Formulation of Partitioned Schemes with Non-Standard Computational Models.
Abstract not provided.
SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Abstract not provided.
Explore the source record for details and available documents.
In the physics program of the CMS experiment during the CERN LHC Run 3, which started in 2022, the long-lived particle triggers have been improved and extended to expand the scope of the corresponding searches. These dedicated triggers and their performance are described in this paper, using several theoretical benchmark models that extend the standard model of particle physics. The results are based on proton-proton collision data collected with the CMS detector during 2022$-$2024 at a center-of-mass energy of 13.6 TeV, corresponding to integrated luminosities of up to 123 fb$^{-1}$.
A quantile-based approach to statistical analysis and probability modeling of data is presented which formulates statistical inference problems as functional inference problems in which the parameters to be estimated are density functions. Density estimators can be non-parametric (computed independently of model identified) or parametric-select (approximated by finite parametric models that can provide standard models whose fit can be tested). Exponential models and autoregressive models are approximating densities which can be justified as maximum entropy for respectively the entropy of a probability density and the entropy of a quantile density. Applications of these ideas are outlined to the problems of modeling: (1) univariate data; (2) bivariate data and tests for independence; and (3) two samples and likelihood ratios. It is proposed that bi-information estimation of a density function can be developed by analogy to the problem of identification of regression models.
The Bahcall-Soneira (1984) model for the distribution of stars in the Galaxy is compared with the observations reported by Gilmore, Reid, and Hewett (1984) in two directions in the sky, the pole and the Morton-Tritton (1982) region. It is shown that the Galaxy model is in good agreement with the observations everywhere it has been tested with modern data, including the magnitude range, V = 17-18, and provided that the globular cluster feature is included in the luminosity function of the field Population II stars.
Vertical modes were derived for a version of the Colorado State Regional Atmospheric Mesoscale Modeling System. The impacts of three options for dealing with the upper boundary of the model were studied. The standard model formulation holds pressure constant at a fixed altitude near the model top, and produces a fastest mode with a speed of about 90 m/sec. An alternative formulation, which allows for an external mode, could require recomputation of vertical modes for every surface elevation on the horizontal grid unless the modes are derived in a particular way. These results have bearing on the feasibility of applying vertical mode initialization to models with scaled height coordinates.
A hierarchical architecture is described which supports space station telerobots in a variety of modes. The system is divided into three hierarchies: task decomposition, world model, and sensory processing. Goals at each level of the task dedomposition heirarchy are divided both spatially and temporally into simpler commands for the next lower level. This decomposition is repreated until, at the lowest level, the drive signals to the robot actuators are generated. To accomplish its goals, task decomposition modules must often use information stored it the world model. The purpose of the sensory system is to update the world model as rapidly as possible to keep the model in registration with the physical world. The architecture of the entire control system hierarch is described and how it can be applied to space telerobot applications.
A set of solar models have been constructed, each based on a single modification to the physics of a reference solar model. In addition, a model combining several of the improvements has been calculated to provide a best solar model. Improvements were made to the nuclear reaction rates, the equation of state, the opacities, and the treatment of the atmosphere. The impact on both the structure and the frequencies of the low-l p-modes of the model to these improvements are discussed. It is found that the combined solar model, which is based on the best physics available (and does not contain any ad hoc assumptions), reproduces the observed oscillation spectrum (for low-l) within the errors associated with the uncertainties in the model physics (primarily opacities).
The paper presents the g-mode oscillation for a set of modern solar models. Each solar model is based on a single modification or improvement to the physics of a reference solar model. Improvements were made to the nuclear reaction rates, the equation of state, the opacities, and the treatment of the atmosphere. The error in the predicted g-mode periods associated with the uncertainties in the model physics is predicted and the specific sensitivities of the g-mode periods and their period spacings to the different model structures are described. In addition, these models are compared to a sample of published observations. A remarkably good agreement is found between the 'best' solar model and the observations of Hill and Gu (1990).
Stellar models with masses ranging from 05.5 to 1.3 solar mass were constructed for comparison with young cluster observations of Li and of rotation velocities. The amount of Li depletion in cool stars is sensitive to the amount of overshoot at the base of the surface convection zone, and the exact metallicity of the models. Even when this is taken into account, the Li observations are a severe constraint for the models and rule out standard models and pure diffusion models. Stellar models which include diffusion and rotational mixing in the radiative regions of stars are able to simultaneously match the Li abundances observed in the Pleiades, the UMa Group, The Hyades, Praesepe, NGC 752, and M67. They also match the observed rotation periods in the Hyades. However, these models are unable to simultaneously explain the presence of the rapidly rotating late G and K stars in the Pleiades and the absence of rapidly rotating late F and early G stars.
The response of the small scales of isotropic turbulence to periodic large scale forcing is studied using two-point closures. The frequency response of the turbulent kinetic energy and dissipation rate, and the phase shifts between production, energy and dissipation are determined as functions of Reynolds number. It is observed that the amplitude and phase of the dissipation exhibit nontrivial frequency and Reynolds number dependence that reveals a filtering effect of the energy cascade. Perturbation analysis is applied to understand this behavior which is shown to depend on distant interactions between widely separated scales of motion. Finally, the extent to which finite dimensional models (standard two-equation models and various generalizations) can reproduce the observed behavior is discussed.
Reynolds-averaged Navier-Stokes computations of a shock-wave/boundary-layer interaction (SWBLI) created by a Mach 2.85 flow over an axisymmetric 30-degree compression corner were carried out. The objectives were to evaluate four turbulence models commonly used in industry, for SWBLIs, and to evaluate the suitability of this test case for use in further turbulence model benchmarking. The Spalart-Allmaras model, Menter's Baseline and Shear Stress Transport models, and a low-Reynolds number k- model were evaluated. Results indicate that the models do not accurately predict the separation location; with the SST model predicting the separation onset too early and the other models predicting the onset too late. Overall the Spalart-Allmaras model did the best job in matching the experimental data. However there is significant room for improvement, most notably in the prediction of the turbulent shear stress. Density data showed that the simulations did not accurately predict the thermal boundary layer upstream of the SWBLI. The effect of turbulent Prandtl number and wall temperature were studied in an attempt to improve this prediction and understand their effects on the interaction. The data showed that both parameters can significantly affect the separation size and location, but did not improve the agreement with the experiment. This case proved challenging to compute and should provide a good test for future turbulence modeling work.
No abstract available
Abstract not provided.
A number of recent experiments have been able to successfully measure the parity violating asymmetry of electron-nucleus scattering and use its value to constrain the nuclear structure. The most recent of these, the Calcium Radius Experiment (CREX), finished taking data in Hall A of Jefferson Lab in 2021, and successfully extracted a neutron radius for 48Ca. While the main measurements of these experiments are parity violating, there is an increasing amount of interest in the parity conserving Beam Normal Single Spin Asymmetry (BNSSA) systematic. If not properly suppressed, the BNSSA can compete with or exceed the parity violating measurement. Recent attempts to model the contributions from standard model suppressed higher order diagrams have struggled to predict behavior of BNSSA for all nuclei. This document reports new measurements of the BNSSA at a beam energy of 2.18 GeV for 12C, 40Ca, 48Ca, and 208Pb from the CREX running period.
An initial investigation into neuron models aimed at efficient stochastic simulation of turbulent flows.
Although unique expected energy models can be generated for a given photovoltaic (PV) site, a standardized model is also needed to facilitate performance comparisons across fleets. Current standardized expected energy models for PV work well with sparse data, but they have demonstrated significant over-estimations, which impacts accurate diagnoses of field operations and maintenance issues. This research addresses this issue by using machine learning to develop a data-driven expected energy model that can more accurately generate inferences for energy production of PV systems. Irradiance and system capacity information was used from 172 sites across the United States to train a series of models using Lasso linear regression. The trained models generally perform better than the commonly used expected energy model from international standard (IEC 61724-1), with the two highest performing models ranging in model complexity from a third-order polynomial with 10 parameters (Radj2 = 0.994) to a simpler, second-order polynomial with 4 parameters (Radj2=0.993), the latter of which is subject to further evaluation. Subsequently, the trained models provide a more robust basis for identifying potential energy anomalies for operations and maintenance activities as well as informing planning-related financial assessments. We conclude with directions for future research, such as using splines to improve model continuity and better capture systems with low (≤1000 kW DC) capacity.
A summary of the constraints from searches performed by the ATLAS collaboration for the electroweak production of charginos and neutralinos is presented. Results from eight separate ATLAS searches are considered, each using 140 fb −1 of proton-proton data at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV collected at the Large Hadron Collider during its second data-taking run. The results are interpreted in the context of the 19-parameter phenomenological minimal supersymmetric standard model, where R-parity conservation is assumed and the lightest supersymmetric particle is assumed to be the lightest neutralino. Constraints from previous electroweak, flavour and dark matter related measurements are also considered. The results are presented in terms of constraints on supersymmetric particle masses and are compared with limits from simplified models. Also shown is the impact of ATLAS searches on parameters such as the dark matter relic density and the spin-dependent and spin-independent scattering cross-sections targeted by direct dark matter detection experiments. The Higgs boson and Z boson ‘funnel regions’, where a low-mass neutralino would not oversaturate the dark matter relic abundance, are almost completely excluded by the considered constraints. Example spectra for non-excluded supersymmetric models with light charginos and neutralinos are also presented.