Spectrophotometry with a transmission grating for detecting faint occultations

High-precision spectrophotometry is highly desirable in detecting and characterizing close-in extrasolar planets to learn about their makeup and temperature. For such a goal, a modest-size telescope with a simple low-resolution spectroscopic instrument is potentially as good or better than a complex general purpose spectrograph since calibration and removal of systematic errors is expected to dominate. We use a transmission grating placed in front of an imaging CCD camera on Steward Observatory's Kuiper 1.5 m telescope to provide a high signal-to-noise, low dispersion visible spectrum of the star HD 209458. We attempt to detect the reflected light signal from the extra-solar planet HD 209458b by differencing the signal just before and after secondary occultation. We present a simple data reduction method and explore the limits of ground based low-dispersion spectrophotometry with a diffraction grating. Reflected light detection levels of 0.1% are achievable for 5000-7000A, too coarse for useful limits on ESPs but potentially useful for determining spectra of short-period binary systems with large (Delta m_vis=6) brightness ratios. Limits on the precison are set by variations in atmospheric seeing in the low-resolution spectrum. Calibration of this effect can be carried out by measurement of atmospheric parameters from the observations themselves, which may allow the precision to be limited by the noise due to photon statistics and atmospheric scintillation effects.Comment: 34 pages and 17 figures. Accepted for publication in PAS

Energy-aware dynamic pricing model for cloud environments

Energy consumption is a critical operational cost for Cloud providers. However, as commercial providers typically use fixed pricing schemes that are oblivious about the energy costs of running virtual machines, clients are not charged according to their actual energy impact. Some works have proposed energy-aware cost models that are able to capture each client’s real energy usage. However, those models cannot be naturally used for pricing Cloud services, as the energy cost is calculated after the termination of the service, and it depends on decisions taken by the provider, such as the actual placement of the client’s virtual machines. For those reasons, a client cannot estimate in advance how much it will pay. This paper presents a pricing model for virtualized Cloud providers that dynamically derives the energy costs per allocation unit and per work unit for each time period. They account for the energy costs of the provider’s static and dynamic energy consumption by sharing out them according to the virtual resource allocation and the real resource usage of running virtual machines for the corresponding time period. Newly arrived clients during that period can use these costs as a baseline to calculate their expenses in advance as a function of the number of requested allocation and work units. Our results show that providers can get comparable revenue to traditional pricing schemes, while offering to the clients more proportional prices than fixed-price models.Peer ReviewedPostprint (author's final draft

Empirical evaluation of the eccentric orifice in small diameter pipes

This investigation has taken different orifice sizes (0.3005 , 0.4000 , 0.5045 , 0.6015 ) and tested their flow characteristics when used in a 1 diameter pipe. Each orifice was initially placed in a fully eccentric position, that is the circumference of the orifice was placed tangent to the inside circumference of the pipe. Data was taken with the orifice eccentric to concentric in increments of 0.050 . Plots of flow coefficient versus Reynold\u27s number were made for each position of the four orifices tested. Empirical equations were developed for determining the flow coefficient of the various orifice sizes placed in any eccentric position. It was also shown that the region near the fully eccentric position was just as stable as the region near the concentric position and is thus very capable of producing accurate flow measurement --Abstract, page ii

From non-symmetric particle systems to non-linear PDEs on fractals

We present new results and challenges in obtaining hydrodynamic limits for non-symmetric (weakly asymmetric) particle systems (exclusion processes on pre-fractal graphs) converging to a non-linear heat equation. We discuss a joint density-current law of large numbers and a corresponding large deviations principle.Comment: v2: 10 pages, 1 figure. To appear in the proceedings for the 2016 conference "Stochastic Partial Differential Equations & Related Fields" in honor of Michael R\"ockner's 60th birthday, Bielefel

Sensitivity of point scale runoff predictions to rainfall resolution

International audienceThis paper investigates the effects of using non-linear, high resolution rainfall, compared to time averaged rainfall on the triggering of hydrologic thresholds and therefore model predictions of infiltration excess and saturation excess runoff. The bounded random cascade model, parameterized to south western Australian rainfall, was used to scale rainfall intensities at various time resolutions ranging from 1.875 min to 2 h. A one dimensional, conceptual rainfall partitioning model was used that instantaneously partitions water into infiltration excess, infiltration, storage, deep drainage, saturation excess and surface runoff, where the fluxes into and out of the soil store are controlled by thresholds. For example, saturation excess is triggered when the soil water content reaches the storage capacity threshold. The results of the numerical modelling were scaled by relating soil infiltration properties to soil draining properties, and inturn, relating these to average storm intensities. By relating maximum soil infiltration capacities to saturated drainage rates (f*), we were able to split soils into two groups; those where all runoff is a result of infiltration excess alone (f*?0.2) and those susceptible to both infiltration excess and saturation excess runoff (f*>0.2). For all soil types, we related maximum infiltration capacities to average storm intensities (k*) and were able to show where model predictions of infiltration excess were most sensitive to rainfall resolution (ln k=0.4) and where using time averaged rainfall data can lead to an under prediction of infiltration excess and an over prediction of the amount of water entering the soil (ln k*>2). For soils susceptible to both infiltration excess and saturation excess, total runoff sensitivity was scaled by relating saturated drainage rates to average storm intensities (g*) and parameter ranges where predicted runoff was dominated by infiltration excess or saturation excess depending on the resolution of rainfall data was determined (ln g*<2). Infiltration excess predicted from high resolution rainfall is short and intense, whereas saturation excess produced from low resolution rainfall is more constant and less intense. This has important implications for the accuracy of current hydrological models that use time averaged rainfall under these soil and rainfall conditions and predictions of further thresholds such as erosion. It offers insight into areas where the understanding of the dynamics of high resolution rainfall is required and a means by which we can improve our understanding of the way variations in rainfall intensities within a storm relate to hydrological thresholds and model predictions

Ground-Penetrating-Radar Reflection Attenuation Tomography with an Adaptive Mesh

Ground-penetrating radar (GPR) attenuation-difference analysis can be a useful tool for studying fluid transport in the subsurface. Surface-based reflection attenuation-difference tomography poses a number of challenges that are not faced by crosshole attenuation surveys. We create and analyze a synthetic attenuation-difference GPR data set to determine methods for processing amplitude changes and inverting for conductivity differences from reflection data sets. Instead of using a traditional grid-based inversion, we use a data-driven adaptive-meshing algorithm to alter the model space and to create amore even distribution of resolution. Adaptive meshing provides a method for improving the resolution of the model space while honoring the data limitations and improving the quality of the attenuation difference inversion. Comparing inversions on a conventional rectangular grid with the adaptive mesh, we find that the adaptively meshed model reduces the inversion computation time by an average of 75% with an improvement in the root mean square error of up to 15%. While the sign of the conductivity change is correctly reproduced by the inversion algorithm, the magnitude varies by as much as much as 50% from the true values. Our heterogeneous conductivity model indicates that the attenuation difference inversion algorithm effectively locates conductivity changes, and that surface-based reflection surveys can produce models as accurate as traditional crosshole surveys

Concept for classifying facade elements based on material, geometry and thermal radiation using multimodal UAV remote sensing

This paper presents a concept for classification of facade elements, based on the material and the geometry of the elements in addition to the thermal radiation of the facade with the usage of a multimodal Unmanned Aerial Vehicle (UAV) system. Once the concept is finalized and functional, the workflow can be used for energy demand estimations for buildings by exploiting existing methods for estimation of heat transfer coefficient and the transmitted heat loss. The multimodal system consists of a thermal, a hyperspectral and an optical sensor, which can be operational with a UAV. While dealing with sensors that operate in different spectra and have different technical specifications, such as the radiometric and the geometric resolution, the challenges that are faced are presented. Addressed are the different approaches of data fusion, such as image registration, generation of 3D models by performing image matching and the means for classification based on either the geometry of the object or the pixel values. As a first step towards realizing the concept, the result from a geometric calibration with a designed multimodal calibration pattern is presented