Furfural Oxidation with Hydrogen Peroxide Over ZSM-5 Based Micro-Mesoporous Aluminosilicates

Micro-mesoporous aluminosilicates based on ZSM-5 zeolite, obtained by a dual template method, as well as in the presence of a dual-functional template (i.e. a Gemini-type surfactant), were tested in the oxidation of furfural with hydrogen peroxide. Even substantial changes in acidity and porosity of the catalysts result in minor variations of selectivity towards the desired products. Application of the synthesized zeolite-based materials in the oxidation of furfural with hydrogen peroxide leads to formation of 2(5H)-furanone (yield up to 28.5%) and succinic acid (up to 19.5%) as the main C4 reaction products. The kinetic model developed previously to treat the results for oxidation of furfural over sulfated zirconia was able to describe the data also for micro-mesoporous aluminosilicates.

Graphical Abstract

     

Grid resource brokering algorithms enabling advance reservations and resource selection based on performance predictions

We present algorithms, methods, and software for a Grid resource manager, that performs resource brokering and job scheduling in production Grids. This decentralized broker selects computational resources based on actual job requirements, job characteristics, and information provided by the resources, with the aim to minimize the total time to delivery for the individual application. The total time to delivery includes the time for program execution, batch queue waiting, and transfer of executable and input/output data to and from the resource. The main features of the resource broker include two alternative approaches to advance reservations, resource selection algorithms based on computer benchmark results and network performance predictions, and a basic adaptation facility. The broker is implemented as a built-in component of a job submission client for the NorduGrid/ARC middleware.     

Copper planar microcoils applied to magnetic actuation

Recent advances in microtechnology allow realization of planar microcoils. These components are integrated in MEMS as magnetic sensor or actuator. In the latter case, it is necessary to maximize the effective magnetic field which is proportional to the current passing through the copper track and depends on the distance to the generation microcoil. The aim of this work was to determine the optimal microcoil design configuration for magnetic field generation. The results were applied to magnetic actuation, taking into account technological constraints. In particular, we have considered different realistic configurations that involve a magnetically actuated device coupled to a microcoil. Calculations by a semi-analytical method using Matlab software were validated by experimental measurements. The copper planar microcoils are fabricated by UV micromoulding on different substrates: flexible polymer (Kapton^®) and silicate on silicon. They are constituted by a spiral-like continuous track. Their total surface is about 1 mm².     

Comparison of the identification performance of conventional FEM updating and integrated DIC

Full‐field identification methods are increasingly used to adequately identify constitutive parameters to describe the mechanical behavior of materials. This paper investigates the more recently introduced one‐step method of integrated digital image correlation (IDIC) with respect to the most commonly used two‐step method of finite element model updating (FEMU), which uses a subset‐based DIC algorithm. To make the comparison as objective as possible, both methods are implemented in the most equivalent manner and use the same FE model. Various virtual test cases are studied to assess the performance of both methods when subjected to different error sources: (1) systematic errors, (2) poor initial guesses for the constitutive parameters, (3) image noise, (4) constitutive model errors, and (5) experimental errors. Results show that, despite the mathematical similarity of both methods, IDIC produces less erroneous and more reliable results than FEMU, particularly for more challenging test cases exhibiting small displacements, complex kinematics, misalignment of the specimen, and image noise. Copyright © 2015 John Wiley & Sons, Ltd.     

Two nonlinear optimization methods for black box identification compared

In this paper, two nonlinear optimization methods for the identification of nonlinear systems are compared. Both methods estimate the parameters of e.g. a polynomial nonlinear state-space model by means of a nonlinear least-squares optimization of the same cost function. While the first method does not estimate the states explicitly, the second method estimates both states and parameters adding an extra constraint equation. Both methods are introduced and their similarities and differences are discussed utilizing simulation data. The unconstrained method appears to be faster and more memory efficient, but the constrained method has a significant advantage as well: it is robust for unstable systems of which bounded input-output data can be measured (e.g. a system captured in a stabilizing feedback loop). Both methods have successfully been applied on real-life measurement data.     

Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCA

A new formulation for multiway spectral clustering is proposed. This method corresponds to a weighted kernel principal component analysis (PCA) approach based on primal-dual least-squares support vector machine (LS-SVM) formulations. The formulation allows the extension to out-of-sample points. In this way, the proposed clustering model can be trained, validated, and tested. The clustering information is contained on the eigendecomposition of a modified similarity matrix derived from the data. This eigenvalue problem corresponds to the dual solution of a primal optimization problem formulated in a high-dimensional feature space. A model selection criterion called the Balanced Line Fit (BLF) is also proposed. This criterion is based on the out-of-sample extension and exploits the structure of the eigenvectors and the corresponding projections when the clusters are well formed. The BLF criterion can be used to obtain clustering parameters in a learning framework. Experimental results with difficult toy problems and image segmentation show improved performance in terms of generalization to new samples and computation times.     

A computational study of vortex-airfoil interaction using high-order finite difference methods

Simulations of the interaction between a vortex and a NACA0012 airfoil are performed with a stable, high-order accurate (in space and time), multi-block finite difference solver for the compressible Navier-Stokes equations.We begin by computing a benchmark test case to validate the code. Next, the flow with steady inflow conditions are computed on several different grids. The resolution of the boundary layer as well as the amount of the artificial dissipation is studied to establish the necessary resolution requirements. We propose an accuracy test based on the weak imposition of the boundary conditions that does not require a grid refinement.Finally, we compute the vortex-airfoil interaction and calculate the lift and drag coefficients. It is shown that the viscous terms add the effect of detailed small scale structures to the lift and drag coefficients.