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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Postural control model interpretation of stabilogram diffusion analysis

Collins and De Luca [Collins JJ. De Luca CJ (1993) Exp Brain Res 95: 308-318] introduced a new method known as stabilogram diffusion analysis that provides a quantitative statistical measure of the apparently random variations of center-of-pressure (COP) trajectories recorded during quiet upright stance in humans. This analysis generates a stabilogram diffusion function (SDF) that summarizes the mean square COP displacement as a function of the time interval between COP comparisons. SDFs have a characteristic two-part form that suggests the presence of two different control regimes: a short-term open-loop control behavior and a longer-term closed-loop behavior. This paper demonstrates that a very simple closed-loop control model of upright stance can generate realistic SDFs. The model consists of an inverted pendulum body with torque applied at the ankle joint. This torque includes a random disturbance torque and a control torque. The control torque is a function of the deviation (error signal) between the desired upright body position and the actual body position, and is generated in proportion to the error signal, the derivative of the error signal, and the integral of the error signal [i.e. a proportional, integral and derivative (PID) neural controller]. The control torque is applied with a time delay representing conduction, processing, and muscle activation delays. Variations in the PID parameters and the time delay generate variations in SDFs that mimic real experimental SDFs. This model analysis allows one to interpret experimentally observed changes in SDFs in terms of variations in neural controller and time delay parameters rather than in terms of open-loop versus closed-loop behavior.

NASA Program Biomedical Research and Countermeasur↗
DOE OSTI2022

Hypothesis testing via AI: Generating physically interpretable models of scientific data with machine learning (Full Technical Report)

Deep learning has demonstrated an exceptional ability to solve complex tasks (an engineering success); however, it has done so at the expense of the ability to generate new knowledge (a scientific failure). We propose an alternative framework—entitled Deep Symbolic Regression (DSR)—in which artificial neural networks (NNs) rapidly generate hypotheses about physical relationships among inputs. This framework bypasses the need to interpret an NN altogether, while still leveraging the representational power of deep learning. The resulting models are tractable mathematical expressions, which are inherently and readily human interpretable and can provide insights into underlying physical phenomena. Further, we fold this methodology into the scientific process by allowing the scientist to directly integrate a priori knowledge and beliefs to accelerate learning. We demonstrate this methodology on symbolic regression—the problem of rediscovering underlying expressions describing a dataset—and achieve state-of-the-art performance across a wide variety of symbolic regression problems. Further, we generalize our DSR framework to apply to the more general class of symbolic optimization problems, in which one seeks to optimize a sequence of symbols or “tokens” under a black-box reward function. Examples of other symbolic optimization problems include neural architecture search and computational antibody design. Our generalized tool, Deep Symbolic Optimization (DSO), has been demonstrated on the task of learning symbolic control policies for reinforcement learning environments, and has been adopted as an enabling capability for computational antibody design.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1995

Scientific visualization tools for the ISTP project: Mission planning, data analysis and model interpretation

Visualization tools are being developed to meet the challenges of mission planning and data analysis presented by the International Solar-Terrestrial Physics (ISTP) program. ISTP encompasses a large number of spacecraft, multiple ground-based observatories, and several theoretical investigations, with the goal of understanding the global behavior of the solar wind/magnetosphere/ionosphere system. The tools include three-dimensional displays of key boundaries in geospace along with spacecraft trajectories, which can be animated and synchronized to universal time. Magnetic field models and MHD simulation results can be invoked to reveal the magnetic topology or to identify magnetic conjunctions between spacecraft and/or ground-based facilities. Simultaneous displays of satellite trajectories, spacecraft-borne observations, and model predictions are available to facilitate data processing and interpretation efforts. The current status of these tools is described, and their implementation at the ISTP Science Planning and Operations Facility and distribution to the entire ISTP community are discussed.

Peredo, M.↗
DOE OSTI2023

Interpretive modelling of boron transport in the boundary plasma of WEST experiments with the impurity powder dropper

Abstract Boron (B) powder injection is a potential alternative to glow discharge boronization as a wall conditioning method for tokamaks. This technique is currently being studied in WEST experiments, during which B powder is injected by an Impurity Powder Dropper developed by PPPL. In order to interpret and analyse experimental trends, and to help develop future experiments, a modelling workflow using a boundary plasma simulation (SOLEDGE-EIRENE) and powder ablation simulation (Dust Injection Simulator) was developed and tested. The effect of adding a B neutral source to simulated deuterium + oxygen (D + O) plasmas was compared to experimental data from the WEST C5 campaign, where B powder was injected in a dedicated experiment. While the impact of B injection on radiated power P rad measurements at the upper divertor was similar, there were significant differences in measurements of P rad , outer strike point electron temperature T e OSP and O-II line intensity at the lower divertor between experiment and simulation. This discrepancy suggests that those parameters were affected by phenomena not present in the simulations, with the most likely candidates being reduced D recycling and a reduced O sourcing from the divertor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Lifetime measurements in 206 Po with a shell-model interpretation

The lifetimes of the first excited 2⁺ and 4⁺ states in 206 Po were measured using the recoil-distance Dopplershift method. The experimental results were compared to large-scale shell-model calculations that describe the deduced transition probabilities well. Those calculations were extended to the neighboring 204,208 Po isotopes giving a good overall description of the yrast states. However, the calculations underpredict the energies of the 6+1 and 8+1 states, which suggests that further improvement of the proton-neutron interaction is required.

190 ≤ A ≤ 219↗
NASA NTRS1988

Model interpretation of type III radio burst characteristics. I - Spatial aspects

The ways that the finite size of the source region and directivity of the emitted radiation modify the observed characteristics of type III radio bursts as they propagate through the interplanetary medium are investigated. A simple model that simulates the radio source region is developed to provide insight into the spatial behavior of the parameters that characterize radio bursts. The model is used to demonstrate that observed radio azimuths are systematically displaced from the geometric centroid of the exciter electron beam in such a way as to cause trajectories of the radio bursts to track back to the observer at low frequencies, rather than to follow expected Archimedean spiral-like paths. The source region model is used to investigate the spatial behavior of the peak intensities of radio bursts, and it is found that the model can qualitatively account for both the frequency dependence and the east-west asymmetry of the observed peak flux densities.

Reiner, M. J.↗
NASA NTRS2002

Model Interpretation of Climate Signals: Application to the Asian Monsoon Climate

This is an invited review paper intended to be published as a Chapter in a book entitled "The Global Climate System: Patterns, Processes and Teleconnections" Cambridge University Press. The author begins with an introduction followed by a primer of climate models, including a description of various modeling strategies and methodologies used for climate diagnostics and predictability studies. Results from the CLIVAR Monsoon Model Intercomparison Project (MMIP) were used to illustrate the application of the strategies to modeling the Asian monsoon. It is shown that state-of-the art atmospheric GCMs have reasonable capability in simulating the seasonal mean large scale monsoon circulation, and response to El Nino. However, most models fail to capture the climatological as well as interannual anomalies of regional scale features of the Asian monsoon. These include in general over-estimating the intensity and/or misplacing the locations of the monsoon convection over the Bay of Bengal, and the zones of heavy rainfall near steep topography of the Indian subcontinent, Indonesia, and Indo-China and the Philippines. The intensity of convection in the equatorial Indian Ocean is generally weaker in models compared to observations. Most important, an endemic problem in all models is the weakness and the lack of definition of the Mei-yu rainbelt of the East Asia, in particular the part of the Mei-yu rainbelt over the East China Sea and southern Japan are under-represented. All models seem to possess certain amount of intraseasonal variability, but the monsoon transitions, such as the onset and breaks are less defined compared with the observed. Evidences are provided that a better simulation of the annual cycle and intraseasonal variability is a pre-requisite for better simulation and better prediction of interannual anomalies.

Lau, William K. M.↗
DOE OSTI2019

The pros and cons of beyond standard model interpretations of ANITA events

The Antarctic Impulsive Transient Antenna (ANITA) experiment has observed two air shower events with energy ~500 PeV emerging from the Earth with exit angles ~30⁰ above the horizon. As was immediately noted by the ANITA Collaboration, these events (in principle) could originate in the atmospheric decay of an upgoing τ-lepton produced through a charged current interaction of a ντ inside the Earth. However, the relatively steep arrival angles of these perplexing events create tension with the standard model (SM) neutrino-nucleon interaction cross section. Deepening the conundrum, the IceCube neutrino telescope and the Pierre Auger Observatory with substantially larger exposures to cosmic ντ's in this energy range have not observed any events. This lack of observation implies that the messenger particle (MP) giving rise to ANITA events must produce an air shower event rate at least a factor of 40 larger than that produced by a flux of τ-neutrinos to avoid conflicts with the upper limits reported by the IceCube and the Pierre Auger collaborations. In addition, the sensitivity of ANITA to MP-induced events must be comparable to or larger than those of IceCube and Auger to avoid conflict with the non-observation of any signal at these facilities. Beyond SM interpretations of ANITA events can be classified according to whether the MPs: (i) live inside the Earth, (ii) originate in neutrino-nucleon collisions inside the Earth, (iii) come from cosmological distances. In this communication we investigate the positive and negative facets of these three classes of models.

None, None↗
DOE OSTI2021

A machine learning aided interpretable model for rupture strength prediction in Fe-based martensitic and austenitic alloys

Abstract The class of 9–12% Cr ferritic-martensitic alloys (FMA) and austenitic stainless steels have received considerable attention due to their numerous applications in high temperature power generation industries. To design high strength steels with prolonged service life requires a thorough understanding of the long-term properties, e.g., creep rupture strength, rupture life, etc., as a function of the chemical composition and processing parameters that govern the microstructural characteristics. In this article, the creep rupture strength of both 9–12% Cr FMA and austenitic stainless steel has been parameterized using curated experimental datasets with a gradient boosting machine. The trained model has been cross validated against unseen test data and achieved high predictive performance in terms of correlation coefficient ( $$R^{2} > 0.98 $$ R 2 > 0.98 for 9–12% Cr FMA and $$R^{2} > 0.95 $$ R 2 > 0.95 for austenitic stainless steel) thus bypassing the need for additional comprehensive tensile test campaigns or physical theoretical calculations. Furthermore, the feature importance has been computed using the Shapley value analysis to understand the complex interplay of different features.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Growth model interpretation of planet size distribution

Significance The discovery of numerous exoplanet systems containing diverse populations of planets orbiting very close to their host stars challenges the planet formation theories based on the solar system. Here, we focus on the planets with radii of 2–4 R ⊕ , whose compositions are debated. They are thought to be either gas dwarfs consisting of rocky cores embedded in H 2 -rich gas envelopes or water worlds containing significant amounts of H 2 O-dominated fluid/ice in addition to rock and gas. We argue that these planets are water worlds.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Challenges and approaches to interpretive modeling of boundary plasma and neutral transport in a closed, pumped divertor

An experimental discharge from the DIII-D tokamak is modeled using the SOLPS-ITER code suite and compared against measurements in the pumped and relatively closed upper divertor. Uncertainties of boundary plasma simulations are identified by attempting to match code inputs to experimental conditions, including iteratively solving transport coefficients to match upstream experimental profiles using varying quantities of core particle flux, different pumping models, and various assumptions of ion thermal transport. Simulated boundary conditions for particle injection at the core interface are shown to be relevant to the plasma solution at the divertor targets, even if upstream transport is modified so that plasma profiles are comparatively similar, although seperatrix density is not held constant. When upstream plasma profiles are matched to experimental measurements by varying diffusive transport coefficients, using either poloidally symmetric or ballooning structure, the model finds a majority of injected energy being transported radially off the computational domain, in conflict with experimental radiated power measurements and heat flux measurements at the divertor target. Imposing a maximum thermal diffusivity or radially shifting the experimental separatrix location of the fitted profiles to increase power conducted to the targets by increasing the upstream electron temperature does not significantly modify this result. Including a thermalizing plenum volume in the simulation domain is shown to maintain the experimental volumetric pumping rate without knowing the neutral energy distribution incident on the pump duct a priori. By modifying transport parameters to match different assumptions for ion temperature, downstream neutral pressure changes by more than a factor of two, suggesting that attention to ion thermal transport may be a critical parameter for simulations to accurately resolve recycling and neutral transport, particularly in a closed divertor geometry. In addition to quantifying various modeling uncertainties, this work motivates both further experimental study and modeling improvements to improve predictive capabilities.

divertor↗
DOE OSTI2021

CrossCheck: Rapid, Reproducible, and Interpretable Model Evaluation

Evaluation beyond aggregate performance metrics, e.g. F1-score, is crucial to both establish an appropriate level of trust in machine learning models and identify future model improvements. In this paper we demonstrate CrossCheck, an interactive visualization tool for rapid crossmodel comparison and reproducible error analysis. We describe the tool and discuss design and implementation details. We then present three use cases (named entity recognition, reading comprehension, and clickbait detection) that show the benefits of using the tool for model evaluation. CrossCheck allows data scientists to make informed decisions to choose between multiple models, identify when the models are correct and for which examples, investigate whether the models are making the same mistakes as humans, evaluate models’ generalizability and highlight models’ limitations, strengths and weaknesses. Furthermore, CrossCheck is implemented as a Jupyter widget, which allows rapid and convenient integration into data scientists’ model development workflows.

Arendt, Dustin L.↗
NASA NTRS1993

A wave model interpretation of the evolution of rotational discontinuities

A hybrid numerical code is employed to trace the evolution of rotational discontinuities (RDs). An extensive parameter variation is carried out, with particular emphasis on beta, Ti/Te, theta sub B (the angle between the normal and total magnetic field), and the helicity of the RD. The RD structure is shown to have features in common with the evolution of both strongly modulated nonlinear wave packets and linear dispersive wave propagation in oblique magnetic fields. For small theta sub B, the RD disperses linearly, giving fast and Alfven waves upstream and downstream, respectively, and the familiar S-shaped hodograms. At larger theta sub B, nonlinearity becomes important and strong coupling to a compressional (sonic) component can occur in the main current layer. The results are applied to RDs observed in the solar wind and at the magnetopause.

Vasquez, Bernard J.↗
NASA NTRS1993

Developing interpretable models with optimized set reduction for identifying high risk software components

Applying equal testing and verification effort to all parts of a software system is not very efficient, especially when resources are limited and scheduling is tight. Therefore, one needs to be able to differentiate low/high fault frequency components so that testing/verification effort can be concentrated where needed. Such a strategy is expected to detect more faults and thus improve the resulting reliability of the overall system. This paper presents the Optimized Set Reduction approach for constructing such models, intended to fulfill specific software engineering needs. Our approach to classification is to measure the software system and build multivariate stochastic models for predicting high risk system components. We present experimental results obtained by classifying Ada components into two classes: is or is not likely to generate faults during system and acceptance test. Also, we evaluate the accuracy of the model and the insights it provides into the error making process.

Briand, Lionel C.↗