Optimisation of material properties for the modelling of large deformation manufacturing processes using a finite element model of the Gleeble compression test

The finite element modelling of manufacturing processes often requires a large amount of large plastic strain flow stress data in order to represent the material of interest over a wide range of temperatures and strain rates. Compression data generated using a Gleeble thermo-mechanical simulator is difficult to interpret due to the complex temperature and strain fields, which exist within the specimen during the test. In this study, a non-linear optimisation process is presented, which includes a finite element model of the compression process to accurately determine the constants of a five-parameter Norton–Hoff material model. The optimisation process is first verified using a reduced three-parameter model and then the full five-parameter model using a known set of constants to produce the target data, from which the errors are assessed. Following this, the optimisation is performed using experimental target data starting from a set of constants derived from the test data using an initial least-squares fit and also an arbitrary starting point within the parameter space. The results of these tests yield coefficients differing by a maximum of less than 10% and significantly improve the representation of the flow stress of the material

Evaluating the robustness of objective pilling classification with the two-dimensional discrete wavelet transform

Previously, we proposed a new method of frequency domain analysis based on the two-dimensional discrete wavelet transform to objectively measure pilling intensity in sample fabric images. We have further evaluated this method, and our results indicate that it is robust to small horizontal and/or vertical translations and to significant variations in the brightness of the image under analysis, and is sensitive to rotation and to dilation of the image. These results suggest that as long as precautions are taken to ensure fabric test samples are imaged under consistent conditions of weave/knit pattern alignment (rotation) and apparent interyarn pitch (dilation), the method will yield repeatable results. <br /

Defects and boundary layers in non-Euclidean plates

We investigate the behavior of non-Euclidean plates with constant negative Gaussian curvature using the F\"oppl-von K\'arm\'an reduced theory of elasticity. Motivated by recent experimental results, we focus on annuli with a periodic profile. We prove rigorous upper and lower bounds for the elastic energy that scales like the thickness squared. In particular we show that are only two types of global minimizers -- deformations that remain flat and saddle shaped deformations with isolated regions of stretching near the edge of the annulus. We also show that there exist local minimizers with a periodic profile that have additional boundary layers near their lines of inflection. These additional boundary layers are a new phenomenon in thin elastic sheets and are necessary to regularize jump discontinuities in the azimuthal curvature across lines of inflection. We rigorously derive scaling laws for the width of these boundary layers as a function of the thickness of the sheet

Algorithm 873: LSTRS: MATLAB Software for Large-Scale Trust-Region Subproblems and Regularization

A MATLAB 6.0 implementation of the LSTRS method is presented. LSTRS was described in Rojas et al. [2000]. LSTRS is designed for large-scale quadratic problems with one norm constraint. The method is based on a reformulation of the trust-region subproblem as a parameterized eigenvalue problem, and consists of an iterative procedure that finds the optimal value for the parameter. The adjustment of the parameter requires the solution of a large-scale eigenvalue problem at each step. LSTRS relies on matrix-vector products only and has low and fixed storage requirements, features that make it suitable for large-scale computations. In the MATLAB implementation, the Hessian matrix of the quadratic objective function can be specified either explicitly, or in the form of a matrix-vector multiplication routine. Therefore, the implementation preserves the matrix-free nature of the method. A description of the LSTRS method and of the MATLAB software, version 1.2, is presented. Comparisons with other techniques and applications of the method are also included. A guide for using the software and examples are provided.34

Intelligent sampling for the measurement of structured surfaces

Uniform sampling in metrology has known drawbacks such as coherent spectral aliasing and a lack of efficiency in terms of measuring time and data storage. The requirement for intelligent sampling strategies has been outlined over recent years, particularly where the measurement of structured surfaces is concerned. Most of the present research on intelligent sampling has focused on dimensional metrology using coordinate-measuring machines with little reported on the area of surface metrology. In the research reported here, potential intelligent sampling strategies for surface topography measurement of structured surfaces are investigated by using numerical simulation and experimental verification. The methods include the jittered uniform method, low-discrepancy pattern sampling and several adaptive methods which originate from computer graphics, coordinate metrology and previous research by the authors. By combining the use of advanced reconstruction methods and feature-based characterization techniques, the measurement performance of the sampling methods is studied using case studies. The advantages, stability and feasibility of these techniques for practical measurements are discussed

Modeling drying kinetics of thyme (thymus vulgaris l.): theoretical and empirical models, and neural networks

[EN] The drying kinetics of thyme was analyzed by considering different conditions: air temperature of between 40 C and 70 C, and air velocity of 1 m/s. A theoretical diffusion model and eight different empirical models were fitted to the experimental data. From the theoretical model application, the effective diffusivity per unit area of the thyme was estimated (between 3.68 10 5 and 2.12 10 4 s 1). The temperature dependence of the effective diffusivity was described by the Arrhenius relationship with activation energy of 49.42 kJ/mol. Eight different empirical models were fitted to the experimental data. Additionally, the dependence of the parameters of each model on the drying temperature was determined, obtaining equations that allow estimating the evolution of the moisture content at any temperature in the established range. Furthermore, artificial neural networks were developed and compared with the theoretical and empirical models using the percentage of the relative errors and the explained variance. The artificial neural networks were found to be more accurate predictors of moisture evolution with VAR 99.3% and ER 8.7%.The authors acknowledge the financial support from the 'Ministerio de Educacion y Ciencia' in Spain, CONSOLIDER INGENIO 2010 (CSD2007-00016).Rodríguez Cortina, J.; Clemente Polo, G.; Sanjuán Pellicer, MN.; Bon Corbín, J. (2014). Modeling drying kinetics of thyme (thymus vulgaris l.): theoretical and empirical models, and neural networks. Food Science and Technology International. 20(1):13-22. https://doi.org/10.1177/1082013212469614S132220

Design and optimisation of organic Rankine cycles for waste heat recovery in marine applications using the principles of natural selection

Power cycles using alternative working fluids are currently receiving significant attention. Selection of working fluid among many candidates is a key topic and guidelines have been presented. A general problem is that the selection is based on numerous criteria, such as thermodynamic performance, boundary conditions, hazard levels and environmental concerns. A generally applicable methodology, based on the principles of natural selection, is presented and used to determine the optimum working fluid, boiler pressure and Rankine cycle process layout for scenarios related to marine engine heat recovery. Included in the solution domain are 109 fluids in sub and supercritical processes, and the process is adapted to the properties of the individual fluid. The efficiency losses caused by imposing process constraints are investigated to help propose a suitable process layout. Hydrocarbon dry type fluids in recuperated processes produced the highest efficiencies, while wet and isentropic fluids were superior in non-recuperated processes. The results suggested that at design point, the requirements of process simplicity, low operating pressure and low hazard resulted in cumulative reductions in cycle efficiency. Furthermore, the results indicated that non-flammable fluids were able to produce near optimum efficiency in recuperated high pressure processes

Computation of the real structured singular value via pole migration

peer-reviewedThe paper introduces a new computationally efficient algorithm to determine a lower bound on the real structured singular value . The algorithm is based on a pole migration approach where an optimization solver is used to compute a lower bound on real independent of a frequency sweep. A distinguishing feature of this algorithm from other frequency independent one-shot tests is that multiple localized optima (if they exist) are identified and returned from the search. This is achieved by using a number of alternative methods to generate different initial conditions from which the optimization solver can initiate its search from. The pole migration algorithm presented has also been extended to determine lower bounds for complex parametric uncertainties as well as full complex blocks. However, the results presented are for strictly real and repeated parametric uncertainty problems as this class of problem is the focus of this paper and are in general the most difficult to solve. Copyright (c) 2014 John Wiley & Sons, Ltd.ACCEPTEDpeer-reviewe