted as a collaborative effort involving the Department of Energy (DOE) Microreactor Program (MRP), the Nuclear Regulatory Commission (NRC), and university partners systematically identifies, reviews, and prioritizes critical phenomena affecting the operation of heat pipes based on their importance and knowledge levels. Additional analyses and discussion are provided for phenomena with high importance and low knowledge, such as wick de-wetting, critical heat flux, contact angles, and pressure dynamics. The discussions included the recognizing challenges and proposing future research directions for both modeling and simulation and experimental efforts. Additionally, the report addresses phenomena with medium importance and low knowledge that could impact heat pipe operation during non-normal or transient operation, including frozen startup, laminar to turbulent transition, geyser boiling, wick priming, underfilling conditions, surface roughness of the wick, NCGs trapped in the wick, and the timescales of startup and shutdown. In conclusion, this comprehensive evaluation serves as a valuable resource for guiding future research and development efforts, supporting the successful integration of heat pipes into critical applications such as nuclear reactors, and contributing to the advancement of heat pipe technologies in safety-critical industries.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

On the congruent feature in NASTRAN

The congruent feature, which is a capability in NASTRAN that can contribute to significant increases in computational efficiencies, is discussed. The usage of the capability and the software design characteristics affecting it are explained. The factors affecting the efficiency of the feature are pointed out. The details pertaining to the software design of the congruent feature are presented; in particular, the congruent element table is described. Serveral examples employing the congruent feature are considered and comparisons of Element Matrix Generator module computer program update times with and without this feature are presented. The results clearly demonstrate the role of the congruent feature in increasing computational efficiencies and its applicability to large-size problems.

Pamidi, P. R.↗

Blade and Rim Seal Design of a First Stage High Pressure Turbine for a 300 MWe Supercritical CO2 Power Cycle

A first stage high-pressure turbine (HPT) blade is optimized for a 300 MWe supercritical CO2 (sCO2) power cycle using the surrogate-assisted genetic algorithm optimizer in Numeca FINE/Design 3D with objectives of increasing efficiency and decreasing heat load to the blade. The National Institute of Standards and Technology Reference Fluid Thermodynamic and Transport Properties Database (NIST REFPROP) [1] data for supercritical CO2 is formatted into tables of bicubic polynomial coefficients for use in condensable gas simulations in FINE/Turbo. Nearly 3000 unique shapes are evaluated via three-dimensional Reynolds Averaged Navier Stokes simulations, yielding increases in efficiency of up to 0.85 percentage points and decreases in heat load of 14%. A final blade, deemed the advanced blade, is chosen for future experimental analysis. Following this, a squealer tip optimization is performed on both the baseline and advanced blade designs. This optimization resulted in a performance gain of 1.25 points in efficiency and 15% reduction in tip heat load compared to the baseline flat tip design at the same clearance. In tandem, an optimization of the rotor-stator platform rim seal is performed using a parametrized geometry allowing for straight, meandering, and knife seal cavities. This multi-objective optimization focuses on decreasing the cooling mass flow and increasing the heat flux from the rotor and stator disk. The optimization resulted in cooling mass flow decreases of up to 26% while maintaining the average heat flux on the rim seal.

Tuite, Logan↗

Diffusion lengths in irradiated N/P InP-on-Si solar cells

Indium phosphide (InP) solar cells were made on silicon (Si) wafers (InP/Si) by to take advantage of both the radiation-hardness properties of the InP solar cell and the light weight and low cost of Si wafers. The InP/Si cell application is for long duration and/or high radiation orbit space missions. Spire has made N/P InP/Si cells of sizes up to 2 cm by 4 cm with beginning-of-life (BOL) AM0 efficiencies over 13% (one-sun, 28C). These InP/Si cells have higher absolute efficiency and power density after a high radiation dose than gallium arsenide (GaAs) or silicon (Si) solar cells after a fluence of about 2e15 1 MeV electrons/sq. cm. In this work, we investigate the minority carrier (electron) base diffusion lengths in the N/P InP/Si cells. A quantum efficiency model was constructed for a 12% BOL AM0 N/P InP/Si cell which agreed well with the absolutely measured quantum efficiency and the sun-simulator measured AM0 photocurrent (30.1 mA/sq. cm). This model was then used to generate a table of AM0 photocurrents for a range of base diffusion lengths. AM0 photocurrents were then measured for irradiations up to 7.7e16 1 MeV electrons/sq. cm (the 12% BOL cell was 8% after the final irradiation). By comparing the measured photocurrents with the predicted photocurrents, base diffusion lengths were assigned at each fluence level. A damage coefficient K of 4e-8 and a starting (unirradiated) base electron diffusion length of 0.8 microns fits the data well. The quantum efficiency was measured again at the end of the experiment to verify that the photocurrent predicted by the model (25.5 mA/sq. cm) agreed with the simulator-measured photocurrent after irradiation (25.7 mA/sq. cm).

Wojtczuk, Steven↗

Cluster compression algorithm: A joint clustering/data compression concept

The Cluster Compression Algorithm (CCA), which was developed to reduce costs associated with transmitting, storing, distributing, and interpreting LANDSAT multispectral image data is described. The CCA is a preprocessing algorithm that uses feature extraction and data compression to more efficiently represent the information in the image data. The format of the preprocessed data enables simply a look-up table decoding and direct use of the extracted features to reduce user computation for either image reconstruction, or computer interpretation of the image data. Basically, the CCA uses spatially local clustering to extract features from the image data to describe spectral characteristics of the data set. In addition, the features may be used to form a sequence of scalar numbers that define each picture element in terms of the cluster features. This sequence, called the feature map, is then efficiently represented by using source encoding concepts. Various forms of the CCA are defined and experimental results are presented to show trade-offs and characteristics of the various implementations. Examples are provided that demonstrate the application of the cluster compression concept to multi-spectral images from LANDSAT and other sources.

Hilbert, E. E.↗

Materials Graph Library (MatGL), an open-source graph deep learning library for materials science and chemistry

Graph deep learning models, which incorporate a natural inductive bias for atomic structures, are of immense interest in materials science and chemistry. Here, we introduce the Materials Graph Library (MatGL), an open-source graph deep learning library for materials science and chemistry. Built on top of the popular Deep Graph Library (DGL) and Python Materials Genomics (Pymatgen) packages, MatGL is designed to be an extensible “batteries-included” library for developing advanced model architectures for materials property predictions and interatomic potentials. At present, MatGL has efficient implementations for both invariant and equivariant graph deep learning models, including the Materials 3-body Graph Network (M3GNet), MatErials Graph Network (MEGNet), Crystal Hamiltonian Graph Network (CHGNet), TensorNet and SO3Net architectures. MatGL also provides several pre-trained foundation potentials (FPs) with coverage of the entire periodic table, and property prediction models for out-of-box usage, benchmarking and fine-tuning. Finally, MatGL integrates with PyTorch Lightning to enable efficient model training.

chemistry↗

MO-E-BRC-00: Online Adaptive Radiotherapy - Considerations for Practical Clinical Implementation

Online adaptive radiation therapy has the potential to ensure delivery of optimal treatment to the patient by accounting for anatomical and potentially functional changes that occur from one fraction to the next and over the course of treatment. While on-line adaptive RT (ART) has been a topic of many publications, discussions, and research, it has until very recently remained largely a concept and not a practical implementation. However, recent advances in on-table imaging, use of deformable image registration for contour generation and dose tracking, faster and more efficient plan optimization, as well as fast quality assurance method has enabled the implementation of ART in the clinic in the past couple of years. The introduction of these tools into routine clinical use requires many considerations and progressive knowledge to understand how processes that have historically taken hours/days to complete can now be done in less than 30 minutes. This session will discuss considerations to perform real time contouring, planning and patient specific QA, as well as a practical workflow and the required resources. Learning Objectives: To understand the difficulties, challenges and available technologies for online adaptive RT. To understand how to implement online adaptive therapy in a clinical environment and to understand the workflow and resources required. To understand the limitations and sources of uncertainty in the online adaptive process I have research funding from ViewRay Inc. and Philips Medical Systems.; R. Kashani, I have research funding from ViewRay Inc. and Philips Medical Systems.; X. Li, Research supported by Elekta Inc.

60 APPLIED LIFE SCIENCES↗