On modelling nonlinear damping in distributed parameter systems
Information is given in viewgraph form on the modeling of nonlinear damping in distributed parameter systems.
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Information is given in viewgraph form on the modeling of nonlinear damping in distributed parameter systems.
Information is given in viewgraph form for turbulence modeling in computational fluid dynamics (CFD). The Eddy Viscosity Models (EVM), Algebraic Second Moment Closures (ASM), and Differential Second-Moment Closures (DSM) are considered. It is concluded that EVM's, ASM's, and DSM's will remain in use, though with a steady decline in importance of EVM's and ASM's in favor of DSM's. Improved versions of low-Re two-equation EVM's should lead to more reliable predictions of separated flows than are achievable at present. Further refinement of sub-models in second moment closures can be expected throughout this decade. There will be increasing attention given to interfacing SMC with higher order approaches such as LES, and an increased use of two-time-scale schemes providing distinct time scales for large and fairly small eddies.
Deriving closed-form analytical expressions for reduced-order models, and judiciously choosing the closures leading to them, has long been the strategy of choice for studying phase- and noise-induced transitions for agent-based models (ABMs). In this paper, we propose a data-driven framework that pinpoints phase transitions for an ABM—the Desai-Zwanzig model—in its mean-field limit, using a smaller number of variables than traditional closed-form models. To this end, we use the manifold learning algorithm Diffusion Maps to identify a parsimonious set of data-driven latent variables, and we show that they are in one-to-one correspondence with the expected theoretical order parameter of the ABM. We then utilize a deep learning framework to obtain a conformal reparametrization of the data-driven coordinates that facilitates, in our example, the identification of a single parameter-dependent ordinary differential equation (ODE) in these coordinates. Additionally, we identify this ODE through a residual neural network inspired by a numerical integration scheme (forward Euler). We then use the identified ODE—enabled through an odd symmetry transformation—to construct the bifurcation diagram exhibiting the phase transition.
In this paper a new three dimensional half-moment model for radiative transfer is presented for a gray medium. It describes the evolution of the zeroth and first directional half moments of the radiative intensity. The closure is provided, similarly to Dubroca and Klar, by the maximum entropy concept. This work generalizes that model to three dimensions. The model presented here (the derivation being done in Ripoll and Wray, called the M(sup 1/2)(sub 1) model, is a hyperbolic system consisting of a total of eight equations in three dimensions, four equations for each direction. Each half model has the classical form of a macroscopic moment model in which the pressure tensor is constructed from the well-known Eddington tensor with a particular Eddington factor. Moreover, different source and border terms occur. The latter introduce couplings between the macroscopic and microscopic quantities and between the + and - streams, through the intensity in the plane perpendicular to the flux. The main theoretical application of the half moment model, treated in this paper, is its reduction to a full moment model, called M(sup +)(sub 1), for the particular but important case of a hot, opaque source radiating in a cold transparent (or semi-transparent) medium for very specific applications, such as stellar interiors or atmospheres, or combustion problems. The structure of the paper is as follows. In section 2, the model M(sup 1/2)(sub 1) is presented. In section 3, for the particular case of a hot, opaque source radiating into a cold medium, the half moment model is reduced to the M(sup +)(sub 1) model. In section 4, we first solve a simple and academic problem to validate the models, followed by a simplified solar atmosphere.
This research combines Volterra theory and proper orthogonal decomposition (POD) into a hybrid methodology for reduced-order modeling of aeroelastic systems. The out-come of the method is a set of linear ordinary differential equations (ODEs) describing the modal amplitudes associated with both the structural modes and the POD basis functions for the uid. For this research, the structural modes are sine waves of varying frequency, and the Volterra-POD approach is applied to the fluid dynamics equations. The structural modes are treated as forcing terms which are impulsed as part of the uid model realization. Using this approach, structural and uid operators are coupled into a single aeroelastic operator. This coupling converts a free boundary uid problem into an initial value problem, while preserving the parameter (or parameters) of interest for sensitivity analysis. The approach is applied to an elastic panel in supersonic cross ow. The hybrid Volterra-POD approach provides a low-order uid model in state-space form. The linear uid model is tightly coupled with a nonlinear panel model using an implicit integration scheme. The resulting aeroelastic model provides correct limit-cycle oscillation prediction over a wide range of panel dynamic pressure values. Time integration of the reduced-order aeroelastic model is four orders of magnitude faster than the high-order solution procedure developed for this research using traditional uid and structural solvers.
A novel method is presented for automated real-time global aerodynamic modeling using local model networks, known as Smoothed Partitioning with Localized Trees in Real Time (SPLITR), as part of NASA’s Learn-to-Fly technology development initiative. The global nonlinear aerodynamics are partitioned into several local regions known as cells, with the dimension, location, and timing of each partition automatically selected based on a residual characterization procedure, under the constraints of real-time operation. Regression trees represent the successive partitioning of the global flight envelope and describe the evolution of the cell structure. Recursive equation-error least-squares parameter estimation in the time domain is used to estimate a model that represents the local aerodynamics in each region, so that it can be updated independently with non-contiguous data in the range of each cell over time. A weighted superposition of these piecewise local models across the flight envelope forms a global nonlinear model that also accurately captures the local aerodynamics. The SPLITR approach is demonstrated using both simulation and flight data, and the results are analyzed in terms of model predictive capabilities as well as interpretability. The results show that SPLITR can be used to automatically partition complex nonlinear aerodynamic behavior, produce an accurate model, and provide valuable physical insight into the local and global aerodynamics.
Eddington's (1926) form of wave equation for small-amplitude, radial, adiabatic stellar pulsations of spherically symmetric, gaseous stars is generalized to include the effects of axial rotation and tangled magnetic fields. Equilibrium quantities possessing dimensions are affected, and the relative importance of rotation and magnetism in affecting pulsation characteristics of the models depends on the choices of gamma and the type of model. Solutions are obtained in closed form for adiabatic pulsation periods of fine analytic stellar models, and nonadiabatic stability criteria are determined by means of the one-zone stellar model. Results are discussed for a range of physical parameters such as rotational angular momenta, central condensations, and magnetic energies; and applications are made to the case of classical Cepheids and other variable giant stars.
A comprehensive model is presented for the powerful H2O masers observed in star-forming regions. The shocks are the result of interaction of dense, high-velocity clumps with dense shells or clumps in the ambient medium. The shocked material is a thin slab in physical space, but breaks up into a network of filaments in velocity space. These filaments are the individual H2O maser features. The results of maser model calculations are presented which provide the maximum brightness temperatures that can be produced in single-temperature environments of any kind.
This poster was presented at the American Geophysical Union (AGU) 2024 Fall Conference. The poster describes the latest developments through collaboration with Carnegie Mellon University on point-source emissions impact modeling using the latest high-resolution reduced-form air pollution model, AP4.
Tabulated results of a wind-tunnel investigation of the aerodynamic loads on a canard airplane model with a single vertical tail are presented for Mach numbers from 0.70 to 2.22. The Reynolds number for the measurements was 2.9 x 10(exp 6) based on the wing mean aerodynamic chord. The results include local static pressure coefficients measured on the wing, body, and vertical tail for angles of attack from -4 deg to + 16 deg, angles of sideslip of 0 deg and 5.3 deg, vertical-tail settings of 0 deg and 5 deg, and nominal canard deflections of 0 deg and 10 deg. Also included are section force and moment coefficients obtained from integrations of the local pressures and model-component force and moment coefficients obtained from integrations of the section coefficients. Geometric details of the model and the locations of the pressure orifices are shown. An index to the data contained herein is presented and definitions of nomenclature are given.
We compute optical and infrared light curves of the pulsating class of delayed detonation models for Type Ia supernovae (SN Ia's) using an elaborate treatment of the Local Thermodynamic Equilbrium (LTE) radiation transport, equation of state and ionization balance, expansion opacity including the cooling by CO, Co(+), and SiO, and a Monte Carlo gamma-ray deposition scheme. The models have an amount of Ni-56 in the range from approximately or equal to 0.1 solar mass up to 0.7 solar mass depending on the density at which the transition from a deflagration to a detonation occurs. Models with a large nickel production give light curves comparable to those of typical Type Ia supernovae. Subluminous supernovae can be explained by models with a low nickel production. Multiband light curves are presented in comparison with the normally bright event SN 1992bc and the subluminous events Sn 1991bg and SN 1992bo to establish the principle that the delayed detonation paradigm in Chandrasekhar mass models may give a common explosion mechanism accounting for both normal and subluminous SN Ia's. Secondary IR-maxima are formed in the models of normal SN Ia's as a photospheric effect if the photospheric radius continues to increase well after maximum light. Secondary maxima appear later and stronger in models with moderate expansion velocities and with radioactive material closer to the surface. Model light curves for subluminous SN Ia's tend to show only one 'late' IR-maximum. In some delayed detonation models shell-like envelopes form, which consist of unburned carbon and oxygen. The formation of molecules in these envelopes is addressed. If the model retains a C/O-envelope and is subluminous, strong vibration bands of CO may appear, typically several weeks past maximum light. CO should be very weak or absent in normal Sn Ia's.
The UNIFI Consortium's tutorial on grid-forming (GFM) inverters provides a comprehensive guide to the modeling, control, and experimental implementation of GFM inverters. As the integration of renewable energy accelerates, the transition from traditional grid following (GFL) to GFM inverters is crucial to ensure stable and sustainable power systems. This document outlines a reference design for three-phase and single-phase GFM inverters developed at the University of Texas at Austin. The tutorial also provides step-by-step guidance for accessing and using UNIFI’s GitHub repository, enabling users to design, build, and test GFM inverters efficiently. By fostering collaboration and equipping users with accessible resources, this initiative aims to drive widespread adoption of GFM technology across academia, utilities, and industries.
A stochastic form of the snowmelt runoff model that can be used for probabilistic decision-making was developed. The use of probabilistic streamflow predictions instead of single valued deterministic predictions leads to greater accuracy in decisions. While the accuracy of the output function is important in decisionmaking, it is also important to understand the relative importance of the coefficients. Therefore, a sensitivity analysis was made for each of the coefficients.
The large, fully three-dimensional n-body programs designed for numerical experiments on the dynamics of galaxies have been used for investigations of protogalactic collapses. The dynamical aspects of galaxy formation dominate in this approach. The present experiments start from a large rotating gaseous mass that is made up of many gas clouds. The large mass collapses because it is out of equilibrium. Stars form as the collapse proceeds. The problem is formulated, limiting-case examples are described, and results from simple 'first cut' models are given. Results with no star formation are contrasted with results for very rapid star formation. All models with gas formed thin disklike structures; some were circular, while others were oval. The principal result from the simple models is that stars continue to form rapidly even after the gas has been depleted to unacceptably low levels (1% of the galactic mass in gas).
The organization of systems that learn from experience is examined, human beings and animals being prime examples of such systems. How is their information processing organized. They build an internal model of the world and base their actions on the model. The model is dynamic and predictive, and it includes the systems' own actions and their effects. In modeling such systems, a large pattern of features represents a moment of the system's experience. Some of the features are provided by the system's senses, some control the system's motors, and the rest have no immediate external significance. A sequence of such patterns then represents the system's experience over time. By storing such sequences appropriately in memory, the system builds a world model based on experience. In addition to the essential function of memory, fundamental roles are played by a sensory system that makes raw information about the world suitable for memory storage and by a motor system that affects the world. The relation of sensory and motor systems to the memory is discussed, together with how favorable actions can be learned and unfavorable actions can be avoided. Results in classical learning theory are explained in terms of the model, more advanced forms of learning are discussed, and the relevance of the model to the frame problem of robotics is examined.
Current research is demonstrating that model-checking and other forms of automated finite-state verification can be effective for checking properties of software systems. Due to the exponential costs associated with model-checking, multiple forms of abstraction are often necessary to obtain system models that are tractable for automated checking. The Bandera Tool Set provides multiple forms of automated support for compiling concurrent Java software systems to models that can be supplied to several different model-checking tools. In this paper, we describe the foundations of Bandera's data abstraction mechanism which is used to reduce the cardinality (and the program's state-space) of data domains in software to be model-checked. From a technical standpoint, the form of data abstraction used in Bandera is simple, and it is based on classical presentations of abstract interpretation. We describe the mechanisms that Bandera provides for declaring abstractions, for attaching abstractions to programs, and for generating abstracted programs and properties. The contributions of this work are the design and implementation of various forms of tool support required for effective application of data abstraction to software components written in a programming language like Java which has a rich set of linguistic features.
The polarization spectrum, or wavelength dependence of the polarization fraction, of interstellar dust emission provides important insights into the grain alignment mechanism of interstellar dust grains. We investigate the far-infrared polarization spectrum of a realistic simulated high-mass star-forming cloud under various models of grain alignment and emission. We find that neither a homogeneous grain alignment model nor a grain alignment model that includes collisional dealignment is able to produce the falling spectrum seen in observations. On the other hand, we find that a grain alignment model with grain alignment efficiency dependent on local temperature is capable of producing a falling spectrum that is in qualitative agreement with observations of OMC-1. For the model most in agreement with OMC-1, we find no correlation between the temperature and the slope of the polarization spectrum. However, we do find a positive correlation between the column density and the slope of the polarization spectrum. We suggest this latter correlation to be the result of wavelength-dependent polarization by absorption.
Zonal and tesseral harmonic coefficients for the geopotential function are usually tabulated in normalized form to provide immediate information as to the relative significance of the coefficients in the gravity model. The normalized form of the geopotential coefficients cannot be used for computational purposes unless the gravity model has been modified to receive them. This modification is usually not done because the absolute or unnormalized form of the coefficients can be obtained from the simple mathematical relationship that relates the two forms. This computation can be quite tedious for hand calculation, especially for the higher order terms, and can be costly in terms of storage and execution time for machine computation. In this report, zonal and tesseral harmonic coefficients for the geopotential function are tabulated in absolute or unnormalized form. The report is designed to be used as a ready reference for both hand and machine calculation to save the user time and effort.