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Small amplitude nonlinear longitudinal plasma oscillations perturbation analysis, discussing Landau damping, monochromatic wave evolution and independent variable expansion
An investigation of approach and landing longitudinal flying qualities, based on data generated using a variable stability NT-33 aircraft combined with significant control system dynamics is described. An optimum pilot lead time for pitch tracking, flight path angle tracking, and combined pitch and flight path angle tracking tasks is determined from a closed loop simulation using integral squared error (ISE) as a performance measure. Pilot gain and lead time were varied in the closed loop simulation of the pilot and aircraft to obtain the best performance for different control system configurations. The results lead to the selection of an optimum lead time using ISE as a performance criterion. Using this value of optimum lead time, a correlation is then found between pilot rating and performance with changes in the control system and in the aircraft dynamics. It is also shown that pilot rating is closely related to pilot workload which, in turn, is related to the amount of lead which the pilot must generate to obtain satisfactory response. The results also indicate that the pilot may use pitch angle tracking for the approach task and then add flight path angle tracking for the flare and touchdown.
Meridional oscillation modes in a global, primitive-equation coupled ocean-atmosphere model have been analyzed in order to determine whether they contain such meridionally propagating modes as surface-pressure perturbations with years-to-decades oscillation periods. A two-layer global ocean model and a two-level global atmosphere model were then formulated. For realistic parameter values and basic states, meridional modes oscillating at periods of several years to several decades are noted to be present in the coupled ocean-atmosphere model; the oscillation periods, travel times, and meridional structures of surface pressure perturbations in one of the modes are found to be comparable to the corresponding characteristics of observed sea-level pressure perturbations.
Hydro power is one of the most flexible sources of electricity production. Power systems with considerable amounts of flexible hydro power potentially offer easier integration of variable generation, e.g., wind and solar. However, there exist operational constraints to ensure mid-/long-term security of supply while keeping river flows and reservoirs levels within permitted limits. In order to properly assess the effective available hydro power flexibility and its value for storage, a detailed assessment of hydro power is essential. Due to the inherent uncertainty of the weather-dependent hydrological cycle, regulation constraints on the hydro system, and uncertainty of internal load as well as variable generation (wind and solar), this assessment is complex. Hence, it requires proper modeling of all the underlying interactions between hydro power and the power system, with a large share of other variable renewables. A summary of existing experience of wind integration in hydro-dominated power systems clearly points to strict simulation methodologies. Recommendations include requirements for techno-economic models to correctly assess strategies for hydro power and pumped storage dispatch. These models are based not only on seasonal water inflow variations but also on variable generation, and all these are in time horizons from very short term up to multiple years, depending on the studied system. Another important recommendation is to include a geographically detailed description of hydro power systems, rivers' flows, and reservoirs as well as grid topology and congestion.
Recent observational studies have shown that satellite retrievals of cloud optical depth based on plane-parallel model theory suffer from systematic biases that depend on viewing geometry, even when observations are restricted to overcast marine stratus layers, arguably the closest to plane parallel in nature. At moderate to low sun elevations, the plane-parallel model significantly overestimates the reflectance dependence on view angle in the forward-scattering direction but shows a similar dependence in the backscattering direction. Theoretical simulations are performed that show that the likely cause for this discrepancy is because the plane-parallel model assumption does not account for subpixel, scale variations in cloud-top height (i.e., "cloud bumps"). Monte Carlo simulation, comparing ID model radiances to radiances from overcast cloud field with 1) cloud-top height variation, but constant cloud volume extinction; 2) flat tops but horizontal variations in cloud volume extinction; and 3) variations in both cloud top height and cloud extinction are performed over a approximately equal to 4 km x 4 km domain (roughly the size of an individual GAC AVHRR pixel). The comparisons show that when cloud-top height variations are included, departures from 1D theory are remarkably similar (qualitatively) to those obtained observationally. In contrast, when clouds are assumed flat and only cloud extinction is variable, reflectance differences are much smaller and do not show any view-angle dependence. When both cloud-top height and cloud extinction variations are included, however, large increases in cloud extinction variability can enhance reflectance difference. The reason 3D-1D reflectance differences are more sensitive to cloud-top height variations in the forward-scattering direction (at moderate to low, sun elevations) is because photons leaving the cloud field in that direction experience fewer scattering events (low-order scattering) and are restricted to the topmost portions of the cloud. While reflectance deviations from 1D theory are much larger for bumpy clouds than for flat clouds with variable cloud extinction, differences in cloud albedo are comparable for these two cases.
The future discoveries in the field of High Energy Physics are led by the development of new types of accelerators. Around the world, there are a lot of researchers that are studying some possible designs for the future accelerators and some of them are considering the use of alternating current inside the superconducting magnets in order to have better efficiency. The work described in this report tries to compare some superconducting magnets made of different materials and to understand which one of them can be considered for its better performance working in a variable magnetic field. For this goal, becomes really important to control the temperature of the coil, and, as visible in the next chapter, to relate this parameter to the frequency of the magnetic field, in order to find, as will be named, the critical frequency .
High resolution numerical simulation can provide insight into important physical processes that occur within the planetary boundary layer (PBL). The present work employs large eddy simulation (LES) nested within the Weather Forecasting and Research (WRF) framework to simulate real conditions in the convective PBL over an area of complex terrain. A multiple nesting approach has been used to downsize the grid spacing size from 12.15 km (mesoscale) to 0.03 km (LES). To minimize artifacts in theWRF-LES solutions resulting from using an inappropriate grid spacing on the WRF-Meso domain, a careful selection of grid spacing has been conducted. The WRF-LES results have been evaluated with in situ and remote sensing observations collected during the US Department of Energy supported Columbia BasinWind Energy Study (CBWES). The comparison for the first and second order moments, turbulence spectrum, and probability density function (pdf) of wind speed show good agreement between the simulation and data. Furthermore, the WRF-LES variables show a great deal of variability in space and time caused by the complex topography in the LES domain. The WRF-LES results show that the flow structures, such as roll vortices and convective cells, over the domain vary depending on both the spatial location and time of the day. In addition to basic studies related to boundary-layer meteorology, results from these simulations can be used in other applications, such as studying the wind energy resources.
A common approach to regulating electricity is through auction-based competitive wholesale markets. The goal of this approach is to provide a reliable supply of power at the lowest reasonable cost to the consumer. This necessitates market structures and operating rules that ensure revenue sufficiency for all generators needed for resource adequacy purposes. Wholesale electricity markets employ marginal-cost pricing to provide cost-effective dispatch such that resources are compensated for their operational costs. However, marginal-cost pricing alone cannot guarantee cost recovery outside of perfect competition, and electricity markets have at least six attributes that preclude them from functioning as perfectly competitive markets. These attributes include market power, externalities, public good attributes, lack of storage, wholesale price caps, and ineffective demand curve. Until (and unless) these failures are ameliorated, some form of corrective action(s) will be necessary to improve market efficiency so that prices can correctly reflect the needed level of system reliability. Many of these options necessarily involve some form of administrative or out-of-market actions, such as scarcity pricing, capacity payments, bilateral or other out-of-market contracts, or some hybrid combination. A key focus with these options is to create a connection between the electricity market and long-term reliability/loss-of-load expectation targets, which are inherently disconnected in the native markets because of the aforementioned market failures. The addition of variable generation resources can exacerbate revenue sufficiency and resource adequacy concerns caused by these underlying market failures. Because variable generation resources have near-zero marginal costs, they effectively suppress energy prices and reduce the capacity factors of conventional generators through the merit-order effect in the simplest case of a convex market; non-convexities can also suppress prices.
Significance The generalized Langevin equation (GLE) provides a precise description of coarse-grained variable dynamics in reduced dimension models. However, computation of the memory kernel poses a major challenge to the practical use of the GLE. This paper presents a data-driven approach to compute the memory kernel, relying on a hierarchy of parameterized rational approximations in terms of the Laplace transform, which can be expanded to arbitrarily high order as necessary. This parameterization makes it convenient to represent the GLE via an extended stochastic model where the memory term is eliminated by properly introducing auxiliary variables. The present method is well-suited for constructing reduced models for nonequilibrium properties of complex systems such as biomolecules, chemical reaction networks, and climate simulations.
Nanocomp Technologies, Inc. is working with Oak Ridge National Laboratory to develop carbon nanotube (CNT) composite materials and evaluate their use in additive manufacturing (3D printing). The first phase demonstrated feasibility and improvements for carbon nanotube (CNT)- acrylonitrile butadiene styrene (ABS) composite filaments use in additive manufacturing, with potential future work centering on further improvements. By focusing the initial phase on standard processing methods (developed mainly for the incorporation of carbon fibers in ABS) and characterization techniques, a basis of knowledge for the incorporation of CNTs in ABS was learned. The ability to understand the various processing variables is critical to the successful development of these composites. From the degradation effects on ABS (caused by excessive temperatures), to the length of time the ABS is in the melt state, to the order of addition of constituents, and also to the many possible mixing approaches, a workable flow sequence that addresses each processing step is critical to the final material properties. Although this initial phase could not deal with each of these variables in-depth, a future study is recommended that will build on the lessons learned for this effort.
Abstract While the hyporheic zone (HZ) accounts for a significant portion of whole stream CO 2 concentrations, HZ respiration modeling studies are lacking in quantifying their contributions to the total CO 2 at large watershed/basin scales. Quantifying the contribution of anaerobic respiration is also underappreciated. This study used a carbon‐nitrogen‐coupled river corridor model to quantify HZ aerobic and anaerobic respiration and determined the key factors controlling their spatial variability within the Columbia River Basin (CRB). The modeled respiration patterns showed high spatial variability. Among the nine sub‐basins composing the CRB, the Lower Columbia and the Willamette, which receive higher precipitation, had higher respiration. Medium‐sized rivers (fourth to sixth orders) produced the highest aerobic and anaerobic respiration among reaches of different sizes. At the basin scale, aerobic respiration is dominant, representing approximately 98.7% of the total respiration across the CRB. While most of the reaches were dominant with aerobic respiration, reaches in agricultural land showed a relatively higher anaerobic respiration (18%) ratio. A variable importance analysis showed that hyporheic exchange flux controlled most of the spatial variability of HZ respiration, dominating over other physical variables such as residence time, stream dissolved organic carbon (DOC), nitrate, and dissolved oxygen (DO). The influence of substrate concentration (DOC and DO) is larger in modeling anaerobic respiration than aerobic respiration. Future efforts will focus on improving the estimation of the HZ exchange flux and the implementation of spatially explicit parameterizations for the reactions of interest to reduce model uncertainty.
Using elemental abundances determined by SPIRIT APX spectrometer on rocks and soils at Gusev Plains and Columbia Hills/ West Spur regions, the Athena Team discussed the aqueous geochemical implications at these sites on Mars. They suggested that these rocks were exposed to variable degrees of aqueous alteration (low to high) at Gusev crater. Earlier, we developed analytical procedures for studying aqueous geochemical behavior of fluids on rocks at Meridiani. In the present study, we apply these methods to rocks at Columbia Hills/West Spur in order to understand the significance of the Gusev rock results in reference to aqueous geochemical processes on Mars . The data analysis procedure is based on treating SO3 ("a") and Cl ("b") as two variables and tracking the relationship between "a" and "b" when the fluids undergo evaporation. This process of evaporation leads to concentration changes in these two elements finally producing salt assemblages on Martian rocks. In some cases on plotting "a"/ "b" versus "b" in salt assemblages, they yield a hyperbolic distribution. The relationship is transformed into a straight line when "a"/"b" is again plotted against 1/"b" in the system. Earlier, we used this procedure in the case of Merdiani rock abrasion tool (RAT) rocks and in this study, we discuss the application of this procedure to Gusev rocks. This study shows that the Gusev Plains rocks were exposed to low SO3/Cl solutions (sulfate-poor) for short period of time (weak interaction), whereas solutions with high SO3/Cl ratios (sulfate-rich) seem to have pervasively interacted with Columbia Hills/ West Spur rocks (strong interaction) at Gusev crater. Our conclusions seem to be consistent with the Mossbauer results given for these rocks
In this paper, we report progress in the development of economically high-order flux-solution-reconstruction (FSR) schemes, which are second-order accurate on general unstructured grids but achieve high-order accuracy when a grid is regular, i.e., has the same stencil (with the same spacing) throughout the domain. Two variants of the FSR schemes are discussed: chain-rule-flux-solution reconstruction (CFSR) and quadratic-form-flux-solution reconstruction (QFSR), where the former is based on the chain rule and the latter on the flux reconstruction expressed as a function of solution variables. These schemes are tested for flows with shock waves with a limiter incorporated in the flux and solution reconstructions. Improved results, compared with second-order methods are demonstrated for inviscid and viscous flows with smooth grids.
We present 11 yr of high-resolution, spectroscopic observations for the star EM Cep. EM Cep switches between B and Be star states, as revealed by the level of Hα emission, but spends most of its time in the B star state. EM Cep has been considered to be an eclipsing, near-contact binary of nearly equal-mass B stars in order to reproduce regular photometric variations; however, this model is problematic due to the lack of any observed Doppler shift in the spectrum. Our observations confirm that there are no apparent Doppler shifts in the wide spectral lines Hα and He i λ6678 in either the B or Be star states. The profiles of He i λ6678 typically exhibited a filled-in absorption core, but we detected weak emission in this line during the highest Be state. Given the lack of observed Doppler shifts, we model EM Cep as an isolated Be star with a variable circumstellar disk. We can reproduce the observed Hα emission profiles over the 11 yr period reasonably well with disk masses on the order of 3--10× 10{sup −11} M{sub ∗} in the Be state with the circumstellar disk seen at an inclination of 78° to the line of sight. From a disk ejection episode in 2014, we estimate a mass-loss rate of ≈3×10{sup −9} M{sub ⊙} yr{sup −1}. The derived disk density parameters are typical of those found for the classical Be stars. We therefore suggest that the EM Cep is a classical Be star and that its photometric variations are the result of β Cep or nonradial pulsations.
Development of HPF versions of NPB and ARC3D showed that HPF has potential to be a high level language for parallelization of CFD applications. The use of HPF requires an intimate knowledge of the applications and a detailed analysis of data affinity, data movement and data granularity. Since HPF hides data movement from the user even with this knowledge it is easy to overlook pieces of the code causing low performance of the application. In order to simplify and accelerate the task of developing HPF versions of existing CFD applications we have designed and partially implemented ADAPT (Automatic Data Distribution and Placement Tool). The ADAPT analyzes a CFD application working on a single structured grid and generates HPF TEMPLATE, (RE)DISTRIBUTION, ALIGNMENT and INDEPENDENT directives. The directives can be generated on the nest level, subroutine level, application level or inter application level. ADAPT is designed to annotate existing CFD FORTRAN application performing computations on single or multiple grids. On each grid the application can considered as a sequence of operators each applied to a set of variables defined in a particular grid domain. The operators can be classified as implicit, having data dependences, and explicit, without data dependences. In order to parallelize an explicit operator it is sufficient to create a template for the domain of the operator, align arrays used in the operator with the template, distribute the template, and declare the loops over the distributed dimensions as INDEPENDENT. In order to parallelize an implicit operator, the distribution of the operator's domain should be consistent with the operator's dependences. Any dependence between sections distributed on different processors would preclude parallelization if compiler does not have an ability to pipeline computations. If a data distribution is "orthogonal" to the dependences of an implicit operator then the loop which implements the operator can be declared as INDEPENDENT.
Uncertainty propagation in complex engineering systems often poses significant computational challenges related to modeling and quantifying probability distributions of model outputs, as those emerge as the result of various sources of uncertainty that are inherent in the system under investigation. Gaussian Processes regression (GPs) is a robust meta-modeling technique that allows for fast model prediction and exploration of response surfaces. Multi-fidelity variations of GPs further leverage information from cheap and low fidelity model simulations in order to improve their predictive performance on the high fidelity model. In order to cope with the high volume of data required to train GPs in high dimensional design spaces, a common practice is to introduce latent design variables that are typically projections of the original input space to a lower dimensional subspace, and therefore substitute the problem of learning the initial high dimensional mapping, with that of training a GP on a low dimensional space. Here in this paper, we present a Bayesian approach to identify optimal transformations that map the input points to low dimensional latent variables. The \projection" mapping consists of an orthonormal matrix that is considered a priori unknown and needs to be inferred jointly with the GP parameters, conditioned on the available training data. The proposed Bayesian inference scheme relies on a two-step iterative algorithm that samples from the marginal posteriors of the GP parameters and the projection matrix respectively, both using Markov Chain Monte Carlo (MCMC) sampling. In order to take into account the orthogonality constraints imposed on the orthonormal projection matrix, a Geodesic Monte Carlo sampling algorithm is employed, that is suitable for exploiting probability measures on manifolds. We extend the proposed framework to multi-fidelity models using GPs including the scenarios of training multiple outputs together. We validate our framework on three synthetic problems with a known lower-dimensional subspace. The benefits of our proposed framework, are illustrated on the computationally challenging aerodynamic optimization of a last-stage blade for an industrial gas turbine, where we study the effect of an 85-dimensional shape parameterization of a three-dimensional airfoil on two output quantities of interest, specifically on the aerodynamic efficiency and the degree of reaction
Coupling generator current to electron-beam loads and dynamic-inductance loads (z pinches) is greatly improved with low-inductance vacuum transmission lines. Typically, magnetically insulated transmission lines (MITLs) utilize nearly constant impedance geometries where the minimum impedance (anode-cathode gap) is limited by electron loss during the setup of magnetic insulation. Constant-impedance MITL designs are not optimized for low inductance (Zτ) when given a constraint on vacuum electron flow. We describe the design and the modeling of MITLs that have a nonconstant impedance. The baseline variable-impedance MITL designs are based on equilibrium vacuum-electron flow models [1] that are incorporated into the Screamer circuit code [2]. Such designs satisfy the MITL limits in the areal density of the loss current and have magnetically insulated flow that is stable everywhere along the MITL. Different MITL designs are then modeled analytically and with a 2-D particle-in-cell computer code in order to quantify subtle electron losses driven by changes to the vacuum impedance as a function of distance along the transmission line. We present a variable-impedance MITL design that delivers more current with a lower inductance than found in constant-impedance MITL designs.
Here, air ingress measurements using the 1/20th-scaled Helium Air Ingress gas Reactor Experiment (HAIRE) facility show key geometric variables of interest and their effect on air ingress in small- and medium-sized breaks in High Temperature Gas cooled Reactors. These variables include but are not limited to break diameter, break angle, and break wall thickness. Differing wall thicknesses for the same break diameter can have order-of-magnitude changes to the air ingress rate, which is a key figure of merit in the air ingress accident scenario. Additionally, different break sizes can change the importance of the angle in the break scenario. With smaller breaks, the flow will not transition from intermittent flow, to countercurrent flow, to diffusive flow as the break rotates from vertically upward toward vertically downward. This would lead to less variability with smaller breaks, which in turn would make the accident scenario more predictable for smaller-sized breaks.