Modelling brittle impact failure of disc particles using material point method

Understanding the impact failure of particles made of brittle materials such as glasses, ceramics and rocks is an important issue for many engineering applications. During the impact, a solid particle is turned into a discrete assembly of many fragments through the development of multiple cracks. The finite element method is fundamentally ill-equipped to model this transition. Recently a so-called material point method (MPM) has been used to study a wide range of problems of material and structural failures. In this paper we propose a new material point model for the brittle failure which incorporates a statistical failure criterion. The capability of the method for modelling multiple cracks is demonstrated using disc particles. Three impact failure patterns observed experimentally are captured by the model: Hertzian ring cracks, meridian cracks, and multi-fragment cracks. Detailed stress analysis is carried out to interpret the experimental observations. In particular it is shown that the experimentally observed dependence of a threshold velocity for the initiation of meridian cracks on the particle size can be explained by the proposed model. The material point based scheme requires a relatively modest programming effort and avoids node splitting which makes it very attractive over the traditional finite element method.     

Initial column profile with composition-dependent relative volatility

When solving the large scale, highly nonlinear, equation systems of steady state multistage distillation processes modelled with theoretical plates, convergence depends on the initial values. The conventionally applied linear initial profiles frequently give rise to divergence when azeotrope is present. The usual practice in such cases is initializing with engineering insight, i.e. anticipating the results. Composition-dependent relative volatility model is developed in the present work, and applied successfully to initialize the composition profiles of distillation columns. The model describes the implicit temperature dependence through composition dependence. Equlibrium plots computed with the new model well approximate the measured data of strongly non-ideal, and even azeotropic, mixtures. The initial column profiles computed with the new model are rather similar to the final solution, and thus accelerate the computation. Processes can be modelled with the new initial profile when the solution algorithms do not converge with the conventional initialization.     

Semantics and pragmatics of Real-Time Maude

At present, designers of real-time systems face a dilemma between expressiveness and automatic verification: if they can specify some aspects of their system in some automaton-based formalism, then automatic verification is possible; but more complex system components may be hard or impossible to express in such decidable formalisms. These more complex components may still be simulated; but there is then little support for their formal analysis. The main goal of Real-Time Maude is to provide a way out of this dilemma, while complementing both decision procedures and simulation tools. Real-Time Maude emphasizes ease and generality of specification, including support for distributed real-time object-based systems. Because of its generality, falling outside of decidable system classes, the formal analyses supported—including symbolic simulation, breadth-first search for failures of safety properties, and model checking of time-bounded temporal logic properties—are in general incomplete (although they are complete for discrete time). These analysis techniques have been shown useful in finding subtle bugs of complex systems, clearly outside the scope of current decision procedures. This paper describes both the semantics of Real-Time Maude specifications, and of the formal analyses supported by the tool. It also explains the tool's pragmatics, both in the use of its features, and in its application to concrete examples.     

Application of probabilistic and fuzzy cognitive approaches in semantic web framework for medical decision support

This study aimed to focus on medical knowledge representation and reasoning using the probabilistic and fuzzy influence processes, implemented in the semantic web, for decision support tasks. Bayesian belief networks (BBNs) and fuzzy cognitive maps (FCMs), as dynamic influence graphs, were applied to handle the task of medical knowledge formalization for decision support. In order to perform reasoning on these knowledge models, a general purpose reasoning engine, EYE, with the necessary plug-ins was developed in the semantic web. The two formal approaches constitute the proposed decision support system (DSS) aiming to recognize the appropriate guidelines of a medical problem, and to propose easily understandable course of actions to guide the practitioners. The urinary tract infection (UTI) problem was selected as the proof-of-concept example to examine the proposed formalization techniques implemented in the semantic web. The medical guidelines for UTI treatment were formalized into BBN and FCM knowledge models. To assess the formal models’ performance, 55 patient cases were extracted from a database and analyzed. The results showed that the suggested approaches formalized medical knowledge efficiently in the semantic web, and gave a front-end decision on antibiotics’ suggestion for UTI.     

Effect of Inducible BMP-7 Expression on the Osteogenic Differentiation of Human Dental Pulp Stem Cells

BMP-7 has shown inductive potential for in vitro osteogenic differentiation of mesenchymal stem cells, which are an ideal resource for regenerative medicine. Externally applied, recombinant BMP-7 was able to induce the osteogenic differentiation of DPSCs but based on our previous results with BMP-2, we aimed to study the effect of the tetracyclin-inducible BMP-7 expression on these cells. DPSC, mock, and DPSC-BMP-7 cell lines were cultured in the presence or absence of doxycycline, then alkaline phosphatase (ALP) activity, mineralization, and mRNA levels of different osteogenic marker genes were measured. In the DPSC-BMP-7 cell line, the level of BMP-7 mRNA significantly increased in the media supplemented with doxycycline, however, the expression of Runx2 and noggin genes was upregulated only after 21 days of incubation in the osteogenic medium with doxycycline. Moreover, while the examination of ALP activity showed reduced activity in the control medium containing doxycycline, the accumulation of minerals remained unchanged in the cultures. We have found that the induced BMP-7 expression failed to induce osteogenic differentiation of DPSCs. We propose three different mechanisms that may worth investigating for the engineering of expression systems that can be used for the induction of differentiation of mesenchymal stem cells.     

Micromagnetic simulation of current-driven domain wall propagation

We develop a method to model the interaction of currents and domain walls in a standard micromagnetic simulator. The interaction of spin-polarized currents and localized magnetic moments can be described by a current-induced effective field, which superposes to other components of the effective magnetic field. Using our method, we examine domain wall propagation in ideal, rough-surfaced and notched domain walls.     

Field-coupled computing in magnetic multilayers

This paper presents a computational study of ion-beam patterned cobalt-platinum multilayers, which could be used for field-coupled computing. We use micromagnetic simulations to reproduce measured hysteresis curves. This parameterized micromagnetic simulator then will be used for simulating interacting magnetic dots. We demonstrate how logic gates can be built from such coupled dots. We also show how electrical wires—placed beneath or above the magnetic dots—can provide a magnetic field, which propagates the magnetic signals.     

Preparation and characterization of hydroxyapatite from eggshell

Hydroxyapatite (HAp) was successfully produced by using recycled eggshell. The observed phases of the synthesised materials were dependent on the mechanochemical activation method (ball milling and attrition milling). The structures of the HAp were characterized by X-ray diffraction, scanning electron microscopy and infrared spectroscopy. Attrition milling proved to be more efficient than ball milling, as resulted nanosize, homogenous HAp even after milling.     

Modelling adhesive contact between fine particles using material point method

This paper presents a numerical study on contact law between extremely fine particles taking into account of the effect of adhesion force and surface roughness. The adhesion force between two particles is calculated from the Erkoc inter-atomic potential. This force is incorporated into a material point model for the dynamic impact between the two particles. Unlike a molecular dynamics model, atoms in the model are embedded in the continuum solid such that they can only move relatively to each other as the continuum solid deforms. The model is numerically efficient while taking into account of the adhesion effect at the same time. Numerical study using this model shows that the Maugis theory (Maugis, 1992) is valid for spherical particles as small as 50 nm in size. The numerical study also shows that a slight change in surface roughness can alter the impact behaviour completely. Therefore an uncertainty in using the Maugis contact law for real particles is how to determine the effective specific surface energy for particles of different surface roughness. Because of the uncertainty, full numerical analysis may have to be used to obtain the adhesive contact law.