Resonances for water waves over flows with piecewise constant vorticity

We investigate three and four-wave resonances of capillary–gravity water waves arising as the free surface of water flows exhibiting piecewise constant vorticity. More precisely, our type of flow has a jump in the vorticity distribution that separates a rotational layer at the top (commonly generated by wind-shear) from another rotational layer adjacent to the sea-bed, region that accommodates strong sheared currents. Instrumental in deriving our findings is the dispersion relation for such flows having a jump in the distribution of the vorticity. In general, for rotational flows of non-constant vorticity, the dispersion relation is very intricate. However, we show that a disentanglement occurs in the case of capillary–gravity water waves for which the ratio “thickness of the near-surface vortical layer/the wavelength of the surface wave” is sufficiently large. More precisely, we find explicitly two solutions, ${\lambda }_0$ and ${\lambda }_1$ that represent the (relative) surface wave speed. We then confirm analytically that ${\lambda }_1$ gives rise to three-wave resonances for capillary–gravity water waves with wavelengths not exceeding 2 cm. However, for significant wavelength range, we establish that ${\lambda }_1$ does not lead to four-wave resonances. In contrast to the previous conclusion ${\lambda }_0$ does not bring about three-wave resonances, but is able to generate four-wave resonances.     

Service stage Petri net models with product form solution

A class of service stage Petri net models whose equilibrium probabilities satisfy local balance equations is presented. Examples of their applicability include bus oriented multiprocessor interconnections, the classical dining philosophers problem and the alternating bit protocol. The natural topological space for embedding the state transition lattice for this class of SSPN is shown to be a multidimensional toroidal manifold.     

A piecewise approach to piecewise approximation

Tensor-product B-spline surfaces offer a convenient means for representing a set of bivariate data, especially if many surface evaluations are required. This is because the compact support property of the tensor-product spline allows the spline value to be obtained in a time that is (almost) independent of the number of coefficients used to define the surface. The main calculation is the precomputation involved in fitting the data and this can be impractically large if there are many spline coefficients to be calculated. Since the surface produced may be evaluated locally and efficiently, it would be advantageous to exploit local properties in order to fit the data in a piecewise manner. An algorithm to do this is presented.     

Performance analysis and design of supply chains: a Petri net approach

In this paper, we investigated a dynamic modelling technique for analysing supply chain networks using generalised stochastic Petri nets (GSPNs). The customer order arrival process is assumed to be Poisson and the service processes at the various facilities of the supply chain are assumed to be exponential. Our model takes into account both the procurement process and delivery logistics that exist between any two members of the supply chain. We compare the performance of two production planning and control policies, the make-to-stock and the assemble-to-order systems in terms of total cost which is the sum of inventory carrying cost and cost incurred due to delayed deliveries. We formulate and solve the decoupling point location problem in supply chains as a total relevant cost (sum of inventory carrying cost and the delay costs) minimisation problem. We use the framework of integrated GSPN-queuing network modelling—with the GSPN at the higher level and a generalised queuing network at the lower level—to solve the decoupling point location problem.     

A Petri net approach to the modelling and analysis of flexible manufacturing systems

In this paper we present an approach for modelling and analyzing flexible manufacturing systems (FMSs) using Petri nets. In this approach, we first build a Petri net model (PNM) of the given FMS in a bottom-up fashion and then analyze important qualitative aspects of FMS behaviour such as existence/absence of deadlocks and buffer overflows. The basis for our approach is a theorem we state and prove for computing the invariants of the union of a finite number of Petri nets when the invariants of the individual nets are known. We illustrate our approach using two typical manufacturing systems: an automated transfer line and a simple FMS.A shorter version of this paper was presented at the 1st ORSA/TIMS Special Interest Conference on FMSs, University of Michigan, Ann Arbor, August 1984.     

A topological approach to the existence of solutions for nonlinear differential equations with piecewise constant argument

In this paper, we investigate qualitative behavior of nonlinear differential equations with piecewise constant argument (PCA). A topological approach of Wa?ewski-type which gives sufficient conditions to guarantee that the graph of at least one solution stays in a given domain is formulated. Moreover, our results are also suitable for a class of general system of discrete equations. By using a regular polyfacial set, we apply our developed topological approach to cellular neural networks (CNNs) with PCA. Some new results are attained to reveal dynamic behavior of CNNs with PCA and discrete-time CNNs. Finally, an illustrative example of CNNs with PCA shows usefulness and effectiveness of our results.     

A method to abstract a stochastic Petri net

We propose a method to abstract a given stochastic Petri net (SPN). We shall show that the reachability tree of the given SPN is isomorphic to a Markov renewal process. Then, the given SPN is transformed to a state transition system (STS) and the STS is reduced. The reduction of states on STS corresponds to a fusion of series transitions on the SPN. The reduced STS is again transformed to an abstract SPN. We show that it is helpful to use the notion of the conditional firstpassage time from a certain state to the others on the STS to reduce nonessential states, thus places and transitions on the given SPN. Mass functions, that is, the distribution functions of conditional first-passage time between preserved states on the reduced MRP, preserve firing probabilities of fused transitions. Firing probability of the preserved transition also preserves the stochastic properties of the fused transitions.     

A variational approach to the determination of domain for Euler flows with constant vorticity

An alternative variational method for a steady, two-dimensional inviscid flow problem to determine the domain given the constant wall velocity and constant vorticity in the whole domain is presented. The uniqueness result is obtained for convex domains.     

All invariant densities of piecewise linear Markov maps are piecewise constant

Let τ: [0,1] → [0,1] be a piecewise linear Markov map. It is shown that all density functions invariant under τ must be piecewise constant. This has useful application to solutions of functional equations.     

An optimization-based approach to assess non-interference in labeled and bounded Petri net systems

An optimization-based approach to assess both strong non-deterministic non- interference (SNNI) and bisimulation SNNI (BSNNI) in discrete event systems modeled as labeled Petri nets is presented in this paper. The assessment of SNNI requires the solution of feasibility problems with integer variables and linear constraints, which is derived by extending a previous result given in the case of unlabeled net systems. Moreover, the BSNNI case can be addressed in two different ways. First, similarly to the case of SNNI, a condition to assess BSNNI, which is necessary and sufficient, can be derived from the one given in the unlabeled framework, requiring the solution of feasibility problems with integer variables and linear constraints. Then, a novel necessary and sufficient condition to assess BSNNI is given, which requires the solution of integer feasibility problems with nonlinear constraints. Furthermore, we show how to recast these problems into equivalent mixed-integer linear programming (MILP) ones. The effectiveness of the proposed approaches is shown by means of several examples. It turns out that there are relevant cases where the new condition to assess BSNNI that requires the solution of MILP problems is computationally more efficient, when compared to the one that requires the solution of feasibility problems.     

Approximation of finite-section equations by piecewise constant functions

The problem is studied of reducing the amount of discrete information required for achieving a prescribed accuracy of solving Fredholm integral equations of the first kind on a half-line. The equations are solved by the finite-section method combined with piecewise constant interpolation of the kernel and the right-hand side at uniform grid points. The approximating properties of the discretization schemes are examined, and the corresponding computational costs are analyzed.     

Petri net modelling of biological regulatory networks

The complexity of biological regulatory networks often defies the intuition of the biologist and calls for the development of proper mathematical methods to model their structures and to delineate their dynamical properties. One qualitative approach consists in modelling regulatory networks in terms of logical equations (using either Boolean or multi-level discretisations). The Petri Net (PN) formalism offers a complementary framework to analyse the dynamical behaviour of large systems, either from a qualitative or from a quantitative point of view.

Our proposal consists in articulating the logical approach with the PN formalism. In a previous work, we have already defined a systematic re-writing of Boolean regulatory models into a standard PN formalism. In this paper, we propose a rigorous and systematic mapping of multi-level logical regulatory models into specific standard Petri nets, called Multi-level Regulatory Petri Nets (MRPNs). We further propose some reduction strategies. Consequently, the resulting models become amenable to the algebraic and computational analyses used by the PN community.

To illustrate our approach, we apply it to a multi-level logical model of the genetic switch controlling the lysis-lysogeny decision in the lambda bacteriophage.     

A piecewise polynomial approach to analyzing interpolatory subdivision

The four-point interpolatory subdivision scheme of Dubuc and its generalizations to irregularly spaced data studied by Warren and by Daubechies, Guskov, and Sweldens are based on fitting cubic polynomials locally. In this paper, we analyze the convergence of the scheme by viewing the limit function as the limit of piecewise cubic functions arising from the scheme. This allows us to recover the regularity results of Daubechies et al. in a simpler way and to obtain the approximation order of the scheme and its first derivative.     

A piecewise constant collocation method using cosine mesh grading for Symm's equation

Summary Here we study the piecewise constant collocation method using mesh grading to solve Symm's integral equation on [–1, 1]. We give a mesh grading for which this method achieves the optimal order of convergence even though the piecewise constant Galerkin method with the same mesh grading does not. Some numerical results are given.     

A new algorithm for simulating viscoelastic flows accommodating piecewise linear finite elements

A three-field finite element scheme designed for solving time-dependent systems of partial differential equations governing viscoelastic flows is introduced. The linearized form of this system is a generalized time-dependent Stokes system. Once a classical time-discretization is performed, the resulting three-field system of equations allows for a stable approximation of velocity, pressure and extra stress tensor, by means of continuous piecewise linear finite elements, in both two and three dimension space. Another advantage of the new formulation is the fact that it implicitly provides an algorithm for the iterative resolution of system non-linearities, in the case of viscoelastic flows. Additionally, convergence in an appropriate sense applying to these three flow fields is demonstrated, for such generalized Stokes system. Numerical results are given in order to illustrate the performance of the new approach.     

具分段常变元的时滞微分方程的振动性

The delay differential equation with piecewise constant argument x′(t)+a(t)x(t)+b(t)x([t-k])=0 is considered,where a(t) and b(t) are continuous functions on [-k,∞),b(t)≥0,k is a positive integer and [·] denotes the greatest integer function.Some new oscillation and nonoscillation conditions are obtained.     

Existence of capillary-gravity water waves with piecewise constant vorticity

In this paper we construct small-amplitude periodic capillary-gravity water waves with a piecewise constant vorticity distribution. They describe water waves traveling on superposed linearly sheared currents that have different vorticities. This is achieved by associating to the height function formulation of the water wave problem a diffraction problem where we impose suitable transmission conditions on each line where the vorticity function has a jump. The solutions of the diffraction problem, found by using local bifurcation theory, are the desired solutions of the hydrodynamical problem.     

Petri net approach to disassembly process planning for products with complex AND/OR precedence relationships

We present a Petri net (PN)-based approach to automatically generate disassembly process plans (DPPs) for product recycling or remanufacturing. We define an algorithm to generate a geometrically-based disassembly precedence matrix (DPM) from a CAD drawing of the product. We then define an algorithm to automatically generate a disassembly Petri net (DPN) from the DPM; the DPN is live, bounded, and reversible. The resulting DPN can be analyzed using the reachability tree method to generate feasible DPPs, and cost functions can be used to determine the optimal DPP. Since reachability tree generation is NP-complete, we develop a heuristic to dynamically explore the v likeliest lowest cost branches of the tree, to identify optimal or near-optimal DPPs. The cost function incorporates tool changes, changes in direction of movement, and individual part characteristics (e.g., hazardous). An example is used to illustrate the procedure. This approach can be used for products containing AND, OR, and complex AND/OR disassembly precedence relationships.     

A Retinex modulated piecewise constant variational model for image segmentation and bias correction

In this paper, we propose a novel Retinex induced piecewise constant variational model for simultaneous segmentation of images with intensity inhomogeneity and bias correction. Firstly, we obtain an additive model by decomposing the original image into a smooth bias component and a structure part based on the Retinex theory. Secondly, the structure part can be modeled by the piecewise constant variational model and thus deduced a new data fidelity term. Finally, we formulate a new energy functional by incorporating the data fidelity term into the level set framework and introducing a GL-regularizer to the level set function and a smooth regularizer to model the bias component. Based on the alternating minimization algorithm and the operator splitting method, we present a numerical scheme to solve the minimization problem efficiently. Experimental results on images from diverse modalities demonstrate the competitive performances of the proposed model and algorithm over other representative methods in term of efficiency and robustness.     

A multiscale time model with piecewise constant argument for a boundedly rational monopolist

We present a dynamic model for a boundedly rational monopolist who, in a partially known environment, follows a rule-of-thumb learning process. We assume that the production activity is continuously carried out and that the costly learning activity only occurs periodically at discrete time periods, so that the resulting dynamical model consists of a piecewise constant argument differential equation. Considering general demand, cost and agent’s reactivity functions, we show that the behavior of the differential model is governed by a nonlinear discrete difference equation. Differently from the classical model with smooth argument, unstable, complex dynamics can arise. The main novelty consists in showing that the occurrence of such dynamics is caused by the presence of multiple (discrete and continuous) time scales and depends on size of the time interval between two consecutive learning processes, in addition to the agent’s reactivity and the sensitivity of the marginal profit.