Computational fluid dynamics (CFD) based approach to consequence assessment of accidental release of hydrocarbon during storage and transportation

This thesis investigated the risk of accidental release of hydrocarbons during transportation and storage. Transportation of hydrocarbons from an offshore platform to processing units through subsea pipelines involves risk of release due to pipeline leakage resulting from corrosion, plastic deformation caused by seabed shakedown or damaged by contact with drifting iceberg. The environmental impacts of hydrocarbon dispersion can be severe. Overall safety and economic concerns of pipeline leakage at subsea environment are immense. A large leak can be detected by employing conventional technology such as, radar, intelligent pigging or chemical tracer but in a remote location like subsea or arctic, a small chronic leak may be undetected for a period of time. In case of storage, an accidental release of hydrocarbon from the storage tank could lead pool fire; further it could escalate to domino effects. This chain of accidents may lead to extremely severe consequences. Analyzing past accident scenarios it is observed that more than half of the industrial domino accidents involved fire as a primary event, and some other factors for instance, wind speed and direction, fuel type and engulfment of the compound. In this thesis, a computational fluid dynamics (CFD) approach is taken to model the subsea pipeline leak and the pool fire from a storage tank. A commercial software package ANSYS FLUENT Workbench 15 is used to model the subsea pipeline leakage. The CFD simulation results of four different types of fluids showed that the static pressure and pressure gradient along the axial length of the pipeline have a sharp signature variation near the leak orifice at steady state condition. Transient simulation is performed to obtain the acoustic signature of the pipe near leak orifice. The power spectral density (PSD) of acoustic signal is strong near the leak orifice and it dissipates as the distance and orientation from the leak orifice increase. The high-pressure fluid flow generates more noise than the low-pressure fluid flow. In order to model the pool fire from the storage tank, ANSYS CFX Workbench 14 is used. The CFD results show that the wind speed has significant contribution on the behavior of pool fire and its domino effects. The radiation contours are also obtained from CFD post processing, which can be applied for risk analysis. The outcome of this study will be helpful for better understanding of the domino effects of pool fire in complex geometrical settings of process industries. The attempt to reduce and prevent risks is discussed based on the results obtained from the numerical simulations of the numerical models.

Hyperspaces, shape theory and computational topology

Esta tesis trata sobre aproximaciones de espacios métricos compactos. La aproximación y reconstrucción de espacios topológicos mediante otros más sencillos es un tema antigüo en topología geométrica. La idea es construir un espacio muy sencillo lo más parecido posible al espacio original. Como es muy difícil (o incluso no tiene sentido) intentar obtener una copia homeomorfa, el objetivo será encontrar un espacio que preserve algunas propriedades topológicas (algebraicas o no) como compacidad, conexión, axiomas de separación, tipo de homotopía, grupos de homotopía y homología, etc. Los primeros candidatos como espacios sencillos con propiedades del espacio original son los poliedros. Ver el artículo [45] para los resultados principales. En el germen de esta idea, destacamos los estudios de Alexandroff en los años 20, relacionando la dimensión del compacto métrico con la dimensión de ciertos poliedros a través de aplicaciones con imágenes o preimágenes controladas (en términos de distancias). En un contexto más moderno, la idea de aproximación puede ser realizada construyendo un complejo simplicial basado en el espacio original, como el complejo de Vietoris-Rips o el complejo de Cech y comparar su realización con él. En este sentido, tenemos el clásico lema del nervio [12, 21] el cual establece que para un recubrimiento por abiertos “suficientemente bueno" del espacio (es decir, un recubrimiento con miembros e intersecciones contractibles o vacías), el nervio del recubrimiento tiene el tipo de homotopía del espacio original. El problema es encontrar estos recubrimientos (si es que existen). Para variedades Riemannianas, existen algunos resultados en este sentido, utilizando los complejos de Vietoris-Rips. Hausmann demostró [35] que la realización del complejo de Vietoris-Rips de la variedad, para valores suficientemente bajos del parámetro, tiene el tipo de homotopía de dicha variedad. En [40], Latschev demostró una conjetura establecida por Hausmann: El tipo de homotopía de la variedad se puede recuperar utilizando un conjunto finito de puntos (suficientemente denso) para el complejo de Vietoris-Rips. Los resultados de Petersen [58], comparando la distancia Gromov-Hausdorff de los compactos métricos con su tipo de homotopía, son también interesantes. Aquí, los poliedros salen a relucir en las demostraciones, no en los resultados...

Production of Referring Expressions for an Unknown Audience : a Computational Model of Communal Common Ground

The research reported in this article is based on the Ph.D. project of Dr. RK, which was funded by the Scottish Informatics and Computer Science Alliance (SICSA). KvD acknowledges support from the EPSRC under the RefNet grant (EP/J019615/1).

The mechanism of ϕC31 integrase directionality : experimental analysis and computational modelling

Acknowledgments We thank Sally Rowland for helpful comments on the manuscript. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

A Comparative Review of Computational Methods as Applied to Gold(I) Complexes and Mechanisms

In the last two decades, the field of homogeneous gold catalysis has been

extremely active, growing at a rapid pace. Another rapidly-growing field—that of

computational chemistry—has often been applied to the investigation of various gold-

catalyzed reaction mechanisms. Unfortunately, a number of recent mechanistic studies

have utilized computational methods that have been shown to be inappropriate and

inaccurate in their description of gold chemistry. This work presents an overview of

available computational methods with a focus on the approximations and limitations

inherent in each, and offers a review of experimentally-characterized gold(I) complexes

and proposed mechanisms as compared with their computationally-modeled

counterparts. No aim is made to identify a “recommended” computational method for

investigations of gold catalysis; rather, discrepancies between experimentally and

computationally obtained values are highlighted, and the systematic errors between

different computational methods are discussed.

Computational Methods for Identifying Hypertrophic Cardiomyopathy using 12-lead ECG

Hypertrophic cardiomyopathy (HCM) is a cardiovascular disease where the heart muscle is partially thickened and blood flow is - potentially fatally - obstructed. It is one of the leading causes of sudden cardiac death in young people. Electrocardiography (ECG) and Echocardiography (Echo) are the standard tests for identifying HCM and other cardiac abnormalities. The American Heart Association has recommended using a pre-participation questionnaire for young athletes instead of ECG or Echo tests due to considerations of cost and time involved in interpreting the results of these tests by an expert cardiologist. Initially we set out to develop a classifier for automated prediction of young athletes’ heart conditions based on the answers to the questionnaire. Classification results and further in-depth analysis using computational and statistical methods indicated significant shortcomings of the questionnaire in predicting cardiac abnormalities. Automated methods for analyzing ECG signals can help reduce cost and save time in the pre-participation screening process by detecting HCM and other cardiac abnormalities. Therefore, the main goal of this dissertation work is to identify HCM through computational analysis of 12-lead ECG. ECG signals recorded on one or two leads have been analyzed in the past for classifying individual heartbeats into different types of arrhythmia as annotated primarily in the MIT-BIH database. In contrast, we classify complete sequences of 12-lead ECGs to assign patients into two groups: HCM vs. non-HCM. The challenges and issues we address include missing ECG waves in one or more leads and the dimensionality of a large feature-set. We address these by proposing imputation and feature-selection methods. We develop heartbeat-classifiers by employing Random Forests and Support Vector Machines, and propose a method to classify full 12-lead ECGs based on the proportion of heartbeats classified as HCM. The results from our experiments show that the classifiers developed using our methods perform well in identifying HCM. Thus the two contributions of this thesis are the utilization of computational and statistical methods for discovering shortcomings in a current screening procedure and the development of methods to identify HCM through computational analysis of 12-lead ECG signals.

Computational models for improved diagnosis and prognosis of stroke using robot-based biomarkers

Stroke is a leading cause of death and permanent disability worldwide, affecting millions of individuals. Traditional clinical scores for assessment of stroke-related impairments are inherently subjective and limited by inter-rater and intra-rater reliability, as well as floor and ceiling effects. In contrast, robotic technologies provide objective, highly repeatable tools for quantification of neurological impairments following stroke. KINARM is an exoskeleton robotic device that provides objective, reliable tools for assessment of sensorimotor, proprioceptive and cognitive brain function by means of a battery of behavioral tasks. As such, KINARM is particularly useful for assessment of neurological impairments following stroke. This thesis introduces a computational framework for assessment of neurological impairments using the data provided by KINARM. This is done by achieving two main objectives. First, to investigate how robotic measurements can be used to estimate current and future abilities to perform daily activities for subjects with stroke. We are able to predict clinical scores related to activities of daily living at present and future time points using a set of robotic biomarkers. The findings of this analysis provide a proof of principle that robotic evaluation can be an effective tool for clinical decision support and target-based rehabilitation therapy. The second main objective of this thesis is to address the emerging problem of long assessment time, which can potentially lead to fatigue when assessing subjects with stroke. To address this issue, we examine two time reduction strategies. The first strategy focuses on task selection, whereby KINARM tasks are arranged in a hierarchical structure so that an earlier task in the assessment procedure can be used to decide whether or not subsequent tasks should be performed. The second strategy focuses on time reduction on the longest two individual KINARM tasks. Both reduction strategies are shown to provide significant time savings, ranging from 30% to 90% using task selection and 50% using individual task reductions, thereby establishing a framework for reduction of assessment time on a broader set of KINARM tasks. All in all, findings of this thesis establish an improved platform for diagnosis and prognosis of stroke using robot-based biomarkers.

Using Computational Significance and Resilience in System Software Stacks.:Keynote Talk

This talk explores how the runtime system and operating system can leverage metrics that express the significance and resilience of application components in order to reduce the energy footprint of parallel applications. We will explore in particular how software can tolerate and indeed exploit higher error rates in future processors and memory technologies that may operate outside their safe margins.

Particle Trajectory Tracing and Computational Electromagnetics for Accelerator and Related Technologies

The main objective of this R&D work is to simulate particle beam optics in CV-28 Cyclotron of Instituto de Engenharia Nuclear – IEN/CNEN, as a support for improvements or optimization of this particle accelerator. Besides 2D magnetostatic field computation results, the authors present an alternative method for charged particle trajectories computation in electrostatic or magnetostatic fields. This task is approached by analytical computation of trajectories, by parts, considering constant fields within each finite element. This method has some advantages over numerical integration ones: numerical miscomputation of trajectories is avoided; stability problem is also avoided, for the magnetostatic field case. Some examples are presented, including positive ion extraction from cyclotrons with strip-foil. This latter technique is an interesting alternative for upgrading positive ion cyclotrons, such as CV-28 Cyclotron. The particle trajectory computation method presented in this work is of interest not only for cyclotrons, but for accelerator and related technology, in general.

Computational approaches and tools for modeling biomass pyrolysis

Thesis (Ph.D.)--University of Washington, 2016-08

PHYSICA: A multiphysics computational framework and its application to casting simulations

Metal casting is a process governed by the interaction of a range of physical phenomena. Most computational models of this process address only what are conventionally regarded as the primary phenomena – heat conduction and solidification. However, to predict other phenomena, such as porosity formation, requires modelling the interaction of the fluid flow, heat transfer, solidification and the development of stressdeformation in the solidified part of the casting. This paper will describe a modelling framework called PHYSICA[1] which has the capability to stimulate such multiphysical phenomena.