Physics Model Calibration via Functional Kernel Regression and Multilevel Modeling
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A mathematical model representing a flexible space vehicle in terms of interconnected discrete masses is recast into hierarchical form to facilitate the application of multilevel control techniques. The model's state equations are temporarily decoupled by utilization of a set of coordination equations. A hierarchical form of the model is constructed with the set of coordination equations at the top of the hierarchy and the set of decoupled scalar state equations in the bottom level.
Multilevel, severely truncated, quasi-geostrophic models with damping that extend from the surface to 100 km, are used to study the stationary-wave response to orography and the concomitant feedbacks on the zonal flow. For a typical winter zonal-wind profile, it is shown that large amplitude or resonant planetary waves of intermediate zonal wavenumbers of about 4 or 5 occur with an equivalent barotropic structure. It is also shown that wave-zonal flow interaction with a mountain torque and temperature transport is stable to small perturbations on the low side of resonance and unstable on the high side of resonance. Resonant zonal wavenumbers of lower wave wavenumber also occur for the same zonal profile and have a node in the vertical with a small amplitude maximum near the surface and a larger amplitude maximum in the stratosphere. Instability depends on the presence of the orography and the basic asymmetric state as Newtonian damping and surface friction are sufficient to damp the baroclinic instability associated with a linear inviscid model.
Hybrid coordinate modeling and multilevel control techniques are applied to a prototype flexible vehicle. The original hybrid coordinate model developed for this vehicle is expressed in terms of one rigid body coordinate and two modal vibration coordinates. Multilevel control techniques of decomposition, coordination and construction of the subproblem hierarchy are applied to this model.
The dynamic analysis of complex structural systems using the finite element method and multilevel substructured models is presented. The fixed-interface method is selected for substructure reduction because of its efficiency, accuracy, and adaptability to restart and reanalysis. This method is extended to reduction of substructures which are themselves composed of reduced substructures. The implementation and performance of the method in a general purpose software system is emphasized. Solution algorithms consistent with the chosen data structures are presented. It is demonstrated that successful finite element software requires the use of software executives to supplement the algorithmic language. The complexity of the implementation of restart and reanalysis porcedures illustrates the need for executive systems to support the noncomputational aspects of the software. It is shown that significant computational efficiencies can be achieved through proper use of substructuring and reduction technbiques without sacrificing solution accuracy. The restart and reanalysis capabilities and the flexible procedures for multilevel substructured modeling gives economical yet accurate analyses of complex structural systems.
Normal aging is associated with declines in neurologic function. Uncompensated visual and vestibular problems may have dire consequences including dangerous falls. Visuo-motor plasticity is a form of behavioral neural plasticity, which is important in the process of adapting to visual or vestibular alteration, including those changes due to pathology, pharmacotherapy, surgery or even entry into microgravity or an underwater environment. To determine the effects of aging on visuo-motor plasticity, we chose the simple and easily measured paradigm of visual-motor rearrangement created by using visual displacement prisms while throwing small balls at a target. Subjects threw balls before, during and after wearing a set of prisms which displace the visual scene by twenty degrees to the right. Data obtained during adaptation were modeled using multilevel modeling techniques for 73 subjects, aged 20 to 80 years. We found no statistically significant difference in measures of visuo-motor plasticity with advancing age. Further studies are underway examining variable practice training as a potential mechanism for enhancing this form of behavioral neural plasticity.
An adiabatic global multilevel primitive equation model using a two time-level, semi-Lagrangian semi-implicit finite-difference integration scheme is presented. A Lorenz grid is used for vertical discretization and a C grid for the horizontal discretization. The momentum equation is discretized in vector form, thus avoiding problems near the poles. The 3D model equations are reduced by a linear transformation to a set of 2D elliptic equations, whose solution is found by means of an efficient direct solver. The model (with minimal physics) is integrated for 10 days starting from an initialized state derived from real data. A resolution of 16 levels in the vertical is used, with various horizontal resolutions. The model is found to be stable and efficient, and to give realistic output fields. Integrations with time steps of 10 min, 30 min, and 1 h are compared, and the differences are found to be acceptable.
This study compares two statistical models to construct summary dose-response curves for low boom community noise surveys. Data from two NASA field surveys are used that consist of multiple responses per survey participant. These data require an approach that accounts for the correlation among repeated annoyance observations from the same participant. A multilevel model accounts for the correlation by allowing estimated parameters to vary with each survey participant. On the other hand, a population average model utilizes generalized estimating equations and accounts for the correlation via a userspecified within-subject correlation structure. A visual comparison of the dose-response curves for these two methods reveals similar results. When comparing specific points along the summary curves, the multilevel model yields more precise confidence bounds than the population average model. The similarity between the summary curves derived from each model lends validity to both approaches for approximating a population representative summary curve, though modeling assumptions may lend favor to the multilevel logistic modeling approach over the population average model.
Mixed-layer models have been used to simulate low-level flows under a variety of situations, including flow over complex terrain and in the vicinity of coastal zones. The advantage of mixed-layer models compared to multilevel models is their simplicity and minimal computational requirements. A disadvantage is that the atmosphere above the mixed layer is not modeled explicitly and approximations pertaining to this layer become necessary. This paper examines five approximations for treating this upper layer for a simple sea-breeze circulation. Approximating the flow immediately above the mixed-layer height h by the mixed-layer velocity and using this velocity to advect potential temperature above h gives a better simulation of the sea breeze than the approximation used by Anthes et al. (1980), which neglected horizontal advection at this level.
This study compares two statistical modeling approaches to construct summary dose-response curves for low boom community noise surveys. NASA field survey data were used that consist of multiple responses from a survey participant. These data require an approach that accounts for the correlation among repeated annoyance observations from the same participant. A multilevel model accounts for the correlation by allowing estimated parameters to vary with each survey participant. On the other hand, a population average model utilizes generalized estimating equations and accounts for the correlation via a user-specified within-subject correlation structure. A visual comparison of the dose-response curves for these two methods reveals similar results. When comparing specific points along the summary curves, the multilevel model yields more precise confidence bounds than the population average model. The similarity between the summary curves derived from each model lends validity to both approaches for approximating a population representative summary curve.
A full approximation scheme (FAS) nonlinear multigrid solver for two-phase flow and transport problems driven by wells with multiple perforations is developed here. It is an extension to our previous work on FAS solvers for diffusion and transport problems. The solver is applicable to discrete problems defined on unstructured grids as the coarsening algorithm is aggregation-based and algebraic. To construct coarse basis that can better capture the radial flow near wells, coarse grids in which perforated well cells are not near the coarse-element interface are desired. This is achieved by an aggregation algorithm proposed in this paper that makes use of the location of well cells in the cell-connectivity graph. Numerical examples in which the FAS solver is compared against Newton's method on benchmark problems are given. In particular, for a refined version of the SAIGUP model, the FAS solver is at least 35% faster than Newton's method for time steps with a CFL number greater than 10.
The Take-Grant Protection Model has in the past been used to model multilevel security hierarchies and simple protection systems. The models are extended to include theft of rights and sharing information, and additional security policies are examined. The analysis suggests that in some cases the basic rules of the Take-Grant Protection Model should be augmented to represent the policy properly; when appropriate, such modifications are made and their efforts with respect to the policy and its Take-Grant representation are discussed.
Assessing photovoltaic module backsheet durability is critical to increasing module lifetime. Laboratory-based accelerating testing has recently failed to predict large scale failures of widely adopted polymeric materials. Additionally, there is a growing concern on characterizing the non-uniformity of field exposure. Therefore, data from field surveys are critical to assess the performance of component lifetimes. Using a documented field survey protocol, 19 field surveys were conducted. The focus of this survey strategy is to investigate spatial continuity in degradation modes. By combining field survey data with real-time satellite weather data, stressor / response models have been trained. Generalized additive Models (GAM) model was created to predict the value of degradation based on measured predictors. Two different GAM constructions were testing using different implementations of basis splines. The model includes variables on the environmental stressors of the system and the location of each measurement in the PV mounting structure. The incorporation of hierarchical structure into the models allowed for material specific degradation rates, while maintaining the assumption of a global trend. The model performed well with an adjusted R2 of 0.975 for yellowness index prediction.
Assessing photovoltaic module backsheet durability is critical to increasing module lifetime. Lab based accelerating testing has recently failed to predict large scale failures of widely adopted polymeric materials. Field surveyed data is critical to assess the performance of component lifetime. Using a documented field survey protocol, 13 field surveys where conducted. Each measurement is encoded with it's spatial location in respect to the other modules. By combining field survey data on degradation predictors with real time satellite weather data, data-driven predictive models of backsheet degradation were trained. LOESS models were constructed to investigate the spatial dependence of measurements. It was found that micro-climatic effects like treelines, ground surface changes, and elevation changes effected the magnitude and variance of the measurements. A GAM model was created to predict the value of degradation based on measured predictors. The model includes variables on the climate of the system and the location of each measurement in the PV mounting structure. The model performed well with an adj:R2 of 0:95 for yellowness index prediction. The model was cross-validated using k-folds.
The structure of opal has long fascinated scientists. It occurs in a number of structural states, ranging from amorphous to exhibiting features of stacking disorder. Opal-CT, where C and T signify cristobalite- and tridymite-like interstratification, represents an important link in the length scales between amorphous and crystalline states. However, details about local atomic (dis)order and arrangements extending to long-range stacking faults in opal polymorphs remain incompletely understood. Here, a multilevel modeling approach is reported that considers stacking states in correlation with the abundance of C and T segments as a high-level structural parameter (i.e. not each atom). Optimization accounting for inter-tetrahedral bond lengths and angles and the regularity of the silicate tetrahedra is included as lower levels of structural parameters. Together, a set of parameters with both coarse-grained and atomistic features for different levels of structural details is refined. Structural disorder at the ~10–100 Å distance scale is evaluated using experimental pair distribution function and diffraction datasets, comparing peak intensities, widths and asymmetry. Here this work presents a complete multilevel structural description of natural opal-CT and explains many of the unusual features observed in X-ray powder diffraction patterns. This modeling approach can be adopted generally for analyzing layered materials and their assembly into 3D structures.
The modular multilevel converter (MMC) is a popular topology in medium- and high-voltage applications, and many efforts have been spent on MMC modeling. However, the impact of submodule voltage sensor noise (SVSN), which becomes more severe due to increasing switching speed of power semiconductors and compact submodule design, has not been considered in conventional models. In this letter, the SVSN is introduced by coupling capacitances between the sensor and power stage in an MMC switching model. Furthermore, the SVSN impact is considered in an MMC average model based on derivation of the relationship between the SVSN and the duty cycle. Here, the proposed MMC switching model and average model considering the SVSN are validated by comparing simulations with experimental results in an MMC prototype using 10-kV SiC MOSFETS.
Background: The effect of ambient air pollution on global variations and trends in asthma prevalence is unclear. Objectives: Our goal was to investigate community-level associations between asthma prevalence data from the International Study of Asthma and Allergies in Childhood (ISAAC) and satellite-based estimates of particulate matter with aerodynamic diameter < 2.5 microm (PM2.5) and nitrogen dioxide (NO2), and modelled estimates of ozone. Methods: We assigned satellite-based estimates of PM2.5 and NO2 at a spatial resolution of 0.1deg × 0.1deg and modeled estimates of ozone at a resolution of 1deg × 1deg to 183 ISAAC centers. We used center-level prevalence of severe asthma as the outcome and multilevel models to adjust for gross national income (GNI) and center- and country-level sex, climate, and population density. We examined associations (adjusting for GNI) between air pollution and asthma prevalence over time in centers with data from ISAAC Phase One (mid-1900s) and Phase Three (2001-2003). Results: For the 13- to 14-year age group (128 centers in 28 countries), the estimated average within-country change in center-level asthma prevalence per 100 children per 10% increase in center-level PM2.5 and NO2 was -0.043 [95% confidence interval (CI): -0.139, 0.053] and 0.017 (95% CI: -0.030, 0.064) respectively. For ozone the estimated change in prevalence per parts per billion by volume was -0.116 (95% CI: -0.234, 0.001). Equivalent results for the 6- to 7-year age group (83 centers in 20 countries), though slightly different, were not significantly positive. For the 13- to 14-year age group, change in center-level asthma prevalence over time per 100 children per 10% increase in PM2.5 from Phase One to Phase Three was -0.139 (95% CI: -0.347, 0.068). The corresponding association with ozone (per ppbV) was -0.171 (95% CI: -0.275, -0.067). Conclusion: In contrast to reports from within-community studies of individuals exposed to traffic pollution, we did not find evidence of a positive association between ambient air pollution and asthma prevalence as measured at the community level.
A method is proposed for treating the lateral boundaries of a limited-area weather prediction model. The method involves the relaxation of the interior flow in the vicinity of the boundary to the external fully prescribed flow. Analytical and numerical results obtained with a linearized multilevel model confirm the effectiveness of this computationally effective method. The method is shown to give an adequate representation of outgoing gravity waves with and without an ambient shear flow and to allow the substantially undistorted transmission of geostrophically balanced flow out of the interior of the limited domain.