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At least 415 records · Page 23

Properties of earthquakes generated by fault dynamics

A model for fault dynamics consisting of a uniform chain of blocks and springs pulled slowly across a rough surface is presented. The only nonlinear element of the model is a slip-stick friction force between the blocks and the surface. It is found that this model gives rise to events of all sizes. The numerical evaluation of the distribution of earthquake magnitudes results in a power-law spectrum similar to what is observed in nature. Like certain other dissipative dynamical systems, the observed large fluctuations in earthquake magnitude persist because the system is in a state of marginal stability.

Carlson, J. M.↗

Recent deformation rates on Venus

Constraints on the recent geological evolution of Venus may be provided by quantitative estimates of the rates of the principal resurfacing processes, volcanism and tectonism. This paper focuses on the latter, using impact craters as strain indicators. The total postimpact tectonic strain lies in the range 0.5-6.5%, which defines a recent mean strain rate of 10(exp -18)-10(exp -17)/s when divided by the mean surface age. Interpretation of the cratering record as one of pure production requires a decline in resurfacing rates at about 500 Ma (catastrophic resurfacing model). If distributed tectonic resurfacing contributed strongly before that time, as suggested by the widespread occurrence of tessera as inliers, the mean global strain rate must have been at least approximately 10(exp -15)/s, which is also typical of terrestrial active margins. Numerical calculations of the response of the lithosphere to inferred mantle convective forces were performed to test the hypothesis that a decrease in surface strain rate by at least two orders of magnitude could be caused by a steady decline in heat flow over the last billion years. Parameterized convection models predict that the mean global thermal gradient decreases by only about 5 K/km over this time; even with the exponential dependence of viscosity upon temperature, the surface strain rate drops by little more than one order of magnitude. Strongly unsteady cooling and very low thermal gradients today are necessary to satisfy the catastrophic model. An alternative, uniformitarian resurfacing hypothesis holds that Venus is resurfaced in quasi-random 'patches' several hundred kilometers in size that occur in response to changing mantle convection patterns.

Grimm, Robert E.↗

A source-sink model of the generation of plate tectonics from non-Newtonian mantle flow

A model of mantle convection which generates plate tectonics requires strain rate- or stress-dependent rheology in order to produce strong platelike flows with weak margins as well as strike-slip deformation and plate spin (i.e., toroidal motion). Here, we employ a simple model of source-sink driven surface flow to determine the form of such a rheology that is appropriate for Earth's present-day plate motions. In this model, lithospheric motion is treated as shallow layer flow driven by sources and sinks which correspond to spreading centers and subduction zones, respectively. Two plate motion models are used to derive the source sink field. As originally implied in the simpler Cartesian version of this model, the classical power law rheologies do not generate platelike flows as well as the hypothetical Whitehead-Gans stick-slip rheology (which incorporates a simple self-lubrication mechanism). None of the fluid rheologies examined, however, produce more than approximately 60% of the original maximum shear. For either plate model, the viscosity fields produced by the power law rheologies are diffuse, and the viscosity lows over strike-slip shear zones or pseudo-margins are not as small as over the prescribed convergent-divergent margins. In contrast, the stick-slip rheology generates very platelike viscosity fields, with sharp gradients at the plate boundaries, and margins with almost uniformly low viscosity. Power law rheologies with high viscosity contrasts, however, lead to almost equally favorable comparisons, though these also yield the least platelike viscosity fields. This implies that the magnitude of toroidal flow and platelike strength distributions are not necessarily related and thus may present independent constraints on the determination of a self-consistent plate-mantle rheology.

Bercovici, David↗

Design Considerations for a New Terminal Area Arrival Scheduler

Design of a terminal area arrival scheduler depends on the interrelationship between throughput, delay and controller intervention. The main contribution of this paper is an analysis of the above interdependence for several stochastic behaviors of expected system performance distributions in the aircraft s time of arrival at the meter fix and runway. Results of this analysis serve to guide the scheduler design choices for key control variables. Two types of variables are analyzed, separation buffers and terminal delay margins. The choice for these decision variables was tested using sensitivity analysis. Analysis suggests that it is best to set the separation buffer at the meter fix to its minimum and adjust the runway buffer to attain the desired system performance. Delay margin was found to have the least effect. These results help characterize the variables most influential in the scheduling operations of terminal area arrivals.

Thipphavong, Jane↗

Tax Credits for Clean Electricity: The Distributional Impacts of Supply-Push Policies in the Power Sector

We evaluate distributional and efficiency consequences of the bulk power clean electricity tax credits authorized by the 2022 Inflation Reduction Act. To do so, we link detailed electricity capacity expansion, computable general equilibrium, data-rich microsimulation, and air pollution models to estimate the policy incidence in terms of economic welfare and health impacts across a wide range of demographic groups. We evaluate the tradeoff between policy efficiency and income progressivity by comparing the tax credits to cap-and-trade policies that vary revenue recycling approaches. Under the scenarios analyzed the bulk power tax credits lead to increased clean electricity technology deployment resulting in a reallocation of capital from elsewhere in the economy, higher prices for capital and other goods, lower power prices, and lower emissions. The tax credits yield progressive outcomes for both economic welfare and health impacts. The health benefits exceed total policy costs and provide greater benefits for low-income and historically-marginalized households given the coincidence of household and emission source locations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

RAFT: Reconfigurable Array of High-Efficiency Ducted Turbines for Hydrokinetic Energy Harvesting

Diversifying the energy harvesting portfolio is crucial to achieving the ambitious goal of transitioning to clean energy by 2030. Marine hydrokinetic energy has garnered renewed interest due to its high harvesting potential in the U.S., and the resource's reliability and predictability—remaining relatively constant on a daily basis and available 24/7. However, there are currently few commercial devices capable of harnessing the energy from flowing water. This project aims to bridge that gap by designing and evaluating a novel hydrokinetic turbine concept that can efficiently harvest energy from both rivers and tidal streams. The RAFT (Reconfigurable Array of High-Efficiency Ducted Turbines) concept introduces a duct surrounding the turbine rotor and creates an array of small 5-kW units. The duct serves two primary purposes: (1) it enhances hydrodynamic efficiency by accelerating flow to the rotor, and (2) it functions as a structural component, facilitating the formation of modular arrays that lower costs. This project focuses on demonstrating this concept and validating these benefits through simulations and scaled prototype testing. The project team includes 8 faculty members and over 20 students from 3 universities, organized into three core areas: hydrodynamics, electrical systems, and structural analysis, with additional teams dedicated to system integration, environmental assessment and risk management, and tech-to-market strategy. The team successfully demonstrated the increased hydrodynamic efficiency of a ducted turbine compared to an unducted version using high-fidelity simulations and prototype tests. Moreover, design optimization efforts led to surpassing the SHARKS program's goal of 60% reduction of the levelized cost of energy with a significant margin.

13 HYDRO ENERGY↗

Constraints on the Cosmic Expansion History from GWTC–3

We use 47 gravitational wave sources from the Third LIGO–Virgo–Kamioka Gravitational Wave Detector Gravitational Wave Transient Catalog (GWTC–3) to estimate the Hubble parameter H(z), including its current value, the Hubble constant H0. Each gravitational wave (GW) signal provides the luminosity distance to the source, and we estimate the corresponding redshift using two methods: the redshifted masses and a galaxy catalog. Using the binary black hole (BBH) redshifted masses, we simultaneously infer the source mass distribution and H(z). The source mass distribution displays a peak around 34 M ⊙ , followed by a drop-off. Assuming this mass scale does not evolve with the redshift results in a H(z) measurement, yielding H 0 = $68$$^{+12}_{–8}$km s –1 Mpc –1 (68% credible interval) when combined with the H 0 measurement from GW170817 and its electromagnetic counterpart. This represents an improvement of 17% with respect to the H 0 estimate from GWTC–1. The second method associates each GW event with its probable host galaxy in the catalog GLADE+, statistically marginalizing over the redshifts of each event's potential hosts. Assuming a fixed BBH population, we estimate a value of H 0 = $68$$^{+8}_{–6}$km s –1 Mpc –1 with the galaxy catalog method, an improvement of 42% with respect to our GWTC–1 result and 20% with respect to recent H 0 studies using GWTC–2 events. However, we show that this result is strongly impacted by assumptions about the BBH source mass distribution; the only event which is not strongly impacted by such assumptions (and is thus informative about H 0 ) is the well-localized event GW190814.

79 ASTRONOMY AND ASTROPHYSICS↗

A Bayesian Approach to the Eagar–Tsai Model for Melt Pool Geometry Prediction with Implications in Additive Manufacturing of Metals

Here, this paper focuses on improving the melt pool geometry predictions and quantifying uncertainties using an adapted version of the Eagar–Tsai (E–T) model that incorporates temperature-dependent properties of the material as well as powder conditions. Additionally, Bayesian inference is employed to predict distributions for the E–T model input parameters of laser absorptivity and powder bed porosity by incorporating experimental results into the analysis. Monte Carlo uncertainty propagation is then used with these parameter distributions to estimate the melt pool depth and associated uncertainty. Our results for the 316L stainless steel suggest that both the absorptivity and powder bed porosity are strongly influenced by the laser power. In contrast, the scanning speed has only a marginal effect on both the absorptivity and powder bed porosity. We constructed a printability map using the Bayesian E–T model based on power-dependent input parameter values to demonstrate the merit of the approach. The Bayesian approach improved the accuracy in predicting the keyhole regions in the laser power-scan speed parameter space for the 316L stainless steel. Although applied to a specific adaptation of the E–T model, the method put forth can be extended to quantify uncertainties in other numerical models as well as in the estimation of unknown parameters.

316L Stainless Steel (SS).↗

Data-based filtered dissipation rate modelling for multi-modal turbulent combustion: evaluating a priori model generalizability

Manifold-based models offer a computationally efficient alternative to directly transporting the thermochemical state in computational simulations of turbulent reacting flows, projecting the high-dimensional thermochemical state-space onto a low-dimensional manifold. Recent efforts have yielded a manifold-based model applicable to multi-modal combustion, enabling reconstruction of the thermochemical state from solutions to two-dimensional manifold equations in mixture fraction and generalized progress variable that are parameterised by three scalar dissipation rates. In coarse-grained simulations such as Large Eddy Simulation (LES), closure of the multi-modal manifold equations and subfilter variances/covariance requires closure of three filtered scalar dissipation rates. Here, the present work adopts a data-based approach, providing closure for the three filtered scalar dissipation rates via deep neural networks (DNNs). High-fidelity datasets corresponding to an autoigniting n-dodecane jet flame and a bluff body swirl-stabilized confined lifted spray flame of two aviation fuels (Jet-A and C1) with different ignition propensities are leveraged to generate training data that spans a diverse range of thermodynamic conditions and combustion modes, including low- and high-temperature ignition regimes in addition to premixed and nonpremixed behaviour. A final DNN model is trained to enforce inherent physical constraints by learning nonlinear functional transformations of the three filtered scalar dissipation rates. The generalizability of this constrained DNN model is demonstrated a priori via conditional statistics evaluated on the lifted spray flame with C1–a configuration that had not been included in the training data. Excellent DNN agreement with conditional DNS statistics is observed, and integrated gradients are computed to identify the most sensitive input variables. The similarity of the marginal PDFs of the most informative input variables and outputs across configurations are quantified via the Wasserstein metric, demonstrating that data-based models may successfully generalize to unseen parametric conditions so long as the most informative input variables share similar distributions across training and testing datasets.

Data-based modelling↗

Far infrared observations of crab-like supernova remnants

Using the Infrared Astronomy Satellite (IRAS) data, an investigation was begun of the far infrared properties of Crab-like supernova remnants and other synchrotron nebulae. Both the co-added scanning data and, where available, pointed observations were examined. To date infrared emission was found from two Crab-like remnants: G24.7+0.6 in which the infrared source near the center of the object was shown to be a compact HII region with EM greater than or approximately 10 to the 7th pc/cm(6); and G0.9+0.1 where a marginal detection of a 25 micron source coincident with the remnant core was used to set limits on the energetics of this synchrotron nebula. Further work, in progress under a second year of this program, should yield additional information concerning the distribution of initial pulsar spin periods and the evolution of synchrotron nebulae.

Helfand, David J.↗

OGLE-2018-BLG-1185b: A Low-mass Microlensing Planet Orbiting a Low-mass Dwarf

We report an analysis of the planetary microlensing event OGLE-2018-BLG-1185, which was observed by a large number of ground-based telescopes and by the Spitzer Space Telescope. The ground-based light curve indicates a low planet–host star mass ratio of q = (6.9 ± 0.2) × 10{sup −5}, which is near the peak of the wide-orbit exoplanet mass-ratio distribution. We estimate the host star and planet masses with a Bayesian analysis using the measured angular Einstein radius under the assumption that stars of all masses have an equal probability of hosting the planet. The flux variation observed by Spitzer is marginal, but still places a constraint on the microlens parallax. Imposing a conservative constraint that this flux variation should be Δf {sub Spz} < 4 instrumental flux units yields a host mass of M{sub host}=0.37{sub −0.21}{sup +0.35} M{sub ⊙} and a planet mass of m{sub p}=8.4{sub −4.7}{sup +7.9} M{sub ⊕}. A Bayesian analysis including the full parallax constraint from Spitzer suggests smaller host star and planet masses of M{sub host}=0.091{sub −0.018}{sup +0.064} M{sub ⊙} and m{sub p}=2.1{sub −0.4}{sup +1.5} M{sub ⊕}, respectively. Future high-resolution imaging observations with the Hubble Space Telescope or Extremely Large Telescope could distinguish between these two scenarios and help reveal the planetary system properties in more detail.

47 OTHER INSTRUMENTATION↗

Numerical flux formulas for the Euler and Navier-Stokes equations. 2: Progress in flux-vector splitting

The accuracy of various numerical flux functions for the inviscid fluxes when used for Navier-Stokes computations is studied. The flux functions are benchmarked for solutions of the viscous, hypersonic flow past a 10 degree cone at zero angle of attack using first order, upwind spatial differencing. The Harten-Lax/Roe flux is found to give a good boundary layer representation, although its robustness is an issue. Some hybrid flux formulas, where the concepts of flux-vector and flux-difference splitting are combined, are shown to give unsatisfactory pressure distributions; there is still room for improvement. Investigations of low diffusion, pure flux-vector splittings indicate that a pure flux-vector splitting can be developed that eliminates spurious diffusion across the boundary layer. The resulting first-order scheme is marginally stable and not monotone.

Coirier, William J.↗

Numerical flux formulas for the Euler and Navier-Stokes equations. II - Progress in flux-vector splitting

The accuracy of various numerical flux functions for the inviscid fluxes when used for Navier-Stokes computations is studied. The flux functions are benchmarked for solutions of the viscous, hypersonic flow past a 10 degree cone at zero angle of attack using first order, upwind spatial differencing. The Harten-Lax/Roe flux is found to give a good boundary layer representation, although its robustness is an issue. Some hybrid flux formulas, where the concepts of flux-vector and flux-difference splitting are combined, are shown to give unsatisfactory pressure distributions; there is still room for improvement. Investigations of low diffusion, pure flux-vector splittings indicate that a pure flux-vector splitting can be developed that eliminates spurious diffusion across the boundary layer. The resulting first-order scheme is marginally stable and not monotone.

Coirier, William J.↗

OGLE-2018-BLG-1185b: A Low-mass Microlensing Planet Orbiting a Low-mass Dwarf

We report an analysis of the planetary microlensing event OGLE-2018-BLG-1185, which was observed by a large number of ground-based telescopes and by the Spitzer Space Telescope. The ground-based light curve indicates a low planet–host star mass ratio ofq=(6.9±0.2)×10−5, which is near the peak of the wide-orbit exoplanet mass-ratio distribution. We estimate the host star and planet masses with a Bayesian analysis using the measured angular Einstein radius under the assumption that stars of all masses have an equal probability of hosting the planet. The flux variation observed by Spitzer is marginal, but still places a constraint on the microlens parallax. Imposing a conservative constraint that this flux variation should beΔfSpz<4 instrumental flux units yields a host mass of=-+MM0.37 host 0.210.35 and a planet mass of =-+ÅmM8.4p4.77.9. A Bayesian analysis including the full parallax constraint from Spitzer suggests smaller host star and planet masses of =-+MM0.091 host 0.0180.064 and =-+ÅmM2.1p0.41.5, respectively. Future high-resolution imaging observations with the Hubble Space Telescope or Extremely Large Telescope could distinguish between these two scenarios and help reveal the planetary system properties in more detail.

Gravitational microlensing↗

Severe Convective Storms in Limited Instability Organized by Pattern and Distribution

Abstract Severe convection occurring in high-shear, low-CAPE (HSLC) environments is a common cool-season threat in the southeastern United States. Previous studies of HSLC convection document the increased operational challenges that these environments present compared to their high-CAPE counterparts, corresponding to higher false-alarm ratios and lower probability of detection for severe watches and warnings. These environments can exhibit rapid destabilization in the hours prior to convection, sometimes associated with the release of potential instability. Here, we use self-organizing maps (SOMs) to objectively identify environmental patterns accompanying HSLC cool-season severe events and associate them with variations in severe weather frequency and distribution. Large-scale patterns exhibit modest variation within the HSLC subclass, featuring strong surface cyclones accompanied by vigorous upper-tropospheric troughs and northward-extending regions of instability, consistent with prior studies. In most patterns, severe weather occurs immediately ahead of a cold front. Other convective ingredients, such as lower-tropospheric vertical wind shear, near-surface equivalent potential temperature (θ e ) advection, and the release of potential instability, varied more significantly across patterns. No single variable used to train SOMs consistently demonstrated differences in the distribution of severe weather occurrence across patterns. Comparison of SOMs based on upper and lower quartiles of severe occurrence demonstrated that the release of potential instability was most consistently associated with higher-impact events in comparison to other convective ingredients. Overall, we find that previously developed HSLC composite parameters reasonably identify high-impact HSLC events. Significance Statement Even when atmospheric instability is not optimal for severe convective storms, in some situations they can still occur, presenting increased challenges to forecasters. These marginal environments may occur at night or during the cool season, when people are less attuned to severe weather threats. Here, we use a sorting algorithm to classify different weather patterns accompanying such storms, and we distinguish which specific patterns and weather system features are most strongly associated with severe storms. Our goals are to increase situational awareness for forecasters and to improve understanding of the processes leading to severe convection in marginal environments.

Meteorology & Atmospheric Sciences↗

Small-Signal Stability Support from Dynamically Configurable Grid-Forming/Following Inverters for Distribution Systems: Preprint

As the penetration of inverter-based resources (IBRs) continues to increase in modern power systems, system stability is challenged by the insufficient inertia induced by IBRs; hence, there is a need to develop various methods to address the potential instabilities. In this paper, grid-forming (GFM) and grid-following (GFL) controls are implemented for inverters with flexible-mode transitions between them. The operation mode transition between GFM and GFL controls is adopted as an additional degree of control flexibility to adjust the small signal stability margin. Further, a holistic and detailed small signal model of the entire system with the dynamics from both synchronous generators (SGs) and IBRs is derived. The effectiveness of the proposed work in adjusting the system small signal stability margin is validated by conducting case studies with varying penetration levels of IBRs. A test system with one SG and five inverters was implemented in MATLAB/Simulink to demonstrate the effectiveness of the proposed approach. Index Terms - grid-following control, grid-forming control, operation mode transition, small-signal stability analysis

grid-following control↗

Bayesian operator inference for data-driven reduced-order modeling

This work proposes a Bayesian inference method for the reduced-order modeling of time-dependent systems. Informed by the structure of the governing equations, the task of learning a reduced-order model from data is posed as a Bayesian inverse problem with Gaussian prior and likelihood. The resulting posterior distribution characterizes the operators defining the reduced-order model, hence the predictions subsequently issued by the reduced-order model are endowed with uncertainty. The statistical moments of these predictions are estimated via a Monte Carlo sampling of the posterior distribution. Since the reduced models are fast to solve, this sampling is computationally efficient. Furthermore, the proposed Bayesian framework provides a statistical interpretation of the regularization term that is present in the deterministic operator inference problem, and the empirical Bayes approach of maximum marginal likelihood suggests a selection algorithm for the regularization hyperparameters. The proposed method is demonstrated on two examples: the compressible Euler equations with noise-corrupted observations, and a single-injector combustion process.

97 MATHEMATICS AND COMPUTING↗

Optimal Bayesian supervised domain adaptation for RNA sequencing data

Abstract Motivation When learning to subtype complex disease based on next-generation sequencing data, the amount of available data is often limited. Recent works have tried to leverage data from other domains to design better predictors in the target domain of interest with varying degrees of success. But they are either limited to the cases requiring the outcome label correspondence across domains or cannot leverage the label information at all. Moreover, the existing methods cannot usually benefit from other information available a priori such as gene interaction networks. Results In this article, we develop a generative optimal Bayesian supervised domain adaptation (OBSDA) model that can integrate RNA sequencing (RNA-Seq) data from different domains along with their labels for improving prediction accuracy in the target domain. Our model can be applied in cases where different domains share the same labels or have different ones. OBSDA is based on a hierarchical Bayesian negative binomial model with parameter factorization, for which the optimal predictor can be derived by marginalization of likelihood over the posterior of the parameters. We first provide an efficient Gibbs sampler for parameter inference in OBSDA. Then, we leverage the gene-gene network prior information and construct an informed and flexible variational family to infer the posterior distributions of model parameters. Comprehensive experiments on real-world RNA-Seq data demonstrate the superior performance of OBSDA, in terms of accuracy in identifying cancer subtypes by utilizing data from different domains. Moreover, we show that by taking advantage of the prior network information we can further improve the performance. Availability and implementation The source code for implementations of OBSDA and SI-OBSDA are available at the following link. https://github.com/SHBLK/BSDA. Supplementary information Supplementary data are available at Bioinformatics online.

Biochemistry & Molecular Biology↗