Thermodynamics of tubelike flexible polymers

In this work we present the general phase behavior of short tubelike flexible polymers. The geometric thickness constraint is implemented through the concept of the global radius of curvature. We use sophisticated Monte Carlo sampling methods to simulate small bead-stick polymer models with Lennard-Jones interaction among non-bonded monomers. We analyze energetic fluctuations and structural quantities to classify conformational pseudophases. We find that the tube thickness influences the thermodynamic behavior of simple tubelike polymers significantly, i.e., for given temperature, the formation of secondary structures strongly depends on the tube thickness

Hydrodynamical investigations of liquid ventilation by means of advanced optical measurement techniques

Although liquid ventilation has been researched and studied for the last six decades, it did not achieve its expected optimal performance. Within this work, a deeper understanding of the fluid dynamics during liquid ventilation shall be gathered to extend the already available clinical knowledge about this ventilation strategy. In order to reach this goal, advanced optical flow measurement techniques are applied in different models of the human conductive airways to obtain global velocity fields, identifying prominent flow structures and to determine important dissolved oxygen transport paths. As the velocity measurements revealed, the evolving flow field is strongly dominated by secondary flow effects and is highly dependent on the local airway geometry. During the visualization experiments of the dissolved oxygen concentration fields, different transportation paths occur at inspirational and expirational flow. The initial concentration distribution can be linked to the underlying flow fields but decouples after the peak velocity phases. With higher flow rates/ tidal volumes, a more homogeneously distributed oxygen concentration can be reached.:List of Figures ....................................................................................... VII List of Tables ........................................................................................XIII Nomenclature ........................................................................................ XV 1 Introduction......................................................................................... 1 1.1 Motivation ........................................................................................1 1.2 Research objectives........................................................................... 3 1.3 Outline............................................................................................ 4 2 State of the art .................................................................................... 5 2.1 Liquid Ventilation............................................................................. 5 2.2 In vitro modeling.............................................................................. 8 2.3 Flow measurements ......................................................................... 11 2.4 Gas transport..................................................................................13 3 Flow field measurements ................................................................... 16 3.1 Hydrodynamic Model.......................................................................16 3.1.1 Lung replica ..........................................................................16 3.1.2 Flow parameter .....................................................................18 3.1.3 Limitations ...........................................................................22 3.2 Particle Tracking Velocimetry (PTV) ................................................24 3.2.1 Measurement principle ...........................................................24 3.2.2 Double-frame 2D-PTV ...........................................................25 3.2.3 Time-resolved 3D-PTV ..........................................................28 3.2.4 Phase-locked ensemble PTV ................................................... 31 3.3 Experimental set-up and measurement procedure ...............................33 3.3.1 Lung flow facility...................................................................33 3.3.2 2D-PTV configuration............................................................36 3.3.3 3D-PTV configuration............................................................36 3.4 Results & Discussion........................................................................38 3.4.1 Artificial lung........................................................................38 3.4.2 Realistic lung ........................................................................52 3.5 Conclusion ......................................................................................59 4 Oxygen transport ...............................................................................61 4.1 Hydrodynamic Model....................................................................... 61 4.1.1 Lung replica .......................................................................... 61 4.1.2 Flow parameter .....................................................................62 4.1.3 Limitations ...........................................................................65 4.2 Oxygen Sensitive Dye ......................................................................66 4.3 Experimental set-up......................................................................... 71 4.4 Results & Discussion........................................................................75 4.4.1 Constant flow rate .................................................................75 4.4.2 Oscillatory flow .....................................................................83 4.5 Conclusion ......................................................................................90 5 Summary............................................................................................ 92 6 Outlook .............................................................................................. 95 Bibliography ............................................................................................ 97Trotz intensiver Forschung in den letzten sechs Jahrzehnten, befindet sich die Flüssigkeitsbeatmung immernoch weit entfernt vom klinischen Alltag. Mit dieser Arbeit soll ein Beitrag geleistet werden, um das Wissen um die strömungsmechanischen Effekte während der Flüssigkeitsbeatmung zu vertiefen. Dazu werden verschiedene Modellexperimente durchgeführt, bei welchen moderne laseroptische Strömungsmessmethoden zum Einsatz kommen. Untersucht werden dabei unterschiedlich komplexe Geometrien der leitenden menschlichen Atemwege mit dem Ziel wesentliche Strömungsstrukturen, globale Geschwindigkeitsfelder und wichtige Transportwege des gelösten Sauerstoffs zu identifiziern. Die Geschwindigkeitsmessungen zeigen ein stark durch sekundäre Strömungseffekte dominiertes Geschwindigkeitsfeld, welches wesentlich von der lokalen Geometrie abhängig ist. Durch die qualitative und quantitative Erfassung der gelösten Sauerstoffkonzentrationsfelder können wichtige Transportwege aufgedeckt werden. Diese unterscheiden sich deutlich zwischen inspiratorischer und expiratorischer Strömungsrichtung. Die initialen Konzentrationsfelder stimmen mit den unterliegenden Geschwindigkeitsfeldern überein, unterscheiden sich ab der verzögernden Strömungsphase jedoch. Höhere Volumenströme/Tidalvolumen tragen dabei zu einer gleichmäßigeren Konzentrationsverteilung bei.:List of Figures ....................................................................................... VII List of Tables ........................................................................................XIII Nomenclature ........................................................................................ XV 1 Introduction......................................................................................... 1 1.1 Motivation ........................................................................................1 1.2 Research objectives........................................................................... 3 1.3 Outline............................................................................................ 4 2 State of the art .................................................................................... 5 2.1 Liquid Ventilation............................................................................. 5 2.2 In vitro modeling.............................................................................. 8 2.3 Flow measurements ......................................................................... 11 2.4 Gas transport..................................................................................13 3 Flow field measurements ................................................................... 16 3.1 Hydrodynamic Model.......................................................................16 3.1.1 Lung replica ..........................................................................16 3.1.2 Flow parameter .....................................................................18 3.1.3 Limitations ...........................................................................22 3.2 Particle Tracking Velocimetry (PTV) ................................................24 3.2.1 Measurement principle ...........................................................24 3.2.2 Double-frame 2D-PTV ...........................................................25 3.2.3 Time-resolved 3D-PTV ..........................................................28 3.2.4 Phase-locked ensemble PTV ................................................... 31 3.3 Experimental set-up and measurement procedure ...............................33 3.3.1 Lung flow facility...................................................................33 3.3.2 2D-PTV configuration............................................................36 3.3.3 3D-PTV configuration............................................................36 3.4 Results & Discussion........................................................................38 3.4.1 Artificial lung........................................................................38 3.4.2 Realistic lung ........................................................................52 3.5 Conclusion ......................................................................................59 4 Oxygen transport ...............................................................................61 4.1 Hydrodynamic Model....................................................................... 61 4.1.1 Lung replica .......................................................................... 61 4.1.2 Flow parameter .....................................................................62 4.1.3 Limitations ...........................................................................65 4.2 Oxygen Sensitive Dye ......................................................................66 4.3 Experimental set-up......................................................................... 71 4.4 Results & Discussion........................................................................75 4.4.1 Constant flow rate .................................................................75 4.4.2 Oscillatory flow .....................................................................83 4.5 Conclusion ......................................................................................90 5 Summary............................................................................................ 92 6 Outlook .............................................................................................. 95 Bibliography ............................................................................................ 9

Freezing and collapse of flexible polymers

We analyze the freezing and collapse transition of a simple model for flexible polymer chains on simple cubic and face-centered cubic lattices by means of sophisticated chain-growth methods. In contrast to bond-fluctuation polymer models in certain parameter ranges, where these two conformational transitions were found to merge in the thermodynamic limit, we conclude from our results that the two transitions remain well-separated in the limit of infinite chain lengths. The reason for this qualitatively distinct behavior is presumably due to the ultrashort attractive interaction range in the lattice models considered here

Critical Loop Gases and the Worm Algorithm

The loop gas approach to lattice field theory provides an alternative, geometrical description in terms of fluctuating loops. Statistical ensembles of random loops can be efficiently generated by Monte Carlo simulations using the worm update algorithm. In this paper, concepts from percolation theory and the theory of self-avoiding random walks are used to describe estimators of physical observables that utilize the nature of the worm algorithm. The fractal structure of the random loops as well as their scaling properties are studied. To support this approach, the O(1) loop model, or high-temperature series expansion of the Ising model, is simulated on a honeycomb lattice, with its known exact results providing valuable benchmarks.Comment: 34 pages, 12 figures; v2: 2 figures and 1 table added; v3: typo's correcte

Surface effects in the crystallization process of elastic flexible polymers

Investigating thermodynamic properties of liquid-solid transitions of flexible homopolymers with elastic bonds by means of multicanonical Monte Carlo simulations, we find crystalline conformations that resemble ground-state structures of Lennard-Jones clusters. This allows us to set up a structural classification scheme for finite-length flexible polymers and their freezing mechanism in analogy to atomic cluster formation. Crystals of polymers with "magic length" turn out to be perfectly icosahedral

Universality of the evaporation/condensation transition

AbstractBy making use of the well-known lattice-gas interpretation, we investigated the evaporation/condensation transition through Monte Carlo simulations of the square lattice Ising model with nearest-neighbour couplings and periodic boundary conditions. The particle density can be varied by choosing different fixed magnetisations. In the analysis of our data we followed recent analytical work by Biskup et al. [Europhys. Lett. 60 (2002) 21], who also used the Ising model to study liquid-vapour systems at a fixed excess δN of particles above the ambient gas density in the limit of large system sizes. By identifying a dimensionless parameter Δ(δN), they showed that for Δ<Δc all excess is absorbed in background fluctuations (“evaporated” system), while for Δ>Δc a single large droplet of the dense phase occurs (“condensed” system). Besides the threshold value Δc also the fraction λ of excess particles forming the droplet is given explicitly.To test the applicability of these asymptotic results to practically accessible system sizes, we measured the volume of the largest minority droplet, corresponding to a fluid drop, for various L×L lattices with L=40,…,640. Using analytic values for the spontaneous magnetisation m0, the susceptibility χ and the Wulff interfacial free-energy density τW for the infinite system, we were able to determine Δc and λ numerically in very good agreement with the theoretical prediction. We also discuss the associated free-energy barrier and its implication for multimagnetical simulations, and put these findings into context with the related droplet/strip transition respectively barrier

Particulate Matter Dispersion Modeling in Agricultural Applications: Investigation of a Transient Open Source Solver

Agriculture is a major emitter of particulate matter (PM), which causes health problems and can act as a carrier of the pathogen material that spreads diseases. The aim of this study was to investigate an open-source solver that simulates the transport and dispersion of PM for typical agricultural applications. We investigated a coupled Eulerian–Lagrangian solver within the open source software package OpenFOAM. The continuous phase was solved using transient large eddy simulations, where four different subgrid-scale turbulence models and an inflow turbulence generator were tested. The discrete phase was simulated using two different Lagrangian solvers. For the validation case of a turbulent flow of a street canyon, the flowfield could be recaptured very well, with errors of around 5% for the non-equilibrium turbulence models (WALE and dynamicKeq) in the main regions. The inflow turbulence generator could create a stable and accurate boundary layer for the mean vertical velocity and vertical profile of the turbulent Reynolds stresses R11. The validation of the Lagrangian solver showed mixed results, with partly good agreements (simulation results within the measurement uncertainty), and partly high deviations of up to 80% for the concentration of particles. The higher deviations were attributed to an insufficient turbulence regime of the used validation case, which was an experimental chamber. For the simulation case of PM dispersion from manure application on a field, the solver could capture the influence of features such as size and density on the dispersion. The investigated solver is especially useful for further investigations into time-dependent processes in the near-source area of PM sources

How the Selection of Training Data and Modeling Approach Affects the Estimation of Ammonia Emissions from a Naturally Ventilated Dairy Barn-Classical Statistics versus Machine Learning

Environmental protection efforts can only be effective in the long term with a reliable quantification of pollutant gas emissions as a first step to mitigation. Measurement and analysis strategies must permit the accurate extrapolation of emission values. We systematically analyzed the added value of applying modern machine learning methods in the process of monitoring emissions from naturally ventilated livestock buildings to the atmosphere. We considered almost 40 weeks of hourly emission values from a naturally ventilated dairy cattle barn in Northern Germany. We compared model predictions using 27 different scenarios of temporal sampling, multiple measures of model accuracy, and eight different regression approaches. The error of the predicted emission values with the tested measurement protocols was, on average, well below 20%. The sensitivity of the prediction to the selected training dataset was worse for the ordinary multilinear regression. Gradient boosting and random forests provided the most accurate and robust emission value predictions, accompanied by the second-smallest model errors. Most of the highly ranked scenarios involved six measurement periods, while the scenario with the best overall performance was: One measurement period in summer and three in the transition periods, each lasting for 14 days