Magnesium sheet alloys, such as wrought AZ31, have material properties that make them an attractive option for use in automotive and aircraft components. However, the low ductility of magnesium alloys at room temperature necessitates the use of high-temperature forming to manufacture complex components. Finite-element-method (FEM) simulations can assist in determining the optimum processing parameters for high-temperature forming, but only if an accurate material constitutive model is used. New material constitutive models describing the deformation behavior of AZ31 sheet at 450°C are proposed. These models account for both active deformation mechanisms at this temperature: grain-boundary-sliding creep and five-power dislocation-climb creep. Phenomena affecting these deformation mechanisms, such as material anisotropy and grain growth, are also investigated. This physics-based approach represents an improvement over previous material models, which require nonphysical parameters and can only predict forming for a limited range of conditions. Tensile tests are conducted to obtain data used in fitting constitutive models. New models are used in FEM simulations of both tensile tests and biaxial gas-pressure bulge tests. Simulation results are compared to experimental data for validation and determination of model accuracy. / text

The International Electrotechnical Commission (IEC) standard 61400-1 for the design of wind turbines does not explicitly address site-specific conditions associated with anomalous atmospheric events or conditions. Examples of such off-standard atmospheric conditions include thunderstorm downbursts, hurricanes, tornadoes, low-level jets, etc. This study is focused on the simulation of thunderstorm downbursts using a deterministic-stochastic hybrid model and the prediction of wind turbine loads resulting from these simulated downburst wind fields. The wind velocity field model for thunderstorm downburst simulation is first discussed; in this model, downburst winds are generated separately from non-turbulent and turbulent parts. The non-turbulent part is based on an available analytical model (with some modifications), while the turbulent part is simulated as a stochastic process using standard turbulence power spectral density functions and coherence functions. Tower and rotor loads are generated using simulation of the aeroelastic response for models of utility-scale wind turbines. The main objective is to improve our understanding from the point of view of design so that we may begin to address transient events such as thunderstorm downbursts based on the simulations carried out in this research study. The study discusses as well the role of control systems (for blade pitch and turbine yaw), of models for representing transient turbulence characteristics, and of correlated demand and loads on multiple units in turbine arrays during thunderstorm downbursts. / text

In today’s industrial world, there are high demands on the environmental aspects. Siemens Industrial Turbomachinery AB (SIT AB) is a company that is keen about the environment, and therefore spends a lot of effort in developing combustion processes in order to reduce NOx (nitrogen oxides) emissions on their engine products. They are also researching in optional fuels, which are more environment-friendly. In order to provide lower emissions the SIT designed a water rig to study the flow dynamics in a DLE (Dry Low Emission) burner. An analyze program (GUI horizontal) was developed with new functions and the existing functions were improved. The program’s function was to evaluate different experimental tests of the flow dynamics in the 3rd generation DLE burners, of the SGT-800 gas turbine engine. The aim was to ensure repeatability to enhance reliability, of the experimental test results for further comparison, for upcoming projects concerning future DLE burners. When repeatability was achieved, implementations of different geometrical modifications were performed in the 3rd generation DLE burner. The reason of the geometrical alterations was to look over if better fuel air mixture could be obtained and accordingly (thus) to reduce hotspots in the burner and in that case reduce NOx emissions.

In this thesis, the folding process of the de novo designed polypeptide chignolin was elucidated through atomic-scale Molecular Dynamics (MD) computer simulations. In a series of long timescale and replica exchange MD simulations, chignolin’s folding and unfolding was observed numerous times and the native state was identified from the computed Gibbs free-energy landscape. The rate of the self-assembly process was predicted from the replica exchange data through a novel algorithm and the structural fluctuations of an enzyme, lysozyme, were analyzed. DNA’s structural flexibility was investigated through experimental structure determination methods in the liquid and gas phase. DNA nanostructures could be maintained in a flat geometry when attached to an electrostatically charged, atomically flat surface and imaged in solution with an Atomic Force Microscope. Free in solution under otherwise identical conditions, the origami exhibited substantial compaction, as revealed by small angle X-ray scattering. This condensation was even more extensive in the gas phase. Protein folding is highly reproducible. It can rapidly lead to a stable state, which undergoes moderate fluctuations, at least for small structures. DNA maintains extensive structural flexibility, even when folded into large DNA origami. One may reflect upon the functional roles of proteins and DNA as a consequence of their atomic-level structural flexibility. DNA, biology’s information carrier, is very flexible and malleable, adopting to ever new conformations. Proteins, nature’s machines, faithfully adopt highly reproducible shapes to perform life’s functions robotically.

Recently it has been suggested that the use of neuromechanical simulations could be used to further our understanding of the neural control mechanisms involved in the control of animal locomotion. The models used to carry out these neuromechanical simulations typically consist of a representation of the neural control systems involved in walking and a representation of the mechanical locomotor apparatus. These separate models are then integrated to produce motion of the locomotor apparatus based on signals that are generated by the neural control models. Typically in past neuromechanical simulations of human walking the parameters of the neural control model have been specifically chosen to produce a walking pattern that resembles the normal human walking pattern as closely as possible. Relatively few of these studies have systematically tested the effect of manipulating the control parameters on the walking pattern that is produced by the locomotor apparatus. The goal of this thesis was to develop models of the locomotor control system and the human locomotor apparatus and systematically manipulate several parameters of the neural control system and determine what effects these parameters would have on the walking pattern of the mechanical model. Specifically neural control models were created of the Central Pattern Generator (CPG), feedback mechanisms from muscle spindles and contact sensors that detect when the foot was contact with the ground. Two models of the human locomotor apparatus were used to evaluate the outputs of the neural control systems; the first was a rod pendulum, which represented a swinging lower-limb, while the second was a 5-segment biped model, which included contact dynamics with the ground and a support system model to maintain balance. The first study of this thesis tested the ability of a CPG model to control the frequency and amplitude of the pendulum model of the lower-limb, with a strictly feedforward control mechanism. It was found that the frequency of the pendulum’s motion was directly linked (or entrained) to the frequency of the CPG’s output. It was also found that the amplitude of the pendulum’s motion was affected by the frequency of the CPG’s output, with the greatest amplitude of motion occurring when the frequency of the CPG matched the pendulum’s natural frequency. The effects of altering several other parameters of the pendulum model, such as the initial angle, the magnitude of the applied viscous damping or the moment arms of the muscles, were also analyzed. The second study again used the pendulum model, and added feedback to the neural control model, via output from simulated muscle spindles. The output from these spindle models was used to trigger a simulated stretch reflex. It was found that the addition of feedback led to sensory entrainment of the CPG output to the natural frequency of the pendulum. The effects of altering the muscle spindle’s sensitivity to length and velocity changes were also examined. The ability of this type of feedback system to respond to mechanical perturbations was also analyzed. The third and fourth studies used a biped model of the musculoskeletal system to assess the effects of altering the parameters of the neural control systems that were developed in the first two studies. In the third study, the neural control system consisted only of feedforward control from the CPG model. It was found that the walking speed of the biped model could be controlled by altering the frequency of the CPG’s output. It was also observed that variability of the walking pattern was decreased when there was a moderate level of inhibition between the CPGs of the left and right hip joints. The final study added feedback from muscle receptors and from contact sensors with the ground. It was found that the most important source of feedback was from the contact sensors to the extensor centres of the CPG. This feedback increased the level of extensor activity and produced significantly faster walking speeds when compared to other types of feedback. This thesis was successful in testing the effects of several control parameters of the neural control system on the movement of mechanical systems. Particularly important findings included the importance of connectivity between the CPGs of the left and right hip joints and positive feedback regarding the loading of the limb for establishing an appropriate forward walking speed. It is hoped that the models developed in this thesis can form the basis of future neuromechanical models and that the simulations carried out in this thesis help provide a better understanding of the interactions between neural and mechanical systems during the control of locomotion.

In order to reduce the discharge of the greenhouse gas CO2, the use of biomass is nowadays promoted as fuel in boilers. Compared to boilers fired with coal and oil the biomass-fired boilers have more complications related to both fouling and corrosion on the heat transfer surfaces. After the combustion, unburned inorganic matter in state of vapour, melts and solid particles are transported in the flue gas and may form deposits on heat transfer surfaces. Deposits on the heat transfer surfaces may result in both increasing corrosion and decreasing boiler efficiency as the heat transfer rate to the superheaters and reheaters decrease by deposits. In order to understand the process of deposit build-up, the whole combustion and transport process had to be analysed including aspects such as, boiler design, fuel properties and combustion environment, followed by particle transport phenomena and the probability for particles to get stuck on the heat transfer tubes. In this thesis numerical simulation of particle trajectories has been conducted as well as measurements of deposits on a special designed deposit probe followed by investigation of on-site measurements of deposit depth on the super-heater tubes in a circulating fluidised bed in Västerås, Sweden. Numerical simulations of particle trajectories in the vicinity of two super-heater tubes were conducted in an Eulerian-Lagrangian mode considering the flue gas and ash particles phase. Particle impingements on the tubes were investigated for different particle sizes. The results from the particle trajectory simulations show that particle larger than 10 µm will mainly impinge on the windward side of the first tube but, however also on the sides of the second tube in the flue gas flow direction. In theory as well as from observations and measurements two tubes can merge together by the deposit build-up. Smaller particles are usually more dispersed due to turbulence and thermophorectic forces, resulting in a more even impingement distribution on the whole surface of the tubes. Probe measurements reveal that the deposit layer growth rate have a significant temperature and time dependence. After the initial deposit build-up a sintering process occurs and sintering is also proven to be dependent on temperature and exposure time. Soot-blowing is the most common method to reduce the effect of deposits on the heat transfer tubes. In the present thesis the soot boiling efficiency is therefore also investigated. The soot-blowing show a strong positive effect on the heat transfer rate in a short time (hours) perspective after a soot-blowing cycle is completed. This positive effect is much weaker when considering a time period of three years. This is an effect of fact that soot-blowing mostly remove the loose part of the deposit material leaving the hard sintered part unaffected. The subject of deposit build up on superheater tubes in large scale boilers involves multi-discipline knowledge and historically, the related research is mostly conducted as measurements and experiments on operating plants. Possibly in the future, theoretical simulations will have a bigger part of research on deposit build-up where the calculations are to be calibrated through measurements on real sites plants.

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Biological transport is an essential phenomenon for the living systems. A mechanistic investigation of biological transport processes is highly important for the characterization of physiological and cellular events, the design and functioning of several biomedical devices and the development of new therapies. To investigate the physical-chemical details of this phenomenon, concerted efforts of both experiments and theory are necessary. Motor proteins constitute a major portion of the active transport in the living cell. However, the actual mechanism of how chemical energy is converted into their directed motion has still remained obscure. Recent experiments on motor proteins have been producing exciting results that have motivated theoretical studies. In order to provide deep insight onto motor protein's mechanochemical coupling we have used stochastic modeling based on discrete-state chemical kinetic model. Such models enable us to (1) resolve the contradiction between experimental observations on heterodimeric kinesins and highly popular hand-over-hand mechanism, (2) take into account the free energy landscape modification of individual motor domains due to interdomain interaction, (3) recognize the effect of spatial fluctuations on biochemical properties of molecular motors, and (4) calculate the dynamical properties such as velocities, dispersions of complex biochemical pathways. We have also initiated the investigation of the dynamics of coupled motor assemblies using stochastic modeling. Furthermore, an extensive Monte Carlo lattice simulation based study on facilitated search process of DNA-binding proteins is presented. This simulation shows that the accelerated search compared to pure Smoluchowski limit can be achieved even in the case where the one-dimensional diffusion is order of magnitude slower than the three-dimensional diffusion. We also show that facilitated search is not only the manifestation of dimensionality reduction but correlation times play a crucial role in the overall search times. Finally, a more general field of stochastic processes, namely first-passage time process is investigated. Explicit expressions of important properties, such as splitting probailities and mean first-passage times, that are relevant to (but not limited to) biological transport, are derived for several complex systems.

Monte Carlo simulations have been used in the past to investigate a variety of surfactant systems; however, there is little published literature for double-headed and gemini surfactants with asymmetric tails. We perform Larson-type Monte Carlo simulations of double-headed and gemini surfactant systems with asymmetric tails in two- and three-dimensions. The model predicts that the addition of a second head group to form a double-headed surfactant results in an increase in the critical micelle concentration (CMC) compared to a single-headed surfactant, in agreement with experiment. It also indicates that the placement of the second head group has an impact on the final CMC value. We study a series of gemini surfactants with asymmetric tails and find no change in the value of the CMC as the ratio of the lengths of the two tails increases. This is contrary to the only experimental study that found there was a slight decrease in the CMC as the ratio of the lengths of the two tails increases. We examine this difference in terms of the relatively small effect surfactant asymmetry has on value of the CMC and the fact that the model is capable of qualitatively reproducing the known dependence of the CMC on other architectural properties. This initial probe into systems of double-headed and gemini surfactants with asymmetric tails confirms many of the previously published findings and provides avenues for possible future research using Monte Carlo simulations.