Background and Objectives: Missing participant data are likely to bias the results of randomized control trials (RCTs) when the reason for missingness is associated with status on the outcome of interest. Unlike dichotomous MPD in RCTs, which have been thoroughly investigated, knowledge regarding continuous MPD in RCTs is much more limited. Our objectives were 1) using an adapted checklist, to assess the reporting quality of simulation studies comparing methods to deal with continuous MPD; 2) identify optimal methods proposed by biostatisticians and tested in simulations studies for continuous MPD in RCTs; 3) evaluate how authors report MPD, and how they plan and conduct analyses to deal with MPD in RCTs. Methods: We conducted two systematic surveys. The first identified methods papers published till 2015 January that compared statistical approaches to deal with continuous MPD in RCTs using at least one simulation. In this sample, we considered both the quality of reporting and the results. The second survey identified a representative sample of individual RCTs published in 2014 in core journals reporting the results of at least one continuous variable addressing a patient-important outcome. Results and conclusion: Our survey identified important limitations in reporting quality of simulation studies that compared statistical approaches to deal with continuous MPD, particularly in the reporting of simulation procedures. Only one of 60 studies reported the random number generator used and none reported starting seeds or failures during simulation. Less then half reported software used to perform simulation (41.7%) or analysis (48.3%), and only 4 (5%) reported justification of number of simulations. When facing continuous MPD in RCTs, results of simulation studies demonstrate that trialists seeking optimal approaches may choose robust regression or mixed models and avoid using last observation caring forward. Continuous MPD frequently occurs in RCTs and the extent is typically substantial (median greater than 10%). Methods sections in trial reports typically do not provide adequate detail on how they dealt with MPD in their primary analysis. Among methods actually implemented to deal with MPD, most authors use only available data, thus excluding MPD from the analysis. Seldom do investigators apply statistical approaches to impute or taking into account of MPD nor conduct sensitivity analysis to address the impact of it. A comprehensive knowledge synthesis summarizing current available statistical approaches and its relative merits, as well as the current used methods in RCTs provide clear implications on how the practise of using methods to handle continuous MPD should shift in individual RCTs. Trialists should use mixed models and robust regressions and avoid using last observation caring forward method. / Thesis / Doctor of Philosophy (PhD)

A scaled gradient descent method for competition of applications of conjugate gradient with priori estimations of the minimum value / This research proposes a novel method of improving the Gradient Descent method in an effort to be competitive with applications of the conjugate gradient method while reducing computation per iteration. Iterative methods for unconstrained optimization have found widespread application in digital signal processing applications for large inverse problems, such as the use of conjugate gradient for parallel image reconstruction in MR Imaging. In these problems, very good estimates of the minimum value at the objective function can be obtained by estimating the noise variance in the signal, or using additional measurements. The method proposed uses an estimation of the minimum to develop a scaling for Gradient Descent at each iteration, thus avoiding the necessity of a computationally extensive line search. A sufficient condition for convergence and proof are provided for the method, as well as an analysis of convergence rates for varying conditioned problems. The method is compared against the gradient descent and conjugate gradient methods. A method with a computationally inexpensive scaling factor is achieved that converges linearly for well-conditioned problems. The method is tested with tricky non-linear problems against gradient descent, but proves unsuccessful without augmenting with a line search. However with line search augmentation the method still outperforms gradient descent in iterations. The method is also benchmarked against conjugate gradient for linear problems, where it achieves similar convergence for well-conditioned problems even without augmenting with a line search. / Thesis / Master of Science (MSc) / This research proposes a novel method of improving the Gradient Descent method in an effort to be competitive with applications of the conjugate gradient method while reducing computation per iteration. Iterative methods for unconstrained optimization have found widespread application in digital signal processing applications for large inverse problems, such as the use of conjugate gradient for parallel image reconstruction in MR Imaging. In these problems, very good estimates of the minimum value at the objective function can be obtained by estimating the noise variance in the signal, or using additional measurements. The method proposed uses an estimation of the minimum to develop a scaling for Gradient Descent at each iteration, thus avoiding the necessity of a computationally extensive line search. A sufficient condition for convergence and proof are provided for the method, as well as an analysis of convergence rates for varying conditioned problems. The method is compared against the gradient descent and conjugate gradient methods. A method with a computationally inexpensive scaling factor is achieved that converges linearly for well-conditioned problems. The method is tested with tricky non-linear problems against gradient descent, but proves unsuccessful without augmenting with a line search. However with line search augmentation the method still outperforms gradient descent in iterations. The method is also benchmarked against conjugate gradient for linear problems, where it achieves similar convergence for well-conditioned problems even without augmenting with a line search.

No / Paper accepted for conference.

Carbon fibres are used in many applications thanks to their exceptional tensile properties in relation to their relatively low weight. These thin strands of at least 90% carbon are mixed with a matrix such as epoxy to form composites used for cars, wind turbines, prosthetics, and many other things. Carbon fibres are often manufactured from polyacrylonitrile (PAN) based on fossil oil, an expensive and non-renewable resource. Developing carbon fibres from renewable resources, like products from the forest industry such as lignin and cellulose could reduce the environmental impact of carbon fibre production. Cellulose precursors have long been used for carbon fibre production, but adding lignin could potentially increase the yield and improve the tensile properties of the carbon fibres. The transition from PAN carbon fibres to lignin-cellulose carbon fibres might also lower the cost. Currently, the properties of cellulose- and lignin-based carbon fibres are poor compared to other fibres on the market. Research like this work focuses on improving the tensile properties of the carbon fibres to make them viable alternatives. The focus of this work was to further develop the three main parts of thermal conversion: stabilisation, low-temperature carbonisation and high-temperature carbonisation, by evaluating the impact of temperature and tension on the tensile properties of the fibre. The fibres were converted using a continuous setup for each process step. The stabilisation profiles tested ranged between 245-260 ⁰C, low-temperature carbonisation between 460-600 ⁰C and high- temperature carbonisation between 1100-1600 ⁰C. Batch conversion was conducted to compare conversion methods. The results showed that the temperature of the low-temperature carbonisation had a large impact on the ability to stretch the carbon fibre and increase the tensile properties with 600 ⁰C being the optimal temperature out of the temperatures tested on the setup used in this thesis. The stretching during the high-temperature carbonisation and the temperature of the stabilisation had less impact on tensile properties. The properties of the precursor fibre are not always indicative of the properties of the carbon fibre, but the methods used for creating the precursor fibres have a great impact on the behaviour during thermal conversion.

In order to improve the continuous casting process of steel, it’s important to have an understanding of the fuid mechanics of the casting process. As experiments on a real caster are usually impractical, both physical and numerical modeling are important for creating this understanding. This report concerns itself with the creation of a numerical model of a physical model of a slab caster, which uses eutectic bismuth-tin alloy to simulate steel, and is built and operated by Swerim in Luleå, Sweden. The geometry of the model was constructed in Siemens NX, and meshing was done using Ansys Meshing. The CFD model itself was made in Ansys Fluent, and data from previous experiments on the physical model was used to verify it. The numerical model does not model any discrete phases in the liquid metal, including slag, argon fow, solid particles or any form of phase transition or heat transfer. The model uses a pump to continuously recirculate the liquid metal into the tundish, from where it fows down into the mold. Qualitatively, the model shows the expected double-roll fow pattern in the mold, and also pressure gradients in the SEN entry region which are consistent with experimental data. Verifcation was done using experimentally determined pump curves, for which the model shows reasonable behavior for mass fows above roughly 20 kg/s, but deviates somewhat below this value. Verifcation was also done using data for mass fows out of the tundish, which is regulated by the stopper position. Here, a large discrepancy between experimental and simulated data is present. Several explanations for this discrepancy were investigated, including the possibility of improper calibration of the stopper positional tracking and incorrect data for dynamic viscosity of the alloy, but the most likely explanation is that cavitation occurs in the SEN entry region due to a large pressure drop which occurs in this region. Cavitation is not implemented in the model, which leads to incorrect mass fow out of the tundish. If this fow is to be accurately captured, it is likely necessary to implement cavitation modeling in future versions of the numerical model.

Master of Science / Material extrusion is a common form of 3D printing that has historically been limited to producing prototypes, models, and low load-bearing parts. This is primarily because parts are manufactured layer-by-layer, resulting in poor adhesion along the build direction, and machines struggle to print with high-strength polymers, which tend to shrink significantly as they cool. However, one way to address these limitations is to use fiber-reinforced materials in combination with multi-axis deposition strategies. In material extrusion, embedded fibers will align themselves along the deposition path, providing structural, thermal, and chemical improvements. Multi-axis toolpathing can enable the deposition of this fiber-filled material in full 3D along a part's expected stress paths. This is possible using a complex kinematic system like an industrial robot arm that can rotate the angle of the tool relative to the part as it is printing. The objective of this work was to develop and test a tool capable of multi-axis continuous carbon fiber reinforcement, which required a dedicated cutting mechanism to shear the fiber at the end of each deposition path, control over the amount of fiber used, and a slender tool profile to avoid collisions during multi-axis printing. The findings of this work revealed that while the use of continuous carbon fiber further reduced the adhesion between deposition paths, it substantially improved the strength of the part along them. To validate the multi-axis capability of the system, a toolpath was generated for a curved tensile bar. The results showed that the continuous carbon fiber multi-axis toolpath resisted a load 820.57% higher than an XY-planar sliced part printed with traditional filament, confirming the effectiveness of the presented approach. Multi-axis motion can also be used for avoiding support material requirements. In traditional 3-axis material extrusion, steep overhanging features often require additional, sacrificial material to be printed underneath. This leads to longer print times, more material waste, and a poor surface finish left behind on the final part. To minimize the amount of support material required, various techniques have been explored, including changing the toolpath, part geometry, or material processing parameters. However, none of these techniques have been successful in eliminating the need for supports entirely. A promising approach to address this issue is multi-axis material extrusion, where the angle of the printing tool and the direction of the layers can be precisely controlled during the printing process. This technique can be used to ensure that the tool is always extruding material onto a well-supported surface, rather than over thin air. However, research to date has not yet fully explored how the range of achievable overhang features changes as the tool is rotated. To address this knowledge gap, this work used an industrial robot arm equipped for material extrusion to investigate the relationship between tool angle, build direction, and achievable overhang threshold. The results showed that the same overhang limitations that exist in the XY plane will rotate with the tool and are unaffected by gravitational forces. These findings provide valuable insights for advancing the use of multi-axis material extrusion in the production of complex and intricate 3D objects without the need of supports.

Thermoset resin based fibre reinforced polymer-matrix composite materials (PMCs) have provided excellent solutions to many industries based on their great specific strength, high design freedom and other characteristics such as water resistance, corrosion resistance, tailorable electrical conductivity, tailorable thermal performance and many others. But, despite of all their benefits, the materials are also limited by uneconomical recycling and management post service life, demanding raw materials storage conditions, less than ideal environmental impact during manufacturing, and relatively low productivity. The purpose of the present work was to investigate economically feasible production of a continuous fibre reinforced thermoplastic composite (CFRTP) alternative solution, for an existing company, that could overcome weak points and limitations of thermosets under increasing environmental needs and pursuit of higher efficiency. Work aimed at fulfilling the following objectives: 1) document existing thermoplastic composite materials and understand selected manufacturing methods, raw materials, mechanical behaviour and operational feasibility; 2) select, design, and build a fully functional CFRTP manufacturing line; 3) design and run Taguchi methods to analyze the product using multifactorial ANOVA to gently introduce rigorous quality control; and 4) identify the input parameters that most affect output product quality, that could be used to optimize the process, as well as input parameters that have no statistically significant effects on the output and therefore do not warrant investment in funds and time in order to control them. Throughout the work, it was showed that CFRTP could been produced efficiently with consistent quality. Unidirectional prepreg can be used directly or further processed for usage in many industries such as pipelines, light construction and automotive components. The design of the CFRTP solution fulfilled necessary conditions and successfully produced CFRTP unidirectional prepreg product. Prepreg produced under 16 different sets of conditions was tested and data was collected. Using Taguchi methods, this study found that the fibre volume fraction, condition of impregnation mould, condition of cooling rollers and extruding temperature all have statistically significant effects on product quality. But limited by restriction from time and cost by production based environments, it is imperative to conduct this work perfectly, in later research a more focused study can be done based on the results of this study. Still, thesis demonstrates a CFRTP mass production solution, verifies CFRTP impregnation and offers a significant route for upgrading environmental protection and production efficiency. The work also identifies key parameters that affect unidirectional prepregs properties.

To better understand the facets of nutrient utilization, a series of in vivo and in vitro studies were undertaken to elucidate the effect of supplementation on utilization of moderate-quality bermudagrass hay and to identify mechanisms to evaluate the role of rumen bacterial populations on feedstuff utilization. A digestion trial was conducted using 6 ruminally cannulated steers receiving bermudagrass hay supplemented with soybean hulls (HULLS), cracked corn (CORN), or soybean hulls and cracked corn (MIX; 75% and 25%, respectively) in a 3x3 Latin Rectangle arrangement. Additionally, ruminal fluid was continuously cultured using the BioFlo® 110 fermentation system to evaluate the in vitro fermentive parameters of ground moderate-quality bermudagrass hay either alone (HAY; 20 g DM L-1 d-1) or supplemented (7 g DM L-1 d-1) with corn (CORN), soybean hulls (SBH), or both (25:75; MIX) in a randomized complete block. Genomic DNA from continuous culture as well as from pure bacterial culture samples were sought to differentially enumerate select bacterial strains via real-time PCR using specie-specific DNA primers. The information is to be used for elucidating responses in ruminal digestibility of varying feed-types. Finally, as an alternative to PCR, bioluminescence of transformed Escherichia coli was evaluated by measuring extent of photonic emission with and without antibiotic selection over time. Evaluations were also made of photonic emission by E. coli grown in ruminal fluid with and without additional feed particles. Data seem to indicate that replacing a portion of corn with soybean hulls may successfully improved fiber digestion and improved ruminal N-utilization. Real-time PCR shows potential for evaluating ruminal bacteria where as biophotonics may need further modification before meaningful in situ evaluations of live ruminants can be employed.

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