Virtual prototyping of an actuator-based structural health monitoring system of wind turbine blades

Testing and evaluating the performance of a Structural Health Monitoring (SHM) system is a challenging and costly task. A proper experimental assessment of the system is not feasible in most cases. A possible solution is a virtual prototype of the monitored object together with the SHM system. This study presents the initial steps of creating a virtual prototype, namely simulation of the elastic wave propagation due to impact of the actuator. It is shown that even this very initial investigation helps to understand the complex vibration pattern of the blade and how the presence of the damage alters it. Similarly, for the same damage size and location, different actuations locations were studied. The location of the actuator affects the wave propagation, as the interaction with the structural parts of the blade significantly complicates the vibration pattern before it actually reaches the damage region. The results clearly indicate that the actuator-based SHM system has a good wave propagation and damage resolution ratio for damage diagnosis in large blades

In situ measurement of bovine serum albumin interaction with gold nanospheres

Here we present in situ observations of adsorption of bovine serum albumin (BSA) on citratestabilized gold nanospheres. We implemented scattering correlation spectroscopy as a tool to quantify changes in the nanoparticle Brownian motion resulting from BSA adsorption onto the nanoparticle surface. Protein binding was observed as an increase in the nanoparticle hydrodynamic radius. Our results indicate the formation of a protein monolayer at similar albumin concentrations as those found in human blood. Additionally, by monitoring the frequency and intensity of individual scattering events caused by single gold nanoparticles passing the observation volume, we found that BSA did not induce colloidal aggregation, a relevant result from the toxicological viewpoint. Moreover, to elucidate the thermodynamics of the gold nanoparticle-BSA association, we measured an adsorption isotherm which was best described by an anti-cooperative binding model. The number of binding sites based on this model was consistent with a BSA monolayer in its native state. In contrast, experiments using poly-ethylene glycol capped gold nanoparticles revealed no evidence for adsorption of BSA

Near-field interactions between metal nanoparticle surface plasmons and molecular excitons in thin-films: part I: absorption

In this and the following paper (parts I and II, respectively), we systematically study the interactions between surface plasmons of metal nanoparticles (NPs) with excitons in thin-films of organic media. In an effort to exclusively probe near-field interactions, we utilize spherical Ag NPs in a size-regime where far-field light scattering is negligibly small compared to absorption. In part I, we discuss the effect of the presence of these Ag NPs on the absorption of the embedding medium by means of experiment, numerical simulations, and analytical calculations, all shown to be in good agreement. We observe absorption enhancement in the embedding medium due to the Ag NPs with a strong dependence on the medium permittivity, the spectral position relative to the surface plasmon resonance frequency, and the thickness of the organic layer. By introducing a low index spacer layer between the NPs and the organic medium, this absorption enhancement is experimentally confirmed to be a near field effect In part II, we probe the impact of the Ag NPs on the emission of organic molecules by time-resolved and steady-state photoluminescence measurements

Bayesian Model Selection Applied to the Analysis of Fluorescence Correlation Spectroscopy Data of Fluorescent Proteins in Vitro and in Vivo

Fluorescence correlation spectroscopy (FCS) is a powerful technique to investigate molecular dynamics with single molecule sensitivity. In particular, in the life sciences it has found widespread application using fluorescent proteins as molecularly specific labels. However, FCS data analysis and interpretation using fluorescent proteins remains challenging due to typically low signal-to-noise ratio of FCS data and correlated noise in autocorrelated data sets. As a result, naive fitting procedures that ignore these important issues typically provide similarly good fits for multiple competing models without clear distinction of which model is preferred given the signal-to-noise ratio present in the data. Recently, we introduced a Bayesian model selection procedure to overcome this issue with FCS data analysis. The method accounts for the highly correlated noise that is present in FCS data sets and additionally penalizes model complexity to prevent over interpretation of FCS data. Here, we apply this procedure to evaluate FCS data from fluorescent proteins assayed in vitro and in vivo. Consistent with previous work, we demonstrate that model selection is strongly dependent on the signal-to-noise ratio of the measurement, namely, excitation intensity and measurement time, and is sensitive to saturation artifacts. Under fixed, low intensity excitation conditions, physical transport models can unambiguously be identified. However, at excitation intensities that are considered moderate in many studies, unwanted artifacts are introduced that result in nonphysical models to be preferred. We also determined the appropriate fitting models of a GFP tagged secreted signaling protein, Wnt3, in live zebrafish embryos, which is necessary for the investigation of Wnt3 expression and secretion in development. Bayes model selection therefore provides a robust procedure to determine appropriate transport and photophysical models for fluorescent proteins when appropriate models are provided, to help detect and eliminate experimental artifacts in solution, cells, and in living organisms.National Science Foundation (U.S.). Physics of Living Systems ProgramNational Institute of Mental Health (U.S.) (Award U01MH106011

A Critical Review on the Structural Health Monitoring Methods of the Composite Wind Turbine Blades

With increasing turbine size, monitoring of blades becomes increasingly im-portant, in order to prevent catastrophic damages and unnecessary mainte-nance, minimize the downtime and labor cost and improving the safety is-sues and reliability. The present work provides a review and classification of various structural health monitoring (SHM) methods as strain measurement utilizing optical fiber sensors and Fiber Bragg Gratings (FBG’s), active/ pas-sive acoustic emission method, vibration‒based method, thermal imaging method and ultrasonic methods, based on the recent investigations and prom-ising novel techniques. Since accuracy, comprehensiveness and cost-effectiveness are the fundamental parameters in selecting the SHM method, a systematically summarized investigation encompassing methods capabilities/ limitations and sensors types, is needed. Furthermore, the damages which are included in the present work are fiber breakage, matrix cracking, delamina-tion, fiber debonding, crack opening at leading/ trailing edge and ice accre-tion. Taking into account the types of the sensors relevant to different SHM methods, the advantages/ capabilities and disadvantages/ limitations of repre-sented methods are nominated and analyzed