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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 235 records · Page 13

Moving closer to experimental level materials property prediction using AI

Abstract While experiments and DFT-computations have been the primary means for understanding the chemical and physical properties of crystalline materials, experiments are expensive and DFT-computations are time-consuming and have significant discrepancies against experiments. Currently, predictive modeling based on DFT-computations have provided a rapid screening method for materials candidates for further DFT-computations and experiments; however, such models inherit the large discrepancies from the DFT-based training data. Here, we demonstrate how AI can be leveraged together with DFT to compute materials properties more accurately than DFT itself by focusing on the critical materials science task of predicting “formation energy of a material given its structure and composition”. On an experimental hold-out test set containing 137 entries, AI can predict formation energy from materials structure and composition with a mean absolute error (MAE) of 0.064 eV/atom; comparing this against DFT-computations, we find that AI can significantly outperform DFT computations for the same task (discrepancies of $$>0.076$$ > 0.076 eV/atom) for the first time.

36 MATERIALS SCIENCE↗

Accelerated screening of functional atomic impurities in halide perovskites using high-throughput computations and machine learning

The pressing need for novel materials that can serve rising demands in solar cell and optoelectronic technologies makes the nexus of halide perovskites, high-throughput computations, and machine learning, very promising. Ever increasing amounts of data on the structure, fundamental properties, and device performance of halide perovskites provide opportunities for learning chemical rules and design principles that make these materials attractive, and applying them across wide chemical spaces. In this work, we show that impurity properties of halide perovskites computed using density functional theory (DFT) can be combined with machine learning (ML) to deliver predictive models and quick identification of optoelectronically active impurity atoms. Our computation lead to the largest reported dataset of the formation energies and charge transition levels of Pb-site impurities in methylammonium lead halide (MAPbX 3 ) perovskites. Descriptors are defined to uniquely represent any impurity atom in any MAPbX 3 compound and mapped to the computed impurity properties using regression techniques such as Gaussian process regression, neural networks, and random forests. We use the best optimized predictive models to make predictions for hundreds of impurities across 9 MAPbX 3 compounds and create lists of dominating impurities, that is, impurities that can shift the equilibrium Fermi level in the perovskite as determined by native point defects. Finally, this accelerated screening powered by computations and machine learning can guide the identification of problematic impurities that may cause undesired recombination of charge carriers, as well as impurities that can be deliberately introduced to tune the perovskite conductivity and resulting photovoltaic absorption.

36 MATERIALS SCIENCE↗

Polarization consistent dielectric screening in polarizable continuum model calculations of solvation energies

A polarization consistent framework, where dielectric screening is affected consistently in polarizable continuum model (PCM) calculations, is employed for the study of solvation energies. The computational framework combines a screened range-separated-hybrid functional (SRSH) with PCM calculations, SRSH-PCM, where dielectric screening is imposed in both PCM self-consistent reaction field (SCRF) iterations and the electronic structure Hamiltonian. We begin by demonstrating the impact of modifying the Hamiltonian to include such dielectric screening in SCRF iterations by considering the solutions of electrostatically embedded Hartree–Fock (HF) exact exchange equations. Long-range screened HF-PCM calculations are shown to capture properly the linear dependence of gap energy of frontier orbitals on the inverse of the dielectric constant, whereas unscreened HF-PCM orbital energies are fallaciously semi-constant with respect to the dielectric constant and, therefore, inconsistent with the ionization energy gaps. Similar trends affect density functional theory (DFT) calculations that aim to achieve predictive quality. Importantly, the dielectric screened calculations are shown to significantly affect DFT- and HF PCM-based solvation energies, where screened solvation energies are smaller compared to the unscreened values. Importantly, SRSH-PCM, therefore, appears to reduce the tendency of DFT-PCM to overestimate solvation energies, where we find the effect to increase with the dielectric constant and the polarity of the molecular solute, trends that enhance the quality of DFT-PCM calculations of solvation energy. Understanding the relationship of dielectric screening in the Hamiltonian and DFT-PCM calculations can ultimately benefit on-going efforts for the design of predictive and parameter free descriptions of solvation energies.

Chemistry↗

Cric searchable image database as a public platform for conventional pap smear cytology data

Amidst the current health crisis and social distancing, telemedicine has become an important part of mainstream of healthcare, and building and deploying computational tools to support screening more efficiently is an increasing medical priority. The early identification of cervical cancer precursor lesions by Pap smear test can identify candidates for subsequent treatment. However, one of the main challenges is the accuracy of the conventional method, often subject to high rates of false negative. While machine learning has been highlighted to reduce the limitations of the test, the absence of high-quality curated datasets has prevented strategies development to improve cervical cancer screening. The Center for Recognition and Inspection of Cells (CRIC) platform enables the creation of CRIC Cervix collection, currently with 400 images (1,376 × 1,020 pixels) curated from conventional Pap smears, with manual classification of 11,534 cells. This collection has the potential to advance current efforts in training and testing machine learning algorithms for the automation of tasks as part of the cytopathological analysis in the routine work of laboratories.

59 BASIC BIOLOGICAL SCIENCES↗

Effects of Secondary Task Modality and Processing Code on Automation Trust and Utilization During Simulated Airline Luggage Screening

The purpose of this research was to examine the impact of environmental distractions on human trust and utilization of automation during the process of visual search. Participants performed a computer-simulated airline luggage screening task with the assistance of a 70% reliable automated decision aid (called DETECTOR) both with and without environmental distractions. The distraction was implemented as a secondary task in either a competing modality (visual) or non-competing modality (auditory). The secondary task processing code either competed with the luggage screening task (spatial code) or with the automation's textual directives (verbal code). We measured participants' system trust, perceived reliability of the system (when a target weapon was present and absent), compliance, reliance, and confidence when agreeing and disagreeing with the system under both distracted and undistracted conditions. Results revealed that system trust was lower in the visual-spatial and auditory-verbal conditions than in the visual-verbal and auditory-spatial conditions. Perceived reliability of the system (when the target was present) was significantly higher when the secondary task was visual rather than auditory. Compliance with the aid increased in all conditions except for the auditory-verbal condition, where it decreased. Similar to the pattern for trust, reliance on the automation was lower in the visual-spatial and auditory-verbal conditions than in the visual-verbal and auditory-spatial conditions. Confidence when agreeing with the system decreased with the addition of any kind of distraction; however, confidence when disagreeing increased with the addition of an auditory secondary task but decreased with the addition of a visual task. A model was developed to represent the research findings and demonstrate the relationship between secondary task modality, processing code, and automation use. Results suggest that the nature of environmental distractions influence interaction with automation via significant effects on trust and system utilization. These findings have implications for both automation design and operator training.

Phillips, Rachel↗

A Faster-Than-Real-Time Framework for Reliability-Oriented Simulation of PV Inverters

Physics-of-Failure (PoF) based reliability assessment for photovoltaic (PV) inverters requires long-duration electrical and electrothermal stress histories, yet generating such stress histories with high-fidelity switching models over year long mission profiles is computationally prohibitive. Conventional methods either sacrifice modeling fidelity for speed or require runtimes that are impractical for design iteration and uncertainty studies. To address this bottleneck, this paper presents a High-Performance Computing (HPC) based simulation frame work for faster-than-real-time reliability-oriented simulation. The proposed framework integrates the Average-to-Switching (A2S) method with parallel computing techniques to accelerate switching-level waveform reconstruction. We further introduce optimization strategies, including cluster merging and sensitivity based mission profile screening, to reduce the computational burden. Evaluated using real-world mission profile inputs and a MATLAB/Simulink switching-model reference, the framework reduces the simulation time for a one-year mission from an intractable multi-year duration to approximately 7.3 minutes while maintaining low waveform error. This acceleration provides a practical reliability-oriented simulation engine that can be coupled with component-specific aging models for subsequent PV inverter PoF assessment.

High-performance Computing↗

Program Facilitates Distributed Computing

KNET computer program facilitates distribution of computing between UNIX-compatible local host computer and remote host computer, which may or may not be UNIX-compatible. Capable of automatic remote log-in. User communicates interactively with remote host computer. Data output from remote host computer directed to local screen, to local file, and/or to local process. Conversely, data input from keyboard, local file, or local process directed to remote host computer. Written in ANSI standard C language.

Hui, Joseph↗

Machine-aided analysis of land use - Landform relations from ERTS-1 MSS imagery, Sand Hills Region, Nebraska

Machine-aided analysis of ERTS-1 MSS data obtained over the Sand Hills of Nebraska indicates that reasonably accurate soils maps can be produced automatically. An interpretation of spectral class spatial distribution and statistical character allows confident assignment of familiar soil and cover type names to computer classes. Resultant computer classification maps are displayed on a television screen or printer image. Correlation between computer maps and the USDA soils map of the same area is high. Geographic distribution of classes of interest can be accentuated by automatic methods. Percentages of cover type for any classified area also can be obtained. Interpretation of machine maps yields information concerning land use, physiographic, soil, and hydrologic patterns of the region.

Sinnock, S.↗

Designing Facilities for Collaborative Operations

A methodology for designing operational facilities for collaboration by multiple experts has begun to take shape as an outgrowth of a project to design such facilities for scientific operations of the planned 2003 Mars Exploration Rover (MER) mission. The methodology could also be applicable to the design of military "situation rooms" and other facilities for terrestrial missions. It was recognized in this project that modern mission operations depend heavily upon the collaborative use of computers. It was further recognized that tests have shown that layout of a facility exerts a dramatic effect on the efficiency and endurance of the operations staff. The facility designs (for example, see figure) and the methodology developed during the project reflect this recognition. One element of the methodology is a metric, called effective capacity, that was created for use in evaluating proposed MER operational facilities and may also be useful for evaluating other collaboration spaces, including meeting rooms and military situation rooms. The effective capacity of a facility is defined as the number of people in the facility who can be meaningfully engaged in its operations. A person is considered to be meaningfully engaged if the person can (1) see, hear, and communicate with everyone else present; (2) see the material under discussion (typically data on a piece of paper, computer monitor, or projection screen); and (3) provide input to the product under development by the group. The effective capacity of a facility is less than the number of people that can physically fit in the facility. For example, a typical office that contains a desktop computer has an effective capacity of .4, while a small conference room that contains a projection screen has an effective capacity of around 10. Little or no benefit would be derived from allowing the number of persons in an operational facility to exceed its effective capacity: At best, the operations staff would be underutilized; at worst, operational performance would deteriorate. Elements of this methodology were applied to the design of three operations facilities for a series of rover field tests. These tests were observed by human-factors researchers and their conclusions are being used to refine and extend the methodology to be used in the final design of the MER operations facility. Further work is underway to evaluate the use of personal digital assistant (PDA) units as portable input interfaces and communication devices in future mission operations facilities. A PDA equipped for wireless communication and Ethernet, Bluetooth, or another networking technology would cost less than a complete computer system, and would enable a collaborator to communicate electronically with computers and with other collaborators while moving freely within the virtual environment created by a shared immersive graphical display.

Norris, Jeffrey↗

The 3-D viscous flow CFD analysis of the propeller effect on an advanced ducted propeller subsonic inlet

A time marching Navier-Stokes code called PARC3D was used to study the 3-D viscous flow associated with an advanced ducted propeller (ADP) subsonic inlet at take-off operating conditions. At a free stream Mach number of 0.2, experimental data for the inlet-with-propeller test model indicated that the airflow was attached on the cowl windward lip at an angle of attack of 25 degrees became unstable at 29 degrees, and separated at 30 degrees. An experimental study with a similar inlet and with no propeller (through-flow) indicated that flow separation occurred at an angle of attack a few degrees below the value observed when the inlet was tested with the propeller. This tends to indicate that the propeller exerts a favorable effect on the inlet performance. During the through-flow experiment a stationary blockage device was used to successfully simulate the propeller effect on the inlet flow field at angles of attack. In the present numerical study, this flow blockage was modeled via a PARC3D computational boundary condition (BC) called the screen BC. The principle formulation of this BC was based on the one-and-half dimension actuator disk theory. This screen BC was applied at the inlet propeller face station of the computational grid. Numerical results were obtained with and without the screen BC. The application of the screen BC in this numerical study provided results which are similar to the results of past experimental efforts in which either the blockage device or the propeller was used.

Iek, Chanthy↗

Advanced display object selection methods for enhancing user-computer productivity

The User-Interface Technology Branch at NCCOSC RDT&E Division has been conducting a series of studies to address the suitability of commercial off-the-shelf (COTS) graphic user-interface (GUI) methods for efficiency and performance in critical naval combat systems. This paper presents an advanced selection algorithm and method developed to increase user performance when making selections on tactical displays. The method has also been applied with considerable success to a variety of cursor and pointing tasks. Typical GUI's allow user selection by: (1) moving a cursor with a pointing device such as a mouse, trackball, joystick, touchscreen; and (2) placing the cursor on the object. Examples of GUI objects are the buttons, icons, folders, scroll bars, etc. used in many personal computer and workstation applications. This paper presents an improved method of selection and the theoretical basis for the significant performance gains achieved with various input devices tested. The method is applicable to all GUI styles and display sizes, and is particularly useful for selections on small screens such as notebook computers. Considering the amount of work-hours spent pointing and clicking across all styles of available graphic user-interfaces, the cost/benefit in applying this method to graphic user-interfaces is substantial, with the potential for increasing productivity across thousands of users and applications.

Osga, Glenn A.↗

High operating temperature heat transfer fluids for solar thermal power generation. Final report

This is the final technical report for the DOE MURI project on developing high-operating temperature heat transfer fluids for solar thermal power generation. This project aimed to evaluate liquid metals as a heat-transport fluid and potential energy storage medium for concentrated solar powered (CSP) systems. The project consisted of five phases, starting with fluid selection and screen and ending with potential CSP integration. The initial fluid selection arrived at heavy liquid metals as candidate fluids such as lead bismuth eutectic (LBE) as the prime liquid-alloy candidate to be studied, given the conditions above. Fifty-seven liquid compositions were initially identified with liquidus temperatures lower than 200°C, composed of elements that provide no driving force to the reduction of Cr 2 O 3 or Al 2 O 3 passivation layers in pipe material which is required for corrosion prevention. LBE was identified as the primary candidate fluid after these compositions were compared against computational thermodynamic modeling to screen all of the selected systems that would be compatible with our design objectives. Twenty-eight of these compositions were also investigated with the rapid characterization methods; the accuracies of the liquidus temperature and the specific heats predicted by the computations were better than 3 percent and 9 percent, respectively. We conducted numerus corrosion tests of various Fe-Cr-Al based steels in LBE and its variants at temperate as high as 800°C. It was found that minor additions to the liquid did not provide sufficient corrosion protection to warrant their use in real applications. Furthermore, we investigated the detailed mechanism of corrosion between heavy liquid metal and the pipe material at these very high temperatures. A liquid metal loop was constructed to operate at these high temperatures. The loop construction and operation lead to valuable lessons learned that will be needed for industrial scale loops. Furthermore, we learned that electromagnetic pumps at these extreme temperatures will have to be reengineered and redesigned to be used for CSP applications.

14 SOLAR ENERGY↗

Energy Scheduling-based Operating Envelopes including a Distribution System Branch Screening Algorithm

This paper presents an energy scheduling-based formulation for computing operating envelopes including a distribution branch screening algorithm, termed DBS-ES. The contribution of the paper is two-fold: firstly, it presents an innovative methodology for calculating operating envelopes using energy scheduling (baseline), and secondly, it enhances this methodology by incorporating a custom distribution branch screening algorithm (DBS-ES). The custom algorithm leverages power system knowledge to reduce both model build time and total processing time while maintaining the same scheduling results as the baseline. The effectiveness of the proposed approach is demonstrated through experiments on the IEEE13, IEEE123, and EPRI Secondary test feeders. Results highlight a 24.5% decrease in model build time and an 8.17% decrease in total processing time when using DBS-ES compared to the baseline, specifically for the IEEE123 test feeder. Additionally, the paper briefly discusses the influence of utility-controlled storage on computing operating envelopes, noting a general incre

24 POWER TRANSMISSION AND DISTRIBUTION↗

Rapid subsurface analysis of frequency-domain thermoreflectance images with K-means clustering

K-means clustering analysis is applied to frequency-domain thermoreflectance (FDTR) hyperspectral image data to rapidly screen the spatial distribution of thermophysical properties at material interfaces. Performing FDTR while raster scanning a sample consisting of 8.6 μm of doped-silicon (Si) bonded to a doped-Si substrate identifies spatial variation in the subsurface bond quality. Routine thermal analysis at select pixels quantifies this variation in bond quality and allows assignment of bonded, partially bonded, and unbonded regions. Performing this same routine thermal analysis across the entire map, however, becomes too computationally demanding for rapid screening of bond quality. To address this, K-means clustering was used to reduce the dimensionality of the dataset from more than 20 000 pixel spectra to just K = 3 component spectra. The three component spectra were then used to express every pixel in the image through a least-squares minimized linear combination providing continuous interpolation between the components across spatially varying features, e.g., bonded to unbonded transition regions. Fitting the component spectra to the thermal model, thermal properties for each K cluster are extracted and then distributed according to the weighting established by the regressed linear combination. Thermophysical property maps are then constructed and capture significant variation in bond quality over 25 μm length scales. The use of K-means clustering to achieve these thermal property maps results in a 74-fold speed improvement over explicit fitting of every pixel.

36 MATERIALS SCIENCE↗

Systematic Screening of COVID-19 Disease Based on Chest CT and RT-PCR for Cancer Patients Undergoing Radiation Therapy in a Coronavirus French Hotspot

Patients with cancer are presumed to be more vulnerable to COVID-19. We evaluated a screening strategy combining chest computed tomography (CT) and reverse-transcription polymerase chain reaction (RT-PCR) for patients treated with radiation therapy at our cancer center located in a COVID-19 French hotspot during the first wave of the pandemic.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Ligand enhanced activity of in situ formed nanoparticles for photocatalytic hydrogen evolution

One consistent challenge of both computational and empirical catalyst screening is ensuring that the variables chosen for the screen are driving the performance analyzed. Furthermore, we compare photocatalytic hydrogen evolution from in situ formed Au and Au/Cu nanoparticles to nanoparticles of the same composition synthesized prior to being used as catalysts, as well as compare them to in situ formed Au and Au/Cu nanoparticles in the presence of exogeneous ligand. For all experiments, we observed that ligand-terminated nanoparticles performed better than un-stabilized in situ formed nanoparticles. We tested the generality of this result by studying Co, Ni, and Pd in the same system and also observed that the introduction of nanoparticle ligand leads to enhanced catalytic activity. Taken together, these results suggest 1) nanoparticle ligands can be beneficial, and even necessary, to produce catalysts with sustained activity 2) For computational prediction of these catalysts, factors relating to particle formation and stability need to be considered when both generating predictions as well as interpreting experimental results based on those predictions

08 HYDROGEN↗

Velocity Vector Field Visualization of Flow in Liquid Acquisition Device Channel

A capillary flow liquid acquisition device (LAD) for cryogenic propellants has been developed and tested in NASA Glenn Research Center to meet the requirements of transferring cryogenic liquid propellants from storage tanks to an engine in reduced gravity environments. The prototypical mesh screen channel LAD was fabricated with a mesh screen, covering a rectangular flow channel with a cylindrical outlet tube, and was tested with liquid oxygen (LOX). In order to better understand the performance in various gravity environments and orientations at different liquid submersion depths of the screen channel LAD, a series of computational fluid dynamics (CFD) simulations of LOX flow through the LAD screen channel was undertaken. The resulting velocity vector field visualization for the flow in the channel has been used to reveal the gravity effects on the flow in the screen channel.

McQuillen, John B.↗