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Results for “Generalized linear mixed models”

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.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Natural SUSY and the Higgs boson

Supersymmetry (SUSY) solves the hierarchy problem by introducing a super partner to each Standard Model(SM) particle. SUSY must be broken in nature, which means the fine-tuning is reintroduced to some level. Natural SUSY models enjoy low fine-tuning by featuring a small super potential parameter μ ~ 125 GeV, while the third generation squarks have mass less than 1.5 TeV. First and second generation sfermions can be at the multi-TeV level which yields a decoupling solution to the SUSY flavor and CP problem. However, models of Natural SUSY have difficulties in predicting a m{sub h} at 125 GeV, because the third generation is too light to give large radiative correction to the Higgs mass. The models of Radiative Natural SUSY (RNS) address this problem by allowing for high scale soft SUSY breaking Higgs mass m{sub Hu} > m{sub 0}, which leads to automatic cancellation by the Renormalization Group (RG) running effect. Coupled with the large mixing in the stop sector, RNS allows low fine-tuning at 3-10 % level and a 125 GeV SM-like Higgs. RNS can be reached at the LHC, and a linear collider. If the strong CP problem is solved by the Peccei-Quinn mechanism, then RNS accommodates mixed axion-Higgsino cold dark matter, where the Higgsino-like WIMPs, which in this case make up only a fraction of the relic abundance, can be detectable at future WIMP detectors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Structural, electronic, mechanical, and dynamical properties of graphene oxides: A first principles study

We report the results of a theoretical study on the structural, electronic, mechanical, and vibrational properties of some graphene oxide models (GDO, a-GMO, z-GMO, ep-GMO and mix-GMO) at ambient pressure. The calculations are based on the ab-initio plane-wave pseudo potential density functional theory, within the generalized gradient approximations for the exchange and correlation functional. The calculated values of lattice parameters, bulk modulus, and its first order pressure derivative are in good agreement with other reports. A linear response approach to the density functional theory is used to derive the phonon frequencies. We discuss the contribution of the phonons in the dynamical stability of graphene oxides and detailed analysis of zone centre phonon modes in all the above mentioned models. Our study demonstrates a wide range of energy gap available in the considered models of graphene oxide and hence the possibility of their use in nanodevices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2013

Mixed non-Gaussianity in multiple-DBI inflation

We study a model of multiple-field DBI inflation leading to mixed form of primordial non-Gaussianity, including equilateral and local bispectrum shapes. We present a general formalism based on the Hamilton-Jacobi approach, allowing us to go beyond slow-roll, combining the three-point function for the fields at Hubble-exit with the non-linear evolution of super-Hubble scales. We are able to obtain analytic results by taking a separable Ansatz for the Hubble rate. We find general expressions for both the equilateral and local type non-Gaussianity parameter f{sub NL}. The equilateral non-Gaussianity includes the usual enhancement for small sound speeds, but multiplied by an analytic factor which can lead to a suppression. We illustrate our results with two scenarios. In the first model, previously found to have detectable local non-Gaussianity, we find that the equilateral signal is not sufficiently suppressed to evade current observational bounds. In our second scenario we construct a model which exhibits both a detectable equilateral f{sub NL} and a negative local f{sub NL}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Magnetised Kelvin-Helmholtz instability in the intermediate regime between subsonic and supersonic regimes

The understanding of the dynamics at play at the Earth's Magnetopause, the boundary separating the Earth's magnetosphere and the solar wind plasmas, is of primary importance for space plasma modeling. We focus our attention on the low latitude flank of the magnetosphere where the velocity shear between the magnetosheath and the magnetospheric plasmas is the energetic source of Kelvin-Helmholtz instability. On the shoulder of the resulting vortex chain, different secondary instabilities are at play depending on the local plasma parameters and compete with the vortex pairing process. Most important, secondary instabilities, among other magnetic reconnection, control the plasma mixing as well as the entry of solar wind plasma in the magnetosphere. We make use of a two-fluid model, including the Hall term and the electron mass in the generalized Ohm's law, to study the 2D non-linear evolution of the Kelvin-Helmholtz instability at the magnetosheath-magnetosphere interface, in the intermediate regime between subsonic and supersonic regimes. We study the saturation mechanisms, depending on the density jump across the shear layer and the magnetic field strength in the plane. In the presence of a weak in-plane magnetic field, the dynamics of the Kelvin-Helmholtz rolled-up vortices self-consistently generates thin current sheets where reconnection instability eventually enables fast reconnection to develop. Such a system enables to study guide field multiple-island collisionless magnetic reconnection as embedded in a large-scale dynamic system, unlike the classical static, ad hoc reconnection setups. In this regime, reconnection is shown to inhibit the vortex pairing process. This study provides a clear example of nonlinear, cross-scale, collisionless plasma dynamics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Global energy balance simulations of shattered pellet injection

The dynamics of shattered pellet injection (SPI) shutdowns are simulated using a time-dependent global energy balance model, based on a modification of the KPRAD framework. The new SPI particle source in the model calculates the ablation of individual pellet fragments that enter the plasma as a temporally resolved plume, thus capturing the effects of earlier fragments on the ablation of those that follow, which has a significant impact on the overall assimilation. Despite the reduced physics and the global averaging of all quantities, results from a large number of DIII-D, KSTAR, and JET experiments are well reproduced, including the plasma cooling timescales, particle assimilation, and current quench (CQ) rates. Cooling timescales and CQ rates are in good agreement for pellets containing as little as ∼1% neon, while particle assimilations are most accurate for neon fractions above ∼15% by number of atoms. Below this, the assimilation tends to be overestimated due to the lack of radial transport in the particle balance, which becomes important in the low-Z limit. Predictive simulations of mixed-composition dual-SPI shutdowns in ITER are compared against those with the 3D non-linear magnetohydrodynamic code JOREK and are found to reproduce overall trends observed in the higher-fidelity modeling across a range of injection scenarios. The general success of the model points to the critical role of energy balance in determining SPI particle assimilation and the subsequent disruption dynamics and highlights the value of these simulations for experimental interpretation and for optimizing the deployment of computationally expensive, higher-fidelity models.

energy balance model↗
DOE OSTI2019

Reported light in the sleep environment: enhancement of the sleep diary

Light is the primary synchronizing cue for the circadian timing system, capable of exerting robust physiological effects, even with very dim and/or brief photic exposure. Mammals, including humans, are particularly susceptible to light at night. As such, measures of light in the sleeping environment are critical for evaluating sleep health. Sleep diaries provide inexpensive measures of sleep, but do not typically include light information. Four questions probing visual perception of light in the bedtime and waking environments were added to the Consensus Sleep Diary for Morning administration. As part of a lighting intervention study, 18 hospital Labor and Delivery Department personnel completed the sleep diary for 1 week in each of two experimental conditions while wearing Actiwatch devices equipped with photosensors. Diary responses were evaluated against photosensor values from the beginning and end of each rest interval (n=194 rest intervals), as well as against sleep measures, utilizing linear mixed models. Responses to light questions were related to actual light measures at bedtime, controlling for shift type and experimental condition. In addition, subjective light information at bedtime and waking was related to both objective and subjective sleep parameters, with data generally indicating poorer sleep with light in the sleeping environment. Questions addressing perception of light in the sleeping environment may provide a crude yet affordable metric of relative photic intensity. Further, as responses relate to sleep outcomes, subjective light information may yield valuable insights regarding mechanisms and outcomes of clinical significance in sleep and circadian research.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

An evaluation of mixed-mode delamination failure criteria

Many different failure criteria have been suggested for mixed mode delamination toughness, but few sets of mixed mode data exist that are consistent over the full mode I opening to mode II shear load range. The mixed mode bending (MMB) test was used to measure the delamination toughness of a brittle epoxy composite, a state of the art toughened epoxy composite, and a tough thermoplastic composite over the full mixed mode range. To gain insight into the different failure responses of the different materials, the delamination fracture surfaces were also examined. An evaluation of several failure criteria which have been reported in the literature was performed, and the range of responses modeled by each criterion was analyzed. A new bilinear failure criterion was analyzed. A new bilinear failure criterion was developed based on a change in the failure mechanism observed from the delamination surfaces. The different criteria were compared to the failure criterion. The failure response of the tough thermoplastic composite could be modeled well with the bilinear criterion but could also be modeled with the more simple linear failure criterion. Since the materials differed in their mixed mode failure response, mixed mode delamination testing will be needed to characterize a composite material. A critical evaluation is provided of the mixed mode failure criteria and should provide general guidance for selecting an appropriate criterion for other materials.

Reeder, J. R.↗
DOE OSTI2016

A Parameter Subset Selection Algorithm for Mixed-Effects Models

Mixed-effects models are commonly used to statistically model phenomena that include attributes associated with a population or general underlying mechanism as well as effects specific to individuals or components of the general mechanism. This can include individual effects associated with data from multiple experiments. However, the parameterizations used to incorporate the population and individual effects are often unidentifiable in the sense that parameters are not uniquely specified by the data. As a result, the current literature focuses on model selection, by which insensitive parameters are fixed or removed from the model. Model selection methods that employ information criteria are applicable to both linear and nonlinear mixed-effects models, but such techniques are limited in that they are computationally prohibitive for large problems due to the number of possible models that must be tested. To limit the scope of possible models for model selection via information criteria, we introduce a parameter subset selection (PSS) algorithm for mixed-effects models, which orders the parameters by their significance. In conclusion, we provide examples to verify the effectiveness of the PSS algorithm and to test the performance of mixed-effects model selection that makes use of parameter subset selection.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

An Extended MHD Study of the 16 October 2015 MMS Diffusion Region Crossing

The Magnetospheric Multiscale (MMS) mission has given us unprecedented access to high cadence particle and field data of magnetic reconnection at Earth's magnetopause. MMS first passed very near an X-line on 16 October 2015, the Burch event, and has since observed multiple X-line crossings. Subsequent 3-D particle-in-cell (PIC) modeling efforts of and comparison with the Burch event have revealed a host of novel physical insights concerning magnetic reconnection, turbulence-induced particle mixing, and secondary instabilities. In this study, we employ the Gkeyll simulation framework to study the Burch event with different classes of extended, multifluid magnetohydrodynamics (MHD), including models that incorporate important kinetic effects, such as the electron pressure tensor, with physics-based closure relations designed to capture linear Landau damping. Such fluid modeling approaches are able to capture different levels of kinetic physics in global simulations and are generally less costly than fully kinetic PIC. Herein we focus on the additional physics one can capture with increasing levels of fluid closure refinement via comparison with MMS data and existing PIC simulations. In particular, we find that the ten-moment model well captures the agyrotropic structure of the pressure tensor in the vicinity of the X-line and the magnitude of anisotropic electron heating observed in MMS and PIC simulations. However, the ten-moment model is found to have difficulty resolving the lower hybrid drift instability, which plays a fundamental role in heating and mixing electrons in the current layer.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1994

Interlaminar stress analysis of dropped-ply laminated plates and shells by a mixed method

A mixed method of approximation based on Reissner's variational principle is developed for the linear analysis of interlaminar stresses in laminated composites, with special interest in laminates that contain terminated internal plies (dropped-ply laminates). Two models are derived, one for problems of generalized plane deformation and the other for the axisymmetric response of shells of revolution. A layerwise approach is taken in which the stress field is assumed with an explicit dependence on the thickness coordinate in each layer. The dependence of the stress field on the thickness coordinate is determined such that the three-dimensional equilibrium equations are satisfied by the approximation. The solution domain is reduced to one dimension by integration through the thickness. Continuity of tractions and displacements between layers is imposed. The governing two-point boundary value problem is composed of a system of both differential and algebraic equations (DAE's) and their associated boundary conditions. Careful evaluation of the system of DAE's was required to arrive at a form that allowed application of a one-step finite difference approximation. A two-stage Gauss implicit Runge-Kutta finite difference scheme was used for the solution because of its relatively high degree of accuracy. Patch tests of the two models revealed problems with solution accuracy for the axisymmetric model of a cylindrical shell loaded by internal pressure. Parametric studies of dropped-ply laminate characteristics and their influence on the interlaminar stresses were performed using the generalized plane deformation model. Eccentricity of the middle surface of the laminate through the ply drop-off was found to have a minimal effect on the interlaminar stresses under longitudinal compression, transverse tension, and in-plane shear. A second study found the stiffness change across the ply termination to have a much greater influence on the interlaminar stresses.

Harrison, Peter N.↗
DOE OSTI2021

Efficient Automated Driving Strategies Leveraging Anticipation and Optimal Control

Automated vehicles and advanced driver assistance systems bring computation, sensing, and communication technologies that exceed human abilities in some ways. For example, automated vehicles may sense a panorama all at once, do not suffer from human impairments and distractions, and could wirelessly communicate precise data with neighboring vehicles. Prototype and commercial deployments have demonstrated the capability to relieve human operators of some driving tasks up to and including fully autonomous taxi rides in some areas. The ultimate impact of this technology’s large-scale market penetration on energy efficiency remains unclear, with potential negative factors like road use by empty vehicles competing with positive ones like automatic eco-driving. Fundamentally enabled by historic and look-ahead data, this dissertation addresses the use of automated driving and driver assistance to optimize vehicle motion for energy efficiency. Facets of this problem include car following, co-optimized acceleration and lane change planning, and collaborative multi-agent guidance. Optimal control, especially model predictive control, is used extensively to improve energy efficiency while maintaining safe and timely driving via constraints. Techniques including chance constraints and mixed integer programming help overcome uncertainty and non-convexity challenges. Extensions of these techniques to tractor trailers on sloping roads are provided by making use of linear parameter-varying models. To approach the wheel-input energy eco-driving problem over generally shaped sloping roads with the computational potential for closed-loop implementation, a linear programming formulation is constructed. Distributed and collaborative techniques that enable connected and automated vehicles to accommodate their neighbors in traffic are also explored and compared to centralized control. Using simulations and vehicle-in-the-loop car following experiments, the proposed algorithms are benchmarked against others that do not make use of look-ahead information.

Dollar, Robert Austin↗
DOE OSTI2017

An efficient MILP framework for integrating nonlinear process dynamics and control in optimal production scheduling calculations

The emphasis currently placed on enterprise-wide decision making and optimization has led to an increased need for methods of integrating nonlinear process dynamics and control information in scheduling calculations. The inevitable high dimensionality and nonlinearity of first-principles dynamic process models makes incorporating them in scheduling calculations challenging. In this work, we describe a general framework for deriving data-driven surrogate models of the closed-loop process dynamics. Focusing on Hammerstein–Wiener and finite step response (FSR) model forms, we show that these models can be (exactly) linearized and embedded in production scheduling calculations. The resulting scheduling problems are mixed-integer linear programs with a special structure, which we exploit in a novel and efficient solution strategy. A polymerization reactor case study is utilized to demonstrate the merits of this method. Finally, our framework compares favorably to existing approaches that embed dynamics in scheduling calculations, showing considerable reductions in computational effort.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1995

Energy spectrum transfer equations of solar wind turbulence

The recent studies of transfer equations for solar wind magnetohydrodynamic (MHD) turbulence are reviewed with emphasis on the comparison with the statistical observational results. Helios and Voyager missions provide an opportunity to study the the radial evolution of the power spectrum. the cross-helicity the Alfven ratio and the minimum variance direction. Spectrum transfer equations are considered as a tool to explore the nature of this radial evolution of the fluctuations. The transfer equations are derived from incompressible MHD equations. Generally one needs to make assumptions about the nature of the fluctuations and the nature of the turbulent non-linear interactions to obtain numerical results which can be compared with the observations. Some special model results for several simple cases SUCH as for structures or strong mixing. for Alfven waves with weak turbulent interactions. and for a superposition of structures and Alfven waves. are discussed. The difference between the various approaches to derive and handle the transfer equations are also addressed. Finally some theoretical description of the compressible fluctuations are also briefly reviewed.

Tu, C.-Y.↗
NASA NTRS2014

Assimilation of MODIS Snow Cover Through the Data Assimilation Research Testbed and the Community Land Model Version 4

To improve snowpack estimates in Community Land Model version 4 (CLM4), the Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover fraction (SCF) was assimilated into the Community Land Model version 4 (CLM4) via the Data Assimilation Research Testbed (DART). The interface between CLM4 and DART is a flexible, extensible approach to land surface data assimilation. This data assimilation system has a large ensemble (80-member) atmospheric forcing that facilitates ensemble-based land data assimilation. We use 40 randomly chosen forcing members to drive 40 CLM members as a compromise between computational cost and the data assimilation performance. The localization distance, a parameter in DART, was tuned to optimize the data assimilation performance at the global scale. Snow water equivalent (SWE) and snow depth are adjusted via the ensemble adjustment Kalman filter, particularly in regions with large SCF variability. The root-mean-square error of the forecast SCF against MODIS SCF is largely reduced. In DJF (December-January-February), the discrepancy between MODIS and CLM4 is broadly ameliorated in the lower-middle latitudes (2345N). Only minimal modifications are made in the higher-middle (4566N) and high latitudes, part of which is due to the agreement between model and observation when snow cover is nearly 100. In some regions it also reveals that CLM4-modeled snow cover lacks heterogeneous features compared to MODIS. In MAM (March-April-May), adjustments to snowmove poleward mainly due to the northward movement of the snowline (i.e., where largest SCF uncertainty is and SCF assimilation has the greatest impact). The effectiveness of data assimilation also varies with vegetation types, with mixed performance over forest regions and consistently good performance over grass, which can partly be explained by the linearity of the relationship between SCF and SWE in the model ensembles. The updated snow depth was compared to the Canadian Meteorological Center (CMC) data. Differences between CMC and CLM4 are generally reduced in densely monitored regions.

data assimilation↗
DOE OSTI2023

Combining Sparse Approximate Factorizations with Mixed-precision Iterative Refinement

The standard LU factorization-based solution process for linear systems can be enhanced in speed or accuracy by employing mixed-precision iterative refinement. Most recent work has focused on dense systems. We investigate the potential of mixed-precision iterative refinement to enhance methods for sparse systems based on approximate sparse factorizations. In doing so, we first develop a new error analysis for LU- and GMRES-based iterative refinement under a general model of LU factorization that accounts for the approximation methods typically used by modern sparse solvers, such as low-rank approximations or relaxed pivoting strategies. We then provide a detailed performance analysis of both the execution time and memory consumption of different algorithms, based on a selected set of iterative refinement variants and approximate sparse factorizations. Our performance study uses the multifrontal solver MUMPS, which can exploit block low-rank factorization and static pivoting. We evaluate the performance of the algorithms on large, sparse problems coming from a variety of real-life and industrial applications showing that mixed-precision iterative refinement combined with approximate sparse factorization can lead to considerable reductions of both the time and memory consumption.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

An analytic approach to quasinormal modes for coupled linear systems

Quasinormal modes describe the ringdown of compact objects deformed by small perturbations. In generic theories of gravity that extend General Relativity, the linearized dynamics of these perturbations is described by a system of coupled linear differential equations of second order. We first show, under general assumptions, that such a system can be brought to a Schrödinger-like form. We then devise an analytic approximation scheme to compute the spectrum of quasinormal modes. We validate our approach using a toy model with a controllable mixing parameter ε and showing that the analytic approximation for the fundamental mode agrees with the numerical computation when the approximation is justified. The accuracy of the analytic approximation is at the (sub-) percent level for the real part and at the level of a few percent for the imaginary part, even when ε is of order one. Our approximation scheme can be seen as an extension of the approach of Schutz and Will [1] to the case of coupled systems of equations, although our approach is not phrased in terms of a WKB analysis, and offers a new viewpoint even in the case of a single equation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

HEMS: Home Energy Management System [SWR-15-12] - Stochastic Optimal Scheduling of Residential Appliances with Renewable Energy Sources

The HEMS algorithm schedules residential appliance operation to minimize the weighted sum of occupant discomfort, total energy cost, peak electricity consumption and carbon footprint, weighted according to occupant preferences. A centralized mixed integer linear programming (MILP) based optimization approach is taken, with the HEMS managing all appliances directly, following a Model Predictive Control (MPC) methodology which determines the optimal schedule over the user-specified scheduling horizon and repeats the optimization at configurable time intervals. The HEMS is developed on the General Algebraic Modeling System (GAMS) using the MILP solver. This system is able to effectively deal with the stochasticity in the distributed system by utilizing Monte Carlo simulation where uncertainties in future electricity price, outdoor temperature, water usage, solar and wind generation can be accounted for. The HEMS controls the operation of the heating, ventilation and air conditioning (HVAC) system, water heater, refrigerator, residential batteries, electric vehicles, standalone micro combined heat and power (CHP) generator, dishwasher, washer/dryer, pool pumps, and lighting.

Pratt, Annabelle↗
DOE OSTI2019

Impact of ethanol blending into gasoline on aromatic compound evaporation and particle emissions from a gasoline direct injection engine

This study examined the interactions of ethanol with aromatic compounds on aromatic species evolution during gasoline evaporation and the consequent impacts on particle emissions from a single-cylinder, gasoline direct injection engine. From a chemical kinetic standpoint, the dilution of the aromatic species in gasoline by ethanol blending should reduce particle emissions because aromatics are the primary species that form particles during gasoline combustion. However, increased evaporative cooling from the ethanol and ethanol's effect on when aromatics in the fuel droplet (or surface film or pool) evaporate can drive an increase in particle emissions. The objective of this study was to quantify these competing effects. The results show that a combination of ethanol's increased evaporative cooling and impact on aromatic compound vapor-liquid equilibrium can extend droplet lifetime and cause aromatics to evaporate later in the droplet evaporation process than would be the case without ethanol. When fuels were burned in a direct-injection single-cylinder engine at high speed (2500 rpm) and relatively high load, ethanol blending caused an increase in particle emissions for fuels containing a low vapor pressure aromatic. At a lower speed (1500 rpm), no statistically significant increase in particle emissions was observed, likely because more time was available for evaporation and mixing to occur. In contrast, particle emissions from a fuel blended with a high vapor pressure aromatic were either insensitive to or reduced by ethanol blending, likewise to engine operating conditions. Current models for predicting particle emissions from gasoline engines, such as particulate matter index (PMI), generally lack variables for non-linear interactions between ethanol and gasoline hydrocarbons. To identify nonlinear interactions between predictor variables that might better explain the observed particle emissions, the least absolute shrinkage and selection operator (LASSO) regularized regression approach was employed. Among the predictor variables evaluated was the Yield Sooting Index (YSI) which is as an improved measure to quantify the aromatic's chemical tendency to generate particle emissions. Following this analysis, two variables were selected based on their frequent appearance. The first was ethanol mole percent multiplied by aromatic mole percent divided by aromatic vapor pressure [(EtOH * Aro%)/Aro VP@443 K]. The second was aromatic mole percent multiplied by aromatic YSI divided by aromatic molecular weight [(Aro% * Aro YSI)/Aro MW]. The results of linear regression including only these two combined explanatory variables achieved an r 2 = 0.959, substantially improved over the PMI model (r 2 = 0.688) and provides insight into how the PMI formalism might be modified to account for non-linear oxygenate-hydrocarbon coupling.

09 BIOMASS FUELS↗