Heavy-element abundances and the interpretation of globular cluster characteristics.
Evolutionary models for all composition parameter permutations for globular cluster age determination
Iben, I., Jr.↗
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.
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The application of sensitivity analysis to models of large scale physiological systems
A survey of the literature of sensitivity analysis as it applies to biological systems is reported as well as a brief development of sensitivity theory. A simple population model and a more complex thermoregulatory model illustrate the investigatory techniques and interpretation of parameter sensitivity analysis. The role of sensitivity analysis in validating and verifying models, and in identifying relative parameter influence in estimating errors in model behavior due to uncertainty in input data is presented. This analysis is valuable to the simulationist and the experimentalist in allocating resources for data collection. A method for reducing highly complex, nonlinear models to simple linear algebraic models that could be useful for making rapid, first order calculations of system behavior is presented.
Leonard, J. I.↗
Measurement of the inclusive and differential $t\overline{t}γ$ cross sections in the dilepton channel and effective field theory interpretation in proton-proton collisions at $\sqrt{s}$ = 13 TeV
The production cross section of a top quark pair in association with a photon is measured in proton-proton collisions in the decay channel with two oppositely charged leptons (e ± μ ∓ , e + e - , or μ + μ - ). The measurement is performed using 138 fb -1 of proton-proton collision data recorded by the CMS experiment at √s = 13 TeV during the 2016–2018 data-taking period of the CERN LHC. A fiducial phase space is defined such that photons radiated by initial-state particles, top quarks, or any of their decay products are included. An inclusive cross section of 175.2 ± 2.5(stat) ± 6.3(syst) fb is measured in a signal region with at least one jet coming from the hadronization of a bottom quark and exactly one photon with transverse momentum above 20 GeV. Differential cross sections are measured as functions of several kinematic observables of the photon, leptons, and jets, and compared to standard model predictions. The measurements are also interpreted in the standard model effective field theory framework, and limits are found on the relevant Wilson coefficients from these results alone and in combination with a previous CMS measurement of the tt¯γ production process using the lepton+jets final state.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Plasma Flow Past Cometary and Planetary Satellite Atmospheres
The tenuous atmospheres and ionospheres of comets and outer planet satellites share many common properties and features. Such similarities include a strong interaction with their outer radiation, fields and particles environs. For comets the interaction is with the magnetized solar wind plasma, whereas for satellites the interaction is with the strongly magnetized and corotating planetary magnetospheric plasma. For this reason there are many common or analogous physical regimes, and many of the same modeling techniques are used to interpret remote sensing and in situ measurements in order to study the important underlying physical phenomena responsible for their appearances. We present here a review of various modeling approaches which are used to elucidate the basic properties and processes shaping the energetics and dynamics of these systems which are similar in many respects.
Combi, Michael R.↗
Interpreting strain tensor data to characterize and monitor reservoirs for CO2 storage and other applications
Recent advances in instrumentation have made it feasible to measure the transient strain tensor caused by small changes in fluid volume or pressure in the subsurface and this has opened the door to new opportunities for characterization and monitoring. We have deployed strainmeters and then conducted injection well tests in an underlying reservoir at 530m depth. The resulting data indicated that the horizontal strain at shallow strainmeters (30 to 40m depth) was tensile and the vertical strain was compressive. The radial strain was less than the horizontal strain, and the strain rates decreased from 100 nanostrain/day to roughly 10 n/d over a few days. The signal at two strainmeters at shallow depth were consistent, although the magnitude of the horizontal strains were different reflecting the different radial directions from the well. The signal at a deep strainmeter deployed at reservoir depth was much different, with tensile vertical strains and compressive horizontal strains. These data can be interpreted by inverting poroelastic forward models developed using numerical and analytical methods. The average horizontal strain in the caprock resembles the transient pressure in the underlying reservoir and classic type-curve methods from transient well testing can be used for preliminary interpretations of strain data. We have developed closed-form analytical solutions to a pressurized poroelastic inclusion and inhomogeneity in a half-space. This model is fast and can be inverted to estimate reservoir stiffness and geometry. Numerical models developed using finite element methods allow more details of the subsurface to be included in the inversion, but they require much longer run times and this makes inversion cumbersome using standard methods. We have developed an inversion approach that uses a proxy model created using machine learning to do most of the forward calculations. The proxy model is periodically updated and refined using the finite element model to ensure accuracy. This approach significantly reduces the computational requirements and makes it feasible to use Bayesian inversion with large numerical models. We have shown that the strain tensor in the caprock is sensitive to pressure in the reservoir, boundaries in the reservoir, and pressure in the caprock caused by leaks. These results indicate that coupling strain tensor data with inversion has the potential to help evaluate reservoirs during initial characterization, and to monitor them during the CO2 injection and storage process.
Murdoch, Larry↗
Cratering and obliteration history of Mars
The review presented is based mainly on the pre-Viking literature. Early interpretations of the Mariner 4 pictures of Martian craters are considered along with interpretations of Mariner 9 pictures. A description of cratering/obliteration models is presented and aspects of obliteration episode interpretation are discussed, taking into account large, intermediate, and small craters. Alternative interpretations of Martian cratering are also considered and questions of absolute chronology are investigated. The geomorphological processes described include exogenic, aeolian, and aqueous processes. The significance of the various processes and activities for the geomorphological evolution of Mars is evaluated.
Chapman, C. R.↗
Charge Exchange, from the Sky to the Laboratory: A Method to Determine State-Selective Cross-Sections for Improved Modeling
Charge exchange (CX) is a semi-resonant recombination process that can lead to spectral line emission in the X-ray band. It occurs in nearly any environment where hot plasma and cold gas interact: in the solar system, in comets and planetary atmospheres, and likely astrophysically, in, for example, supernova remnants and galaxy clusters. It also contributes to the soft X-ray background. Accurate spectral modeling of CX is thus critical to properly interpreting our astrophysical observations, but the commonly used CX models in popular spectral fitting packages often rely on scaling equations and may not accurately describe observations or laboratory measurements. This paper introduces a method that can be applied to high-resolution CX spectra to directly extract state-selective CX cross-sections for electron capture, a key parameter for properly simulating the resulting CX spectrum.
Gabriele L. Betancourt-Martinez↗
Influence of physical and chemical hydrology on bioremediation of a U-contaminated aquifer informed by reactive transport modeling incorporating 238 U/ 235 U ratios
Microbially-catalyzed reductive immobilization of aqueous uranium (U) as a solid phase has been proposed as a U remediation technique. Both laboratory and field experiments have demonstrated that this reduction reaction alters the 238 U/ 235 U ratio, producing a 238 U-enriched U(IV) solid. In contrast, other major U reactive transport processes fractionate these isotopes much less. This suggests the potential to quantify the extent of bioreduction occurring in groundwater containing U using the 238 U/ 235 U ratio, which would substantially improve upon current practices largely relying on U concentration measurements alone. Current reactive transport models for uranium dynamics include only concentration measurements, which are strongly influenced by highly coupled reactive transformation and aqueous transport processes. The complex physical and chemical behavior of U potentially compromises such quantitative analysis of U storage and release. Here we report the first numerical reactive transport model which explicitly incorporates variations in the 238 U/ 235 U ratio of U and demonstrates improved interpretation of the principal chemical reactions and groundwater transport processes affecting the subsurface mobility and distribution of this widespread contaminant. Recent U bioreduction studies performed in a contaminated aquifer in Rifle, Colorado, USA applied Rayleigh distillation models to interpret U stable isotope fractionation observed as a result of acetate amendment. These simplified models were unable to resolve the spatiotemporal pattern of U isotope fractionation recorded in the aqueous solutes. Here, we employ the multi-component, isotope-enabled CrunchTope reactive transport software to interpret these measured U isotope ratios, and demonstrate accurate reproduction of observed trends in both geochemistry and 238 U/ 235 U ratios for two consecutive years of field experiments. Overall, our results indicate that accurately modeling both the U concentration and isotope ratio distributions greatly constrains the parameter space of the model. We find that the transport properties of U in the Rifle aquifer are governed by the presence of low-permeability regions, which the isotopes are uniquely sensitive to. When U reduction is spatially constrained by these low-permeability regions, the shift in the 238 U/ 235 U ratio becomes more muted. Accurate modeling of observed U isotope ratios thus provides a powerful means to better understand bioremediation, and the current study serves to advance the application of this novel method.
238U/235U↗
Autonomous Inversion of In Situ Deformation Measurement Data for Injection-Induced Stress Change
Geologic carbon storage (GCS) is likely to play a key part of the global effort to dramatically reduce CO2 emissions and perhaps even reduce atmospheric CO2 concentrations through carbon negative operations. A critical part of effort to commercialize and widely deploy this technology is developing the capability to rapidly assimilate real-time monitoring data into a form that will enable site operators to make decisions to manage the safe and efficient operations. Two of the risks associate with GCS are the risk of inducing fractures in the sealing formations that can create leakage pathways and the risk of inducing earthquakes of sufficient magnitude to cause public concern, property damage, or safety risks. To properly manage these risks the site operator needs to know the initial state of stress, the change in stress induced by injection, and the relationship between operational parameters such as injection rate and pressure and the change in stress. Current methods of estimating the change in stress require choosing the type of constitutive model and the model parameters based on core, log, and geophysical data during the characterization phase, with little feedback from operational observations to validate or refine these choices. These characterization methods interrogate the geologic formations using length scales, loading rates or magnitudes that are quite different from those encountered by the actual storage system. It is shown that errors in the assumed constitutive response, even when informed by laboratory tests on core samples, are likely to be common, large, and underestimate the magnitude of stress change caused by injection. Recent advances in borehole-based strain instruments and borehole and surface-based tilt and displacement instruments have now enabled monitoring of the deformation of the storage system throughout its operational lifespan. This data can enable validation and refinement of the knowledge of the geomechanical properties and state of the system, but brings with it a challenge to transform the raw data into actionable knowledge. We demonstrate a method that uses automatic differentiation and a finite-element based geomechanical model perform a gradient-based deterministic inversion of geomechanical monitoring data. This approach allows autonomous integration of the instrument data without the need for time consuming manual interpretation and selection of updated model parameters. Furthermore, only isotropic linear elasticity is considered in this paper, the approach presented is very flexible as to what type of geomechanical constitutive response can be used. The approach is easily adaptable to nonlinear physics-based constitutive models to account for common rock behaviors such as creep and plasticity. The approach also enables training of machine learning-based constitutive models by allowing back propagation of errors through the finite element calculations. This enables strongly enforcing known physics, such as conservation of momentum and continuity, while allowing data-driven models to learn the truly unknown physics such as the constitutive or petrophysical responses.
Burghardt, Jeffrey A.↗
Frequency shifts of ionospheric nfH resonances.
New observational data are analyzed to interpret mechanisms responsible for large positive frequency shifts of Alouette II plasma resonances (corresponding to the first and second electron cyclotron harmonics) relative to frequency values expected from model magnetic field calculations. It is shown that the frequency shifts can be consistently explained by plasma wave dispersion effects combined with sounder transmitter frequency deviation (positive offset of several kilohertz) and a negative offset (several tens of gammas) in the geomagnetic field relative to the model field. Plasma wave dispersion effects are observed on the electron cyclotron second harmonic resonance when it is in the vicinity of the resonance observed near the upper hybrid frequency. The observations suggest that an oblique echo model may be required for interpretation of the electron cyclotron second harmonic resonance.
Benson, R. F.↗
Assimilation of Geosat Altimetric Data in a Nonlinear Shallow-Water Model of the Indian Ocean by Adjoint Approach. Part II: Some Validation and Interpretation of the Assimilated Results: Some Validation and Interpretation of the Assimilated Results - Part 2
This paper examines the results of assimilating Geosat sea level variations relative to the November 1986-November 1988 mean reference, in a nonlinear reduced-gravity model of the Indian Ocean, Data have been assimilated during one year starting in November 1986 with the objective of optimizing the initial conditions and the yearly averaged reference surface. The thermocline slope simulated by the model with or without assimilation is validated by comparison with the signal, which can be derived from expandable bathythermograph measurements performed in the Indian Ocean at that time. The topography simulated with assimilation on November 1986 is in very good agreement with the hydrographic data. The slopes corresponding to the South Equatorial Current and to the South Equatorial Countercurrent are better reproduced with assimilation than without during the first nine months. The whole circulation of the cyclonic gyre south of the equator is then strongly intensified by assimilation. Another assimilation experiment is run over the following year starting in November 1987. The difference between the two yearly mean surfaces simulated with assimilation is in excellent agreement with Geosat. In the southeastern Indian Ocean, the correction to the yearly mean dynamic topography due to assimilation over the second year is negatively correlated to the one the year before. This correction is also in agreement with hydrographic data. It is likely that the signal corrected by assimilation is not only due to wind error, because simulations driven by various wind forcings present the same features over the two years. Model simulations run with a prescribed throughflow transport anomaly indicate that assimilation is rather correcting in the interior of the model domain for inadequate boundary conditions with the Pacific.
Greiner, Eric↗
Inter-well connectivity detection in CO 2 WAG projects using statistical recurrent unit models
Routine well-wise injection and production measurements contain significant information on subsurface structure and properties. Data-driven technology that interprets surface data into subsurface structure or properties can assist operators in making informed decisions by providing a better understanding of field assets. Our machine-learning framework is built on the statistical recurrent unit (SRU) model and interprets well-based injection/production data into inter-well connectivity without relying on a geologic model. We test it on synthetic and field-scale CO 2 EOR projects utilizing the water-alternating-gas (WAG) process. SRU is a special type of recurrent neural network (RNN) that allows for better characterization of temporal trends, by learning various statistics of the input at different time scales. In our application, the complete states (injection rate, pressure and cumulative injection) at injectors and pressure states at producers are fed to SRU as the input and the phase rates at producers are treated as the output. Once the SRU is trained and validated, it is then used to assess the connectivity of each injector to any producer using permutation variable importance method, wherein inputs corresponding to an injector are shuffled and the increase in prediction error at a given producer is recorded as the importance (connectivity metric) of the injector to the producer. This method is tested in both synthetic and field-scale cases. The validation of the proposed data-driven inter-well connectivity assessment is performed using synthetic data from simulation models where inter-well connectivity can be easily measured using the streamline-based flux allocation. The SRU model is shown to offer excellent prediction performance on the synthetic case. Despite significant measurement noise and frequent well shut-ins imposed in the field-scale case, the SRU model offers good prediction accuracy, the overall relative error of the phase production rates at most producers ranges from 10% to 30%. It is shown that the dominant connections identified by the data-driven method and streamline method are in close agreement. This significantly improves confidence in our data-driven procedure. The novelty of this work is that it is purely data-driven method and can directly interpret routine surface measurements to intuitive subsurface knowledge. Furthermore, the streamline-based validation procedure provides physics-based backing to the results obtained from data analytics. This study results in a reliable and efficient data analytics framework that is well-suited for large field applications.
42 ENGINEERING↗
Utility of correlation techniques in gravity and magnetic interpretation
Two methods of quantitative combined analysis, internal correspondence and clustering, are presented. Model studies are used to illustrate implementation and interpretation procedures of these methods, particularly internal correspondence. Analysis of the results of applying these methods to data from the midcontinent and a transcontinental profile show they can be useful in identifying crustal provinces, providing information on horizontal and vertical variations of physical properties over province size zones, validating long wave-length anomalies, and isolating geomagnetic field removal problems. Thus, these techniques are useful in considering regional data acquired by satellites.
Chandler, V. W.↗
Maximizing the Scientific Return of the Sentinels Mission Using Global MHD Models
The Sentinels mission promises to provide a unique view of the acceleration and transport processes of energetic particles as well as the initiation and evolution of coronal mass ejections (CMEs). A crucial component in understanding the physics associated with these processes lies in the large-scale structure of the corona and heliosphere, particularly during the eruption and propagation of fast CMEs. In this talk we review the current status of our MHD modeling efforts, focusing on Sentinels-specific science, and project forward to envisage what capabilities we may have developed by the time that the Sentinels launch (2012). In conjunction with Solar Orbiter, the farside and near-Earth Sentinels spacecraft will provide simultaneous photospheric magnetograph measurements at multiple longitudes, which will lead to major improvements in our ability to prescribe accurate, time-dependent global boundary conditions. Data returned from the inner heliospheric Sentinels will be used to validate these results. The model results can be used in a variety of ways to interpret the observations. For example, products from the model, such as the properties of CME-driven shocks and CME-associated reconnection sites can be used to interpret complex energetic particle profiles. Also, by tracing along magnetic field lines, the inferred sites of the energetic particles can be connected directly with the in situ measurements at each spacecraft. Perhaps more so than any previous mission, sophisticated models will be required to unravel the broad and disparate measurements returned by the suite of Sentinels spacecraft.
Riley, P.↗
The IR energy distribution of SS433
The infrared energy distribution of the emission-line object SS 433 in the range 1 to 10 microns is determined. Photometric measurements were made with a 2.2-m telescope using an InSb detector and a 6-arcsec diaphragm for 1.2- to 4.8-micron observations and a gallium-doped germanium bolometer with a 6-arcsec diaphragm for 8- to 13-micron observations. Results indicate the presence of substantial night-to-night flux density and color variations, and a decrease in flux density at wavelengths greater than 5 microns. The energy cut-off is used to estimate a physical size of 1 AU for the emitting region and an electron density of 10 to the 11th/cu cm on the basis of a model of reddened free-free emission from an ionized plasma, with self-absorption of radiation over 5 microns. The greater variability observed at longer wavelengths is also interpreted in terms of this model.
Wynn-Williams, C. G.↗
Siple station experiments on wave-particle interactions in the magnetosphere
Natural and controlled whistler-mode signals have been used to study nonlinear mechanisms of wave growth and wave-wave interactions (WWI) in the magnetosphere; three general classes of WWI (triggering, suppression, and entrainment) are identified and interpreted in terms of a model based on cyclotron resonance interaction. This model is also used to estimate the wave field intensity associated with different types of WWI. A new type of triggered emission, the band-limited impulse (BLI) is interpreted in terms of the switching of phase-bunched currents. In addition, an experiment to find a threshold for the excitation of the coherent wave instability is discussed, and observed VLF wave-induced transient bursts of X-rays, light and E-region ionization enhancements are considered with regard to a step function wave interacting with all resonant electrons in a given energy range.
Helliwell, R. A.↗
An Extremely Luminous and Variable Ultraluminous X-ray Source in the Outskirts of Circinus Observed with Nustar
Following a serendipitous detection with the Nuclear Spectroscopic Telescope Array (NuSTAR), we present a multiepoch spectral and temporal analysis of an extreme ultraluminous X-ray source (ULX) located in the outskirts of the Circinus galaxy, hereafter Circinus ULX5, including coordinated XMM-Newton+NuSTAR follow-up observations. The NuSTAR data presented here represent one of the first instances of a ULX reliably detected at hard (E greater than 10 keV) X-rays. CircinusULX5is variable on long time scales by at least a factor of approx. 5 in flux, and was caught in a historically bright state during our 2013 observations (0.3-30.0 keV luminosity of 1.6 × 10(exp 40) erg s(exp−1)). During this epoch, the source displayed a curved 3-10 keV spectrum, broadly similar to other bright ULXs. Although pure thermal models result in a high energy excess in the NuSTAR data, this excess is too weak to be modeled with the disk reflection interpretation previously proposed to explain the 3-10 keV curvature in other ULXs. In addition to flux variability, clear spectral variability is also observed. While in many cases the interpretation of spectral components in ULXs is uncertain, the spectral and temporal properties of all the high quality data sets currently available strongly support a simple disk-corona model reminiscent of that invoked for Galactic binaries, with the accretion disk becoming more prominent as the luminosity increases. However, although the disk temperature and luminosity are well correlated across all time scales currently probed, the observed luminosity follows L alpha T (exp 1.70+/-0.17), flatter than expected for simple blackbody radiation. The spectral variability displayed here is highly reminiscent of that observed from known Galactic black hole binaries (BHBs) at high luminosities. This comparison implies a black hole mass of approx. 90M for Circinus ULX5. However, given the diverse behavior observed from Galactic BHB accretion disks, this mass estimate is still uncertain. Finally, the limits placed on any undetected iron absorption features with the 2013 data set imply that we are not viewing the central regions of Circinus ULX5 through any extreme super-Eddington outflow.
black hole physics↗
Predictive understanding of the surface tension and velocity of sound in ionic liquids using machine learning
Knowledge of the physical properties of ionic liquids (ILs), such as the surface tension and speed of sound, is important for both industrial and research applications. Unfortunately, technical challenges and costs limit exhaustive experimental screening efforts of ILs for these critical properties. Previous work has demonstrated that the use of quantum-mechanics-based thermochemical property prediction tools, such as the conductor-like screening model for real solvents, when combined with machine learning (ML) approaches, may provide an alternative pathway to guide the rapid screening and design of ILs for desired physiochemical properties. However, the question of which machine-learning approaches are most appropriate remains. In the present study, we examine how different ML architectures, ranging from tree-based approaches to feed-forward artificial neural networks, perform in generating nonlinear multivariate quantitative structure–property relationship models for the prediction of the temperature- and pressure-dependent surface tension of and speed of sound in ILs over a wide range of surface tensions (16.9–76.2 mN/m) and speeds of sound (1009.7–1992 m/s). The ML models are further interrogated using the powerful interpretation method, shapley additive explanations. We find that several different ML models provide high accuracy, according to traditional statistical metrics. The decision tree-based approaches appear to be the most accurate and precise, with extreme gradient-boosting trees and gradient-boosting trees being the best performers. However, our results also indicate that the promise of using machine-learning to gain deep insights into the underlying physics driving structure–property relationships in ILs may still be somewhat premature.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗