Near-infrared Instrumentation For Rapid-response Astronomy

Ɣ-ray bursts (GRBs) are the Universe's most luminous transient events. Since the discovery of GRBs was announced in 1973, efforts have been ongoing to obtain data over a broader range of the electromagnetic spectrum at the earliest possible times following the initial detection. The discovery of the theorized ``afterglow'' emission in radio through X-ray bands in the late 1990s confirmed the cosmological nature of these events. At present, GRB afterglows are among the best probes of the early Universe (z ≳ 9). In addition to informing theories about GRBs themselves, observations of afterglows probe the circum-burst medium (CBM), properties of the host galaxies and the progress of cosmic reionization. To explore the early-time variability of afterglows, I have developed a generalized analysis framework which models near-infrared (NIR), optical, ultra-violet (UV) and X-ray light curves without assuming an underlying model. These fits are then used to construct the spectral energy distribution (SED) of afterglows at arbitrary times within the observed window. Physical models are then used to explore the evolution of the SED parameter space with time. I demonstrate that this framework produces evidence of the photodestruction of dust in the CBM of GRB 120119A, similar to the findings from a previous study of this afterglow. The framework is additionally applied to the afterglows of GRB 140419A and GRB 080607. In these cases the evolution of the SEDs appears consistent with the standard fireball model. Having introduced the scientific motivations for early-time observations, I introduce the Rapid Infrared Imager-Spectrometer (RIMAS). Once commissioned on the 4.3 meter Discovery Channel Telescope (DCT), RIMAS will be used to study the afterglows of GRBs through photometric and spectroscopic observations beginning within minutes of the initial burst. The instrument will operate in the NIR, from 0.97 μm to 2.37 μm, permitting the detection of very high redshift (z ≳ 7) afterglows which are attenuated at shorter wavelengths by Lyman-ɑ absorption in the intergalactic medium (IGM). A majority of my graduate work has been spent designing and aligning RIMAS's cryogenic (~80 K) optical systems. Design efforts have included an original camera used to image the field surrounding spectroscopic slits, tolerancing and optimizing all of the instrument's optics, thermal modeling of optomechanical systems, and modeling the diffraction efficiencies for some of the dispersive elements. To align the cryogenic optics, I developed a procedure that was successfully used for a majority of the instrument's sub-assemblies. My work on this cryogenic instrument has necessitated experimental and computational projects to design and validate designs of several subsystems. Two of these projects describe simple and effective measurements of optomechanical components in vacuum and at cryogenic temperatures using an 8-bit CCD camera. Models of heat transfer via electrical harnesses used to provide current to motors located within the cryostat are also presented.

Fachada flexível para casa padronizada em condomínios

The employment of flexibility in the design of façades makes them adaptable to adverse weather conditions, resulting in both minimization of environmental discomfort and improvement of energy efficiency. The present study highlights the potential of flexible façades as a resource to reduce rigidity and form repetition, which are usually employed in condominiums of standardized houses; as such, the work presented herein contributes to field of study of architectural projects strategies for adapting and integrating buildings within the local climate context. Two façade options were designed using as reference the bionics and the kinetics, as well as their applications to architectural constructions. This resulted in two lightweight and dynamic structures, which cater to constraints of comfort through combinations of movements, which control the impact of solar radiation and of cooling in the environment. The efficacy and technical functionality of the façades were tested with comfort analysis and graphic computation software, as well as with physical models. Thus, the current research contributes to the improvement of architectural solutions aimed at using passive energy strategies in order to offer both better quality for the users and for the sustainability of the planet

Packaging and Deployment of Large Planar Spacecraft Structures

This thesis presents a set of novel methods to biaxially package planar structures by folding and wrapping. The structure is divided into strips connected by folds that can slip during wrapping to accommodate material thickness. These packaging schemes are highly efficient, with theoretical packaging efficiencies approaching 100%. Packaging tests on meter-scale physical models have demonstrated packaging efficiencies of up to 83%. These methods avoid permanent deformation of the structure, allowing an initially flat structure to be deployed to a flat state.

Also presented are structural architectures and deployment schemes that are compatible with these packaging methods. These structural architectures use either in-plane pretension -- suitable for membrane structures -- or out-of-plane bending stiffness to resist loading. Physical models are constructed to realize these structural architectures. The deployment of these types of structures is shown to be controllable and repeatable by conducting experiments on lab-scale models.

These packaging methods, structural architectures, and deployment schemes are applicable to a variety of spacecraft structures such as solar power arrays, solar sails, antenna arrays, and drag sails; they have the potential to enable larger variants of these structures while reducing the packaging volume required. In this thesis, these methods are applied to the preliminary structural design of a space solar power satellite. This deployable spacecraft, measuring 60 m x 60 m, can be packaged into a cylinder measuring 1.5 m in height and 1 m in diameter. It can be deployed to a flat configuration, where it acts as a stiff lightweight support framework for multifunctional tiles that collect sunlight, generate electric power, and transmit it to a ground station on Earth.

DYNAMIC MODEL BASED STATE ESTIMATION IN A HEAVY DUTY DIESEL AFTERTREATMENT SYSTEM FOR ONBOARD DIAGNOSTICS AND CONTROLS

Estimating un-measurable states is an important component for onboard diagnostics (OBD) and control strategy development in diesel exhaust aftertreatment systems. This research focuses on the development of an Extended Kalman Filter (EKF) based state estimator for two of the main components in a diesel engine aftertreatment system: the Diesel Oxidation Catalyst (DOC) and the Selective Catalytic Reduction (SCR) catalyst. One of the key areas of interest is the performance of these estimators when the catalyzed particulate filter (CPF) is being actively regenerated. In this study, model reduction techniques were developed and used to develop reduced order models from the 1D models used to simulate the DOC and SCR. As a result of order reduction, the number of states in the estimator is reduced from 12 to 1 per element for the DOC and 12 to 2 per element for the SCR. The reduced order models were simulated on the experimental data and compared to the high fidelity model and the experimental data. The results show that the effect of eliminating the heat transfer and mass transfer coefficients are not significant on the performance of the reduced order models. This is shown by an insignificant change in the kinetic parameters between the reduced order and 1D model for simulating the experimental data. An EKF based estimator to estimate the internal states of the DOC and SCR was developed. The DOC and SCR estimators were simulated on the experimental data to show that the estimator provides improved estimation of states compared to a reduced order model. The results showed that using the temperature measurement at the DOC outlet improved the estimates of the CO , NO , NO2 and HC concentrations from the DOC. The SCR estimator was used to evaluate the effect of NH3 and NOX sensors on state estimation quality. Three sensor combinations of NOX sensor only, NH3 sensor only and both NOX and NH3 sensors were evaluated. The NOX only configuration had the worst performance, the NH3 sensor only configuration was in the middle and both the NOX and NH3 sensor combination provided the best performance.

X-ray analysis of local mid-infrared selected Compton-thick AGN candidates

Cosmic X-ray background synthesis models (Gilli 2007) require a significant fraction of obscured AGN, some of which are expected to be heavily obscured (Compton-thick), but the number density of observationally found obscured sources is still an open issue (Vignali 2010, 2014). This thesis work takes advantage of recent NuSTAR data and is based on a multiwavelength research approach. Gruppioni et al. 2016 compared the AGN bolometric luminosity, for a sample of local 12 micron Seyfert galaxies, derived from the SED decomposition to the same quantity obtained by the 2-10 keV luminosity (IPAC-NED). A difference up to two orders of magnitude resulted between these quantities for some sources. Thus, the intrinsic X-ray luminosity obtained correcting for the obscuration may be underestimated. In this thesis we have tested this hypothesis by re-analysing the X-ray spectra of three of the sources (UGC05101, NGC1194 and NGC3079), for which observations from NuSTAR and Chandra and/or XMM-Newton were available. This is meant to extend our analysis to energies above 10 keV and thus estimate the AGN column density as reliable as possible. For spectral fitting we made use of both the commonly used XSPEC package and the two very recent MYtorus and BNtorus physical models. The available wide bandpass allowed us to achieve new and more solid insights into the X-ray spectral properties of these sources. The measured absorption column densities are highly suggestive of heavy obscuration. Once corrected the X-ray AGN luminosity for the obscuration estimated through our spectral analysis, we compared the L(X) values in the 2-10 keV band with those derived from the MIR band, by means of the relation by Gandhi, 2009. As expected, the values derived from this relation are in good agreement with those we measured, indicating that the column densities were underestimated in the previous literature works.

Decoding complex flow phenomena via Dynamic Mode Decomposition

In this thesis, the viability of the Dynamic Mode Decomposition (DMD) as a technique to analyze and model complex dynamic real-world systems is presented. This method derives, directly from data, computationally efficient reduced-order models (ROMs) which can replace too onerous or unavailable high-fidelity physics-based models. Optimizations and extensions to the standard implementation of the methodology are proposed, investigating diverse case studies related to the decoding of complex flow phenomena. The flexibility of this data-driven technique allows its application to high-fidelity fluid dynamics simulations, as well as time series of real systems observations. The resulting ROMs are tested against two tasks: (i) reduction of the storage requirements of high-fidelity simulations or observations; (ii) interpolation and extrapolation of missing data. The capabilities of DMD can also be exploited to alleviate the cost of onerous studies that require many simulations, such as uncertainty quantification analysis, especially when dealing with complex high-dimensional systems. In this context, a novel approach to address parameter variability issues when modeling systems with space and time-variant response is proposed. Specifically, DMD is merged with another model-reduction technique, namely the Polynomial Chaos Expansion, for uncertainty quantification purposes. Useful guidelines for DMD deployment result from the study, together with the demonstration of its potential to ease diagnosis and scenario analysis when complex flow processes are involved.

Analysis of dynamic models for structural insight and model reduction .2. A multi-stage compressor shutdown case-study

In this second paper, the three structural measures which have been developed are used in the modelling of a three stage centrifugal synthesis gas compressor. The goal of this case study is to determine the essential mathematical structure which must be incorporated into the compressor model to accurately model the shutdown of this system. A simple, accurate and functional model of the system is created via three structural measures. It was found that the model can be correctly reduced into its basic modes and that the order of the differential system can be reduced from 51(st) to 20(th). Of the 31 differential equational 21 reduce to algebraic relations, 8 become constants and 2 can be deleted thereby increasing the algebraic set from 70 to 91 equations. An interpretation is also obtained as to which physical phenomena are dominating the dynamics of the compressor add whether the compressor will enter surge during the shutdown. Comparisons of the reduced model performance against the full model are given, showing the accuracy and applicability of the approach. Copyright (C) 1996 Elsevier Science Ltd

Conceptual-physical bridging – From BPMN models to physical implementations on kettle

Developing and implementing data-oriented workflows for data migration processes are complex tasks involving several problems related to the integration of data coming from different schemas. Usually, they involve very specific requirements - every process is almost unique. Having a way to abstract their representation will help us to better understand and validate them with business users, which is a crucial step for requirements validation. In this demo we present an approach that provides a way to enrich incrementally conceptual models in order to support an automatic way for producing their correspondent physical implementation. In this demo we will show how B2K (Business to Kettle) system works transforming BPMN 2.0 conceptual models into Kettle data-integration executable processes, approaching the most relevant aspects related to model design and enrichment, model to system transformation, and system execution.

Automatic generation of ETL physical systems from BPMN conceptual models

ETL conceptual modeling is a very important activity in any data warehousing system project implementation. Owning a high-level system representation allowing for a clear identification of the main parts of a data warehousing system is clearly a great advantage, especially in early stages of design and development. However, the effort to model conceptually an ETL system rarely is properly rewarded. Translating ETL conceptual models directly into something that saves work and time on the concrete implementation of the system process it would be, in fact, a great help. In this paper we present and discuss a hybrid approach to this problem, combining the simplicity of interpretation and power of expression of BPMN on ETL systems conceptualization with the use of ETL patterns to produce automatically an ETL skeleton, a first prototype system, which has the ability to be executed in a commercial ETL tool like Kettle.

A comparative study of the physical, chemical and microbiological status of soils, as influenced by conventional and reduced tillage

Historically, shifts to reduced and no-tillage management for production of crops were fostered by needs to decrease soil erosion and loss of organic matter, reduce fuel and labour costs and conserve soil water, as compared with conventional fallow tillage management. Recent interest in maintaining soil quality has been stimulated by a renewed awareness of the importance of soil condition to both the sustainability of agricultural production systems and environmental quality (Doran and Parkin, 1996). The aim of this project was to determine the impact on the physical, chemical and microbiological status of the soil of conventional and reduced tillage. It has been suggested that the reduced soil disturbance associated with the tine cultivator improves soil structure, increases nutrient content in the top 10cm of soil, increases microbial activity and improves physical characteristics. From this study it was determined that the environmental benefits linked to reduced tillage in literature, did not develop in the first two years of this programmes implementation. The results of this study determined that soil nutrients did not increase in concentration in the top 10 cm of soil under reduced cultivation. The only exception was exchangeable potassium. As potassium is not a mobile nutrient its movement is dependent on soil disturbance, therefore under reduced cultivation its concentration was allowed to accumulate in the upper horizon of the soil profile. Microbial activity was greater in the conventionally tilled treatments, as determined by total aerobic bacterial numbers. This could be due to the increased rates of soil aeration in this treatment. Numbers of aerobic bacteria were greater in the conventional tillage treatments at both incubation temperatures of 22 and 32° C. The physical characteristics of the soil determined, indicate that below the depth of soil cultivation, cone penetration resistance increases. Therefore the reduced cultivation treatments would be more prone to soil compaction, higher in the soil profile.

Simulation of interacting populations in inhomogeneous flows using reduced models

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2010

Gut Microbiota Composition in Male Rat Models under Different Nutritional Status and Physical Activity and Its Association with Serum Leptin and Ghrelin Levels.

BACKGROUND Several evidences indicate that gut microbiota is involved in the control of host energy metabolism. OBJECTIVE To evaluate the differences in the composition of gut microbiota in rat models under different nutritional status and physical activity and to identify their associations with serum leptin and ghrelin levels. METHODS IN A CASE CONTROL STUDY, FORTY MALE RATS WERE RANDOMLY ASSIGNED TO ONE OF THESE FOUR EXPERIMENTAL GROUPS: ABA group with food restriction and free access to exercise; control ABA group with food restriction and no access to exercise; exercise group with free access to exercise and feed ad libitum and ad libitum group without access to exercise and feed ad libitum. The fecal bacteria composition was investigated by PCR-denaturing gradient gel electrophoresis and real-time qPCR. RESULTS In restricted eaters, we have found a significant increase in the number of Proteobacteria, Bacteroides, Clostridium, Enterococcus, Prevotella and M. smithii and a significant decrease in the quantities of Actinobacteria, Firmicutes, Bacteroidetes, B. coccoides-E. rectale group, Lactobacillus and Bifidobacterium with respect to unrestricted eaters. Moreover, a significant increase in the number of Lactobacillus, Bifidobacterium and B. coccoides-E. rectale group was observed in exercise group with respect to the rest of groups. We also found a significant positive correlation between the quantity of Bifidobacterium and Lactobacillus and serum leptin levels, and a significant and negative correlation among the number of Clostridium, Bacteroides and Prevotella and serum leptin levels in all experimental groups. Furthermore, serum ghrelin levels were negatively correlated with the quantity of Bifidobacterium, Lactobacillus and B. coccoides-Eubacterium rectale group and positively correlated with the number of Bacteroides and Prevotella. CONCLUSIONS Nutritional status and physical activity alter gut microbiota composition affecting the diversity and similarity. This study highlights the associations between gut microbiota and appetite-regulating hormones that may be important in terms of satiety and host metabolism.

Selecting statistical models to study the relationship between soybean yield and soil physical properties

Statistical models allow the representation of data sets and the estimation and/or prediction of the behavior of a given variable through its interaction with the other variables involved in a phenomenon. Among other different statistical models, are the autoregressive state-space models (ARSS) and the linear regression models (LR), which allow the quantification of the relationships among soil-plant-atmosphere system variables. To compare the quality of the ARSS and LR models for the modeling of the relationships between soybean yield and soil physical properties, Akaike's Information Criterion, which provides a coefficient for the selection of the best model, was used in this study. The data sets were sampled in a Rhodic Acrudox soil, along a spatial transect with 84 points spaced 3 m apart. At each sampling point, soybean samples were collected for yield quantification. At the same site, soil penetration resistance was also measured and soil samples were collected to measure soil bulk density in the 0-0.10 m and 0.10-0.20 m layers. Results showed autocorrelation and a cross correlation structure of soybean yield and soil penetration resistance data. Soil bulk density data, however, were only autocorrelated in the 0-0.10 m layer and not cross correlated with soybean yield. The results showed the higher efficiency of the autoregressive space-state models in relation to the equivalent simple and multiple linear regression models using Akaike's Information Criterion. The resulting values were comparatively lower than the values obtained by the regression models, for all combinations of explanatory variables.

Modelling hydrodynamics in the Rio Parana, Argentina : an evaluation and inter-comparison of reduced-complexity and physics based models applied to a large sand-bed river

Depth-averaged velocities and unit discharges within a 30 km reach of one of the world's largest rivers, the Rio Parana, Argentina, were simulated using three hydrodynamic models with different process representations: a reduced complexity (RC) model that neglects most of the physics governing fluid flow, a two-dimensional model based on the shallow water equations, and a three-dimensional model based on the Reynolds-averaged Navier-Stokes equations. Row characteristics simulated using all three models were compared with data obtained by acoustic Doppler current profiler surveys at four cross sections within the study reach. This analysis demonstrates that, surprisingly, the performance of the RC model is generally equal to, and in some instances better than, that of the physics based models in terms of the statistical agreement between simulated and measured flow properties. In addition, in contrast to previous applications of RC models, the present study demonstrates that the RC model can successfully predict measured flow velocities. The strong performance of the RC model reflects, in part, the simplicity of the depth-averaged mean flow patterns within the study reach and the dominant role of channel-scale topographic features in controlling the flow dynamics. Moreover, the very low water surface slopes that typify large sand-bed rivers enable flow depths to be estimated reliably in the RC model using a simple fixed-lid planar water surface approximation. This approach overcomes a major problem encountered in the application of RC models in environments characterised by shallow flows and steep bed gradients. The RC model is four orders of magnitude faster than the physics based models when performing steady-state hydrodynamic calculations. However, the iterative nature of the RC model calculations implies a reduction in computational efficiency relative to some other RC models. A further implication of this is that, if used to simulate channel morphodynamics, the present RC model may offer only a marginal advantage in terms of computational efficiency over approaches based on the shallow water equations. These observations illustrate the trade off between model realism and efficiency that is a key consideration in RC modelling. Moreover, this outcome highlights a need to rethink the use of RC morphodynamic models in fluvial geomorphology and to move away from existing grid-based approaches, such as the popular cellular automata (CA) models, that remain essentially reductionist in nature. In the case of the world's largest sand-bed rivers, this might be achieved by implementing the RC model outlined here as one element within a hierarchical modelling framework that would enable computationally efficient simulation of the morphodynamics of large rivers over millennial time scales. (C) 2012 Elsevier B.V. All rights reserved.