Search for dissertations about: "mixing state"
Showing result 1 - 5 of 133 swedish dissertations containing the words mixing state.
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1. Primary Marine Aerosol Production : Studies using bubble-bursting experiments
Abstract : Aerosol particles affect the Earth’s climate, although their impact is associated with large uncertainties. Primary marine aerosol represents a significant fraction of the global aerosol budget considering the Earth’s 70-percentage coverage by oceans. READ MORE
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2. Aspects of probabalistic serviceability limit state design of dry deep mixing
Abstract : An expanding population and increased need for infrastructure increasingly necessitate construction on surfaces with poor soil conditions. To facilitate the construction of buildings, roads and railroads in areas with poor soil conditions, these areas are often improved by means of foundation engineering. READ MORE
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3. Mechanisms of adhesive mixing for drug particle inhalation (Numerical investigation of the interplay between formulation variables)
Abstract : Formulation of therapeutic dry powders for lung drug delivery via inhalation is done via adhesive mixing. In this process, micron-sized active pharmaceutical ingredient particles are blended with relatively coarse carrier particles until stable adhesive units of carrier and drug particles are formed. READ MORE
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4. Concepts for compact solid-state lasers in the visible and UV
Abstract : In many fields, scientific or industrial, optical devices that can be tailored in terms of spectral qualities and output power depending on the application in question are attractive. Nonlinear optics in combination with powerful laser sources provide a tool to achieve essentially any wavelength in the electromagnetic spectrum, and the advancement of material technology during the last decade has opened up new possibilities in terms of realising such devices. READ MORE
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5. On Bounds and Asymptotics of Sequential Monte Carlo Methods for Filtering, Smoothing, and Maximum Likelihood Estimation in State Space Models
Abstract : This thesis is based on four papers (A-D) treating filtering, smoothing, and maximum likelihood (ML) estimation in general state space models using stochastic particle filters (also referred to as sequential Monte Carlo (SMC) methods). The aim of Paper A is to study the bias of Monte Carlo integration estimates produced by the so-called bootstrap particle filter. READ MORE