Nonlinear modal analysis via non‐parametric machine learning tools

Modal analysis is an important tool in the structural dynamics community; it is widely utilised to understand and investigate the dynamical characteristics of linear structures. Many methods have been proposed in recent years regarding the extension to nonlinear analysis, such as nonlinear normal modes or the method of normal forms, with the main objective being to formulate a mathematical model of a nonlinear dynamical structure based on observations of input/output data from the dynamical system. In fact, for the majority of structures where the effect of nonlinearity becomes significant, nonlinear modal analysis is a necessity. The objective of the current paper is to demonstrate a machine learning approach to output‐only nonlinear modal decomposition using kernel independent component analysis and locally linear‐embedding analysis. The key element is to demonstrate a pattern recognition approach which exploits the idea of independence of principal components from the linear theory by learning the nonlinear manifold between the variables. In this work, the importance of output‐only modal analysis via “blind source” separation tools is highlighted as the excitation input/force is not needed and the method can be implemented directly via experimental data signals without worrying about the presence or not of specific nonlinearities in the structure.     

Unsupervised Segmentation of Stereoscopic Video Objects: Constrained Segmentation Fusion Versus Greedy Active Contours

In this paper, we present a novel memory access reduction scheme (MARS) for two-dimension fast cosine transform (2-D FCT). It targets programmable DSPs with high memory-access latency. It reduces the number of memory accesses by: 1) reducing the number of weighting factors and 2) combining butterflies in vector-radix 2-D FCT pruning diagram from two stages to one stage with an efficient structure. Hardware platform based on general purpose processor is used to verify the effectiveness of the proposed method for vector-radix 2-D FCT pruning implementation. Experimental results validate the benefits of the proposed method with reduced memory access, less clock cycle and fewer memory space compared with the conventional implementation.     

Tailoring Wetting Properties at Extremes States to Obtain Antifogging Functionality

Fog formation decreases light transmission of optically clear materials. A promising approach to address this problem is to control the wetting properties of the material at extremes states, which requires imparting micro and nano morphology features on the surface. However, such features may affect the optical properties of the surface. In this work, superhydrophobic and superhydrophilic surfaces, with different morphology characteristics ranging from nanoscale to hierarchical micro-nanoscale are fabricated and evaluated in order to investigate which wetting extreme and surface morphology is more suitable to preserve the light-transmitting properties and exhibit antifogging functionalities. The performance of the aforementioned surfaces is compared for the first time in two different testing modes: under intense fog flow and no surface cooling, and under no-flow and surface cooling, which enhances dew condensation on the surfaces. It is demonstrated that superhydrophilic surfaces with nanoscale morphology maintain their optical transmittance under fog flow for more than 20 min. This duration is one of the longest reported in the literature revealing the long-term antifogging functionality of the proposed surfaces. Finally, by tailoring the morphology and the surface wetting properties, an optically switching surface (initially “milky” which becomes “clear”) when exposed to humidity is demonstrated.     

Embedded Metal Oxide Plasmonics Using Local Plasma Oxidation of AZO for Planar Metasurfaces

New methods for achieving high-quality conducting oxide metasurfaces are of great importance for a range of emerging applications from infrared thermal control coatings to epsilon-near-zero nonlinear optics. This work demonstrates the viability of plasma patterning as a technique to selectively and locally modulate the carrier density in planar Al-doped ZnO (AZO) metasurfaces without any associated topographical surface profile. This technique stands in strong contrast to conventional physical patterning which results in nonplanar textured surfaces. The approach can open up a new route to form novel photonic devices with planar metasurfaces, for example, antireflective coatings and multi-layer devices. To demonstrate the performance of the carrier-modulated AZO metasurfaces, two types of devices are realized using the demonstrated plasma patterning. A metasurface optical solar reflector is shown to produce infrared emissivity equivalent to a conventional etched design. Second, a multiband metasurface is achieved by integrating a Au visible-range metasurface on top of the planar AZO infrared metasurface. Independent control of spectral bands without significant cross-talk between infrared and visible functionalities is achieved. Local carrier tuning of conducting oxide films offers a conceptually new approach for oxide-based photonics and nanoelectronics and opens up new routes for integrated planar metasurfaces in optical technology.     

Modeling and simulation of biphasic catalytic hydrogenation of a hydroformylated fuel

A model was developed based upon PR78 CEOS, Twu's alpha function and vdW mixing rules for simulating a pioneering chemical process of fuel upgrading. The chemical process of aqueous biphasic hydrogenation of a real hydroformylated fuel was experimentally conducted and simulated. The hydrogenation of the fuel occurred in aqueous media with in situ produced Ru-catalyst converting containing aldehydes to the corresponding alcohols. The above heterogenization of the homogeneous catalyst offered to the process an efficient and convenient way of catalyst recovery. The reaction temperature effect and the influence of hydrogen pressure in aqueous biphasic catalytic hydrogenation were examined. RuCl₃/TPPTS catalytic system proved to be an effective catalyst for fuel upgrading process, with the highest conversion of the aldehydes present in a hydroformylated fuel to reach 98.9% at 120 °C, 75 bar and at a short reaction time (2 h). A complete phase behavior of the fuel as well as a validation test of the simulation model were accomplished.     

Treatment of textile dyehouse wastewater by TiO2 photocatalysis

The oxidative degradation of an actual textile dyehouse wastewater was investigated by means of photocatalysis in the presence of TiO2. The UV-A-induced photocatalytic oxidation over TiO2 suspensions was capable of decolorizing the effluent completely, as well as reducing chemical oxygen demand (COD) sufficiently (COD reduction generally varied between about 40% and 90% depending on the operating conditions) after 4 h of treatment. Two crystalline forms of TiO2, viz. anatase and rutile, were tested for their photocatalytic activity and anatase was found to be more active than rutile. The extent of photocatalytic degradation was found to increase with increasing TiO2 concentration up to 0.5 g/L TiO2, above which degradation remained practically constant, reaching a plateau. Furthermore, textile effluent degradation was enhanced at acidic conditions (i.e. pH = 3) and in the presence of hydrogen peroxide. To assess catalyst activity on repeated use, experiments were performed where the catalyst was recovered and reused; after three successive uses, TiO2 had sufficiently retained its photocatalytic activity. Finally, the luminescent marine bacteria Vibrio fischeri was used to assess the acute ecotoxicity of samples prior to and after the photocatalytic treatment and it was found that ecotoxicity was fully eliminated following photocatalytic oxidation.