Good Vibrations: Calculating Excited-State Frequencies Using Ground-State Self-Consistent Field Models
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ABSTRACT The variability in spatial resolution of seismic velocity models obtained via tomographic methodologies is attributed to many factors, including inversion strategies, ray-path coverage, and data integrity. Integration of such models, with distinct resolutions, is crucial during the refinement of community models, thereby enhancing the precision of ground-motion simulations. Toward this goal, we introduce the probability graphical model (PGM), combining velocity models with heterogeneous resolutions and nonuniform data point distributions. The PGM integrates data relations across varying resolution subdomains, enhancing detail within low-resolution (LR) domains by utilizing information and prior knowledge from high-resolution (HR) subdomains through a maximum posterior problem. Assessment of efficacy, utilizing both 2D and 3D velocity models—consisting of synthetic checkerboard models and a fault-zone model from Ridgecrest, California—demonstrates noteworthy improvements in accuracy, compared to state-of-the-art fusion techniques. Specifically, we find reductions of 30% and 44% in computed travel-time residuals for 2D and 3D models, respectively, as compared to conventional smoothing techniques. Unlike conventional methods, the PGM’s adaptive weight selection facilitates preserving and learning details from complex, nonuniform HR models and applies the enhancements to the LR background domain.
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presentation for MORe 2024
The Sloan Digital Sky Survey MaNGA program has now obtained integral field spectroscopy for over 10,000 galaxies in the nearby universe. We use the final MaNGA data release DR17 to study the correlation between ionized gas velocity dispersion and galactic star formation rate, finding a tight correlation in which σ Hα from galactic H ιι regions increases significantly from ~18–30 km s –1 , broadly in keeping with previous studies. In contrast, σ Hα from diffuse ionized gas increases more rapidly from 20–60 km s –1 . Using the statistical power of MaNGA, we investigate these correlations in greater detail using multiple emission lines and determine that the observed correlation of σ Hα with local star formation rate surface density is driven primarily by the global relation of increasing velocity dispersion at higher total star formation rate, as are apparent correlations with stellar mass. Assuming H ιι region models consistent with our finding that σ [O III] < σ Hα < σ [O I] , we estimate the velocity dispersion of the molecular gas in which the individual H ιι regions are embedded, finding values σ Mol = 5–30 km s –1 consistent with ALMA observations in a similar mass range. Finally, we use variations in the relation with inclination and disk azimuthal angle to constrain the velocity dispersion ellipsoid of the ionized gas σ z /σ r = 0.84 ± 0.03 and σ Φ /σ r = 0.91 ± 0.03, similar to that of young stars in the Galactic disk. Our results are most consistent with the theoretical models in which turbulence in modern galactic disks is driven primarily by star formation feedback.
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A grid of flux-constant model atmospheres for stars with effective temperatures between 3750 and 6000 K, log g between 0.75 and 3.0, and (A/H) between -3.0 and 0.0 has been constructed. The line absorption is approximated by opacity distribution functions. Metal lines and molecular lines, including those from the infrared bands of CO and CN, are taken into account. The variation of the structure of the models with metal abundance and microturbulence parameter is found to be quite regular and not very drastic. The surface cooling produced by CO is important for all the models with a maximum temperature of 5000 K, while CN mainly causes a backwarming effect but is not very important for solar CNO abundances. The effects of convection, estimated by using the mixing-length approximation, are important only for the coldest models. The models compare very well with models from overlapping regions of other grids. A solar model consistent with the grid models is found to agree satisfactorily with empirical solar model atmospheres. The careful use of scaled solar models for stars with (A/H) approximately equal to zero is justified.
The radial intensity profile of the quiet solar limb has been measured at high spatial resolution using the VLA at 4.9 GHz and the Owens Valley solar interferometer at 10.7 GHz during the partial solar eclipse of October 12, 1977. The spatial resolution (13.8 arcsec at 4.9 GHz and 7.4 arcsec at 10.7 GHz) was provided primarily by the lunar limb. Substantial limb brightening at 4.9 GHz was found with a peak brightness temperature corresponding to an 80% increase over the disk value, and a possible small limb enhancement at 10.7 GHz. The results are consistent with a simple model consisting of a uniform disk (provided by a thoroughly roughened transition zone) overlaid by a corona in hydrostatic equilibrium with a density of 5 x 10 to the 8th at its base. The lack of the secant-like variation in the microwave intensity from center to limb is explained by a corona contained in loop structures rather than in spherically symmetric layers.
A fuel-efficient cruise performance model which facilitates maximizing the specific range of General Aviation airplanes powered by spark-ignition piston engines and propellers is presented. Airplanes of fixed design only are considered. The uses and limitations of typical Pilot Operating Handbook cruise performance data, for constructing cruise performance models suitable for maximizing specific range, are first examined. These data are found to be inadequate for constructing such models. A new model of General Aviation piston-prop airplane cruise performance is then developed. This model consists of two subsystem models: the airframe-propeller-atmosphere subsystem model; and the engine-atmosphere subsystem model. The new model facilitates maximizing specific range; and by virtue of its implicity and low volume data storge requirements, appears suitable for airborne microprocessor implementation.
The validity of the Velli, Grappin and Mangeney (1989) model is evaluated. It is argued that the model is incorrect because it mixes different dynamical models, assumes weak nonlinearities, makes predictions that vary with observations, and violates causality. It is proposed that self-similar behavior in the coronal source region of the magnetohydrodynamic fluctuations cause the Kolmogorov-like spectra.
We have observed six Herbig Ae/Be stars at 50 and 100 microns with the Kuiper Airborne Observatory (KAO). All were classified as group I sources by Hillenbrand et al., signifying that their spectral energy distributions could be modeled with stars surrounded only by accretion disks. If the far-infrared emission is assumed to arise in a disk, it should be unresolved at 100 microns, regardless of the size of the disk. In contrast, we find that five out of six sources are clearly resolved at 100 microns. Three sources were also observed at 50 microns and at least two were resolved. Consequently the far-infrared emission must arise in another component, most plausibly a circumstellar envelope. This suggests that the group I sources may be less distinct from the group II sources than previously suggested. Since the presence of an envelope can affect both the actual temperature distribution in a disk and the temperature distribution derived from modeling the emission, more consistent models, including both disks and envelopes, are needed for these sources.
A fast, reliable way of predicting aerodynamic coefficients is produced using a neural network optimized by a genetic algorithm. Basic aerodynamic coefficients (e.g. lift, drag, pitching moment) are modelled as functions of angle of attack and Mach number. The neural network is first trained on a relatively rich set of data from wind tunnel tests of numerical simulations to learn an overall model. Most of the aerodynamic parameters can be well-fitted using polynomial functions. A new set of data, which can be relatively sparse, is then supplied to the network to produce a new model consistent with the previous model and the new data. Because the new model interpolates realistically between the sparse test data points, it is suitable for use in piloted simulations. The genetic algorithm is used to choose a neural network architecture to give best results, avoiding over-and under-fitting of the test data.
A continuum damage model for the prediction of damage onset and structural collapse of structures manufactured in fiber-reinforced plastic laminates is proposed. The principal damage mechanisms occurring in the longitudinal and transverse directions of a ply are represented by a damage tensor that is fixed in space. Crack closure under load reversal effects are taken into account using damage variables established as a function of the sign of the components of the stress tensor. Damage activation functions based on the LaRC04 failure criteria are used to predict the different damage mechanisms occurring at the ply level. The constitutive damage model is implemented in a finite element code. The objectivity of the numerical model is assured by regularizing the dissipated energy at a material point using Bazant's Crack Band Model. To verify the accuracy of the approach, analyses of coupon specimens were performed, and the numerical predictions were compared with experimental data.
This paper introduces a new approach to the development of equivalent models. Models of various accuracy and simulation speed may be needed in different contexts of design and analysis, or within different simulators.
In this paper, we describe the details of our numerical model for simulating ship solidbody motion in a given environment. In this model, the fully nonlinear dynamical equations governing the time-varying solid-body ship motion under the forces arising from ship wave interactions are solved with given initial conditions. The net force and moment (torque) on the ship body are directly calculated via integration of the hydrodynamic pressure over the wetted surface and the buoyancy effect from the underwater volume of the actual ship hull with a hybrid finite-difference/finite-element method. Neither empirical nor free parametrization is introduced in this model, i.e. no a priori experimental data are needed for modelling. This model is benchmarked with many experiments of various ship hulls for heave, roll and pitch motion. In addition to the benchmark cases, numerical experiments are also carried out for strongly nonlinear ship motion with a fixed heading. These new cases demonstrate clearly the importance of nonlinearities in ship motion modelling.
We describe a two year campaign of simultaneous automated meteor optical and head echo radar measurements conducted with the Middle Atmosphere Alomar Radar System (MAARSY). This campaign was established with the following goals: Compare trajectories as measured by MAARSY and the two optical stations for a range of meteoroid masses. Compare photometric and dynamic mass measured optically with radar-derived masses (inter-calibration of mass scales). Use the best observed simultaneous events to fuse all metric, photometric and ionization estimates together and apply different ablation models to self-consistently model these highest quality events.
Poor air quality is currently responsible for large impacts on human health across the world. In addition, the air pollutants ozone (O3) and particulate matter less than 2.5 µm in diameter (PM2.5) are also radiatively active in the atmosphere and can influence Earth's climate. It is important to understand the effect of air quality and climate mitigation measures over the historical period and in different future scenarios to ascertain any impacts from air pollutants on both climate and human health. The Coupled Model Intercomparison Project Phase 6 (CMIP6) presents an opportunity to analyse the change in air pollutants simulated by the current generation of climate and Earth system models that include a representation of chemistry and aerosols (particulate matter). The shared socio-economic pathways (SSPs) used within CMIP6 encompass a wide range of trajectories in precursor emissions and climate change, allowing for an improved analysis of future changes to air pollutants. Firstly, we conduct an evaluation of the available CMIP6 models against surface observations of O3 and PM2.5. CMIP6 models consistently overestimate observed surface O3 concentrations across most regions and in most seasons by up to 16 ppb, with a large diversity in simulated values over Northern Hemisphere continental regions. Conversely, observed surface PM2.5 concentrations are consistently underestimated in CMIP6 models by up to 10 µg m−3, particularly for the Northern Hemisphere winter months, with the largest model diversity near natural emission source regions. The biases in CMIP6 models when compared to observations of O3 and PM2.5 are similar to those found in previous studies. Over the historical period (1850–2014) large increases in both surface O3 and PM2.5 are simulated by the CMIP6 models across all regions, particularly over the mid to late 20th century, when anthropogenic emissions increase markedly. Large regional historical changes are simulated for both pollutants across East and South Asia with an annual mean increase of up to 40 ppb for O3 and 12 µg m−3 for PM2.5. In future scenarios containing strong air quality and climate mitigation measures (ssp126), annual mean concentrations of air pollutants are substantially reduced across all regions by up to 15 ppb for O3 and 12 µg m−3 for PM2.5. However, for scenarios that encompass weak action on mitigating climate and reducing air pollutant emissions (ssp370), annual mean increases in both surface O3 (up 10 ppb) and PM2.5 (up to 8 µg m−3) are simulated across most regions, although, for regions like North America and Europe small reductions in PM2.5 are simulated due to the regional reduction in precursor emissions in this scenario. A comparison of simulated regional changes in both surface O3 and PM2.5 from individual CMIP6 models highlights important regional differences due to the simulated interaction of aerosols, chemistry, climate and natural emission sources within models. The projection of regional air pollutant concentrations from the latest climate and Earth system models used within CMIP6 shows that the particular future trajectory of climate and air quality mitigation measures could have important consequences for regional air quality, human health and near-term climate. Differences between individual models emphasise the importance of understanding how future Earth system feedbacks influence natural emission sources, e.g. response of biogenic emissions under climate change.
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