Aerodynamic, structural and aero-elasticity modelling of large composite wind turbine blades

Large wind turbine blades, manufactured from fibre reinforced laminated composite materials, are key structural components of wind turbine systems. The demands for efficient and accurate modelling techniques of these composite blades have significantly increased. Over past decades, although complex computational models have been widely developed, more analytically based models are still very much desired to drive the design and optimization of these composite blades forward to be lighter, stronger, efficient and durable. The research work in this thesis aims to develop such more analytically based aerodynamic, structural and aero-elasticity models for large wind turbine blades manufactured from fibre reinforced laminated composite materials. Firstly, an improved blade element momentum (BEM) model has been developed by collectively integrating the individual corrections with the classic BEM model. Compared to other existing models, present BEM model accounts for blade tip and root losses more accurately. For laminar flow, the 3-D cross-flow is negligibly small. In this case, present BEM model with statically measured 2-D aerodynamic coefficients agrees closely to experimental measurements. However, stall delay correction is required for a 3-D rotating blade in stall. A new stall delay model is developed based on Snel s stall delay model. Verifications are performed and discussed for the extensively studied NREL UAE phase-VI test. The predictions of distributive and collective factors, e.g. normalised force coefficients, shaft torque and etc. have been compared to experimental measurements. The present BEM model and stall delay model are original and more accurate than existing models. Secondly, significant deficiency is discovered in the analytical thin-walled closed-section composite beam (TWCSCB) model proposed by Librescu and Vo, which is widely used by others for structural modelling of wind turbine blades. To correct such deficiency, an improved TWCSCB model is developed in a novel manner that is applicable to both single-cell and multi-cell closed sections made of arbitrary composite laminates. The present TWCSCB model has been validated for a variety of geometries and arbitrary laminate layups. The numerical verifications are also performed on a realistic wind turbine blade (NPS-100) for structural analysis. Consistently accurate correlations are found between present TWCSCB model and the ABAQUS finite element (FE) shell model. Finally, the static aero-elasticity model is developed by combining the developed BEM model and TWCSCB model. The interactions are accounted through an iterative process. The numerical applications are carried out on NPS-100 wind turbine. The numerical results show some significant corrections by modelling wind turbine blades with elastic coupling

Enhancing the SST Turbulence Model with Symbolic Regression: A Generalizable and Interpretable Data-Driven Approach

Turbulence modeling within the RANS equations' framework is essential in engineering due to its high efficiency. Field inversion and machine learning (FIML) techniques have improved RANS models' predictive capabilities for separated flows. However, FIML-generated models often lack interpretability, limiting physical understanding and manual improvements based on prior knowledge. Additionally, these models may struggle with generalization in flow fields distinct from the training set. This study addresses these issues by employing symbolic regression (SR) to derive an analytical relationship between the correction factor of the baseline turbulence model and local flow variables, enhancing the baseline model's ability to predict separated flow across diverse test cases. The shear-stress-transport (SST) model undergoes field inversion on a curved backward-facing step (CBFS) case to obtain the corrective factor field beta, and SR is used to derive a symbolic map between local flow features and beata. The SR-derived analytical function is integrated into the original SST model, resulting in the SST-SR model. The SST-SR model's generalization capabilities are demonstrated by its successful predictions of separated flow on various test cases, including 2D-bump cases with varying heights, periodic hill case where separation is dominated by geometric features, and the three-dimensional Ahmed-body case. In these tests, the model accurately predicts flow fields, showing its effectiveness in cases completely different from the training set. The Ahmed-body case, in particular, highlights the model's ability to predict the three-dimensional massively separated flows. When applied to a turbulent boundary layer with Re_L=1.0E7, the SST-SR model predicts wall friction coefficient and log layer comparably to the original SST model, maintaining the attached boundary layer prediction performance.Comment: 37 pages, 46 figure

Microenvironment Determinants of Brain Metastasis

Metastasis accounts for 90% of cancer-related mortality. Brain metastases generally present during the late stages in the natural history of cancer progression. Recent advances in cancer treatment and management have resulted in better control of systemic disease metastatic to organs other than the brain and improved patient survival. However, patients who experience recurrent disease manifest an increasing number of brain metastases, which are usually refractory to therapies. To meet the new challenges of controlling brain metastasis, the research community has been tackling the problem with novel experimental models and research tools, which have led to an improved understanding of brain metastasis. The time-tested "seed-and-soil" hypothesis of metastasis indicates that successful outgrowth of deadly metastatic tumors depends on permissible interactions between the metastatic cancer cells and the site-specific microenvironment in the host organs. Consistently, recent studies indicate that the brain, the major component of the central nervous system, has unique physiological features that can determine the outcome of metastatic tumor growth. The current review summarizes recent discoveries on these tumor-brain interactions, and the potential clinical implications these novel findings could have for the better treatment of patients with brain metastasis

Riemannian Adaptive Regularized Newton Methods with H\"older Continuous Hessians

This paper presents strong worst-case iteration and operation complexity guarantees for Riemannian adaptive regularized Newton methods, a unified framework encompassing both Riemannian adaptive regularization (RAR) methods and Riemannian trust region (RTR) methods. We comprehensively characterize the sources of approximation in second-order manifold optimization methods: the objective function's smoothness, retraction's smoothness, and subproblem solver's inexactness. Specifically, for a function with a $\mu$-H\"older continuous Hessian, when equipped with a retraction featuring a $\nu$-H\"older continuous differential and a $\theta$-inexact subproblem solver, both RTR and RAR with $2+\alpha$ regularization (where $\alpha=\min\{\mu,\nu,\theta\}$) locate an $(\epsilon,\epsilon^{\alpha/(1+\alpha)})$-approximate second-order stationary point within at most $O(\epsilon^{-(2+\alpha)/(1+\alpha)})$ iterations and at most $\tilde{O}(\epsilon^{-(4+3\alpha)/(2(1+\alpha))})$ Hessian-vector products. These complexity results are novel and sharp, and reduce to an iteration complexity of $O(\epsilon^{-3/2})$ and an operation complexity of $\tilde{O}(\epsilon^{-7/4})$ when $\alpha=1$

ECGadv: Generating Adversarial Electrocardiogram to Misguide Arrhythmia Classification System

Deep neural networks (DNNs)-powered Electrocardiogram (ECG) diagnosis systems recently achieve promising progress to take over tedious examinations by cardiologists. However, their vulnerability to adversarial attacks still lack comprehensive investigation. The existing attacks in image domain could not be directly applicable due to the distinct properties of ECGs in visualization and dynamic properties. Thus, this paper takes a step to thoroughly explore adversarial attacks on the DNN-powered ECG diagnosis system. We analyze the properties of ECGs to design effective attacks schemes under two attacks models respectively. Our results demonstrate the blind spots of DNN-powered diagnosis systems under adversarial attacks, which calls attention to adequate countermeasures.Comment: Accepted by AAAI 202

Transcriptional Down-Regulation and rRNA Cleavage in Dictyostelium discoideum Mitochondria during Legionella pneumophila Infection

Bacterial pathogens employ a variety of survival strategies when they invade eukaryotic cells. The amoeba Dictyostelium discoideum is used as a model host to study the pathogenic mechanisms that Legionella pneumophila, the causative agent of Legionnaire's disease, uses to kill eukaryotic cells. Here we show that the infection of D. discoideum by L. pneumophila results in a decrease in mitochondrial messenger RNAs, beginning more than 8 hours prior to detectable host cell death. These changes can be mimicked by hydrogen peroxide treatment, but not by other cytotoxic agents. The mitochondrial large subunit ribosomal RNA (LSU rRNA) is also cleaved at three specific sites during the course of infection. Two LSU rRNA fragments appear first, followed by smaller fragments produced by additional cleavage events. The initial LSU rRNA cleavage site is predicted to be on the surface of the large subunit of the mitochondrial ribosome, while two secondary sites map to the predicted interface with the small subunit. No LSU rRNA cleavage was observed after exposure of D. discoideum to hydrogen peroxide, or other cytotoxic chemicals that kill cells in a variety of ways. Functional L. pneumophila type II and type IV secretion systems are required for the cleavage, establishing a correlation between the pathogenesis of L. pneumophila and D. discoideum LSU rRNA destruction. LSU rRNA cleavage was not observed in L. pneumophila infections of Acanthamoeba castellanii or human U937 cells, suggesting that L. pneumophila uses distinct mechanisms to interrupt metabolism in different hosts. Thus, L. pneumophila infection of D. discoideum results in dramatic decrease of mitochondrial RNAs, and in the specific cleavage of mitochondrial rRNA. The predicted location of the cleavage sites on the mitochondrial ribosome suggests that rRNA destruction is initiated by a specific sequence of events. These findings suggest that L. pneumophila specifically disrupts mitochondrial protein synthesis in D. discoideum during the course of infection

Underwater and Surface Aquatic Locomotion of Soft Biomimetic Robot Based on Bending Rolled Dielectric Elastomer Actuators

All-around, real-time navigation and sensing across the water environments by miniature soft robotics are promising, for their merits of small size, high agility and good compliance to the unstructured surroundings. In this paper, we propose and demonstrate a mantas-like soft aquatic robot which propels itself by flapping-fins using rolled dielectric elastomer actuators (DEAs) with bending motions. This robot exhibits fast-moving capabilities of swimming at 57mm/s or 1.25 body length per second (BL/s), skating on water surface at 64 mm/s (1.36 BL/s) and vertical ascending at 38mm/s (0.82 BL/s) at 1300 V, 17 Hz of the power supply. These results show the feasibility of adopting rolled DEAs for mesoscale aquatic robots with high motion performance in various water-related scenarios.Comment: 6 Pages, 12 Figures, Published at IROS 202

Structure mechanical modeling of thin-walled closed- section composite beams, part 2: multi-cell cross section

The methodology used in part 1 [1] of the work for single-cell thin-walled closed-section composite beams is extended to multi-cell thin-walled closed-section composite beams. The effect of material anisotropies is fully considered on the mid-surface shear strain of all the cross sectional members including skin walls and internal members. Numerical comparisons with ABAQUS finite element simulations are performed for three-cell box and elliptical beams with a variety of laminate layups under various loading conditions and excellent agreements are observed. Significant deficiency of some existing models are shown