Recirculation and ingestion characteristics of a large scale VTOL lift engine pod Topical report
Recirculation and ingestion characteristics of large scale model VTOL lift engine pod
Hall, G. R.↗
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Apollo-Soyuz test project Extreme Ultraviolet Telescope MA-083
Follow-on studies to the Apollo-Soyuz Extreme Ultraviolet Telescope experiment (MA-083) include analyses of individual target stars or classes of stars, not only with regard to the EUV data but also in connection with theoretical models and observations in other parts of the spectrum. Topics discussed include: observations of SS Cygni, Proxima Centauri, HZ 43, and Feige 24; computer searches for new EUV sources; Sirius: models and inferences; EUV emission from a hot gas; and the diffuse EUV background.
Bowyer, C. S.↗
Navier-Stokes computation of compressible turbulent flows with a second order closure, part 1
A second order closure turbulence model for compressible flows is developed and implemented in a 2D Reynolds-averaged Navier-Stokes solver. From the beginning where a kappa-epsilon turbulence model was implemented in the bidiagonal implicit method of MACCORMACK (referred to as the MAC3 code) to the final stage of implementing a full second order closure in the efficient line Gauss-Seidel algorithm, numerous work was done, individually and collectively. Besides the collaboration itself, the final product of this work is a second order closure derived from the Launder, Reece, and Rodi model to account for near wall effects, which has been called FRAME model, which stands for FRench-AMerican-Effort. During the reporting period, two different problems were worked out. The first was to provide Ames researchers with a reliable compressible boundary layer code including a wide collection of turbulence models for quick testing of new terms, both in two equations and in second order closure (LRR and FRAME). The second topic was to complete the implementation of the FRAME model in the MAC5 code. The work related to these two different contributions is reported. dilatation in presence of stron shocks. This work, which has been conducted during a work at the Center for Turbulence Research with Zeman aimed also to cros-check earlier assumptions by Rubesin and Vandromme.
Haminh, Hieu↗
Real-Time Dynamic Modeling - Data Information Requirements and Flight Test Results
Practical aspects of identifying dynamic models for aircraft in real time were studied. Topics include formulation of an equation-error method in the frequency domain to estimate non-dimensional stability and control derivatives in real time, data information content for accurate modeling results, and data information management techniques such as data forgetting, incorporating prior information, and optimized excitation. Real-time dynamic modeling was applied to simulation data and flight test data from a modified F-15B fighter aircraft, and to operational flight data from a subscale jet transport aircraft. Estimated parameter standard errors and comparisons with results from a batch output-error method in the time domain were used to demonstrate the accuracy of the identified real-time models.
Morelli, Eugene A.↗
Real-Time Dynamic Modeling - Data Information Requirements and Flight Test Results
Practical aspects of identifying dynamic models for aircraft in real time were studied. Topics include formulation of an equation-error method in the frequency domain to estimate non-dimensional stability and control derivatives in real time, data information content for accurate modeling results, and data information management techniques such as data forgetting, incorporating prior information, and optimized excitation. Real-time dynamic modeling was applied to simulation data and flight test data from a modified F-15B fighter aircraft, and to operational flight data from a subscale jet transport aircraft. Estimated parameter standard errors, prediction cases, and comparisons with results from a batch output-error method in the time domain were used to demonstrate the accuracy of the identified real-time models.
Morelli, Eugene A.↗
Physics-based modeling and data analytics [Slides]
This presentation contains a summary of ongoing work within the physics-based modeling and data analytics work package within the Nuclear Materials Discovery and Qualification initiative (NMDQi). Topics include work on MOOSE-based crystal plasticity, molecular dynamics modeling of recombination in metals and alloys, the MOOSE Stochastic Tools Module, and machine learning and atomistic modeling to predict thermo-kinetic properties of nuclear structural materials.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Error and Uncertainty Quantification in the Numerical Simulation of Complex Fluid Flows
The failure of numerical simulation to predict physical reality is often a direct consequence of the compounding effects of numerical error arising from finite-dimensional approximation and physical model uncertainty resulting from inexact knowledge and/or statistical representation. In this topical lecture, we briefly review systematic theories for quantifying numerical errors and restricted forms of model uncertainty occurring in simulations of fluid flow. A goal of this lecture is to elucidate both positive and negative aspects of applying these theories to practical fluid flow problems. Finite-element and finite-volume calculations of subsonic and hypersonic fluid flow are presented to contrast the differing roles of numerical error and model uncertainty. for these problems.
Barth, Timothy J.↗
Tevatron greatest hits
The Tevatron collider led the World energy frontier program in particle physics during the late 20th and early 21st centuries. During this exciting period the standard model of particle physics was in its final stages of development and the search for physics beyond the standard model became one of the main research topics. In this review article we summarize the design and performance of the Tevatron collider and its two detectors, CDF and D0, as well as their evolution. Here, highlights of the Tevatron scientific results are provided, including the discovery of the top quark and measurements of its properties, studies and discoveries of the particles containing heavy quarks, precision studies of the strong and electroweak forces, searches for beyond the standard model particles and interactions, as well as the hunt for the Higgs boson.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Shift Happens: Building Robust AI Models with Domain Adaptation
Artificial Intelligence (AI) is revolutionizing physics research—from probing the large-scale structure of the Universe to modeling subatomic interactions and fundamental forces. Yet, a major challenge persists: AI models trained on simulations or old experiment / astronomical survey often perform poorly when applied to new data—exposing issues of dataset (domain) shift, model robustness, and uncertainty in predictions. This summer school session will introduce students to common challenges in applying AI across domains and present solutions based on domain adaptation—a set of techniques designed to improve model generalization under domain shift. We will cover foundational ideas, practical strategies, and current research frontiers in this area. Through examples in astrophysics, we'll explore how domain adaptation can help bridge the gap between synthetic and real-world data, improve trust in model outputs, and advance scientific discovery. The concepts discussed are broadly applicable across physics and other scientific disciplines, making this a valuable topic for anyone interested in building robust, transferable AI models for science.
Ciprijanovic, A. [Fermilab] (ORCID:000000031281719↗
Mesoscale meteorology - Theories, observations and models; Proceedings of the Advanced Study Institute, Bonas, Gers, France, July 13-31, 1982
Among the topics discussed are mesoscale processes and variability, regional and cyclonic scale motions and their prediction modeling, fronts, mesoscale instabilities, buoyancy (gravity) waves and topographic forcing, buoyant convection, boundary layers, and observational technology. The specific issues investigated include methods for initializing mesoscale forecast models, an energy theory for the propagation of gravity currents, a theory for rain bands within extratropical cyclones, the morning glory as a nonlinear wave phenomenon, cumulus clouds, the prediction of severe convection, planetary boundary layer parameterization, and three-dimensional wind field analysis from Doppler radar data.
Lilly, D. K.↗
Magnesium- and intermetallic alloys-based hydrides for energy storage: modelling, synthesis and properties
Hydrides based on magnesium and intermetallic compounds provide a viable solution to the challenge of energy storage from renewable sources, thanks to their ability to absorb and desorb hydrogen in a reversible way with a proper tuning of pressure and temperature conditions. Therefore, they are expected to play an important role in the clean energy transition and in the deployment of hydrogen as an efficient energy vector. This review, by experts of Task 40 ‘Energy Storage and Conversion based on Hydrogen’ of the Hydrogen Technology Collaboration Programme of the International Energy Agency, reports on the latest activities of the working group ‘Magnesium- and Intermetallic alloys-based Hydrides for Energy Storage’. The following topics are covered by the review: multiscale modelling of hydrides and hydrogen sorption mechanisms; synthesis and processing techniques; catalysts for hydrogen sorption in Mg; Mg-based nanostructures and new compounds; hydrides based on intermetallic TiFe alloys, high entropy alloys, Laves phases, and Pd-containing alloys. Finally, an outlook is presented on current worldwide investments and future research directions for hydrogen-based energy storage.
Energy storage↗
Infinite neural network quantum states: entanglement and training dynamics
We study infinite limits of neural network quantum states (∞-NNQS), which exhibit representation power through ensemble statistics, and also tractable gradient descent dynamics. Ensemble averages of entanglement entropies are expressed in terms of neural network correlators, and architectures that exhibit volume-law entanglement are presented. The analytic calculations of entanglement entropy bound are tractable because the ensemble statistics are simplified in the Gaussian process limit. A general framework is developed for studying the gradient descent dynamics of neural network quantum states (NNQS), using a quantum state neural tangent kernel (QS-NTK). For ∞-NNQS the training dynamics is simplified, since the QS-NTK becomes deterministic and constant. An analytic solution is derived for quantum state supervised learning, which allows an ∞-NNQS to recover any target wavefunction. Numerical experiments on finite and infinite NNQS in the transverse field Ising model and Fermi Hubbard model demonstrate excellent agreement with theory. ∞-NNQS opens up new opportunities for studying entanglement and training dynamics in other physics applications, such as in finding ground states.
quantum state supervised learning↗
Review of Grey Box/Black Box Data Contamination Metrics on Open and Commercial Models
Dataset contamination is a problem where benchmarks and tasks used to evaluate the capabilities of Large Language Models (LLMs) have been incorporated into the training dataset of the models. This gives a false sense of performance that can overestimate how these models will function on truly unseen data. This problem becomes worse with commercial LLMs with larger and non-accessible training data, so techniques have been developed to try to measure the degree to which a model is contaminated with a benchmark’s data. To understand the effectiveness of these techniques, particularly when evaluating contamination on coding tasks, we review trends and categorize techniques by the degree of access to the model that is required. The research literature on this topic has reported mixed effectiveness of these techniques, so we select a set of black box (text access only) and grey box (access to model loss/probabilities required) techniques and apply them to both commercial and non-commercial models. We implement these metrics as part of a framework to test the contamination of Python code in LLMs to see to what extent we can replicate the effectiveness (or ineffectiveness) of these contamination detection techniques. Though we find mixed results in the capabilities of these metrics to identify contamination, we do observe evidence that they can identify contamination (broadly) in fine-tuned models when both a baseline and fine-tuned model is present. Additionally, similarity metrics were able to identify between contaminated and uncontaminated data even in situations where the data is distributionally similar (e.g., drawn from the same set of code projects).
97 MATHEMATICS AND COMPUTING↗
Goddard Conference on Mass Storage Systems and Technologies, Volume 1
Copies of nearly all of the technical papers and viewgraphs presented at the Goddard Conference on Mass Storage Systems and Technologies held in Sep. 1992 are included. The conference served as an informational exchange forum for topics primarily relating to the ingestion and management of massive amounts of data and the attendant problems (data ingestion rates now approach the order of terabytes per day). Discussion topics include the IEEE Mass Storage System Reference Model, data archiving standards, high-performance storage devices, magnetic and magneto-optic storage systems, magnetic and optical recording technologies, high-performance helical scan recording systems, and low end helical scan tape drives. Additional topics addressed the evolution of the identifiable unit for processing purposes as data ingestion rates increase dramatically, and the present state of the art in mass storage technology.
Kobler, Ben↗
Papers presented to the Conference on Chondrules and the Protoplanetary Disk
The following topics are covered in the presented papers: (1) producing chondrules; (2) carbons, CAI's, and chondrules; (3) large scale processes in the solar nebula; (4) chondrule-matrix relationships in chondritic meteorites; (5) overview of nebula models; (6) constraints placed on the nature of chondrule precursors; (7) turbulent diffusion and concentration of chondrules in the protoplanetary nebula; (8) heating and cooling in the solar nebula; (9) crystallization trends of precursor pyroxene in ordinary chondrites; (10) precipitation induced vertical lightning in the protoplanetary nebula; (11) the role of chondrules in nebular fractionations of volatiles and other elements; (12) astronomical observations of phenomena in disks; (13) experimental constraints on models for origins of chondrules, and various other topics.
Source record↗
Goddard Conference on Mass Storage Systems and Technologies, volume 2
Papers and viewgraphs from the conference are presented. Discussion topics include the IEEE Mass Storage System Reference Model, data archiving standards, high-performance storage devices, magnetic and magneto-optic storage systems, magnetic and optical recording technologies, high-performance helical scan recording systems, and low end helical scan tape drives. Additional discussion topics addressed the evolution of the identifiable unit for processing (file, granule, data set, or some similar object) as data ingestion rates increase dramatically, and the present state of the art in mass storage technology.
Kobler, Ben↗
Solar fusion III: New data and theory for hydrogen-burning stars
In stars that lie on the main sequence in the Hertzsprung-Russell diagram, like our Sun, hydrogen is fused to helium in a number of nuclear reaction chains and series, such as the proton-proton chain and the carbon-nitrogen-oxygen cycles. Precisely determined thermonuclear rates of these reactions lie at the foundation of the standard solar model. This review, the third decadal evaluation of the nuclear physics of hydrogen-burning stars, is motivated by the great advances made in recent years by solar neutrino observatories, putting experimental knowledge of the proton-proton (𝑝𝑝)-chain neutrino fluxes in the few-percent precision range. The basis of the review is a one-week community meeting held in July 2022 in Berkeley, California, and many subsequent digital meetings and exchanges. The relevant reactions of solar and stellar hydrogen burning are reviewed here from both theoretical and experimental perspectives. Recommendations for the state of the art of the astrophysical 𝑆 factor and its uncertainty are formulated for each of them. Furthermore, several other topics of paramount importance for the solar model are reviewed as well: recent and future neutrino experiments, electron screening, radiative opacities, and current and upcoming experimental facilities. In addition to reaction-specific recommendations, general recommendations are also formed.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Climate Model Diagnostic and Evaluation: With a Focus on Satellite Observations
Each year, we host a summer school that brings together the next generation of climate scientists - about 30 graduate students and postdocs from around the world - to engage with premier climate scientists from the Jet Propulsion Laboratory and elsewhere. Our yearly summer school focuses on topics on the leading edge of climate science research. Our inaugural summer school, held in 2011, was on the topic of "Using Satellite Observations to Advance Climate Models," and enabled students to explore how satellite observations can be used to evaluate and improve climate models. Speakers included climate experts from both NASA and the National Oceanic and Atmospheric Administration (NOAA), who provided updates on climate model diagnostics and evaluation and remote sensing of the planet. Details of the next summer school will be posted here in due course.
climate↗