Two-variable periodic perturbation of kinetic oscillations

Using one of the generic models (CO oxidation on Pt with surface-oxide formation) predicting kinetic oscillations in heterogeneous catalytic reactions, we show that the efficiency of two-variable periodic perturbations with respect to converting natural period-1 oscillations to period-l oscillations at the forcing frequency is remarkably sensitive to the kind of perturbations used. Counter-phase perturbations are much more effective compared to in-phase perturbations. The physics underlying these findings is suggestive of their applicability to many other models and/or real systems exhibiting kinetic oscillations.     

A case study of factor influencing role improvisation in crisis response teams

Common characteristics of crisis situations are ambiguous and unplanned for events. The need for improvised roles can therefore be an imperative factor for the success of an operation. The aim of this study is to deepen the understanding of the processes taking place during improvised work “as it happens”. A case study of a crisis management team at work is presented and provides an in-depth analysis of the information and communication flow of persons acting in improvised roles, including contextual factors influencing the task at hand. The analysis suggests that three main factors lay behind decreased performance by the team when some of its members were forced to take on roles for which they lacked professional training; lack of language skills, lack of domain knowledge and insufficient organizational structure of the tasks. Based on the observations from this case study, we suggest three ways of improving a team’s performance and hence resilience when forced to improvise due to lack of personnel in one or more required competence areas. These are training to take on the responsibility for tasks or roles outside ones professional area of specialization, developing formal routines for changes in roles and tasks and developing and using tools and routines for information sharing.     

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.     

Design and implementation of the Node Identity Internetworking Architecture

The Internet Protocol (IP) has been proven very flexible, being able to accommodate all kinds of link technologies and supporting a broad range of applications. The basic principles of the original Internet architecture include end-to-end addressing, global routeability and a single namespace of IP addresses that unintentionally serves both as locators and host identifiers. The commercial success and widespread use of the Internet have lead to new requirements, which include Internetworking over business boundaries, mobility and multi-homing in an untrusted environment. Our approach to satisfy these new requirements is to introduce a new Internetworking layer, the node identity layer. Such a layer runs on top of the different versions of IP, but could also run directly on top of other kinds of network technologies, such as MPLS and 2G/3G PDP contexts. This approach enables connectivity across different communication technologies, supports mobility, multi-homing, and security from ground up. This paper describes the Node Identity Architecture in detail and discusses the experiences from implementing and running a prototype.     

Selective determination of urea using urease immobilized on ZnO nanowires

Well-aligned zinc oxide (ZnO) nanowire arrays were fabricated on gold-coated plastic substrates using a low-temperature aqueous chemical growth (ACG) method. The ZnO nanowire arrays with 50–130 nm diameters and ∼1 μm in lengths were used in an enzyme-based urea sensor through immobilization of the enzyme urease that was found to be sensitive to urea concentrations from 0.1 mM to 100 mM. Two linear sensitivity regions were observed when the electrochemical responses (EMF) of the sensors were plotted vs. the logarithmic concentration range of urea from 0.1 mM to 100 mM. The proposed sensor showed a sensitivity of 52.8 mV/decade for 0.1–40 mM urea and a fast response time less than 4 s was achieved with good selectivity, reproducibility and negligible response to common interferents such as ascorbic acid and uric acid, glucose, K⁺ and Na⁺ ions.     

Modelling of interstitials in the bcc phase

There are several widespread thermodynamic datasets which produce a spurious bcc interstitial solution at high temperature and high X content (X is an interstitally dissolved element). The reason for this is the standard model for bcc interstitial solutions (M(V a,X)₃), which requires careful selection of optimising parameters to minimise spurious appearances of the bcc phase. In this work the model M(V a,X)₁ is suggested as an alternative. This model is much easier to handle and its parameters can be directly compared with those of the fcc phase. The two models are compared for the Fe–C and Nb–N systems. In the Fe–C system almost identical results are achieved. In Nb–N there are some differences for high N content, but there is no experimental data to clearly support any model.     

Active learning for extended finite state machines

We present a black-box active learning algorithm for inferring extended finite state machines (EFSM)s by dynamic black-box analysis. EFSMs can be used to model both data flow and control behavior of software and hardware components. Different dialects of EFSMs are widely used in tools for model-based software development, verification, and testing. Our algorithm infers a class of EFSMs called register automata. Register automata have a finite control structure, extended with variables (registers), assignments, and guards. Our algorithm is parameterized on a particular theory, i.e., a set of operations and tests on the data domain that can be used in guards.Key to our learning technique is a novel learning model based on so-called tree queries. The learning algorithm uses tree queries to infer symbolic data constraints on parameters, e.g., sequence numbers, time stamps, identifiers, or even simple arithmetic. We describe sufficient conditions for the properties that the symbolic constraints provided by a tree query in general must have to be usable in our learning model. We also show that, under these conditions, our framework induces a generalization of the classical Nerode equivalence and canonical automata construction to the symbolic setting. We have evaluated our algorithm in a black-box scenario, where tree queries are realized through (black-box) testing. Our case studies include connection establishment in TCP and a priority queue from the Java Class Library.     

Outflow Boundary Conditions for the Fourier Transformed One-Dimensional Vlasov–Poisson System

In order to facilitate numerical simulations of plasma phenomena where kinetic processes are important, we have studied the technique of Fourier transforming the Vlasov equation analytically in the velocity space, and solving the resulting equation numerically. Special attention has been paid to the boundary conditions of the Fourier transformed system. By using outgoing wave boundary conditions in the Fourier transformed space, small-scale information in velocity space is carried outside the computational domain and is lost. Thereby the so-called recurrence phenomenon is reduced. This method is an alternative to using numerical dissipation or smoothing operators in velocity space. Different high-order methods are used for computing derivatives as well as for the time-stepping, leading to an over-all fourth-order method.