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At least 199 records · Page 11

Evidence for a Low Bulk Crustal Density for Mars from Gravity and Topography

Knowledge of the average density of the crust of a planet is important in determining its interior structure. The combination of high-resolution gravity and topography data has yielded a low density for the Moon’s crust, yet for other terrestrial planets the resolution of the gravity field models has hampered reasonable estimates. By using well-chosen constraints derived from topography during gravity field model determination using satellite tracking data, we show that we can robustly and independently determine the average bulk crustal density directly from the tracking data, using the admittance between topography and imperfect gravity. We find a low average bulk crustal density for Mars, 2582 ± 209 kgm−3. This bulk crustal density is lower than that assumed until now. Densities for volcanic complexes are higher, consistent with earlier estimates, implying large lateral variations in crustal density. In addition, we find indications that the crustal density increases with depth.

Goossens, Sander J.↗

Incorporating geological structure into sensitivity analysis of subsurface contaminant transport

Simulating subsurface contaminant transport at the kilometer-scale often entails modeling reactive flow and transport within and through complex geologic structures. These structures are typically meshed by hand and as a result geologic structure is usually represented by one or a few deterministically generated geological models for uncertainty studies of flow and transport in the subsurface. Uncertainty in geologic structure can have a significant impact on contaminant transport. In this study, the impact of geologic structure on contaminant tracer transport in a shale formation is investigated for a simplified generic deep geologic repository for permanent disposal of spent nuclear fuel. An open-source modeling framework is used to perform a sensitivity analysis study on transport of two tracers from a generic spent nuclear fuel repository with uncertain location of the interfaces between the stratum of the geologic structure. The automated workflow uses sampled realizations of the geological structural model in addition to uncertain flow parameters in a nested sensitivity analysis. Concentration of the tracers at observation points within, in line with, and downstream of the repository are used as the quantities of interest for determining model sensitivity to input parameters and geological realization. Finally, the results of the study indicate that the location of strata interfaces in the geological structure has a first-order impact on tracer transport in the example shale formation, and that this impact may be greater than that of the uncertain flow parameters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Integrating deep neural networks with full-waveform inversion: Reparameterization, regularization, and uncertainty quantification

Full-waveform inversion (FWI) is an accurate imaging approach for modeling the velocity structure by minimizing the misfit between recorded and predicted seismic waveforms. However, the strong nonlinearity of FWI resulting from fitting oscillatory waveforms can trap the optimization in local minima. We have adopted a neural-network-based full-waveform inversion (NNFWI) method that integrates deep neural networks with FWI by representing the velocity model with a generative neural network. Neural networks can naturally introduce spatial correlations as regularization to the generated velocity model, which suppresses noise in the gradients and mitigates local minima. Furthermore, the velocity model generated by neural networks is input to the same partial differential equation (PDE) solvers used in conventional FWI. The gradients of the neural networks and PDEs are calculated using automatic differentiation, which back propagates gradients through the acoustic PDEs and neural network layers to update the weights of the generative neural network. Experiments on 1D velocity models, the Marmousi model, and the 2004 BP model determine that NNFWI can mitigate local minima, especially for imaging high-contrast features such as salt bodies, and it significantly improves the inversion in the presence of noise. Adding dropout layers to the neural network model also allows analyzing the uncertainty of the inversion results through Monte Carlo dropout. NNFWI opens a new pathway to combine deep learning and FWI for exploiting the characteristics of deep neural networks and the high accuracy of PDE solvers. Because NNFWI does not require extra training data and optimization loops, it provides an attractive and straightforward alternative to conventional FWI.

58 GEOSCIENCES↗

Bayesian time-varying occupancy model for West Nile virus in Ontario, Canada

Occupancy models determine the true presence or absence of a species by adjusting for imperfect detection in surveys. They often assume that species presences can be detected only if sites are occupied during a sampling season. We extended these models to estimate occupancy rates that vary throughout a sampling season as well as account for spatial dependence among sites. For these methods, we constructed a fast Gibbs sampler with the Pólya-Gamma augmentation strategy to conduct inference on covariate effects. We applied these methods to evaluate how environmental conditions and surveillance practices are associated with the presence of West Nile virus in mosquito traps across Ontario, Canada from 2002 to 2017. We found that urban land cover and warm temperatures drove viral occupancy, whereas viral testing on pools with higher proportions of Culex mosquitoes was more likely to result in a positive test for West Nile virus. Models with time-varying occupancy effects achieved much lower Watanabe-Akaike information criteria than models without such effects. Our final model had strong predictive performance on test data that included some of the most extreme seasons, demonstrating the promise of these methods in the study of pathogens spread by mosquito vectors.

60 APPLIED LIFE SCIENCES↗

Evaluation of semiempirical atmospheric density models for orbit determination applications

This paper presents the results of an investigation of the orbit determination performance of the Jacchia-Roberts (JR), mass spectrometer incoherent scatter 1986 (MSIS-86), and drag temperature model (DTM) atmospheric density models. Evaluation of the models was performed to assess the modeling of the total atmospheric density. This study was made generic by using six spacecraft and selecting time periods of study representative of all portions of the 11-year cycle. Performance of the models was measured for multiple spacecraft, representing a selection of orbit geometries from near-equatorial to polar inclinations and altitudes from 400 kilometers to 900 kilometers. The orbit geometries represent typical low earth-orbiting spacecraft supported by the Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD). The best available modeling and orbit determination techniques using the Goddard Trajectory Determination System (GTDS) were employed to minimize the effects of modeling errors. The latest geopotential model available during the analysis, the Goddard earth model-T3 (GEM-T3), was employed to minimize geopotential model error effects on the drag estimation. Improved-accuracy techniques identified for TOPEX/Poseidon orbit determination analysis were used to improve the Tracking and Data Relay Satellite System (TDRSS)-based orbit determination used for most of the spacecraft chosen for this analysis. This paper shows that during periods of relatively quiet solar flux and geomagnetic activity near the solar minimum, the choice of atmospheric density model used for orbit determination is relatively inconsequential. During typical solar flux conditions near the solar maximum, the differences between the JR, DTM, and MSIS-86 models begin to become apparent. Time periods of extreme solar activity, those in which the daily and 81-day mean solar flux are high and change rapidly, result in significant differences between the models. During periods of high geomagnetic activity, the standard JR model was outperformed by DTM. Modification of the JR model to use a geomagnetic heating delay of 3 hours, as used in DTM, instead of the 6.7-hour delay produced results comparable to or better than the DTM performance, reducing definitive orbit solution ephermeris overlap differences by 30 to 50 percent. The reduction in the overlap differences would be useful for mitigating the impact of geomagnetic storms on orbit prediction.

Cox, C. M.↗

Ice-Ridge Pile Up and the Genesis of Martian "Shorelines"

Unique geomorphologic features such as basin terraces exhibiting topographic continuity have been found within several Martian craters as shown in Viking, MOC, and THEMIS images. These features, showing similarity to terrestrial shorelines, have been mapped and cataloged with significant effort [1]. Currently, open wave action on the surface of paleolakes has been hypothesized as the geomorphologic agent responsible for the generation of these features [2]. As consequence, feature interpretations, including shorelines, wave-cut benches, and bars are, befittingly, lacustrine. Because such interpretations and their formation mechanisms have profound implications for the climate and potential biological history of Mars, confidence is crucial. The insight acquired through linked quantitative modeling of geomorphologic agents and processes is key to accurately interpreting these features. In this vein, recent studies [3,4] involving the water wave energy in theoretical open water basins on Mars show minimal erosional effects due to water waves under Martian conditions. Consequently, sub-glacial lake flattens the surface, produces a local velocity increase over the lake, and creates a deviation of the ice flow from the main flow direction [11]. These consequences of ice flow are observed at Lake Vostok, Antarctica an excellent Martian analogue [11]. Martian observations include reticulate terrain exhibiting sharp inter-connected ridges speculated to reflect the deposition and reworking of ice blocks at the periphery of ice-covered lakes throughout Hellas [12]. Our model determines to what extent ice, a terrestrial geomorphologic agent, can alter the Martian landscape. Method: We study the evolution of crater ice plugs as the formation mechanism of surface features frequently identified as shorelines. In particular, we perform model integrations involving parameters such as ice slope and purity, atmospheric pressure and temperature, crater shape and composition, and an energy balance between solar flux, geothermal flux, latent heat, and ablation. Our ultimate goal is to understand how an intracrater ice plug could create the observed shoreline features and how these

Barnhart, C. J.↗

The Role of Phytoplankton Biomacromolecules in Controlling Ocean Surface Roughness

Satellite altimetric data routinely map sea surface topography by measuring the ocean return signal. One source of altimeter measurement contamination occurs when the radar ocean backscatter becomes unusually large, a situation termed a Sigma-0 bloom. Past research suggests Sigma-0 blooms are associated with weak wind and natural surface slick conditions where capillary waves at the air–sea interface are suppressed. To date, no explicit connection between these conditions and Sigma-0 bloom presence has been provided. Using a series of simplified equations, our reduced model determines capillary wave heights from estimates of planktonic carbon concentrations and regional wind speed. Our results suggest that the radar signal reflection increases as capillary wave height decreases. This relationship depends on surfactant concentration, surfactant composition, and wind speed. Model sensitivity analysis indicates that the interface reflectivity depends on biological activity and wind speed. Our proposed simplified model provides a method to identify potential Sigma-0 bloom regions. We conclude that because of the demonstrated impact of biological surfactants on ocean roughness, it is necessary to consider the biological activity, i.e., phytoplankton bloom events, when interpreting signals from radar altimetry and when developing ocean hydrology models.

54 ENVIRONMENTAL SCIENCES↗

Status of the Dielectric Constant of Sea Water at L-Band for Remote Sensing of Salinity

The model expressing the dielectric constant of sea water at microwave frequencies as a function of salinity and temperature is an important element in remote sensing of sea surface salinity. It is also important independently as a description of the physical properties of salt water. A major milestone was the development in the late 1970s by Klein and Swift of a model based on laboratory measurements at L- and S-band and a functional form supported by theory for polar molecules and previous work on freshwater. Much of the subsequent work has focused on measurements at higher frequency and determining model parameters tuned to apply for applications, such as remote sensing of sea surface temperature (SST). Interest in the dielectric constant at 1.4 GHz (L-band) increased again with the development of soil moisture ocean salinity (SMOS) and Aquarius to measure salinity from space, but there have been few new measurements at L-band and often confusion regarding the applicability of new models at 1.4 GHz. The objective of this article is to compare available models in the context of how well they represent the dielectric constant of sea water at 1.4 GHz. Among the criteria applied will be the recent measurements at the George Washington University of the dielectric constant at 1.4 GHz

Microwave Remote Sensing↗

Passive Roll Stabilization of the Near Earth Asteroid Scout Solar Sail Mission

The Near Earth Asteroid (NEA) Scout is a small satellite, solar sail mission set to launch on Artemis I. Analysis of the NEA Scout solar radiation pressure model determined that, for certain solar incidence angles, there exists at least one locally stable equilibrium point about the “roll” axis, or the axis normal to the solar sail plane. This analysis is extended to three other geometrically similar solar sail models, and a Lyapunov stability analysis is conducted demonstrating that the stable equilibria are locally stable for the majority of roll angles in a wide range of solar incidence angles. Under certain assumptions, it is possible that only two axis control is required for non-spinning solar sails. If the roll axis is controlled, an active rate damping controller can be designed to asymptotically stabilize the system. Simulation results are presented that follow the stability analysis, where in the homogenous case, the system enters a limit cycle and, in the actively damped case, the system asymptotically converges to the equilibrium point.

Ivan Rodrigues Bertaska↗

Search for subgrid scale parameterization by projection pursuit regression

The dependence of subgrid-scale stresses on variables of the resolved field is studied using direct numerical simulations of isotropic turbulence, homogeneous shear flow, and channel flow. The projection pursuit algorithm, a promising new regression tool for high-dimensional data, is used to systematically search through a large collection of resolved variables, such as components of the strain rate, vorticity, velocity gradients at neighboring grid points, etc. For the case of isotropic turbulence, the search algorithm recovers the linear dependence on the rate of strain (which is necessary to transfer energy to subgrid scales) but is unable to determine any other more complex relationship. For shear flows, however, new systematic relations beyond eddy viscosity are found. For the homogeneous shear flow, the results suggest that products of the mean rotation rate tensor with both the fluctuating strain rate and fluctuating rotation rate tensors are important quantities in parameterizing the subgrid-scale stresses. A model incorporating these terms is proposed. When evaluated with direct numerical simulation data, this model significantly increases the correlation between the modeled and exact stresses, as compared with the Smagorinsky model. In the case of channel flow, the stresses are found to correlate with products of the fluctuating strain and rotation rate tensors. The mean rates of rotation or strain do not appear to be important in this case, and the model determined for homogeneous shear flow does not perform well when tested with channel flow data. Many questions remain about the physical mechanisms underlying these findings, about possible Reynolds number dependence, and, given the low level of correlations, about their impact on modeling. Nevertheless, demonstration of the existence of causal relations between sgs stresses and large-scale characteristics of turbulent shear flows, in addition to those necessary for energy transfer, provides important insight into the relation between scales in turbulent flows.

Meneveau, C.↗

Determination of airplane model structure from flight data by using modified stepwise regression

The linear and stepwise regressions are briefly introduced, then the problem of determining airplane model structure is addressed. The MSR was constructed to force a linear model for the aerodynamic coefficient first, then add significant nonlinear terms and delete nonsignificant terms from the model. In addition to the statistical criteria in the stepwise regression, the prediction sum of squares (PRESS) criterion and the analysis of residuals were examined for the selection of an adequate model. The procedure is used in examples with simulated and real flight data. It is shown that the MSR performs better than the ordinary stepwise regression and that the technique can also be applied to the large amplitude maneuvers.

Klein, V.↗

Surface hot-film method for the measurement of transition, separation and reattachment points

A real-time method of determining positions of laminar-to-turbulent transition region, separation and reattachment points and stagnation points using an array of simultaneously operated surface-mounted hot-film sensors has been developed and applied to a wind-tunnel test of a multielement airfoil model. Determination of various types of transitions and flow directions in various regimes of flows seen on multielement airfoils are possible without precise sensor calibration or laborious post-test data analysis. The results agree with established method and theoretical methods, but determination of turbulent reattachment points are not yet satisfactory.

Nakayama, Akihiko↗

ACDC (Automated Campbell Diagram Code) [SWR-26-042]

This application provides a web-based graphical user interface to generating Campbell Diagrams and visualizing mode shapes for OpenFAST turbine models. Determining the aeroelastic stability and dynamic characteristics of wind turbines is a critical step in turbine design and analysis. Historically, extracting natural frequencies and mode shapes from OpenFAST—the industry-standard whole-turbine simulation code—has been a fragmented and tedious process. It required manual model configuration, command-line linearization execution, and complex post-processing via proprietary scripts to handle rotating-frame dynamics. To address these workflow bottlenecks, we present the Automated Campbell Diagram Code (ACDC), an open-source graphical software tool developed by the National Laboratory of the Rockies (NLR) under the DOE-funded Distributed Wind Aeroelastic Modeling (dWAM) project. ACDC streamlines the end-to-end linearization and stability analysis workflow into a single, intuitive cross-platform application. The software guides users through OpenFAST model configuration, definition of operating points, and the automated execution of steady-state trim and linearization simulations. Under the hood, ACDC automates the complex mathematical post-processing steps required for rotating systems, including Multi-Blade Coordinate (MBC) transformations, eigenanalysis, and advanced modal tracking utilizing the Modal Assurance Criterion (MAC) and spectral clustering. Finally, ACDC processes these results to automatically generate Campbell diagrams and features a robust 3D visualization engine to animate full-system mode shapes. By eliminating the reliance on external post-processing environments and manual data manipulation, ACDC significantly accelerates dynamic analysis and lowers the barrier to entry for wind energy researchers and engineers.

Summerville, Brent [National Laboratory of the Roc↗

Method and system for non-linear motion estimation

A method and system for extrapolating and interpolating a visual signal including determining a first motion vector between a first pixel position in a first image to a second pixel position in a second image, determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image, determining a third motion vector between one of the first pixel position in the first image and the second pixel position in the second image, and the second pixel position in the second image and the third pixel position in the third image using a non-linear model, determining a position of the fourth pixel in a fourth image based upon the third motion vector.

Lu, Ligang↗

Insights for Canadian electricity generation planning from an integrated assessment model: Should we be more cautious about hydropower cost overruns?

Hydropower accounts for approximately 60% of electricity generation in Canada, with growth expected in the coming decades as part of renewable energy transitions; however, frequent cost overruns threaten the viability of this growth. Here, using the integrated assessment model GCAM, we develop an endogenous representation of hydropower for Canada that accounts for market dynamics, thus permitting analysis of hydropower competition with other electricity generation technologies, both with and without cost overruns. Results show that modelling hydropower resources endogenously increases Canadian hydropower deployment relative to an assumption of fixed hydropower production, from 417 to 495 TWh annually by 2050. In scenarios that apply cost overruns at historical levels, hydropower loses market share to more easily scalable technologies like wind power. When including high cost overrun assumptions, the model determines that hydropower falls from about 73% to 65% of Canadian electricity generation by 2050, while wind power increases from about 8% to 11%. Countries may be better able to achieve electrification and renewable energy targets at lower cost by avoiding large-scale, overrun-prone hydropower and nuclear generation projects. Model results support that cost overruns are important considerations for policy decisions related to electricity sector development in Canada and elsewhere.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Direct-imaging Discovery and Dynamical Mass of a Substellar Companion Orbiting an Accelerating Hyades Sun-like Star with SCExAO/CHARIS

We present the direct-imaging discovery of a substellar companion in orbit around a Sun-like star member of the Hyades open cluster. So far, no other substellar companions have been unambiguously confirmed via direct imaging around main-sequence stars in Hyades. The star HIP 21152 is an accelerating star as identified by the astrometry from the Gaia and Hipparcos satellites. We detected the companion, HIP 21152 B, in multiple epochs using the high-contrast imaging from SCExAO/CHARIS and Keck/NIRC2. We also obtained the stellar radialvelocity data from the Okayama 188 cm telescope. The CHARIS spectroscopy reveals that HIP 21152 B’s spectrum is consistent with the L/T transition, best fit by an early T dwarf. Our orbit modeling determines the semimajor axis and the dynamical mass of HIP 21152 B to be 17 +7.2 −3.8 and 27.8 +8.4 −5.4 M Jub , respectively. The mass ratio of HIP 21152 B relative to its host is ≈2%, near the planet/brown dwarf boundary suggested by recent surveys. Mass estimates inferred from luminosity-evolution models are slightly higher (33–42 MJup). With a dynamical mass and a well-constrained age due to the system’s Hyades membership, HIP 21152 B will become a critical benchmark in understanding the formation, evolution, and atmosphere of a substellar object as a function of mass and age. Our discovery is yet another key proof of concept for using precision astrometry to select direct-imaging targets.

Masayuki Kuzuhara↗