Evaluation of log‐of‐power extremum seeking control for wind turbines using large eddy simulations

The extremum seeking control (ESC) algorithm has been proposed to determine operating parameters that maximize power production below rated wind speeds (region II). This is usually done by measuring the turbine's power signal to determine optimal values for parameters of the control law or actuator settings. This paper shows that the standard ESC with power feedback is quite sensitive to variations in mean wind speed, with long convergence time at low wind speeds and aggressive transient response, possibly unstable, at high wind speeds. The paper also evaluates the performance, as measured by the dynamic and steady state response, of the ESC with feedback of the logarithm of the power signal (LP‐ESC). Large eddy simulations (LES) demonstrate that the LP‐ESC, calibrated at a given wind speed, exhibits consistent robust performance at all wind speeds in a typical region II. The LP‐ESC is able to achieve the optimal set‐point within a prescribed settling time, despite variations in the mean wind speed, turbulence, and shear. The LES have been conducted using realistic wind input profiles with shear and turbulence. The ESC and LP‐ESC are implemented in the LES without assuming the availability of analytical gradients.     

A Double Resonance Method for Studying Collision Rates in an Intense Laser Field

Abstract

We propose a method for studying the modification of atomic collision rates in the presence of an intense laser field. This method employs a three-level lambda-system driven by two laser pulses: one strong and the other weak. The weak laser is used to populate a particular dressed state produced by the intense laser at some time during the pulse history. We show that this point can be selected by tuning the frequency of the weak laser. The spectrum of the emission produced by the dressed state is then recorded. Measuring this spectrum, both in the presence and in the absence of collisions, enables one to deduce the dependence of the collision rates on laser intensity. The method has other advantages discussed in the text.     

Anelastic reorganisation of fibre-reinforced biological tissues

In this work, we contribute to the study of the structural reorganisation of biological tissues in response to mechanical stimuli. We specialise our investigation to a class of hydrated soft tissues, whose internal structure features reinforcing fibres. These are oriented statistically within the tissue, and their pattern of orientation is such that, at each material point, the tissue is anisotropic. From its natural, stress-free state, the tissue can be distorted anelastically into a global reference configuration, and then deformed under the action of external mechanical loads. The anelastic distortions are responsible for changing irreversibly the internal structure of the tissue, which, in the present context, occurs through both the rearrangement of the bonds among the tissue cells and the deformation-driven reorientation of the fibres. The anelastic strains, in addition, are assumed to model the onset and evolution of microcracks in the tissue, which may be triggered by the mechanical loads applied to the tissue in the case of traumatic events, or diseases. For our purposes, we formulate an anisotropic model of remodelling and we consider a fully isotropic model of structural reorganisation for comparison, with the aim to study if, how, and to what extent the evolution of anelastic distortions is influenced by the tissue’s anisotropy.

     

Dependency solving: A separate concern in component evolution management

Maintenance of component-based software platforms often has to face rapid evolution of software components. Component dependencies, conflicts, and package managers with dependency solving capabilities are the key ingredients of prevalent software maintenance technologies that have been proposed to keep software installations synchronized with evolving component repositories. We review state-of-the-art package managers and their ability to keep up with evolution at the current growth rate of popular component-based platforms, and conclude that their dependency solving abilities are not up to the task.We show that the complexity of the underlying upgrade planning problem is NP-complete even for seemingly simple component models, and argue that the principal source of complexity lies in multiple available versions of components. We then discuss the need of expressive languages for user preferences, which makes the problem even more challenging.We propose to establish dependency solving as a separate concern from other upgrade aspects, and present CUDF as a formalism to describe upgrade scenarios. By analyzing the result of an international dependency solving competition, we provide evidence that the proposed approach is viable.     

Advanced Modeling of Food Convective Drying: A Comparison Between Artificial Neural Networks and Hybrid Approaches

In the present paper, three different approaches are proposed to model the convective drying of food. The performance of thin-layer, pure neural network and hybrid neural model is compared in a wide range of operating conditions, with two different vegetables, available either as cylinders or as slabs with different characteristic dimensions. It was found that the thin-layer model was adequate to describe food drying behavior, but it could be applied only as a fitting procedure. Pure neural models gave accurate predictions in some situations, but exhibited poor performance when tested outside the range of operating conditions exploited during their development. Finally, it was shown that hybrid neural models, formulated as a combination of both theoretical and neural network models, are capable of offering the most accurate predictions of system behavior with average relative errors never exceeding 10%, even in operating conditions unexploited during the definition of the neural part of the model. The results obtained proved that the hybrid neural paradigm is a novel and efficient modeling technique that could be used successfully in food processing, thus allowing drying process optimization to be achieved, and efficient and fast on-line controllers to be implemented.     

Controlled suppression of the photoluminescence superlinear dependence on excitation density in quantum dots

We have shown that it is possible to tune, up to complete suppression, the photoluminescence superlinear dependence on the excitation density in quantum dot samples at high temperatures by annealing treatments. The effect has been attributed to the reduction of the defectivity of the material induced by annealing.     

Core Cross-Linked Amphiphilic Star-Block Copolymers with (Meth)acrylic Acid Shells Prepared by Atom Transfer Radical Polymerization

Core cross-linked amphiphilic star-block copolymers were prepared by hydrolysis of the outer shell of star-block copolymers prepared using copper mediated atom transfer radical polymerization (ATRP). In an arm-first approach, linear poly(tert-butyl methacrylate) macroinitiators (PtBMA-Cl) were extended with styrene to yield PtBMA-b-PS-Cl and then cross-linked with divinylbenzene (DVB) in order to yield (PtBMA-b-PS)_arms-PDVB_core star-block copolymers. Then, PMAA-b-PS block and (PMAA-PS)_arms-PDVB_core star-block copolymers were obtained by hydrolysis of the PtBMA blocks in both linear and cross-linked copolymers, as confirmed by ¹H NMR analyses. The amphiphilic character of these copolymers was confirmed by solubilisation in water. Several factors affecting the polymer aggregation and solubility such as the length, the composition of the arms and the catalyst used were studied. An acrylate analogue, that is, (PAA-b-PS)_arms-PDVB_core, was also prepared for comparison purposes. Atomic force microscopy (AFM) and differential scanning calorimetry (DSC) were used to elucidate the morphology and the thermal behaviour of the star-block copolymers.     

A smartphone-based fall detection system

Falls are a major cause of injuries and hospital admissions among elderly people. Thus, the caregiving process and the quality of life of older adults can be improved by adopting systems for the automatic detection of falls. This paper presents a smartphone-based fall detection system that monitors the movements of patients, recognizes a fall, and automatically sends a request for help to the caregivers. To reduce the problem of false alarms, the system includes novel techniques for the recognition of those activities of daily living that could be erroneously mis-detected as falls (such as sitting on a sofa or lying on a bed). To limit the intrusiveness of the system, a small external sensing unit can also be used for the acquisition of movement data.