Parallel TreeSPH

We describe PTreeSPH, a gravity treecode combined with an SPH hydrodynamics code designed for massively parallel supercomputers having distributed memory. Our computational algorithm is based on the popular TreeSPH code of Hernquist & Katz (1989). PTreeSPH utilizes a domain decomposition procedure and a synchronous hypercube communication paradigm to build self-contained subvolumes of the simulation on each processor at every timestep. Computations then proceed in a manner analogous to a serial code. We use the Message Passing Interface (MPI) communications package, making our code easily portable to a variety of parallel systems. PTreeSPH uses individual smoothing lengths and timesteps, with a communication algorithm designed to minimize exchange of information while still providing all information required to accurately perform SPH computations. We have additionally incorporated cosmology, periodic boundary conditions with forces calculated using a quadrupole Ewald summation method, and radiative cooling and heating from a parameterized ionizing background following Katz, Weinberg & Hernquist (1996). The addition of other physical processes, such as star formation, is straightforward. A cosmological simulation from z=49 to z=2 with 64^3 gas particles and 64^3 dark matter particles requires ~6000 node-hours on a Cray T3D, with a communications overhead of ~10% and is load balanced to a ~90% level. When used on the new Cray T3E, this code will be capable of performing cosmological hydrodynamical simulations down to z=0 with ~2x10^6 particles, or to z=2 with ~10^7 particles, in a reasonable amount of time. Even larger simulations will be practical in situations where the matter is not highly clustered or when periodic boundaries are not required.Comment: 30 pages, 6 Postscript figures, Submitted to New Astronom

Learning and Searching Methods for Robust, Real-Time Visual Odometry.

Accurate position estimation provides a critical foundation for mobile robot perception and control. While well-studied, it remains difficult to provide timely, precise, and robust position estimates for applications that operate in uncontrolled environments, such as robotic exploration and autonomous driving. Continuous, high-rate egomotion estimation is possible using cameras and Visual Odometry (VO), which tracks the movement of sparse scene content known as image keypoints or features. However, high update rates, often 30~Hz or greater, leave little computation time per frame, while variability in scene content stresses robustness. Due to these challenges, implementing an accurate and robust visual odometry system remains difficult. This thesis investigates fundamental improvements throughout all stages of a visual odometry system, and has three primary contributions: The first contribution is a machine learning method for feature detector design. This method considers end-to-end motion estimation accuracy during learning. Consequently, accuracy and robustness are improved across multiple challenging datasets in comparison to state of the art alternatives. The second contribution is a proposed feature descriptor, TailoredBRIEF, that builds upon recent advances in the field in fast, low-memory descriptor extraction and matching. TailoredBRIEF is an in-situ descriptor learning method that improves feature matching accuracy by efficiently customizing descriptor structures on a per-feature basis. Further, a common asymmetry in vision system design between reference and query images is described and exploited, enabling approaches that would otherwise exceed runtime constraints. The final contribution is a new algorithm for visual motion estimation: Perspective Alignment Search~(PAS). Many vision systems depend on the unique appearance of features during matching, despite a large quantity of non-unique features in otherwise barren environments. A search-based method, PAS, is proposed to employ features that lack unique appearance through descriptorless matching. This method simplifies visual odometry pipelines, defining one method that subsumes feature matching, outlier rejection, and motion estimation. Throughout this work, evaluations of the proposed methods and systems are carried out on ground-truth datasets, often generated with custom experimental platforms in challenging environments. Particular focus is placed on preserving runtimes compatible with real-time operation, as is necessary for deployment in the field.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113365/1/chardson_1.pd

Using Machine Learning for Model Physics: an Overview

In the overview, a generic mathematical object (mapping) is introduced, and its relation to model physics parameterization is explained. Machine learning (ML) tools that can be used to emulate and/or approximate mappings are introduced. Applications of ML to emulate existing parameterizations, to develop new parameterizations, to ensure physical constraints, and control the accuracy of developed applications are described. Some ML approaches that allow developers to go beyond the standard parameterization paradigm are discussed.Comment: 50 pages, 3 figures, 1 tabl

Advances in Robotics, Automation and Control

The book presents an excellent overview of the recent developments in the different areas of Robotics, Automation and Control. Through its 24 chapters, this book presents topics related to control and robot design; it also introduces new mathematical tools and techniques devoted to improve the system modeling and control. An important point is the use of rational agents and heuristic techniques to cope with the computational complexity required for controlling complex systems. Through this book, we also find navigation and vision algorithms, automatic handwritten comprehension and speech recognition systems that will be included in the next generation of productive systems developed by man

Carbon fluxes in a mature deciduous forest under elevated CO₂

This PhD thesis addressed several major aspects of the carbon (C) cycle in a c. 100-year-old, mixed deciduous forest under elevated CO₂ with an emphasis on below-ground processes. The aim was to assess the responses of tree fine roots and soil respiration to canopy CO₂ enrichment (? 550 ppm) in this tallest forest studied to date. Furthermore, leaf gas-exchange of the five study species was examined to ascertain the long-term response of photosynthetic carbon uptake to elevated atmospheric CO₂. Investigations at the Swiss Canopy Crane (SCC) experimental site were guided by the following key questions: (1) Does below-ground C allocation to fine root production increase in response to CO₂ enrichment in order to acquire more nutrients to match the enhanced C supply in the forest canopy? (2) Is below-ground metabolism enhanced and therefore forest soil respiration stimulated by canopy CO₂ enrichment? (3) Is leaf-level photosynthesis persistently stimulated by elevated CO₂ in this stand or had these mature broad-leaved trees reduced their carbon up- take by photosynthetic down-regulation under long-term CO₂ enrichment? Findings from earlier studies at the SCC site, including 13C isotope tracing, all point towards an in- creased flux of C through CO₂-enriched trees to the soil but neither fine root biomass nor soil respiration were stimulated by elevated CO₂. Surprisingly, fine root biomass in bulk soil and ingrowth cores showed strong reductions by ? 30% in year five and six but were unaffected in the following seventh year of CO₂ enrichment. Given the absence of a positive biomass response of fine roots, we assumed that the extra C assimilated in the CO₂-enriched forest canopy was largely respired back to the atmosphere via increases in fine root and rhizosphere respiration and the metabolization of increased root derived exudates by soil microbes. Indeed, 52% higher soil air CO₂ concentration during the growing season and 14% greater soil microbial biomass both in- dicated enhanced below-ground metabolism in soil under CO₂-enriched trees. However, this did not translate into a persistent stimulation of soil respiration. At times of high or continuous precipitation soil water savings under CO₂-exposed trees (resulting from reduced sapflow) led to excessive soil moisture (> 45 vol.-%) impeding soil gas-exchange and thus soil respiration. Depending on the interplay between soil temperature and the consistently high soil water content in this stand, instantaneous rates of soil respiration were periodically reduced or increased under elevated CO₂ but on a diel scale and integrated over the growing season soil CO₂ emissions were similar under CO₂-enriched and control trees. Soil respiration could therefore not explain the fate of the extra C. The lacking sink capacity for additional assimilates led us to assume downward adjustment of photosynthetic capacity in CO₂-enriched trees thereby reducing carbon uptake in the forest canopy. Photosynthetic acclimation cannot completely eliminate the CO₂-driven stimulation in carbon uptake, but a reduction could hamper the detection of a CO₂ effect considering the low statistical power inevitably involved with such large-scale experiments. However, after eight years of CO₂ enrichment we found sustained stimulation in leaf photosynthesis (42-49%) indicating a lack of closure in the carbon budget for this stand under elevated atmospheric CO₂

Development and demonstration of an on-board mission planner for helicopters

Mission management tasks can be distributed within a planning hierarchy, where each level of the hierarchy addresses a scope of action, and associated time scale or planning horizon, and requirements for plan generation response time. The current work is focused on the far-field planning subproblem, with a scope and planning horizon encompassing the entire mission and with a response time required to be about two minutes. The far-feld planning problem is posed as a constrained optimization problem and algorithms and structural organizations are proposed for the solution. Algorithms are implemented in a developmental environment, and performance is assessed with respect to optimality and feasibility for the intended application and in comparison with alternative algorithms. This is done for the three major components of far-field planning: goal planning, waypoint path planning, and timeline management. It appears feasible to meet performance requirements on a 10 Mips flyable processor (dedicated to far-field planning) using a heuristically-guided simulated annealing technique for the goal planner, a modified A* search for the waypoint path planner, and a speed scheduling technique developed for this project

Detail Enhancing Denoising of Digitized 3D Models from a Mobile Scanning System

The acquisition process of digitizing a large-scale environment produces an enormous amount of raw geometry data. This data is corrupted by system noise, which leads to 3D surfaces that are not smooth and details that are distorted. Any scanning system has noise associate with the scanning hardware, both digital quantization errors and measurement inaccuracies, but a mobile scanning system has additional system noise introduced by the pose estimation of the hardware during data acquisition. The combined system noise generates data that is not handled well by existing noise reduction and smoothing techniques. This research is focused on enhancing the 3D models acquired by mobile scanning systems used to digitize large-scale environments. These digitization systems combine a variety of sensors – including laser range scanners, video cameras, and pose estimation hardware – on a mobile platform for the quick acquisition of 3D models of real world environments. The data acquired by such systems are extremely noisy, often with significant details being on the same order of magnitude as the system noise. By utilizing a unique 3D signal analysis tool, a denoising algorithm was developed that identifies regions of detail and enhances their geometry, while removing the effects of noise on the overall model. The developed algorithm can be useful for a variety of digitized 3D models, not just those involving mobile scanning systems. The challenges faced in this study were the automatic processing needs of the enhancement algorithm, and the need to fill a hole in the area of 3D model analysis in order to reduce the effect of system noise on the 3D models. In this context, our main contributions are the automation and integration of a data enhancement method not well known to the computer vision community, and the development of a novel 3D signal decomposition and analysis tool. The new technologies featured in this document are intuitive extensions of existing methods to new dimensionality and applications. The totality of the research has been applied towards detail enhancing denoising of scanned data from a mobile range scanning system, and results from both synthetic and real models are presented

Contributions to Modulation and Control Algorithms for Multilevel Converters

Las actuales tendencias de la red eléctrica han lanzado a la industria a la búsqueda de sistemas de generación, distribución y consumo de energía eléctrica más eficientes. Generación distribuida, reducción de componentes pasivos, líneas DC de alta tensión son, entre otras, las posibles líneas de investigación que están actualmente siendo consideradas como el futuro de la red eléctrica. Sin embargo, nada de esto sería posible si no fuera por los avances alcanzados en el campo de la electrónica de potencia. El trabajo aquí presentado comienza con una breve introducción a la electrónica de potencia, concretamente a los convertidores de potencia conectados a red, sus estrategias de control más comunes y enfoques ante redes desbalanceadas. A continuación, las contribuciones del autor sobre el control y modulación de una topología particular de convertidores, conocidos como convertidores multinivel, se presentan como el principal contenido de este trabajo. Este tipo de convertidores mejoran la eficiencia y ciertas prestaciones, en comparación con convertidores más tradicionales, a costa de una mayor complejidad en el control al incrementar la cantidad de los componentes hardware. A pesar de que existen numerosas topologías de convertidores multinivel y algunas de ellas son brevemente expuestas en este trabajo, la mayoría de las aportaciones están enfocadas para convertidores del tipo diode-clamped converter. Adicionalmente, se incluye una aportación para convertidores del tipo multinivel modular, y otra para convertidores en cascada. Se espera que el contenido de la introducción de este trabajo, junto a las contribuciones particulares para convertidores multinivel sirva de inspiración para futuros investigadores del campo

The GEOS-5 Data Assimilation System-Documentation of Versions 5.0.1, 5.1.0, and 5.2.0

This report documents the GEOS-5 global atmospheric model and data assimilation system (DAS), including the versions 5.0.1, 5.1.0, and 5.2.0, which have been implemented in products distributed for use by various NASA instrument team algorithms and ultimately for the Modem Era Retrospective analysis for Research and Applications (MERRA). The DAS is the integration of the GEOS-5 atmospheric model with the Gridpoint Statistical Interpolation (GSI) Analysis, a joint analysis system developed by the NOAA/National Centers for Environmental Prediction and the NASA/Global Modeling and Assimilation Office. The primary performance drivers for the GEOS DAS are temperature and moisture fields suitable for the EOS instrument teams, wind fields for the transport studies of the stratospheric and tropospheric chemistry communities, and climate-quality analyses to support studies of the hydrological cycle through MERRA. The GEOS-5 atmospheric model has been approved for open source release and is available from: http://opensource.gsfc.nasa.gov/projects/GEOS-5/GEOS-5.php