Optimization of Sandwich Composites Fuselages Under Flight Loads

The sandwich composites fuselages appear to be a promising choice for the future aircrafts because of their structural efficiency and functional integration advantages. However, the design of sandwich composites is more complex than other structures because of many involved variables. In this paper, the fuselage is designed as a sandwich composites cylinder, and its structural optimization using the finite element method (FEM) is outlined to obtain the minimum weight. The constraints include structural stability and the composites failure criteria. In order to get a verification baseline for the FEM analysis, the stability of sandwich structures is studied and the optimal design is performed based on the analytical formulae. Then, the predicted buckling loads and the optimization results obtained from a FEM model are compared with that from the analytical formulas, and a good agreement is achieved. A detailed parametric optimal design for the sandwich composites cylinder is conducted. The optimization method used here includes two steps: the minimization of the layer thickness followed by tailoring of the fiber orientation. The factors comprise layer number, fiber orientation, core thickness, frame dimension and spacing. Results show that the two-step optimization is an effective method for the sandwich composites and the foam sandwich cylinder with core thickness of 5 mm and frame pitch of 0.5 m exhibits the minimum weight.     

Flame-Made Pt/K/Al2O3 for NO x Storage–Reduction (NSR) Catalysts

High surface area Pt/K/Al₂O₃ catalysts were prepared with a 2-nozzle flame spray method resulting in Pt clusters on γ-Al₂O₃ and amorphous K storage material as evidenced by Raman spectroscopy. The powders had a high NO _x storage capacity and were regenerated fast in a model exhaust gas environment. From 300 to 400 °C no excess NO _x was detected in the off gas during transition from fuel lean to fuel rich conditions, resulting in a highly effective NO _x removal performance. Above 500 °C, the NSR activity was lost and not recovered at lower temperatures as K-compounds were partially crystallized on the catalyst.     

Numerical simulations of the IPPE target geometry flows

A high speed water and liquid lithium (Li) flow is computed over the IPPE geometry to evaluate the performance of different turbulence models in 2D and 3D simulations. Results reported are the thickness of the liquid jet, irregularities in the surface, transient phenomena at the wall which can affect fluid surface and effect of the variation in bulk velocity on these quantities. All models show good near wall resolution of the boundary layer and expected profiles for the free surface flow. Predicted turbulent kinetic energy compare well with published data. Fluctuations of the flow surface at the control location (center of the curved section) and elsewhere are well within 1 mm for all models. However it was observed that the predictions are strongly dependent on the model used. Overall, the predictions of RANS models are close to each other whereas predictions of laminar simulations are close to those obtained with LES models.     

Non‐Toxic Dry‐Coated Nanosilver for Plasmonic Biosensors

The plasmonic properties of noble metals facilitate their use for in vivo bio‐applications such as targeted drug delivery and cancer cell therapy. Nanosilver is best suited for such applications as it has the lowest plasmonic losses among all such materials in the UV‐visible spectrum. Its toxicity, however, can destroy surrounding healthy tissues and thus, hinders its safe use. Here, that toxicity against a model biological system (Escherichia coli) is “cured” or blocked by coating nanosilver hermetically with a about 2 nm thin SiO₂ layer in one‐step by a scalable flame aerosol method followed by swirl injection of a silica precursor vapor (hexamethyldisiloxane) without reducing the plasmonic performance of the enclosed or encapsulated silver nanoparticles (20–40 nm in diameter as determined by X‐ray diffraction and microscopy). This creates the opportunity to safely use powerful nanosilver for intracellular bio‐applications. The label‐free biosensing and surface bio‐functionalization of these ready‐to‐use, non‐toxic (benign) Ag nanoparticles is presented by measuring the adsorption of bovine serum albumin (BSA) in a model sensing experiment. Furthermore, the silica coating around nanosilver prevents its agglomeration or flocculation (as determined by thermal annealing, optical absorption spectroscopy and microscopy) and thus, enhances its biosensitivity, including bioimaging as determined by dark field illumination.     

Continuous flame aerosol synthesis of carbon-coated nano-LiFePO4 for Li-ion batteries

Core–shell, nano-sized LiFePO₄-carbon particles were made in one step by scalable flame aerosol technology at 7 g/h. Core LiFePO₄ particles were made in an enclosed flame spray pyrolysis (FSP) unit and were coated in-situ downstream by auto thermal carbonization (pyrolysis) of swirl-fed C₂H₂ in an O₂-controlled atmosphere. The formation of acetylene carbon black (ACB) shell was investigated as a function of the process fuel-oxidant equivalence ratio (EQR). The core–shell morphology was obtained at slightly fuel-rich conditions (1.0<EQR<1.07) whereas segregated ACB and LiFePO₄ particles were formed at fuel-lean conditions (0.8<EQR<1). Post-annealing of core–shell particles in reducing environment (5 vol% H₂ in argon) at 700 °C for up to 4 h established phase pure, monocrystalline LiFePO₄ with a crystal size of 65 nm and 30 wt% ACB content. Uncoated LiFePO₄ or segregated LiFePO₄–ACB grew to 250 nm at these conditions. Annealing at 800 °C induced carbothermal reduction of LiFePO₄ to Fe₂P by ACB shell consumption that resulted in cavities between carbon shell and core LiFePO₄ and even slight LiFePO₄ crystal growth but better electrochemical performance. The present carbon-coated LiFePO₄ showed superior cycle stability and higher rate capability than the benchmark, commercially available LiFePO₄.     

Dental Polymer Nanocomposites Light-Cured under Polyester Strip: Effect of Water or Ethanol/Water Solution on Surface Characteristics Studied by SEM and AFM

The purpose of this work is the study of surface characteristics of four dental light-cured dimethacrylate-based resin nanocomposites after immersion in water or an ethanol/water solution, using scanning electron microscopy and atomic force microscopy. Water and ethanol treatment affected the morphology and component distribution on the surface of samples. Scanning electron microscopy revealed changes on a large scale in the surface morphology of treated samples caused by immersion in water while the ethanol/water solution treatment influenced sample integrity too. It was proven that the use of atomic force microscopy in the phase-imaging mode is crucial in revealing subtle changes in component distribution on the polymer composite surface which are not accompanied by significant morphological changes.     

Effect of Liquid Properties on Heat Transfer from Miniature Heaters at Different Gravity Conditions

This work presents experiments for the estimation of heat transfer from sub-millimeter spheroidal heaters at varying gravity conditions. Experiments were performed during the 50^th Parabolic Flight Campaign of European Space Agency (May 2009). Heat pulses of varying strength were given to a miniature heater submerged in the liquid while its thermal response was registered during heating. Tests were conducted in water and FC-72, two liquids with distinctly different thermophysical properties. Runs were also conducted with packed beds and dense suspensions of two size classes of polystyrene particles in water. The contribution of natural convection in heat transfer was estimated from differences observed when the acceleration varied from 0g to 1.8g. Although the analysis of data is not finished yet, it is evident that natural convection is more profound in FC-72 than water. In addition, closely packed particles suppress entirely natural convection but this is not so for dense particle suspensions.     

Active learning Rotation Forest for multiclass classification

Although the achievements of the computer science field have facilitated the tasks of collecting, storing, and accessing vast amounts of data efficiently, its annotation still remains a non–easily resolvable problem since no automated mechanism can perform reliably enough. This fact is even more profound when the objective is the high quality of generalization ability. Active learning constitutes a scheme that is exploited for tackling such problems, controlling the demanded human effort under a trade‐off assumption concerning the achievement of higher accuracy rates. In this work, the well‐known Rotation Forest algorithm is integrated with the active learning theory for constructing a robust and accurate classifier. Thus, apart from exploiting the collected labeled data, unlabeled data mining takes place through appropriate queries, whereas human expert decisions over the most questionable of them enrich the initial ones. Comprehensive comparisons of the proposed algorithm against four distinct learners inside the same learning scheme were executed. Moreover, the baseline strategy of random sampling and the corresponding supervised scenarios were included. During the evaluation stage, 13 publicly available multiclass datasets were assessed, and the obtained results verified our assumptions, regarding also the significant supremacy of the proposed algorithm against the majority of its rivals.