COMPUTATIONAL ANALYSIS OF THE AEROELASTIC DYNAMICS OF A WIND TURBINE BLADE WITH VARIABLE-SPEED STALL CONTROL

The accuracy of simulating the aerodynamics and structural properties of the blades is crucial in the wind-turbine technology. Hence the models used to implement these features need to be very precise and their level of detailing needs to be high. With the variety of blade designs being developed the models should be versatile enough to adapt to the changes required by every design. We are going to implement a combination of numerical models which are associated with the structural and the aerodynamic part of the simulation using the computational power of a parallel HPC cluster. The structural part models the heterogeneous internal structure of the beam based on a novel implementation of the Generalized Timoshenko Beam Model Technique.. Using this technique the 3-D structure of the blade is reduced into a 1-D beam which is asymptotically equivalent. This reduces the computational cost of the model without compromising its accuracy. This structural model interacts with the Flow model which is a modified version of the Blade Element Momentum Theory. The modified version of the BEM accounts for the large deflections of the blade and also considers the pre-defined structure of the blade. The coning, sweeping of the blade, tilt of the nacelle and the twist of the sections along the blade length are all computed by the model which aren’t considered in the classical BEM theory. Each of these two models provides feedback to the other and the interactive computations lead to more accurate outputs. We successfully implemented the computational models to analyze and simulate the structural and aerodynamic aspects of the blades. The interactive nature of these models and their ability to recompute data using the feedback from each other makes this code more efficient than the commercial codes available. In this thesis we start off with the verification of these models by testing it on the well-known benchmark blade for the NREL-5MW Reference Wind Turbine, an alternative fixed-speed stall-controlled blade design proposed by Delft University, and a novel alternative design that we proposed for a variable-speed stall-controlled turbine, which offers the potential for more uniform power control and improved annual energy production.. To optimize the power output of the stall-controlled blade we modify the existing designs and study their behavior using the aforementioned aero elastic model.

DESIGN AND IMPLEMENT DYNAMIC PROGRAMMING BASED DISCRETE POWER LEVEL SMART HOME SCHEDULING USING FPGA

With the development and capabilities of the Smart Home system, people today are entering an era in which household appliances are no longer just controlled by people, but also operated by a Smart System. This results in a more efficient, convenient, comfortable, and environmentally friendly living environment. A critical part of the Smart Home system is Home Automation, which means that there is a Micro-Controller Unit (MCU) to control all the household appliances and schedule their operating times. This reduces electricity bills by shifting amounts of power consumption from the on-peak hour consumption to the off-peak hour consumption, in terms of different “hour price”. In this paper, we propose an algorithm for scheduling multi-user power consumption and implement it on an FPGA board, using it as the MCU. This algorithm for discrete power level tasks scheduling is based on dynamic programming, which could find a scheduling solution close to the optimal one. We chose FPGA as our system’s controller because FPGA has low complexity, parallel processing capability, a large amount of I/O interface for further development and is programmable on both software and hardware. In conclusion, it costs little time running on FPGA board and the solution obtained is good enough for the consumers.

Liraglutide once a day versus exenatide twice a day for type 2 diabetes: a 26-week randomised, parallel-group, multinational, open-label trial (LEAD-6)

BACKGROUND: Unlike most antihyperglycaemic drugs, glucagon-like peptide-1 (GLP-1) receptor agonists have a glucose-dependent action and promote weight loss. We compared the efficacy and safety of liraglutide, a human GLP-1 analogue, with exenatide, an exendin-based GLP-1 receptor agonist. METHODS: Adults with inadequately controlled type 2 diabetes on maximally tolerated doses of metformin, sulphonylurea, or both, were stratified by previous oral antidiabetic therapy and randomly assigned to receive additional liraglutide 1.8 mg once a day (n=233) or exenatide 10 microg twice a day (n=231) in a 26-week open-label, parallel-group, multinational (15 countries) study. The primary outcome was change in glycosylated haemoglobin (HbA(1c)). Efficacy analyses were by intention to treat. The trial is registered with ClinicalTrials.gov, number NCT00518882. FINDINGS: Mean baseline HbA(1c) for the study population was 8.2%. Liraglutide reduced mean HbA(1c) significantly more than did exenatide (-1.12% [SE 0.08] vs -0.79% [0.08]; estimated treatment difference -0.33; 95% CI -0.47 to -0.18; p<0.0001) and more patients achieved a HbA(1c) value of less than 7% (54%vs 43%, respectively; odds ratio 2.02; 95% CI 1.31 to 3.11; p=0.0015). Liraglutide reduced mean fasting plasma glucose more than did exenatide (-1.61 mmol/L [SE 0.20] vs -0.60 mmol/L [0.20]; estimated treatment difference -1.01 mmol/L; 95% CI -1.37 to -0.65; p<0.0001) but postprandial glucose control was less effective after breakfast and dinner. Both drugs promoted similar weight losses (liraglutide -3.24 kg vs exenatide -2.87 kg). Both drugs were well tolerated, but nausea was less persistent (estimated treatment rate ratio 0.448, p<0.0001) and minor hypoglycaemia less frequent with liraglutide than with exenatide (1.93 vs 2.60 events per patient per year; rate ratio 0.55; 95% CI 0.34 to 0.88; p=0.0131; 25.5%vs 33.6% had minor hypoglycaemia). Two patients taking both exenatide and a sulphonylurea had a major hypoglycaemic episode. INTERPRETATION: Liraglutide once a day provided significantly greater improvements in glycaemic control than did exenatide twice a day, and was generally better tolerated. The results suggest that liraglutide might be a treatment option for type 2 diabetes, especially when weight loss and risk of hypoglycaemia are major considerations.

An insulin infusion advisory system for type 1 diabetes patients based on non-linear model predictive control methods

In this paper, an Insulin Infusion Advisory System (IIAS) for Type 1 diabetes patients, which use insulin pumps for the Continuous Subcutaneous Insulin Infusion (CSII) is presented. The purpose of the system is to estimate the appropriate insulin infusion rates. The system is based on a Non-Linear Model Predictive Controller (NMPC) which uses a hybrid model. The model comprises a Compartmental Model (CM), which simulates the absorption of the glucose to the blood due to meal intakes, and a Neural Network (NN), which simulates the glucose-insulin kinetics. The NN is a Recurrent NN (RNN) trained with the Real Time Recurrent Learning (RTRL) algorithm. The output of the model consists of short term glucose predictions and provides input to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. For the development and the evaluation of the IIAS, data generated from a Mathematical Model (MM) of a Type 1 diabetes patient have been used. The proposed control strategy is evaluated at multiple meal disturbances, various noise levels and additional time delays. The results indicate that the implemented IIAS is capable of handling multiple meals, which correspond to realistic meal profiles, large noise levels and time delays.

Verbal instructions and top-down saccade control.

Few studies have addressed the interaction between instruction content and saccadic eye movement control. To assess the impact of instructions on top-down control, we instructed 20 healthy volunteers to deliberately delay saccade triggering, to make inaccurate saccades or to redirect saccades--i.e. to glimpse towards and then immediately opposite to the target. Regular pro- and antisaccade tasks were used for comparison. Bottom-up visual input remained unchanged and was a gap paradigm for all instructions. In the inaccuracy and delay tasks, both latencies and accuracies were detrimentally impaired by either type of instruction and the variability of latency and accuracy was increased. The intersaccadic interval (ISI) required to correct erroneous antisaccades was shorter than the ISI for instructed direction changes in the redirection task. The word-by-word instruction content interferes with top-down saccade control. Top-down control is a time consuming process, which may override bottom-up processing only during a limited time period. It is questionable whether parallel processing is possible in top-down control, since the long ISI for instructed direction changes suggests sequential planning.

Searching for the majority: algorithms of voluntary control.

Voluntary control of information processing is crucial to allocate resources and prioritize the processes that are most important under a given situation; the algorithms underlying such control, however, are often not clear. We investigated possible algorithms of control for the performance of the majority function, in which participants searched for and identified one of two alternative categories (left or right pointing arrows) as composing the majority in each stimulus set. We manipulated the amount (set size of 1, 3, and 5) and content (ratio of left and right pointing arrows within a set) of the inputs to test competing hypotheses regarding mental operations for information processing. Using a novel measure based on computational load, we found that reaction time was best predicted by a grouping search algorithm as compared to alternative algorithms (i.e., exhaustive or self-terminating search). The grouping search algorithm involves sampling and resampling of the inputs before a decision is reached. These findings highlight the importance of investigating the implications of voluntary control via algorithms of mental operations.

Numerical solution of optimal control problems with constant control delays

We investigate a class of optimal control problems that exhibit constant exogenously given delays in the control in the equation of motion of the differential states. Therefore, we formulate an exemplary optimal control problem with one stock and one control variable and review some analytic properties of an optimal solution. However, analytical considerations are quite limited in case of delayed optimal control problems. In order to overcome these limits, we reformulate the problem and apply direct numerical methods to calculate approximate solutions that give a better understanding of this class of optimization problems. In particular, we present two possibilities to reformulate the delayed optimal control problem into an instantaneous optimal control problem and show how these can be solved numerically with a stateof- the-art direct method by applying Bock’s direct multiple shooting algorithm. We further demonstrate the strength of our approach by two economic examples.

Low-frequency drug-resistant HIV-1 and risk of virological failure to first-line NNRTI-based ART: a multicohort European case-control study using centralized ultrasensitive 454 pyrosequencing.

OBJECTIVES It is still debated if pre-existing minority drug-resistant HIV-1 variants (MVs) affect the virological outcomes of first-line NNRTI-containing ART. METHODS This Europe-wide case-control study included ART-naive subjects infected with drug-susceptible HIV-1 as revealed by population sequencing, who achieved virological suppression on first-line ART including one NNRTI. Cases experienced virological failure and controls were subjects from the same cohort whose viraemia remained suppressed at a matched time since initiation of ART. Blinded, centralized 454 pyrosequencing with parallel bioinformatic analysis in two laboratories was used to identify MVs in the 1%-25% frequency range. ORs of virological failure according to MV detection were estimated by logistic regression. RESULTS Two hundred and sixty samples (76 cases and 184 controls), mostly subtype B (73.5%), were used for the analysis. Identical MVs were detected in the two laboratories. 31.6% of cases and 16.8% of controls harboured pre-existing MVs. Detection of at least one MV versus no MVs was associated with an increased risk of virological failure (OR = 2.75, 95% CI = 1.35-5.60, P = 0.005); similar associations were observed for at least one MV versus no NRTI MVs (OR = 2.27, 95% CI = 0.76-6.77, P = 0.140) and at least one MV versus no NNRTI MVs (OR = 2.41, 95% CI = 1.12-5.18, P = 0.024). A dose-effect relationship between virological failure and mutational load was found. CONCLUSIONS Pre-existing MVs more than double the risk of virological failure to first-line NNRTI-based ART.

Biological variation of established and novel biomarkers for atherosclerosis: Results from a prospective, parallel-group cohort study.

BACKGROUND Biomarkers are a promising tool for the management of patients with atherosclerosis, but their variation is largely unknown. We assessed within-subject and between-subject biological variation of biomarkers in peripheral artery disease (PAD) patients and healthy controls, and defined which biomarkers have a favorable variation profile for future studies. METHODS Prospective, parallel-group cohort study, including 62 patients with stable PAD (79% men, 65±7years) and 18 healthy control subjects (44% men, 57±7years). Blood samples were taken at baseline, and after 3-, 6-, and 12-months. We calculated within-subject (CVI) and between-subject (CVG) coefficients of variation and intra-class correlation coefficient (ICC). RESULTS Mean levels of D-dimer, hs-CRP, IL-6, IL-8, MMP-9, MMP-3, S100A8/A9, PAI-1, sICAM-1, and sP-selectin levels were higher in PAD patients than in healthy controls (P≤.05 for all). CVI and CVG of the different biomarkers varied considerably in both groups. An ICC≥0.5 (indicating moderate-to-good reliability) was found for hs-CRP, D-Dimer, E-selectin, IL-10, MCP-1, MMP-3, oxLDL, sICAM-1 and sP-selectin in both groups, for sVCAM in healthy controls and for MMP-9, PAI-1 and sCD40L in PAD patients. CONCLUSIONS Single biomarker measurements are of limited utility due to large within-subject variation, both in PAD patients and healthy subjects. D-dimer, hs-CRP, MMP-9, MMP-3, PAI-1, sP-selectin and sICAM-1 are biomarkers with both higher mean levels in PAD patients and a favorable variation profile making them most suitable for future studies.

A Parallel Solver for the Time-Periodic Navier–Stokes Equations

We investigate parallel algorithms for the solution of the Navier–Stokes equations in space-time. For periodic solutions, the discretized problem can be written as a large non-linear system of equations. This system of equations is solved by a Newton iteration. The Newton correction is computed using a preconditioned GMRES solver. The parallel performance of the algorithm is illustrated.

SOP: Parallel surrogate global optimization with Pareto center selection for computationally expensive single objective problems

This paper presents a parallel surrogate-based global optimization method for computationally expensive objective functions that is more effective for larger numbers of processors. To reach this goal, we integrated concepts from multi-objective optimization and tabu search into, single objective, surrogate optimization. Our proposed derivative-free algorithm, called SOP, uses non-dominated sorting of points for which the expensive function has been previously evaluated. The two objectives are the expensive function value of the point and the minimum distance of the point to previously evaluated points. Based on the results of non-dominated sorting, P points from the sorted fronts are selected as centers from which many candidate points are generated by random perturbations. Based on surrogate approximation, the best candidate point is subsequently selected for expensive evaluation for each of the P centers, with simultaneous computation on P processors. Centers that previously did not generate good solutions are tabu with a given tenure. We show almost sure convergence of this algorithm under some conditions. The performance of SOP is compared with two RBF based methods. The test results show that SOP is an efficient method that can reduce time required to find a good near optimal solution. In a number of cases the efficiency of SOP is so good that SOP with 8 processors found an accurate answer in less wall-clock time than the other algorithms did with 32 processors.

Environmental control on the occurrence of high-coercivity magnetic minerals and formation of iron sulfides in a 640 ka sediment sequence from Lake Ohrid (Balkans)

The bulk magnetic mineral record from Lake Ohrid, spanning the past 637 kyr, reflects large-scale shifts in hydrological conditions, and, superimposed, a strong signal of environmental conditions on glacial–interglacial and millennial timescales. A shift in the formation of early diagenetic ferrimagnetic iron sulfides to siderites is observed around 320 ka. This change is probably associated with variable availability of sulfide in the pore water. We propose that sulfate concentrations were significantly higher before  ∼  320 ka, due to either a higher sulfate flux or lower dilution of lake sulfate due to a smaller water volume. Diagenetic iron minerals appear more abundant during glacials, which are generally characterized by higher Fe / Ca ratios in the sediments. While in the lower part of the core the ferrimagnetic sulfide signal overprints the primary detrital magnetic signal, the upper part of the core is dominated by variable proportions of high- to low-coercivity iron oxides. Glacial sediments are characterized by high concentration of high-coercivity magnetic minerals (hematite, goethite), which relate to enhanced erosion of soils that had formed during preceding interglacials. Superimposed on the glacial–interglacial behavior are millennial-scale oscillations in the magnetic mineral composition that parallel variations in summer insolation. Like the processes on glacial–interglacial timescales, low summer insolation and a retreat in vegetation resulted in enhanced erosion of soil material. Our study highlights that rock-magnetic studies, in concert with geochemical and sedimentological investigations, provide a multi-level contribution to environmental reconstructions, since the magnetic properties can mirror both environmental conditions on land and intra-lake processes.

Impact of reactive oxygen species (ROS) on the control of parasite loads and inflammation in Leishmania amazonensis infection

Background: Reactive oxygen species (ROS) protect the host against a large number of pathogenic microorganisms. ROS have different effects on parasites of the genus Leishmania: some parasites are susceptible to their action, while others seem to be resistant. The role of ROS in L. amazonensis infection in vivo has not been addressed to date. Methods: In this study, C57BL/6 wild-type mice (WT) and mice genetically deficient in ROS production by phagocytes (gp91phox−/− ) were infected with metacyclic promastigotes of L. amazonensis to address the effect of ROS in parasite control. Inflammatory cytokines, parasite loads and myeloperoxidase (MPO) activity were evaluated. In parallel, in vitro infection of peritoneal macrophages was assessed to determine parasite killing, cytokine, NO and ROS production. Results: In vitro results show induction of ROS production by infected peritoneal macrophages, but no effect in parasite killing. Also, ROS do not seem to be important to parasite killing in vivo, but they control lesion sizes at early stages of infection. IFN-γ, TNF-α and IL-10 production did not differ among mouse strains. Myeloperoxidase assay showed augmented neutrophils influx 6 h and 72 h post - infection in gp91phox−/− mice, indicating a larger inflammatory response in gp91phox−/− even at early time points. At later time points, neutrophil numbers in lesions correlated with lesion size: larger lesions in gp91phox−/− at earlier times of infection corresponded to larger neutrophil infiltrates, while larger lesions in WT mice at the later points of infection also displayed larger numbers of neutrophils. Conclusion: ROS do not seem to be important in L. amazonensis killing, but they regulate the inflammatory response probably by controlling neutrophils numbers in lesions.

Multiple gradient echo propeller (MGREP) MRI: Technical development and potential applications

The PROPELLER (Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction) magnetic resonance imaging (MRI) technique has inherent advantages over other fast imaging methods, including robust motion correction, reduced image distortion, and resistance to off-resonance effects. These features make PROPELLER highly desirable for T2*-sensitive imaging, high-resolution diffusion imaging, and many other applications. However, PROPELLER has been predominantly implemented as a fast spin-echo (FSE) technique, which is insensitive to T2* contrast, and requires time-inefficient signal averaging to achieve adequate signal-to-noise ratio (SNR) for many applications. These issues presently constrain the potential clinical utility of FSE-based PROPELLER. ^ In this research, our aim was to extend and enhance the potential applications of PROPELLER MRI by developing a novel multiple gradient echo PROPELLER (MGREP) technique that can overcome the aforementioned limitations. The MGREP pulse sequence was designed to acquire multiple gradient-echo images simultaneously, without any increase in total scan time or RF energy deposition relative to FSE-based PROPELLER. A new parameter was also introduced for direct user-control over gradient echo spacing, to allow variable sensitivity to T2* contrast. In parallel to pulse sequence development, an improved algorithm for motion correction was also developed and evaluated against the established method through extensive simulations. The potential advantages of MGREP over FSE-based PROPELLER were illustrated via three specific applications: (1) quantitative T2* measurement, (2) time-efficient signal averaging, and (3) high-resolution diffusion imaging. Relative to the FSE-PROPELLER method, the MGREP sequence was found to yield quantitative T2* values, increase SNR by ∼40% without any increase in acquisition time or RF energy deposition, and noticeably improve image quality in high-resolution diffusion maps. In addition, the new motion algorithm was found to improve the performance considerably in motion-artifact reduction. ^ Overall, this work demonstrated a number of enhancements and extensions to existing PROPELLER techniques. The new technical capabilities of PROPELLER imaging, developed in this thesis research, are expected to serve as the foundation for further expanding the scope of PROPELLER applications. ^

An empirical evaluation of the Random Forests classifier models for variable selection in a large-scale lung cancer case-control study

Random Forests™ is reported to be one of the most accurate classification algorithms in complex data analysis. It shows excellent performance even when most predictors are noisy and the number of variables is much larger than the number of observations. In this thesis Random Forests was applied to a large-scale lung cancer case-control study. A novel way of automatically selecting prognostic factors was proposed. Also, synthetic positive control was used to validate Random Forests method. Throughout this study we showed that Random Forests can deal with large number of weak input variables without overfitting. It can account for non-additive interactions between these input variables. Random Forests can also be used for variable selection without being adversely affected by collinearities. ^ Random Forests can deal with the large-scale data sets without rigorous data preprocessing. It has robust variable importance ranking measure. Proposed is a novel variable selection method in context of Random Forests that uses the data noise level as the cut-off value to determine the subset of the important predictors. This new approach enhanced the ability of the Random Forests algorithm to automatically identify important predictors for complex data. The cut-off value can also be adjusted based on the results of the synthetic positive control experiments. ^ When the data set had high variables to observations ratio, Random Forests complemented the established logistic regression. This study suggested that Random Forests is recommended for such high dimensionality data. One can use Random Forests to select the important variables and then use logistic regression or Random Forests itself to estimate the effect size of the predictors and to classify new observations. ^ We also found that the mean decrease of accuracy is a more reliable variable ranking measurement than mean decrease of Gini. ^