Microstructural Modelling of Nb Microalloyed Steels during Thin Slab Direct Rolling Processing

The microstructural evolution during the hot rolling of coarse grain sized austenite has been modeled considering all the microstructural mechanisms (dynamic, static and metadynamic recrystallization, strain induced precipitation) that can take place during an industrial TSDR production of three Nb microalloyed steels. Based on the results obtained from the model, processing maps have been drawn for 0.02%, 0.035% and 0.05% Nb microalloyed steels. Optimum processing conditions to exploit all the benefits of the Nb microalloying have been defined considering a final gauge thickness range between 1.5 and 12.65 mm. In addition, and facing the difficulties present in the production of thick hot strip, several alternative thermomechanical schedules are proposed, which would originate microstructures with a suitable combination of homogeneity and retained strain prior to transformation.     

Stochastic analysis of file-swarming systems

File swarming (or file sharing) is one of the most important applications in P2P networks. In this paper, we propose a stochastic framework to analyze a file-swarming system under realistic setting: constraints in upload/download capacity, collaboration among peers and incentive for chunk exchange. We first extend the results in the coupon system [L. Massoulie, M. Vojnovic, Coupon replication systems, in: Proc. ACM SIGMETRICS, Banff, Alberta, Canada, 2005] by providing a tighter performance bound. Then we generalize the coupon system by considering peers with limited upload and download capacity. We illustrate the last-piece problem and show the effectiveness of using forward error-correction (FEC) code and/or multiple requests to improve the performance. Lastly, we propose a framework to analyze an incentive-based file-swarming system. The stochastic framework we propose can serve as a basis for other researchers to analyze and design more advanced features of file-swarming systems.     

An approach to integrating shape and biomedical attributes in vascular models

Computational models have been used widely in tissue engineering research and have proven to be powerful tools for bio-mechanical analysis (i.e., blood flow, growth models, drug delivery, etc). This paper focuses on developing higher-fidelity models for vascular structures and blood vessels that integrate computational shape representations with biomedical properties and features. Previous work in computer-aided vascular modeling comes from two communities. For those in biomedical imaging, the goal of past research has been to develop image understanding techniques for the interpretation of x-ray, magnetic resonance imaging (MRI), or other radiological data. These representations are predominantly discrete shape models that are not tied to physiological properties. The other corpus of existing work comes from those interested in developing physiological models for vascular growth and behavior based on bio-medical attributes. These models usually either have a highly simplified shape representation, or lack one entirely. Further, neither of these representations are suitable for the kind of interactive modeling required by tissue engineering applications.This paper aims to bridge these two approaches and develop a set of mathematical tools and algorithms for feature-based representation and computer-aided modeling of vascular trees for use in computer-aided tissue engineering applications. The paper offers a multi-scale representation based on swept volumes and a feature-based representation that can attribute the geometric representation with information about blood flow, pressure, and other biomedical properties. The paper shows how the resulting representation can be used as part of an overall approach for designing and visualizing vascular scaffolds. As a real-world example, we show how this computational model can be used to develop a tissue scaffold for liver tissue engineering. Such scaffolds may prove useful in a number of biomedical applications, including the growth of replacement tissue grafts and in vitro study of the pharmacological affects of new drugs on tissue cultures.     

A Generic Pigment Model for Digital Painting

We propose a generic pigment model suitable for digital painting in a wide range of genres including traditional Chinese painting and water-based painting. The model embodies a simulation of the pigment-water solution and its interaction with the brush and the paper at the level of pigment particles; such a level of detail is needed for achieving highly intricate effects by the artist. The simulation covers pigment diffusion and sorption processes at the paper surface, and aspects of pigment particle deposition on the paper. We follow rules and formulations from quantitative studies of adsorption and diffusion processes in surface chemistry and the textile industry. The result is a pigment model that spans a continuum from the very wet to the very dry brush stroke effects. We also propose a new pigment mixing method based on machine learning techniques to emulate pigment mixing in real life as well as to support the creation of new artificial pigments. To experiment with the proposed model, we embedded the model in a sophisticated digital brush system. The combined system exhibits interactive speed on a modest PC platform. http://www.cs.hku.hk/~songhua/pigment provides supplementary materials for this paper.     

Modeling of a multisector ecological economic system with lags

A model of a diversified ecological economic system with lags is proposed and investigated using sufficient optimality conditions. A turnpike solution of the problem, boundary trajectories, and control switchpoints are found. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 114–122, March–April 2007.     

Expressing the equivalence of non‐isothermal and isothermal heat sterilization processes

Currently, the sterility of heat‐processed food and pharmaceuticals is assessed in terms of an F₀ value, based on the equivalence of the heat treatment to an isothermal process at a reference temperature. This F₀ value, however, has a meaning if, and only if, the inactivation kinetics of the targeted spores (or cells) follow a first‐order relationship and the temperature dependence of the D value, the reciprocal of the rate constant, is log‐linear. There is growing evidence that these conditions are not satisfied by many spores, including those of Clostridium botulinum and vegetative cells. Consequently, a replacement for the F₀ value is proposed in the form of a momentary equivalent time at the reference temperature based on the actual survival pattern of the spores, which need not be log‐linear. This equivalent time can be calculated together with the theoretical survival ratio in real time, thus enabling an operator to monitor the lethality of ongoing industrial heat processes. The concept is demonstrated with published survival data of C. botulinum, for which the Weibullian and log‐logistic models served as primary and secondary models, respectively. The safety factor according to the proposed method is in the number of added minutes of processing, beyond the theoretical time needed to reduce the survival ratio of the targeted spores or cells to a level that would produce practical (or commercial) sterility. Copyright © 2006 Society of Chemical Industry     

用偏微分方程构造过渡面

用偏微分方程的构造曲面是一种新兴的方法，本文借若干算例说明如何用偏微分方程构造两已知曲面之间的过渡面。论文着重讨论用四阶方程构造一阶连续的过渡面。     

The operational semantics of user-defined relationships in object oriented database systems

In semantic data models, abstract relationship (e.g. generalization, aggregation, etc.) semantics are defined, specifying how insertion, deletion and modification operations made at a higher level of abstraction can affect the objects abstracted over and vice versa. These semantics, also known as structural constraints, are expressed through so-called update rules. This perspective has been somewhat lost in most object-oriented systems, where user-defined relationships are supported as simple pointers and their semantics are embedded, distributed and replicated within the operations accessing these pointers. This paper inherits and extends the treatment of relationships found in semantic data models to behavioural object-oriented models by presenting an approach to uniformly capture the update rules for user-defined relationships. The stress is not on supporting relationships as first-class objects, but on describing their update rules (or operational semantics) through a set of constructors namely, reaction, anticipation, delegation and exception. The approach has been borne out by an implementation in an active object-oriented database system.     

Nonlinear black-box modeling in system identification: a unified overview

A nonlinear black-box structure for a dynamical system is a model structure that is prepared to describe virtually any nonlinear dynamics. There has been considerable recent interest in this area, with structures based on neural networks, radial basis networks, wavelet networks and hinging hyperplanes, as well as wavelet-transform-based methods and models based on fuzzy sets and fuzzy rules. This paper describes all these approaches in a common framework, from a user's perspective. It focuses on what are the common features in the different approaches, the choices that have to be made and what considerations are relevant for a successful system-identification application of these techniques. It is pointed out that the nonlinear structures can be seen as a concatenation of a mapping form observed data to a regression vector and a nonlinear mapping from the regressor space to the output space. These mappings are discussed separately. The latter mapping is usually formed as a basis function expansion. The basis functions are typically formed from one simple scalar function, which is modified in terms of scale and location. The expansion from the scalar argument to the regressor space is achieved by a radial- or a ridge-type approach. Basic techniques for estimating the parameters in the structures are criterion minimization, as well as two-step procedures, where first the relevant basis functions are determined, using data, and then a linear least-squares step to determine the coordinates of the function approximation. A particular problem is to deal with the large number of potentially necessary parameters. This is handled by making the number of ‘used’ parameters considerably less than the number of ‘offered’ parameters, by regularization, shrinking, pruning or regressor selection.     

EFFECT OF CRACKING REACTIONS KINETICS ON THE MODEL PREDICTIONS OF AN INDUSTRIAL FLUID CATALYTIC CRACKING UNIT

Fluid catalytic cracking (FCC) is one of the most complex processes in the petroleum industry. The large degree of uncertainty in the kinetics of the cracking reactions and catalyst deactivation by coke deposition in the riser reactor are among several factors that contribute to the process complexity. The model developed by the authors (Ali and Rohani, 1995) is used lo investigate the effect of the three-lumped kinetic scheme (Weekman and Nace, 1970) and the four-lumped scheme (Lee ct ah, 1989) on the model predictability and reliability. The effect of changes in the catalyst circulation rate, gas oil feed rate, and oxygen feed concentration on various process variables is compared. It is shown that the three-lumped kinetic scheme, despite its extensive use in the literature (McFarlane et ah, 1993; Elnashaie and Elshishini, 1993; Theologos and Markatos, 1993; Arandes and de Lasa, 1992; Lopez-lsunza and Ruiz-Martinez, 1991), leads to erroneous results and should not be used in the dynamic simulation of the FCC units,