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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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NASA NTRS2016

Using Remotely Piloted Aircraft and Onboard Processing to Optimize and Expand Data Collection

Remotely piloted aircraft (RPA) have the potential to revolutionize local to regional data collection for geophysicists as platform and payload size decrease while aircraft capabilities increase. In particular, data from RPAs combine high-resolution imagery available from low flight elevations with comprehensive areal coverage, unattainable from ground investigations and difficult to acquire from manned aircraft due to budgetary and logistical costs. Low flight elevations are particularly important for detecting signals that decay exponentially with distance, such as electromagnetic fields. Onboard data processing coupled with high-bandwidth telemetry open up opportunities for real-time and near real-time data processing, producing more efficient flight plans through the use of payload-directed flight, machine learning and autonomous systems. Such applications not only strive to enhance data collection, but also enable novel sensing modalities and temporal resolution. NASA’s Airborne Science Program has been refining the capabilities and applications of RPA in support of satellite calibration and data product validation for several decades. In this paper, we describe current platforms, payloads, and onboard data systems available to the research community. Case studies include Fluid Lensing for littoral zone 3D mapping, structure from motion for terrestrial 3D multispectral imaging, and airborne magnetometry on medium and small RPAs.

Fladeland, Matthew M.↗
DOE OSTI2022

Immunogenicity and protective efficacy of a rhesus adenoviral vaccine targeting conserved COVID-19 replication transcription complex

The COVID-19 pandemic marks the third coronavirus pandemic this century (SARS-CoV-1, MERS, SARS-CoV-2), emphasizing the need to identify and evaluate conserved immunogens for a pan-sarbecovirus vaccine. Here we investigate the potential utility of a T-cell vaccine strategy targeting conserved regions of the sarbecovirus proteome. We identified the most conserved regions of the sarbecovirus proteome as portions of the RNA-dependent RNA polymerase (RdRp) and Helicase proteins, both of which are part of the coronavirus replication transcription complex (RTC). Fitness constraints suggest that as SARS-CoV-2 continues to evolve these regions may better preserve cross-reactive potential of T-cell responses than Spike, Nucleocapsid, or Membrane proteins. We sought to determine if vaccine-elicited T-cell responses to the highly conserved regions of the RTC would reduce viral loads following challenge with SARS-CoV-2 in mice using a rhesus adenovirus serotype 52 (RhAd52) vector. The RhAd52.CoV.Consv vaccine generated robust cellular immunity in mice and led to significant reductions in viral loads in the nasal turbinates following challenge with a mouse-adapted SARS-CoV-2. These data suggest the potential utility of T-cell targeting of conserved regions for a pan-sarbecovirus vaccine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Broad absorption line quasars in the Dark Energy Spectroscopic Instrument Early Data Release

Broad absorption line (BAL) quasars are characterized by gas clouds that absorb flux at the wavelength of common quasar spectral features, although blueshifted by velocities that can exceed $0.1c$. BAL features are interesting as signatures of significant feedback, yet they can also compromise cosmological studies with quasars by distorting the shape of the most prominent quasar emission lines, impacting redshift accuracy and measurements of the matter density distribution traced by the Lyman $\alpha$ forest. We present a catalogue of BAL quasars discovered in the Dark Energy Spectroscopic Instrument (DESI) survey Early Data Release, which were observed as part of DESI Survey Validation, as well as the first two months of the main survey. We describe our method to automatically identify BAL quasars in DESI data, the quantities we measure for each BAL, and investigate the completeness and purity of this method with mock DESI observations. We mask the wavelengths of the BAL features and re-evaluate each BAL quasar redshift, finding new redshifts which are $243\, {\rm km}\, {\rm s}^{-1}$ smaller on average for the BAL quasar sample. These new, more accurate redshifts are important to obtain the best measurements of quasar clustering, especially at small scales. Finally, we present some spectra of rarer classes of BALs that illustrate the potential of DESI data to identify such populations for further study.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Advancing Fusion with Machine Learning Research Needs Workshop Report

Abstract Machine learning and artificial intelligence (ML/AI) methods have been used successfully in recent years to solve problems in many areas, including image recognition, unsupervised and supervised classification, game-playing, system identification and prediction, and autonomous vehicle control. Data-driven machine learning methods have also been applied to fusion energy research for over 2 decades, including significant advances in the areas of disruption prediction, surrogate model generation, and experimental planning. The advent of powerful and dedicated computers specialized for large-scale parallel computation, as well as advances in statistical inference algorithms, have greatly enhanced the capabilities of these computational approaches to extract scientific knowledge and bridge gaps between theoretical models and practical implementations. Large-scale commercial success of various ML/AI applications in recent years, including robotics, industrial processes, online image recognition, financial system prediction, and autonomous vehicles, have further demonstrated the potential for data-driven methods to produce dramatic transformations in many fields. These advances, along with the urgency of need to bridge key gaps in knowledge for design and operation of reactors such as ITER, have driven planned expansion of efforts in ML/AI within the US government and around the world. The Department of Energy (DOE) Office of Science programs in Fusion Energy Sciences (FES) and Advanced Scientific Computing Research (ASCR) have organized several activities to identify best strategies and approaches for applying ML/AI methods to fusion energy research. This paper describes the results of a joint FES/ASCR DOE-sponsored Research Needs Workshop on Advancing Fusion with Machine Learning, held April 30–May 2, 2019, in Gaithersburg, MD (full report available at https://science.osti.gov/-/media/fes/pdf/workshop-reports/FES_ASCR_Machine_Learning_Report.pdf ). The workshop drew on broad representation from both FES and ASCR scientific communities, and identified seven Priority Research Opportunities (PRO’s) with high potential for advancing fusion energy. In addition to the PRO topics themselves, the workshop identified research guidelines to maximize the effectiveness of ML/AI methods in fusion energy science, which include focusing on uncertainty quantification, methods for quantifying regions of validity of models and algorithms, and applying highly integrated teams of ML/AI mathematicians, computer scientists, and fusion energy scientists with domain expertise in the relevant areas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Limits of special material detectability fundamental to idealized dual-energy radiographic systems

Analysis of dual-energy radiographic approaches to the detection of “special” material, i.e. contraband, in otherwise innocuous scenes, such as maritime cargo containers encountered at ports of entry, reveals fundamental limitations of data obtained along a single line-of-sight. The basic equations that describe idealized systems are presented and analyzed so as to identify challenges that are only exacerbated by scatter, noise, and measurement uncertainty. In the mono-energetic limit, the instrumentation and measurement methods reduce to a system of linear equations that are simple to treat: it is observed that there exists a threshold for the minimum amount of high-Z material that can be detected unambiguously (without the risk of false positive or false negative indications), even when the background materials are of finite and of well-known variety. The threshold depends on the quality of prior information about the cargo and the selection of probing energies, and can therefore be minimized by good system design practices and measurement procedures, but persists as a general challenge to security operations. In discussion of this result, it is noted that techniques incorporating other prior information, such as the geometry of cargo and potential contraband, along with data from 2D imaging, have far greater potential. For instance, a simple data analysis method capable of differentiating high-Z spheres from those of more common material is presented. This simple example demonstrates that, although simple line-of-sight transmission radiography may suffer fundamental limitations, there remains good cause to be optimistic about the potential for image analysis in radiographic material identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRSDate not supplied

One-Carbon Metabolism and SANS 2022 Update

Spaceflight Associated Neuro-ocular Syndrome, or SANS, affects a subset of astronauts (1, 2), and biochemical evidence has documented differences in those astronauts (3). Specifically, they had higher circulating concentrations of metabolites of the one-carbon metabolic pathway (1C), including homocysteine, and these concentrations were higher before flight (3). After ruling out many potential confounding factors in these otherwise healthy individuals (e.g., sex, kidney function, vitamin status, coffee consumption), a study of genetics was warranted. In an initial pilot effort, we documented a genetic predisposition to develop ophthalmic changes after long-duration space flight (4). That is, from a limited study of 5 single-nucleotide polymorphisms (SNPs), we found that the G allele for the MTRR A66G SNP was associated with a greater risk of choroidal folds and cotton-wool spots after flight, and the C allele for SHMT1 C1420T was protective against optic disc edema (4). These data provide a potential pathway for understanding why some individuals develop SANS, while others do not. The initial pilot study of 5 SNPs yielded striking findings, but the 1C pathway is far more complex. An effort was undertaken to examine more than 500 1C SNPs to see if a broader examination could help illuminate this association. That work is ongoing. The astronaut findings led us to advocate for the inclusion of 1C pathway genetic and biochemistry testing on other SANS-related projects, noting that genetics might help identify responders, non-responders, or outliers. The first such effort yielded evidence of an association of specific forms of the MTRR and SHMT-1 SNPs and vitamin B12 status with end-tidal CO2 after acute carbon dioxide exposure (5). The second such effort led to the identification that individuals exposed to strict head-down tilt and CO2 for 30-d who developed optic disc edema also had risk alleles for the two SNPs described above (6). Additionally, we identified a clinical population with many characteristics either attributed or purported to be involved in the ocular changes seen in affected astronauts: women with polycystic ovary syndrome (PCOS). PCOS is a condition of androgen excess and anovulatory menstrual cycles. The shared characteristics and clinical findings between SANS and PCOS generally include higher circulating homocysteine concentrations, increased retinal nerve fiber layer thickness, increased androgen concentrations (or responses), and altered carbohydrate metabolism. To our knowledge, no study has examined whether women with PCOS have asymptomatic ophthalmic anomalies observed in astronauts with SANS. While researchers have evaluated the one-carbon metabolism pathway polymorphisms of PCOS patients, and initial studies show an association with certain one-carbon polymorphisms, none have looked at the set of SNPs identified in our studies that are associated with ophthalmic changes in astronauts. Accordingly, we designed a study to evaluate the association of one-carbon pathway SNPs and ophthalmic findings in patients with PCOS and/or IIH compared to controls. Subjects provided blood samples for vitamin and one carbon biochemistry analyses, an extensive analysis of >500 SNPs associated with one carbon metabolism and had eye examinations and ocular imaging. Data analysis are underway. The data collected to date have shown associations between one carbon pathway biochemistry and genetics and incidence of SANS. The mechanisms for SANS has yet to be identified, although many hypotheses exist. Based on our data, we have developed (8, 9) and expanded (6) a multi-hit hypothesis for how these seemingly disparate findings could be linked. While intriguing, the hypothesis represents the starting point for further research. We aim to clarify the relationship between B-vitamin status and genetics with regard to the risk of SANS. Ultimately, understanding the mechanism(s) behind this will provide a means to predict, prevent, or treat these ophthalmologic pathologies in astronauts, and terrestrial populations.

S M Smith↗
DOE OSTI2022

Composition design of high-entropy alloys with deep sets learning

High entropy alloys (HEAs) are an important material class in the development of next-generation structural materials, but the astronomically large composition space cannot be efficiently explored by experiments or first-principles calculations. Machine learning (ML) methods might address this challenge, but ML of HEAs has been hindered by the scarcity of HEA property data. In this work, the EMTO-CPA method was used to generate a large HEA dataset (spanning a composition space of 14 elements) containing 7086 cubic HEA structures with structural properties, 1911 of which have the complete elastic tensor calculated. The elastic property dataset was used to train a ML model with the Deep Sets architecture. The Deep Sets model has better predictive performance and generalizability compared to other ML models. Association rule mining was applied to the model predictions to describe the compositional dependence of HEA elastic properties and to demonstrate the potential for data-driven alloy design.

36 MATERIALS SCIENCE↗
NASA NTRS1987

A three-dimensional dual potential procedure with applications to wind tunnel inlets and interacting boundary layers

A dual potential decomposition of the velocity field into a scalar and a vector potential function is extended to three dimensions and used in the finite-difference simulation of steady three-dimensional inviscid rotational flows and viscous flow. The finite-difference procedure was used to simulate the flow through the 80 by 120 ft wind tunnel at NASA Ames Research Center. Rotational flow produced by the stagnation pressure drop across vanes and screens which are located at the entrance of the inlet is modeled using actuator disk theory. Results are presented for two different inlet vane and screen configurations. The numerical predictions are in good agreement with experimental data. The dual potential procedure was also applied to calculate the viscous flow along two and three dimensional troughs. Viscous effects are simulated by injecting vorticity which is computed from a boundary layer algorithm. For attached flow over a three dimensional trough, the present calculations are in good agreement with other numerical predictions. For separated flow, it is shown from a two dimensional analysis that the boundary layer approximation provides an accurate measure of the vorticity in regions close to the wall; whereas further away from the wall, caution has to be exercised in using the boundary-layer equations to supply vorticity to the dual potential formulation.

Rao, K. V.↗
DOE OSTI2026

Do we have globally representative data to understand soil processes?

Understanding and modeling soils and soil organic matter (SOM) are central to a variety of human needs, from food production to ecosystem management. Soil data have been collected for over a century, but the global spatial and process representativeness of soil data remains unclear. We assessed the representativeness of currently available soil data that could be used to understand a variety of SOM processes. We used 16 open-source soil databases and data from over 281,000 unique locations globally, categorizing the databases into three main data types necessary to understand SOM processes: soil carbon stocks and fluxes, mechanistic drivers of these stocks and fluxes, and soil carbon gain or loss potential. We found that stock and driver data have extensive global coverage. However, data on soil carbon gain or loss potential, particularly data describing change in soils over time such as time series data, are severely limited in their global coverage. We conclude that while significant strides have been made in measuring soil carbon stocks and fluxes, and their drivers, we are limited in global data related to changes in soils over time. Our recommendations for soil data generators are to ensure precise metadata reporting and prioritizing sampling in underrepresented areas like tropical, arctic, mountainous, wetland and arid regions. We also encourage designing revisit schemes that explicitly support change detection and reporting multi-modal datasets that can aid in model development. Targeted measurement of low coverage soil data types and regions is necessary for a range of applications including current and future biogeochemical predictions, and their management and policy implications.

carbon fluxes↗
DOE OSTI2025

Measurement of double-differential charged-current Drell-Yan cross-sections at high transverse masses in $pp$ collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

This paper presents a first measurement of the cross-section for the charged-current Drell-Yan process pp → W ± → ℓ ± ν above the resonance region, where ℓ is an electron or muon. The measurement is performed for transverse masses, $m$$^{W}_{T}$, between 200 GeV and 5000 GeV, using a sample of 140 fb −1 of pp collision data at a centre-of-mass energy of = 13 TeV collected by the ATLAS detector at the LHC during 2015–2018. The data are presented single differentially in transverse mass and double differentially in transverse mass and absolute lepton pseudorapidity. A test of lepton flavour universality shows no significant deviations from the Standard Model. The electron and muon channel measurements are combined to achieve a total experimental precision of 3% at low $m$$^{W}_{T}$. The single- and double differential W-boson charge asymmetries are evaluated from the measurements. A comparison to next-to-next-to-leading-order perturbative QCD predictions using several recent parton distribution functions and including next-to-leading-order electroweak effects indicates the potential of the data to constrain parton distribution functions. The data are also used to constrain four fermion operators in the Standard Model Effective Field Theory formalism, in particular the lepton-quark operator Wilson coefficient $c$$^{(c)}_{ℓq}$.

Hadron-Hadron Scattering↗
DOE OSTI2019

Comparison of conventional versus liposomal irinotecan in combination with fluorouracil for advanced pancreatic cancer: a single-institution experience

The majority of pancreatic cancers are diagnosed at an advanced stage, when surgical options are limited and treatment relies on systemic chemotherapy. In the NAPOLI-1 trial, liposomal irinotecan in combination with fluorouracil (nal-iri/5FU) was shown to improve overall survival when compared to fluorouracil alone for metastatic pancreatic cancer. Other retrospective studies have shown the combination of fluorouracil and conventional irinotecan (FOLFIRI) to be a viable option, though no randomized trials have compared nal-iri/5FU to FOLFIRI. The purpose of this single-center, retrospective, cohort study was to determine if nal-iri/5FU and FOLFIRI are similarly effective for the treatment of advanced pancreatic cancer. Due to the potential for treatment bias, inverse probability of treatment weighting was utilized to correct for baseline differences between the groups. The primary outcome of progression-free survival was similar at 4.1 months for nal-iri/5FU and 3.1 months for FOLFIRI. Overall survival and adverse effect frequency were also similar. Pegfilgrastim was used in 16% and 15% of patients, respectively, and nal-iri/5FU patients required significantly less atropine during treatment (36 vs. 70%). A cost analysis was conducted and concluded that the treatment with nal-iri/5FU was nearly 30 times more expensive than FOLFIRI treatment. Together, these data suggest a potential role for FOLFIRI for the treatment of advanced pancreatic cancer in the absence of clear benefits in effectiveness, toxicity, or cost for nal-iri/5FU.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Amorphous tantala and its relationship with the molten state

The structure factors of molten Ta 2 O 5 and Nb 2 O 5 have been measured by high-energy x-ray and pulsed neutron diffraction. These are compared to transmission-mode x-ray diffraction through a self-supported 15-μm ion-beam sputtered amorphous tantala film. Atomistic models derived from the diffraction data by means of empirical potential structure refinement reveal that tantala and niobia liquids are very close to isomorphous, as confirmed by measurement of a molten mixture, Ta 0.8 Nb 1.2 O 5 . Nonetheless, peak Nb-O bond lengths are about 1% shorter than those for Ta-O, at temperatures, T*=T/T melt , scaled to the melting points. Mean coordination numbers are n MO ≃5.6(1),n OM ≃2.23(4) in the liquid state, and n TaO ≃6.6(2),n OTa ≃2.63(8) in the solid. The liquids are built from five- and six-fold M-O polyhedra which connect principally by corner sharing, with a minority of edge sharing; a-Ta 2 O 5 on the other hand has a local structure more akin to the crystalline polymorphs, built primarily from six- and seven-fold polyhedra, with a larger degree of edge sharing. The structural differences between liquid and amorphous Ta 2 O 5 , coupled with observations of increasing peak bond lengths upon cooling, are consistent with the interpretation that the amorphous film reaches a supercooled liquidlike metastable equilibrium during deposition. In other words, the amorphous film shares a common progenitor state with a hypothetical glass quenched from a fragile melt. In addition, we show that recent classical interatomic potentials do not fully reproduce the diffraction data, and infer that inclusion of attractive (non-Coulombic) Ta-Ta interactions is important, particularly for obtaining the correct degree of edge sharing, coordination numbers, and densities. In conclusion, nanoscale inhomogeneity of the amorphous film is confirmed by the observation of small-angle x-ray scattering.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2010

Visual Data Comm: A Tool for Visualizing Data Communication in the Multi Sector Planner Study

Data comm is a new technology proposed in future air transport system as a potential tool to provide comprehensive data connectivity. It is a key enabler to manage 4D trajectory digitally, potentially resulting in improved flight times and increased throughput. Future concepts with data comm integration have been tested in a number of human-in-the-loop studies but analyzing the results has proven to be particularly challenging because future traffic environment in which data comm is fully enabled has assumed high traffic density, resulting in data set with large amount of information. This paper describes the motivation, design, current and potential future application of Visual Data Comm (VDC), a tool for visualizing data developed in Java using Processing library which is a tool package designed for interactive visualization programming. This paper includes an example of an application of VDC on data pertaining to the most recent Multi Sector Planner study, conducted at NASA s Airspace Operations Laboratory in 2009, in which VDC was used to visualize and interpret data comm activities

Lee, Hwasoo Eric↗
DOE OSTI2025

How Representative Are Uncrewed Aircraft System Measurements of the Convective Boundary Layer?

Abstract Uncrewed aircraft systems (UAS) demonstrate significant potential for filling data gaps in the atmospheric boundary layer. However, the extent to which UAS observations—typically vertical profiles taken over 15 min—are representative of the boundary layer as a whole remains poorly characterized. Using large eddy simulations (LES) of the daytime convective boundary layer (CBL), we quantify random errors in UAS measurements that occur due to insufficient statistical convergence of the time average to the true ensemble mean. Random errors in first‐order moments increase as the CBL becomes increasingly unstable, and are largest near the surface for most quantities. Errors are on the order of 2–6 m for wind speed, 15–60 for wind direction, 0.2–3 K for potential temperature, and 0.1–1 g for specific humidity, with errors in turbulent fluxes on the order of 50%–100%. Sampling strategies that mitigate random errors are discussed in light of our results.

Greene, Brian R. [Now at Verisk Extreme Event Solu↗
DOE OSTI2018

Pharmacological characterization of the neurotrophic sesquiterpene jiadifenolide reveals a non-convulsant signature and potential for progression in neurodegenerative disease studies

The ‘neurotrophic sesquiterpenes’ refer to a group of molecules derived from the Illicium genus of flowering plant. They display neurotrophic effects in cultured neuron preparations and have been suggested to be cognitive enhancers and potential therapeutics for neurodegenerative disorders and dementias. Recent synthetic advances generated sufficient quantities of jiadifenolide for in vivo investigation into its biological effects. Jiadifenolide did not induce convulsions in mice nor did it enhance or diminish convulsions induced by pentylenetetrazole. Other negative allosteric modulators of GABA A receptors, picrotoxin, tetramethylenedisulfotetramine (TETS), and bilobalide all induced convulsions. Either i.p. or i.c.v. dosing generated micromolar plasma and brain levels of jiadifenolide but only small effects on locomotion of mice. However, jiadifenolide decreased d-amphetamine-induced hyperlocomotion in mice, an antipsychotic-like drug effect. Jiadifenolide did not significantly alter body temperature or behavior in the forced-swim test in mice. Molecular simulation data suggested a potential site in the pore/M2 helix region that is at an overlapping, yet lower position than those observed for other ‘cage convulsant’ compounds such as TETS and picrotoxin. We hypothesize here that a position nearer to the entrance of the pore channel may allow for easier displacement of jiadifenolide from its blocking location leading to lower potency and lower side-effect liability. Like jiadifenolide, memantine (Namenda), one of the few drugs used in the symptomatic treatment of dementias, occupies a unique site on the NMDA receptor complex that creates low binding affinity that is associated with its reduced side-effect profile. Given the potential therapeutic applications of jiadifenolide and its relatively inert effects on overt behavior, the possibility of clinical utility for jiadifenolide and related compounds becomes intriguing.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2008

Space Nutrition: Effects on Bone and Potential Nutrition Countermeasures

Optimal nutrition will be critical for crew members who embark on space exploration missions. Nutritional assessment provides an opportunity to ensure that crewmembers begin their missions in optimal nutritional status, to document changes during a mission and , if necessary, to provide intervention to maintain that status throughout the mission, and to assesses changes after landing in order to facilitate the return to their normal status as soon as possible after landing. We report here the findings from our nutritional assessment of the US astronauts who participated in the first eight International Space Station (ISS) missions. Bone loss during space flight remains one of the most critical challenges to astronaut health on space exploration missions. An increase in bone resorption of ISS crew members after flight was indicated by several markers. Vitamin D status also remains a challenge for long-duration space travelers, who lack ultraviolet light exposure in the shielded craft. Many nutrients affect bone, including calcium, protein, fatty acids, sodium, and others. Data supporting their potential as countermeasures for space flight, as published in many papers, will be reviewed in this presentation. Defining nutrient requirements, and being able to provide and maintain those nutrients on exploration missions, will be critical for maintaining crew member health. Please note, this abstract is not required for the meeting. A presentation on the topics described above will be given. This abstract is for travel documentation only.

Smith, Scott M.↗
NASA NTRS2013

A CFD Database for Airfoils and Wings at Post-Stall Angles of Attack

This paper presents selected results from an ongoing effort to develop an aerodynamic database from Reynolds-Averaged Navier-Stokes (RANS) computational analysis of airfoils and wings at stall and post-stall angles of attack. The data obtained from this effort will be used for validation and refinement of a low-order post-stall prediction method developed at NCSU, and to fill existing gaps in high angle of attack data in the literature. Such data could have potential applications in post-stall flight dynamics, helicopter aerodynamics and wind turbine aerodynamics. An overview of the NASA TetrUSS CFD package used for the RANS computational approach is presented. Detailed results for three airfoils are presented to compare their stall and post-stall behavior. The results for finite wings at stall and post-stall conditions focus on the effects of taper-ratio and sweep angle, with particular attention to whether the sectional flows can be approximated using two-dimensional flow over a stalled airfoil. While this approximation seems reasonable for unswept wings even at post-stall conditions, significant spanwise flow on stalled swept wings preclude the use of two-dimensional data to model sectional flows on swept wings. Thus, further effort is needed in low-order aerodynamic modeling of swept wings at stalled conditions.

Petrilli, Justin↗
DOE OSTI2026

Neural network potentials with effective charge separation for non-equilibrium dynamics of ionic solids: a ZnO case study

Developing neural network potentials (NNPs) accurate under non-equilibrium dynamics is challenging, as such systems require extensive sampling beyond equilibrium phases. Here we construct high-fidelity NNPs for zinc oxide (ZnO), a polymorphic ionic solid, using density functional theory (DFT) reference data. To efficiently capture transitional configurations, we combine enhanced-sampling molecular dynamics with empirical potentials, data distillation, and pretraining on short-range atomic energies (A-Train), followed by transfer learning with DFT-relabeled datasets. This hierarchical approach improves transferability across polymorphs and stress states. We further introduce effective charge separation, treating long-range Coulombic terms analytically while short-range residual interactions are learned by the NNP. The optimal effective charges fall in the range 0.5–1.0 q e , consistent with dielectric-screened values derived from formal charges but distinct from Bader estimates. Motivated by this observation, we propose a simple data-driven protocol in which effective charges are optimized by comparing DFT reference energies with explicit Coulomb calculations, without additional NNP training. This strategy improves accuracy and transferability in DFT-level predictions of energies, forces, and stress. Together, these results provide a practical charge-selection framework for robust NNP development in ionic solids, enabling reliable simulation of polymorphic phase transformations and non-equilibrium dynamics.

Chemistry↗