The determination of three-dimensional stress tensors on multilayer thin films

The three-dimensional residual stress condition of copper sputtered on Kapton films was studied by two nondestructive x-ray diffraction techniques. Four samples were evaluated—one control sample, and three heat-treated samples. Because of concerns about steep stress gradients normal to the specimen surface, an experimental technique described by Dölle⁽¹⁾ was used to obtain the residual strain tensors in the near surface region. The resulting stress tensors were compared to data obtained through a modification of the technique described by Dölle, referred to as the differential method.⁽²⁾     

Application of nondestructive techniques for the prediction of elastic anistropy of a textured polycrystalline material

Effect of processing parameters including cold work and grain size on texture development in copper and 68:32 -brass thin sheets is investigated. The preferred orientation of grains (texture) is represented quantitatively by the orientation distribution function (ODF) as derived either by X-ray diffraction or by ultrasonic velocity measurements. The texture-induced elastic moduli are derived in the sheet plane at various orientations to the rolling direction. The predicted values of elastic moduli are compared with the mechanically measured ones. An attempt is made to empirically correlate ODF coefficients to the mechanically measured elastic modulus and plastic strain ratio (r-value). The sources of discrepancies such as the limitations of the measuring techniques and the models applied are discussed.     

An optimization approach for the localization of defects in an inhomogeneous medium from acoustic far-field measurements at a fixed frequency

We are interested in the localization of defects in non-homogeneous non-absorbing media, with far-field measurements, generated by plane waves. We present here a way to handle the inhomogeneous background problem by the means of a constrained optimization approach; in the lines of the inf criterion from the factorization method for constant backgrounds. We show that both cost function and constraints present a simple form that is easy to compute. They can thus be treated by many well-known optimization methods, and we numerically illustrate four of them.     

A Mechanistic Perspective on Process-Induced Changes in Glucosinolate Content in Brassica Vegetables: A Review

Brassica vegetables are consumed mostly after processing, which is expected to give beneficial effects on the vegetable properties, such as improved palatability and bioavailability of nutrients, or shelf life extension. But processing also results to various changes in the content of health promoting phytochemicals like glucosinolates. This paper reviews the effects of processing on the glucosinolates content by using a mechanism approach underlying processing method employed. Cultural differences between Eastern and Western preparation practices and their possible effect on glucosinolate retention are highlighted. Boiling and blanching considerably reduce the glucosinolate content mainly due to mechanisms of cell lysis, diffusion, and leaching, and partly due to thermal and enzymatic degradation. Steaming, microwave processing, and stir frying either retain or slightly reduce the glucosinolates content due to low degrees of leaching; moreover, these methods seem to enhance extractability of glucosinolates from the plant tissue. Fermentation reduces the glucosinolate content considerably, but the underlying mechanisms are not yet studied in detail. Studying the changes of glucosinolates during processing by a mechanistic approach is shown to be valuable to understand the impact of processing and to optimize processing conditions for health benefits of these compounds.     

Multiscale modeling in food engineering

Since many years food engineers have attempted to describe physical phenomena such as heat and mass transfer that occur in food during unit operations by means of mathematical models. Foods are hierarchically structured and have features that extend from the molecular scale to the food plant scale. In order to reduce computational complexity, food features at the fine scale are usually not modeled explicitly but incorporated through averaging procedures into models that operate at the coarse scale. As a consequence, detailed insight into the processes at the microscale is lost, and the coarse scale model parameters are apparent rather than physical parameters. As it is impractical to measure these parameters for the large number of foods that exist, the use of advanced mathematical models in the food industry is still limited. A new modeling paradigm – multiscale modeling – has appeared that may alleviate these problems. Multiscale models are essentially a hierarchy of sub-models which describe the material behavior at different spatial scales in such a way that the sub-models are interconnected. In this article we will introduce the underlying physical and computational concepts. We will give an overview of applications of multiscale modeling in food engineering, and discuss future prospects.