SEARCH · Engineering Papers

Results for “model interpretability”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22

All sources NASA NTRS DOE OSTI

NASA NTRS2004

Lava Lakes on Io: New Perspectives from Modeling

Ionian paterae are a class of volcanic feature that are characterized by irregular craters with steep walls, flat floors, and arcuate margins that may or may not exhibit nesting. Loki (310 W, 12 N) is Io's largest patera at approx.200 km in diameter (Figure 1), and may account for 15% of Io's total heat flow. Earth-based infrared data, as well as information collected using the Galileo Near-Infrared Mapping Spectrometer (NIMS) and the Photopolarimeter Radiometer (PPR) have been used to interpret Loki s eruption style. Debate continues over whether Loki s occasional (periodic or not) temperature increases are due to an overturning lava lake within the patera, or to an eruption of surface flows on the patera floor. Interpretation of model results and comparisons with active terrestrial lava lakes suggest that Loki behaves quite differently from active lava lakes on Earth, and that surface flows (rather than an overturning lava lake) are a more likely explanation of Loki's thermal brightening.

Gregg, Tracy K. P.↗

NASA NTRS1994

K'-band observations of the evil eye galaxy: Are the optical and near-infrared dust albedos identical?

New measurements of the reduction of the V-band surface brightness across the prominent dust feature in the galaxy NGC 4826 are compared with corresponding increases in the V-K' color within the context of radiative transfer models invoking both absorption and scattering. The K'-band surface brightness is found to be higher than expected from standard dust models. We interpret the difference as resulting from a high effective dust albedo at K', with a likely value in excess of 0.8, provided the near-IR extinction curve in NGC 4826 is identical to the Galactic one. The high effective albedo may result from scattering by dust with a maximum grain size at least twice as large as assumed by standard models, a conclusion already indirectly hinted at by recent studies of dust star-forming regions and reflection nebulae. At least part of the high effective albedo at K' may result from near-IR nonequilibrium continuum emission attributable to very small grains.

Witt, Adolf N.↗

DOE OSTI2023

Statistical Learning for Nonlinear Model Reduction from Local Simulations of Stochastic and Particle- and Agent-Based Systems

Stochastic physical systems across the sciences that have very high-dimensional state spaces, with a large number of fast degrees of freedom that force direct simulators to proceed by integration steps that are orders of magnitude smaller than events of interests (e.g., particle collisions). Examples range from molecular motion to dynamics of large populations of cells. A grand challenge in the simulation and understanding of such systems is the systematic construction of accurate, interpretable, reduced models, enabling faster simulations, revealing fundamental properties of the dynamics, and predicting phenomena of interest that the original simulator could not reached with sufficient accuracy or within a given computational budget. In this projected we developed novel statistical estimation/machine learning techniques for analyzing and building empirical reduced models for important families of high-dimensional stochastic systems, in particular: - we developed techniques for estimating interaction kernels in interacting particle- and agent-based systems, which are ubiquitous in Physics, Biology and many other sciences, given observed trajectories of the system; - we developed techniques for nonlinear model reduction for high-dimensional stochastic systems that have a small number of unknown, nonlinear slow variables, and a large number of fast modes, that are possibly of large magnitude, given observed short trajectories of the system in the form of bursts of trajectories from different initial conditions; - we developed novel techniques for estimating linear dynamical systems on graphs when both the dynamics and the underlying graph are unknown, and we have a sparse set of space-time observations; - we considered the problem of estimating an unknown nonlinear observation function of a standard process (e.g. Brownian motion), so that we can recognized if an observed dynamics is "just" a nonlinear version of a known dynamics; we also developed benchmarks for learning algorithms aimed at learning and classifying diffusion processes.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1974

Radiative contribution to the thermal conductivity of fibrous insulations

An approach is shown for using a simple two-flux model to interpret infrared transmission data for a variety of reuseable surface insulations materials and to calculate the radiation transmission. A description is given of preliminary experiments on mullite and silica-based materials. The calculated parameters are compared with the measured values of the total thermal conductivity, as determined on guarded hot plate equipment. It is pointed out that for many samples the newly developed four-flux model must be utilized because the scattering properties of the fibers are often dependent on the wavelength of the radiation.

Linford, R. M. F.↗

NASA NTRS2013

An Outburst Scenario for the X-ray Spectral Variability in 3C 111

We present a combined Suzaku and Swift BAT broad-band E=0.6-200 keV spectral analysis of three 3C 111 observations obtained in 2010. The data are well described with an absorbed power-law continuum and a weak (R approximately equal to 0.2) cold reflection component from distant material. We constrain the continuum cutoff at E(sub C) approximately equal to 150- 200 keV, which is in accordance with X-ray Comptonization corona models and supports claims that the jet emission is only dominant at much higher energies. Fe XXVI Ly alpha emission and absorption lines are also present in the first and second observations, respectively. The modelling and interpretation of the emission line is complex and we explore three possibilities. If originating from ionized disc reflection, this should be emitted at r(sub in) greater than or equal to 50 r(sub g) or, in the lamp-post configuration, the illuminating source should be at a height of h greater than or equal to 30 r(sub g) over the black hole. Alternatively, the line could be modeled with a hot collisionally ionized plasma with temperature kT = 22.0(sup +6.1)(sub −3.2) keV or a photo-ionized plasma with logXi=4.52(sup +0.10)(sub −0.16) erg per second cm, and column density N(sub H) greater than 3×10(sup 23) per square centimeter. However, the first and second scenarios are less favored on statistical and physical grounds, respectively. The blue-shifted absorption line in the second observation can be modelled as an ultra-fast outflow (UFO) with ionization parameter logXi=4.47(sup +0.76) (sub −0.04) erg per second cm, column density NH=(5.3(sup +1.8)(sub −1.3))×10(sup 22) per square centimeter and outflow velocity v(sub out) = 0.104+/-0.006c. Interestingly, the parameters of the photoionized emission model remarkably match those of the absorbing UFO, supporting the possibility that the same material could be responsible for both emission and absorption. We suggest an outburst scenario in which an accretion disc wind, initially lying out of the line of sight and observed in emission, then crosses our view to the source and it is observed in absorption as a mildly-relativistic UFO.

Outburst↗

DOE OSTI2023

Explaining machine-learning models for gamma-ray detection and identification

As more complex predictive models are used for gamma-ray spectral analysis, methods are needed to probe and understand their predictions and behavior. Recent work has begun to bring the latest techniques from the field of Explainable Artificial Intelligence (XAI) into the applications of gamma-ray spectroscopy, including the introduction of gradient-based methods like saliency mapping and Gradient-weighted Class Activation Mapping (Grad-CAM), and black box methods like Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP). In addition, new sources of synthetic radiological data are becoming available, and these new data sets present opportunities to train models using more data than ever before. In this work, we use a neural network model trained on synthetic NaI(Tl) urban search data to compare some of these explanation methods and identify modifications that need to be applied to adapt the methods to gamma-ray spectral data. We find that the black box methods LIME and SHAP are especially accurate in their results, and recommend SHAP since it requires little hyperparameter tuning. We also propose and demonstrate a technique for generating counterfactual explanations using orthogonal projections of LIME and SHAP explanations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Identifying Critical Infrastructure in Imagery Data Using Explainable Convolutional Neural Networks

To date, no method utilizing satellite imagery exists for detailing the locations and functions of critical infrastructure across the United States, making response to natural disasters and other events challenging due to complex infrastructural interdependencies. This paper presents a repeatable, transferable, and explainable method for critical infrastructure analysis and implementation of a robust model for critical infrastructure detection in satellite imagery. This model consists of a DenseNet-161 convolutional neural network, pretrained with the ImageNet database. The model was provided additional training with a custom dataset, containing nine infrastructure classes. The resultant analysis achieved an overall accuracy of 90%, with the highest accuracy for airports (97%), hydroelectric dams (96%), solar farms (94%), substations (91%), potable water tanks (93%), and hospitals (93%). Critical infrastructure types with relatively low accuracy are likely influenced by data commonality between similar infrastructure components for petroleum terminals (86%), water treatment plants (78%), and natural gas generation (78%). Local interpretable model-agnostic explanations (LIME) was integrated into the overall modeling pipeline to establish trust for users in critical infrastructure applications. The results demonstrate the effectiveness of a convolutional neural network approach for critical infrastructure identification, with higher than 90% accuracy in identifying six of the critical infrastructure facility types.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1986

Detailed observations of the plasma sheet during a substorm on April 24, 1979

Plasma, magnetic field, and energetic particle data obtained by ISEE 1 and 2 satellites for the April 24, 1979 substorm are studied in relation to the neutral line model and the boundary layer model. The ISEE 1 and 2 instruments and experiments utilized to collect the data are discussed. The major reconfiguration of the tail plasma and magnetic field plasma region, and the plasma ion flows observed support the neutral line model for interpreting substorms. The plasma ion distribution function and plasma flow are examined. The region of lobe-plasma sheet interface referred to as the separatrix layer is identified. The differences in times of plasma sheet dropout and recovery, and absence or presence of flux anisotropies are investigated. Energetic particle measurements are analyzed to study the relationship between energetic ions and plasma ions, and the velocity distributions. The data support the application of the neutral line model to the evaluation of substorms; however, the data are inconsistent with the boundary layer dynamics model.

Hones, E. W., Jr.↗

NASA NTRS1992

Transient periodicities in X-ray-active red dwarfs - First results from Mount Cuba and interpretation with an oscillating loop model

Results from a program at the Mount Cuba Astronomical Observatory to optically monitor transient periodicities in flare stars are reported. The data are analyzed for periodicities by means of a modified autocorrelation approach. A randomization technique is used to assess the statistical significance of periods. In AD Leonis, variability with amplitude 0.4 percent and a period of 4.1 min was detected during one run on March 6, 1991: the probability that this periodicity is due to chance is 10 exp -5. Further observations obtained on AD Leo within 1-2 hr on the same night showed no significant variability (0.01). It is shown that optical periodicities of the sort detected may be interpreted as arising from oscillations in coronal loops.

Mullan, D. J.↗

NASA NTRS1989

Primitive bodies - Molecular abundances in Comet Halley as probes of cometary formation environments

The most recent results on abundances of molecules in Halley's comet are examined in the context of various models for the environment in which comets formed. These environments include molecular clouds associated with star-forming regions, the solar nebula, gaseous disks around proto-planets, and combinations of these. Of all constituents in a cometary nucleus, the highly volatile molecules such as methane, ammonia, molecular nitrogen, and carbon monoxide are most sensitive to the final episode of cometary grain formation and incorporation in the comet's nucleus; hence they likely reflect at least some chemical processing in the solar nebula. Proper interpretation requires modeling of a number of physical processes including gas phase chemistry, chemistry on grain surfaces, and fractionation effects resulting from preferential incorporation of certain gases in proto-cometary grains. The abundance of methane in Halley's comet could be a key indicator of where that comet formed, provided the methane abundance on grains in star-forming regions can be observationally constrained.

Lunine, Jonathan I.↗

NASA NTRS2005

A Theoretical Investigation of Oxidation Efficiency of a Volatile Removal Assembly Reactor Under Microgravity Conditions

Volatile Removal Assembly (VRA) is a subsystem of the Closed Environment Life Support System (CELSS) installed in the International Space Station. It is used for removing contaminants (volatile organics) in the wastewater produced by the space station crews. The major contaminants are formic acid, ethanol, and propylene glycol. The VRA contains a slim packbed reactor (3.5 cm diameter and four 28 cm long tubes in series) to perform catalyst oxidation of wastewater at elevated pressure and temperature under microgravity conditions. In the reactor, the contaminants are burned with oxygen gas (O2) to form water and carbon dioxide (CO2) that dissolves in the water stream. Optimal design of the reactor requires a thorough understanding about how the reactor performs under microgravity conditions. The objective of this study was to develop a mathematical model to interpret experimental data obtained from normal and microgravity conditions, and to predict the performance of VRA reactor under microgravity conditions. Catalyst oxidation kinetics and the total oxygen-water contact area control the efficiency of catalyst oxidation for mass transfer, which depends on oxygen gas holdup and distribution in the reactor. The process involves bubbly flow in porous media with chemical reactions in microgravity environment. This presents a unique problem in fluid dynamics that has not been studied. Guo et al. (2004) developed a mathematical model that predicts oxygen holdup in the VRA reactor. No mathematical model has been found in the literature that can be used to predict the efficiency of catalyst oxidation under microgravity conditions.

Guo, Boyun↗

DOE OSTI2021

Fast ion transport by sawtooth instability in the presence of ICRF-NBI synergy in JET plasmas

JET experiments have shown that the three-ion scenarios using waves in the ion cyclotron range of frequencies (ICRF) is an efficient way to build fast ion population through beam ion acceleration by radio frequency (RF) waves. Here, such a heating scheme is applied to plasmas with at least two thermal ion species. Analysis of mixed discharges with complex heating schemes requires a workflow that allows to model thermal and fast ion transport consistently. This paper is dedicated to modelling of a mixed plasma discharge with significant fraction of fast ions and contributes to development of fast ion transport models. For interpretive analysis with the TRANSP code a JET hydrogen-deuterium (HD) plasma discharge with neutral beam injection (NBI) and ICRF heating has been chosen. The task is complicated by NBI-ICRF synergy and plasma magnetohydrodynamic activity, like sawtooth crashes. D beam ions accelerated by RF waves form a high energy tail in fast ion distribution. Significant difference between the neutron rate computed by TRANSP and measured one is observed if the same diffusivity for electrons and ions is assumed. Sensitivity studies show that uncertainties in input plasma parameters and thermal ion transport models are crucial for modelling mixed plasma discharges and increased D transport is required to reach the plasma composition consistent with diagnostic measurements at the plasma edge. Fast ion redistribution by a sawtooth instability is characterised by non-resonant transport due to reconnection of magnetic field lines and resonant transport caused by resonance interaction between the instability and fast ions. With ORBIT simulations it has been shown that resonant interaction strongly affects fast ions of high energies, like beam ions accelerated by RF waves and fusion products. For the considered case, fast ion profiles simulated by ORBIT remain peaked after the sawtooth crashes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2005

Bio-Optics of the Chesapeake Bay from Measurements and Radiative Transfer Calculations

We combined detailed bio-optical measurements and radiative transfer (RT) modeling to perform an optical closure experiment for optically complex and biologically productive Chesapeake Bay waters. We used this experiment to evaluate certain assumptions commonly used when modeling bio-optical processes, and to investigate the relative importance of several optical characteristics needed to accurately model and interpret remote sensing ocean-color observations in these Case 2 waters. Direct measurements were made of the magnitude, variability, and spectral characteristics of backscattering and absorption that are critical for accurate parameterizations in satellite bio-optical algorithms and underwater RT simulations. We found that the ratio of backscattering to total scattering in the mid-mesohaline Chesapeake Bay varied considerably depending on particulate loading, distance from land, and mixing processes, and had an average value of 0.0128 at 530 nm. Incorporating information on the magnitude, variability, and spectral characteristics of particulate backscattering into the RT model, rather than using a volume scattering function commonly assumed for turbid waters, was critical to obtaining agreement between RT calculations and measured radiometric quantities. In situ measurements of absorption coefficients need to be corrected for systematic overestimation due to scattering errors, and this correction commonly employs the assumption that absorption by particulate matter at near infrared wavelengths is zero.

Tzortziou, Maria↗

NASA NTRS2023

Solar Flare Ribbon Fronts. I. Constraining Flare Energy Deposition with IRIS Spectroscopy

Spectral lines formed at lower atmospheric layers show peculiar profiles at the "leading edge" of ribbons during solar flares. In particular, increased absorption of the BBSO/GST He I λ10830 line, as well as broad and centrally reversed profiles in the spectra of the Mg II and C II lines observed by the IRIS satellite, has been reported. In this work, we aim to understand the physical origin of such peculiar IRIS profiles, which seem to be common of many, if not all, flares. To achieve this, we quantify the spectral properties of the IRIS Mg II profiles at the ribbon leading edge during four large flares and perform a detailed comparison with a grid of radiative hydrodynamic models using the RADYN+FP code. We also studied their transition region (TR) counterparts, finding that these ribbon front locations are regions where TR emission and chromospheric evaporation are considerably weaker compared to other parts of the ribbons. Based on our comparison between the IRIS observations and modeling, our interpretation is that there are different heating regimes at play in the leading edge and the main bright part of the ribbons. More specifically, we suggest that bombardment of the chromosphere by more gradual and modest nonthermal electron energy fluxes can qualitatively explain the IRIS observations at the ribbon leading front, while stronger and more impulsive energy fluxes are required to drive chromospheric evaporation and more intense TR emission in the bright ribbon. Our results provide a possible physical origin for the peculiar behavior of the IRIS chromospheric lines in the ribbon leading edge and new constraints for the flare models.

Solar flares↗

DOE OSTI2024

TCR-H: explainable machine learning prediction of T-cell receptor epitope binding on unseen datasets

Artificial-intelligence and machine-learning (AI/ML) approaches to predicting T-cell receptor (TCR)-epitope specificity achieve high performance metrics on test datasets which include sequences that are also part of the training set but fail to generalize to test sets consisting of epitopes and TCRs that are absent from the training set, i.e., are ‘unseen’ during training of the ML model. We present TCR-H, a supervised classification Support Vector Machines model using physicochemical features trained on the largest dataset available to date using only experimentally validated non-binders as negative datapoints. TCR-H exhibits an area under the curve of the receiver-operator characteristic (AUC of ROC) of 0.87 for epitope ‘hard splitting’ (i.e., on test sets with all epitopes unseen during ML training), 0.92 for TCR hard splitting and 0.89 for ‘strict splitting’ in which neither the epitopes nor the TCRs in the test set are seen in the training data. Furthermore, we employ the SHAP (Shapley additive explanations) eXplainable AI (XAI) method for post hoc interrogation to interpret the models trained with different hard splits, shedding light on the key physiochemical features driving model predictions. TCR-H thus represents a significant step towards general applicability and explainability of epitope:TCR specificity prediction.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1981

Solar Corona Explorer: A mission for the physical diagnosis of the solar corona

Mission objectives and spacecraft requirements for the Solar Corona Explorer (SCE), a proposed free flying, unmanned solar research craft to be tenatively launched in 1987, were defined. The SCE's purpose is to investigate structure, dynamics and evolution of the corona, globally and in the required physical detail, to study the close coupling between the inner corona and the heliosphere. Investigative objectives are: (1) to understand the corona as the source of varying interplanetary plasma and of varying solar X-ray and extreme ultraviolet fluxes; (2) to develop the capabilities to model the corona with sufficient precision to forecast the Earth's variable environment in space, on the scales from weeks to years; (3) to develop an understanding of the physical processes that determine the dynamics and physical state of the coronal plasma, particularly acceleration processes; and (4) to develop insight and test theory on the Sun applicable to stellar coronae and winds, and in particular, to understand why cool stars put such a large fraction of their energy into X-rays. Considered related factors are: (1) duration of the mission; (2) onboard measuring instrumentation; (3) ground support equipment and procedures; and (4) programs of interpretation and modeling.

Source record↗

DOE OSTI2021

Quantification of Cas9 binding and cleavage across diverse guide sequences maps landscapes of target engagement

The RNA-guided nuclease Cas9 has unlocked powerful methods for perturbing both the genome through targeted DNA cleavage and the regulome through targeted DNA binding, but limited biochemical data have hampered efforts to quantitatively model sequence perturbation of target binding and cleavage across diverse guide sequences. We present scalable, sequencing-based platforms for high-throughput filter binding and cleavage and then perform 62,444 quantitative binding and cleavage assays on 35,047 on- and off-target DNA sequences across 90 Cas9 ribonucleoproteins (RNPs) loaded with distinct guide RNAs. We observe that binding and cleavage efficacy, as well as specificity, vary substantially across RNPs; canonically studied guides often have atypically high specificity; sequence context surrounding the target modulates Cas9 on-rate; and Cas9 RNPs may sequester targets in nonproductive states that contribute to “proofreading” capability. Lastly, we distill our findings into an interpretable biophysical model that predicts changes in binding and cleavage for diverse target sequence perturbations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Implementation of a 9-point stencil in SOLPS-ITER and implications for Alcator C-Mod divertor plasma simulations

The SOLPS-ITER code suite is used worldwide for plasma edge modeling, the interpretation of experiments, as well as for the design of the ITER divertor. The numerical scheme of the plasma solver of the code, B2.5, is based on the assumption of perfectly ﬁeld-aligned grids, while in practice grids are often strongly distorted to match divertor target shapes. Neglecting these grid distortion leads to qualitatively and quantitatively incorrect results for ﬂuid neutral simulations, and may affect results in cold (detached) divertors even when using kinetic neutral simulations. In this contribution, we present the ﬁrst results of a newly implemented 9-point stencil in B2.5 to properly handle misaligned grids. The new scheme is then applied to ﬂuid neutral simulations of a well-diagnosed and previously modeled Alcator C-Mod discharge. Results are compared with the original 5-point scheme neglecting grid distortion effects, as well as with simulations including a full kinetic neutral model. We conclude that the 9-point stencil is essential to correctly model the transport of ﬂuid neutrals on distorted grids, and to capture the effects of divertor closure on the ﬂuid neutral behavior.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗