Accelerating solutions of one-dimensional unsteady PDEs with GPU-based swept time-space decomposition

NASA Astrophysics Data System (ADS)

Magee, Daniel J.; Niemeyer, Kyle E.

2018-03-01

The expedient design of precision components in aerospace and other high-tech industries requires simulations of physical phenomena often described by partial differential equations (PDEs) without exact solutions. Modern design problems require simulations with a level of resolution difficult to achieve in reasonable amounts of time-even in effectively parallelized solvers. Though the scale of the problem relative to available computing power is the greatest impediment to accelerating these applications, significant performance gains can be achieved through careful attention to the details of memory communication and access. The swept time-space decomposition rule reduces communication between sub-domains by exhausting the domain of influence before communicating boundary values. Here we present a GPU implementation of the swept rule, which modifies the algorithm for improved performance on this processing architecture by prioritizing use of private (shared) memory, avoiding interblock communication, and overwriting unnecessary values. It shows significant improvement in the execution time of finite-difference solvers for one-dimensional unsteady PDEs, producing speedups of 2 - 9 × for a range of problem sizes, respectively, compared with simple GPU versions and 7 - 300 × compared with parallel CPU versions. However, for a more sophisticated one-dimensional system of equations discretized with a second-order finite-volume scheme, the swept rule performs 1.2 - 1.9 × worse than a standard implementation for all problem sizes.

Modelling atmospheric flows with adaptive moving meshes

NASA Astrophysics Data System (ADS)

Kühnlein, Christian; Smolarkiewicz, Piotr K.; Dörnbrack, Andreas

2012-04-01

An anelastic atmospheric flow solver has been developed that combines semi-implicit non-oscillatory forward-in-time numerics with a solution-adaptive mesh capability. A key feature of the solver is the unification of a mesh adaptation apparatus, based on moving mesh partial differential equations (PDEs), with the rigorous formulation of the governing anelastic PDEs in generalised time-dependent curvilinear coordinates. The solver development includes an enhancement of the flux-form multidimensional positive definite advection transport algorithm (MPDATA) - employed in the integration of the underlying anelastic PDEs - that ensures full compatibility with mass continuity under moving meshes. In addition, to satisfy the geometric conservation law (GCL) tensor identity under general moving meshes, a diagnostic approach is proposed based on the treatment of the GCL as an elliptic problem. The benefits of the solution-adaptive moving mesh technique for the simulation of multiscale atmospheric flows are demonstrated. The developed solver is verified for two idealised flow problems with distinct levels of complexity: passive scalar advection in a prescribed deformational flow, and the life cycle of a large-scale atmospheric baroclinic wave instability showing fine-scale phenomena of fronts and internal gravity waves.

Numerical Simulations of Reacting Flows Using Asynchrony-Tolerant Schemes for Exascale Computing

NASA Astrophysics Data System (ADS)

Cleary, Emmet; Konduri, Aditya; Chen, Jacqueline

2017-11-01

Communication and data synchronization between processing elements (PEs) are likely to pose a major challenge in scalability of solvers at the exascale. Recently developed asynchrony-tolerant (AT) finite difference schemes address this issue by relaxing communication and synchronization between PEs at a mathematical level while preserving accuracy, resulting in improved scalability. The performance of these schemes has been validated for simple linear and nonlinear homogeneous PDEs. However, many problems of practical interest are governed by highly nonlinear PDEs with source terms, whose solution may be sensitive to perturbations caused by communication asynchrony. The current work applies the AT schemes to combustion problems with chemical source terms, yielding a stiff system of PDEs with nonlinear source terms highly sensitive to temperature. Examples shown will use single-step and multi-step CH4 mechanisms for 1D premixed and nonpremixed flames. Error analysis will be discussed both in physical and spectral space. Results show that additional errors introduced by the AT schemes are negligible and the schemes preserve their accuracy. We acknowledge funding from the DOE Computational Science Graduate Fellowship administered by the Krell Institute.

Variational formulation for dissipative continua and an incremental J-integral

NASA Astrophysics Data System (ADS)

Rahaman, Md. Masiur; Dhas, Bensingh; Roy, D.; Reddy, J. N.

2018-01-01

Our aim is to rationally formulate a proper variational principle for dissipative (viscoplastic) solids in the presence of inertia forces. As a first step, a consistent linearization of the governing nonlinear partial differential equations (PDEs) is carried out. An additional set of complementary (adjoint) equations is then formed to recover an underlying variational structure for the augmented system of linearized balance laws. This makes it possible to introduce an incremental Lagrangian such that the linearized PDEs, including the complementary equations, become the Euler-Lagrange equations. Continuous groups of symmetries of the linearized PDEs are computed and an analysis is undertaken to identify the variational groups of symmetries of the linearized dissipative system. Application of Noether's theorem leads to the conservation laws (conserved currents) of motion corresponding to the variational symmetries. As a specific outcome, we exploit translational symmetries of the functional in the material space and recover, via Noether's theorem, an incremental J-integral for viscoplastic solids in the presence of inertia forces. Numerical demonstrations are provided through a two-dimensional plane strain numerical simulation of a compact tension specimen of annealed mild steel under dynamic loading.

Non-fragile consensus algorithms for a network of diffusion PDEs with boundary local interaction

NASA Astrophysics Data System (ADS)

Xiong, Jun; Li, Junmin

2017-07-01

In this study, non-fragile consensus algorithm is proposed to solve the average consensus problem of a network of diffusion PDEs, modelled by boundary controlled heat equations. The problem deals with the case where the Neumann-type boundary controllers are corrupted by additive persistent disturbances. To achieve consensus between agents, a linear local interaction rule addressing this requirement is given. The proposed local interaction rules are analysed by applying a Lyapunov-based approach. The multiplicative and additive non-fragile feedback control algorithms are designed and sufficient conditions for the consensus of the multi-agent systems are presented in terms of linear matrix inequalities, respectively. Simulation results are presented to support the effectiveness of the proposed algorithms.

Solving PDEs with Intrepid

DOE PAGES

Bochev, P.; Edwards, H. C.; Kirby, R. C.; ...

2012-01-01

Intrepid is a Trilinos package for advanced discretizations of Partial Differential Equations (PDEs). The package provides a comprehensive set of tools for local, cell-based construction of a wide range of numerical methods for PDEs. This paper describes the mathematical ideas and software design principles incorporated in the package. We also provide representative examples showcasing the use of Intrepid both in the context of numerical PDEs and the more general context of data analysis.

Free-form geometric modeling by integrating parametric and implicit PDEs.

PubMed

Du, Haixia; Qin, Hong

2007-01-01

Parametric PDE techniques, which use partial differential equations (PDEs) defined over a 2D or 3D parametric domain to model graphical objects and processes, can unify geometric attributes and functional constraints of the models. PDEs can also model implicit shapes defined by level sets of scalar intensity fields. In this paper, we present an approach that integrates parametric and implicit trivariate PDEs to define geometric solid models containing both geometric information and intensity distribution subject to flexible boundary conditions. The integrated formulation of second-order or fourth-order elliptic PDEs permits designers to manipulate PDE objects of complex geometry and/or arbitrary topology through direct sculpting and free-form modeling. We developed a PDE-based geometric modeling system for shape design and manipulation of PDE objects. The integration of implicit PDEs with parametric geometry offers more general and arbitrary shape blending and free-form modeling for objects with intensity attributes than pure geometric models.

Clinical and Molecular Genetics of the Phosphodiesterases (PDEs)

PubMed Central

Azevedo, Monalisa F.; Faucz, Fabio R.; Bimpaki, Eirini; Horvath, Anelia; Levy, Isaac; de Alexandre, Rodrigo B.; Ahmad, Faiyaz; Manganiello, Vincent

2014-01-01

Cyclic nucleotide phosphodiesterases (PDEs) are enzymes that have the unique function of terminating cyclic nucleotide signaling by catalyzing the hydrolysis of cAMP and GMP. They are critical regulators of the intracellular concentrations of cAMP and cGMP as well as of their signaling pathways and downstream biological effects. PDEs have been exploited pharmacologically for more than half a century, and some of the most successful drugs worldwide today affect PDE function. Recently, mutations in PDE genes have been identified as causative of certain human genetic diseases; even more recently, functional variants of PDE genes have been suggested to play a potential role in predisposition to tumors and/or cancer, especially in cAMP-sensitive tissues. Mouse models have been developed that point to wide developmental effects of PDEs from heart function to reproduction, to tumors, and beyond. This review brings together knowledge from a variety of disciplines (biochemistry and pharmacology, oncology, endocrinology, and reproductive sciences) with emphasis on recent research on PDEs, how PDEs affect cAMP and cGMP signaling in health and disease, and what pharmacological exploitations of PDEs may be useful in modulating cyclic nucleotide signaling in a way that prevents or treats certain human diseases. PMID:24311737

Scalable Nonlinear Solvers for Fully Implicit Coupled Nuclear Fuel Modeling. Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai, Xiao-Chuan; Keyes, David; Yang, Chao

2014-09-29

The focus of the project is on the development and customization of some highly scalable domain decomposition based preconditioning techniques for the numerical solution of nonlinear, coupled systems of partial differential equations (PDEs) arising from nuclear fuel simulations. These high-order PDEs represent multiple interacting physical fields (for example, heat conduction, oxygen transport, solid deformation), each is modeled by a certain type of Cahn-Hilliard and/or Allen-Cahn equations. Most existing approaches involve a careful splitting of the fields and the use of field-by-field iterations to obtain a solution of the coupled problem. Such approaches have many advantages such as ease of implementationmore » since only single field solvers are needed, but also exhibit disadvantages. For example, certain nonlinear interactions between the fields may not be fully captured, and for unsteady problems, stable time integration schemes are difficult to design. In addition, when implemented on large scale parallel computers, the sequential nature of the field-by-field iterations substantially reduces the parallel efficiency. To overcome the disadvantages, fully coupled approaches have been investigated in order to obtain full physics simulations.« less

Numerical solution of modified differential equations based on symmetry preservation.

PubMed

Ozbenli, Ersin; Vedula, Prakash

2017-12-01

In this paper, we propose a method to construct invariant finite-difference schemes for solution of partial differential equations (PDEs) via consideration of modified forms of the underlying PDEs. The invariant schemes, which preserve Lie symmetries, are obtained based on the method of equivariant moving frames. While it is often difficult to construct invariant numerical schemes for PDEs due to complicated symmetry groups associated with cumbersome discrete variable transformations, we note that symmetries associated with more convenient transformations can often be obtained by appropriately modifying the original PDEs. In some cases, modifications to the original PDEs are also found to be useful in order to avoid trivial solutions that might arise from particular selections of moving frames. In our proposed method, modified forms of PDEs can be obtained either by addition of perturbation terms to the original PDEs or through defect correction procedures. These additional terms, whose primary purpose is to enable symmetries with more convenient transformations, are then removed from the system by considering moving frames for which these specific terms go to zero. Further, we explore selection of appropriate moving frames that result in improvement in accuracy of invariant numerical schemes based on modified PDEs. The proposed method is tested using the linear advection equation (in one- and two-dimensions) and the inviscid Burgers' equation. Results obtained for these tests cases indicate that numerical schemes derived from the proposed method perform significantly better than existing schemes not only by virtue of improvement in numerical accuracy but also due to preservation of qualitative properties or symmetries of the underlying differential equations.

Variable Step Integration Coupled with the Method of Characteristics Solution for Water-Hammer Analysis, A Case Study

NASA Technical Reports Server (NTRS)

Turpin, Jason B.

2004-01-01

One-dimensional water-hammer modeling involves the solution of two coupled non-linear hyperbolic partial differential equations (PDEs). These equations result from applying the principles of conservation of mass and momentum to flow through a pipe, and usually the assumption that the speed at which pressure waves propagate through the pipe is constant. In order to solve these equations for the interested quantities (i.e. pressures and flow rates), they must first be converted to a system of ordinary differential equations (ODEs) by either approximating the spatial derivative terms with numerical techniques or using the Method of Characteristics (MOC). The MOC approach is ideal in that no numerical approximation errors are introduced in converting the original system of PDEs into an equivalent system of ODEs. Unfortunately this resulting system of ODEs is bound by a time step constraint so that when integrating the equations the solution can only be obtained at fixed time intervals. If the fluid system to be modeled also contains dynamic components (i.e. components that are best modeled by a system of ODEs), it may be necessary to take extremely small time steps during certain points of the model simulation in order to achieve stability and/or accuracy in the solution. Coupled together, the fixed time step constraint invoked by the MOC, and the occasional need for extremely small time steps in order to obtain stability and/or accuracy, can greatly increase simulation run times. As one solution to this problem, a method for combining variable step integration (VSI) algorithms with the MOC was developed for modeling water-hammer in systems with highly dynamic components. A case study is presented in which reverse flow through a dual-flapper check valve introduces a water-hammer event. The predicted pressure responses upstream of the check-valve are compared with test data.

Numerical modeling of bubble dynamics in viscoelastic media with relaxation

NASA Astrophysics Data System (ADS)

Warnez, M. T.; Johnsen, E.

2015-06-01

Cavitation occurs in a variety of non-Newtonian fluids and viscoelastic materials. The large-amplitude volumetric oscillations of cavitation bubbles give rise to high temperatures and pressures at collapse, as well as induce large and rapid deformation of the surroundings. In this work, we develop a comprehensive numerical framework for spherical bubble dynamics in isotropic media obeying a wide range of viscoelastic constitutive relationships. Our numerical approach solves the compressible Keller-Miksis equation with full thermal effects (inside and outside the bubble) when coupled to a highly generalized constitutive relationship (which allows Newtonian, Kelvin-Voigt, Zener, linear Maxwell, upper-convected Maxwell, Jeffreys, Oldroyd-B, Giesekus, and Phan-Thien-Tanner models). For the latter two models, partial differential equations (PDEs) must be solved in the surrounding medium; for the remaining models, we show that the PDEs can be reduced to ordinary differential equations. To solve the general constitutive PDEs, we present a Chebyshev spectral collocation method, which is robust even for violent collapse. Combining this numerical approach with theoretical analysis, we simulate bubble dynamics in various viscoelastic media to determine the impact of relaxation time, a constitutive parameter, on the associated physics. Relaxation time is found to increase bubble growth and permit rebounds driven purely by residual stresses in the surroundings. Different regimes of oscillations occur depending on the relaxation time.

Algorithm for Stabilizing a POD-Based Dynamical System

NASA Technical Reports Server (NTRS)

Kalb, Virginia L.

2010-01-01

This algorithm provides a new way to improve the accuracy and asymptotic behavior of a low-dimensional system based on the proper orthogonal decomposition (POD). Given a data set representing the evolution of a system of partial differential equations (PDEs), such as the Navier-Stokes equations for incompressible flow, one may obtain a low-dimensional model in the form of ordinary differential equations (ODEs) that should model the dynamics of the flow. Temporal sampling of the direct numerical simulation of the PDEs produces a spatial time series. The POD extracts the temporal and spatial eigenfunctions of this data set. Truncated to retain only the most energetic modes followed by Galerkin projection of these modes onto the PDEs obtains a dynamical system of ordinary differential equations for the time-dependent behavior of the flow. In practice, the steps leading to this system of ODEs entail numerically computing first-order derivatives of the mean data field and the eigenfunctions, and the computation of many inner products. This is far from a perfect process, and often results in the lack of long-term stability of the system and incorrect asymptotic behavior of the model. This algorithm describes a new stabilization method that utilizes the temporal eigenfunctions to derive correction terms for the coefficients of the dynamical system to significantly reduce these errors.

A reaction-based paradigm to model reactive chemical transport in groundwater with general kinetic and equilibrium reactions.

PubMed

Zhang, Fan; Yeh, Gour-Tsyh; Parker, Jack C; Brooks, Scott C; Pace, Molly N; Kim, Young-Jin; Jardine, Philip M; Watson, David B

2007-06-16

This paper presents a reaction-based water quality transport model in subsurface flow systems. Transport of chemical species with a variety of chemical and physical processes is mathematically described by M partial differential equations (PDEs). Decomposition via Gauss-Jordan column reduction of the reaction network transforms M species reactive transport equations into two sets of equations: a set of thermodynamic equilibrium equations representing N(E) equilibrium reactions and a set of reactive transport equations of M-N(E) kinetic-variables involving no equilibrium reactions (a kinetic-variable is a linear combination of species). The elimination of equilibrium reactions from reactive transport equations allows robust and efficient numerical integration. The model solves the PDEs of kinetic-variables rather than individual chemical species, which reduces the number of reactive transport equations and simplifies the reaction terms in the equations. A variety of numerical methods are investigated for solving the coupled transport and reaction equations. Simulation comparisons with exact solutions were performed to verify numerical accuracy and assess the effectiveness of various numerical strategies to deal with different application circumstances. Two validation examples involving simulations of uranium transport in soil columns are presented to evaluate the ability of the model to simulate reactive transport with complex reaction networks involving both kinetic and equilibrium reactions.

Simulation of all-scale atmospheric dynamics on unstructured meshes

NASA Astrophysics Data System (ADS)

Smolarkiewicz, Piotr K.; Szmelter, Joanna; Xiao, Feng

2016-10-01

The advance of massively parallel computing in the nineteen nineties and beyond encouraged finer grid intervals in numerical weather-prediction models. This has improved resolution of weather systems and enhanced the accuracy of forecasts, while setting the trend for development of unified all-scale atmospheric models. This paper first outlines the historical background to a wide range of numerical methods advanced in the process. Next, the trend is illustrated with a technical review of a versatile nonoscillatory forward-in-time finite-volume (NFTFV) approach, proven effective in simulations of atmospheric flows from small-scale dynamics to global circulations and climate. The outlined approach exploits the synergy of two specific ingredients: the MPDATA methods for the simulation of fluid flows based on the sign-preserving properties of upstream differencing; and the flexible finite-volume median-dual unstructured-mesh discretisation of the spatial differential operators comprising PDEs of atmospheric dynamics. The paper consolidates the concepts leading to a family of generalised nonhydrostatic NFTFV flow solvers that include soundproof PDEs of incompressible Boussinesq, anelastic and pseudo-incompressible systems, common in large-eddy simulation of small- and meso-scale dynamics, as well as all-scale compressible Euler equations. Such a framework naturally extends predictive skills of large-eddy simulation to the global atmosphere, providing a bottom-up alternative to the reverse approach pursued in the weather-prediction models. Theoretical considerations are substantiated by calculations attesting to the versatility and efficacy of the NFTFV approach. Some prospective developments are also discussed.

Denoising by coupled partial differential equations and extracting phase by backpropagation neural networks for electronic speckle pattern interferometry.

PubMed

Tang, Chen; Lu, Wenjing; Chen, Song; Zhang, Zhen; Li, Botao; Wang, Wenping; Han, Lin

2007-10-20

We extend and refine previous work [Appl. Opt. 46, 2907 (2007)]. Combining the coupled nonlinear partial differential equations (PDEs) denoising model with the ordinary differential equations enhancement method, we propose the new denoising and enhancing model for electronic speckle pattern interferometry (ESPI) fringe patterns. Meanwhile, we propose the backpropagation neural networks (BPNN) method to obtain unwrapped phase values based on a skeleton map instead of traditional interpolations. We test the introduced methods on the computer-simulated speckle ESPI fringe patterns and experimentally obtained fringe pattern, respectively. The experimental results show that the coupled nonlinear PDEs denoising model is capable of effectively removing noise, and the unwrapped phase values obtained by the BPNN method are much more accurate than those obtained by the well-known traditional interpolation. In addition, the accuracy of the BPNN method is adjustable by changing the parameters of networks such as the number of neurons.

Muscle activation described with a differential equation model for large ensembles of locally coupled molecular motors.

PubMed

Walcott, Sam

2014-10-01

Molecular motors, by turning chemical energy into mechanical work, are responsible for active cellular processes. Often groups of these motors work together to perform their biological role. Motors in an ensemble are coupled and exhibit complex emergent behavior. Although large motor ensembles can be modeled with partial differential equations (PDEs) by assuming that molecules function independently of their neighbors, this assumption is violated when motors are coupled locally. It is therefore unclear how to describe the ensemble behavior of the locally coupled motors responsible for biological processes such as calcium-dependent skeletal muscle activation. Here we develop a theory to describe locally coupled motor ensembles and apply the theory to skeletal muscle activation. The central idea is that a muscle filament can be divided into two phases: an active and an inactive phase. Dynamic changes in the relative size of these phases are described by a set of linear ordinary differential equations (ODEs). As the dynamics of the active phase are described by PDEs, muscle activation is governed by a set of coupled ODEs and PDEs, building on previous PDE models. With comparison to Monte Carlo simulations, we demonstrate that the theory captures the behavior of locally coupled ensembles. The theory also plausibly describes and predicts muscle experiments from molecular to whole muscle scales, suggesting that a micro- to macroscale muscle model is within reach.

Numerical modeling of bubble dynamics in viscoelastic media with relaxation

PubMed Central

Warnez, M. T.; Johnsen, E.

2015-01-01

Cavitation occurs in a variety of non-Newtonian fluids and viscoelastic materials. The large-amplitude volumetric oscillations of cavitation bubbles give rise to high temperatures and pressures at collapse, as well as induce large and rapid deformation of the surroundings. In this work, we develop a comprehensive numerical framework for spherical bubble dynamics in isotropic media obeying a wide range of viscoelastic constitutive relationships. Our numerical approach solves the compressible Keller–Miksis equation with full thermal effects (inside and outside the bubble) when coupled to a highly generalized constitutive relationship (which allows Newtonian, Kelvin–Voigt, Zener, linear Maxwell, upper-convected Maxwell, Jeffreys, Oldroyd-B, Giesekus, and Phan-Thien-Tanner models). For the latter two models, partial differential equations (PDEs) must be solved in the surrounding medium; for the remaining models, we show that the PDEs can be reduced to ordinary differential equations. To solve the general constitutive PDEs, we present a Chebyshev spectral collocation method, which is robust even for violent collapse. Combining this numerical approach with theoretical analysis, we simulate bubble dynamics in various viscoelastic media to determine the impact of relaxation time, a constitutive parameter, on the associated physics. Relaxation time is found to increase bubble growth and permit rebounds driven purely by residual stresses in the surroundings. Different regimes of oscillations occur depending on the relaxation time. PMID:26130967

Multi-symplectic integrators: numerical schemes for Hamiltonian PDEs that conserve symplecticity

NASA Astrophysics Data System (ADS)

Bridges, Thomas J.; Reich, Sebastian

2001-06-01

The symplectic numerical integration of finite-dimensional Hamiltonian systems is a well established subject and has led to a deeper understanding of existing methods as well as to the development of new very efficient and accurate schemes, e.g., for rigid body, constrained, and molecular dynamics. The numerical integration of infinite-dimensional Hamiltonian systems or Hamiltonian PDEs is much less explored. In this Letter, we suggest a new theoretical framework for generalizing symplectic numerical integrators for ODEs to Hamiltonian PDEs in R2: time plus one space dimension. The central idea is that symplecticity for Hamiltonian PDEs is directional: the symplectic structure of the PDE is decomposed into distinct components representing space and time independently. In this setting PDE integrators can be constructed by concatenating uni-directional ODE symplectic integrators. This suggests a natural definition of multi-symplectic integrator as a discretization that conserves a discrete version of the conservation of symplecticity for Hamiltonian PDEs. We show that this approach leads to a general framework for geometric numerical schemes for Hamiltonian PDEs, which have remarkable energy and momentum conservation properties. Generalizations, including development of higher-order methods, application to the Euler equations in fluid mechanics, application to perturbed systems, and extension to more than one space dimension are also discussed.

Ordering Unstructured Meshes for Sparse Matrix Computations on Leading Parallel Systems

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Li, Xiaoye; Heber, Gerd; Biswas, Rupak

2000-01-01

The ability of computers to solve hitherto intractable problems and simulate complex processes using mathematical models makes them an indispensable part of modern science and engineering. Computer simulations of large-scale realistic applications usually require solving a set of non-linear partial differential equations (PDES) over a finite region. For example, one thrust area in the DOE Grand Challenge projects is to design future accelerators such as the SpaHation Neutron Source (SNS). Our colleagues at SLAC need to model complex RFQ cavities with large aspect ratios. Unstructured grids are currently used to resolve the small features in a large computational domain; dynamic mesh adaptation will be added in the future for additional efficiency. The PDEs for electromagnetics are discretized by the FEM method, which leads to a generalized eigenvalue problem Kx = AMx, where K and M are the stiffness and mass matrices, and are very sparse. In a typical cavity model, the number of degrees of freedom is about one million. For such large eigenproblems, direct solution techniques quickly reach the memory limits. Instead, the most widely-used methods are Krylov subspace methods, such as Lanczos or Jacobi-Davidson. In all the Krylov-based algorithms, sparse matrix-vector multiplication (SPMV) must be performed repeatedly. Therefore, the efficiency of SPMV usually determines the eigensolver speed. SPMV is also one of the most heavily used kernels in large-scale numerical simulations.

University Capstone Project: Enhanced Initiation Techniques for Thermochemical Energy Conversion

DTIC Science & Technology

2013-03-01

technologies such as scramjets, gas turbine engines (relight and afterburner ignition), and pulsed detonation engines ( PDEs ) because of the limited...events in a flow tube were recorded, and the PDE engine was fired while monitoring ignition time and wave speed throughout the detonation process...long steel tube fitted with a 36” long, 2” x 2” square polycarbonate test section is used in place of the instrumented detonation tube. The PDE

Automatic computation of the travelling wave solutions to nonlinear PDEs

NASA Astrophysics Data System (ADS)

Liang, Songxin; Jeffrey, David J.

2008-05-01

Various extensions of the tanh-function method and their implementations for finding explicit travelling wave solutions to nonlinear partial differential equations (PDEs) have been reported in the literature. However, some solutions are often missed by these packages. In this paper, a new algorithm and its implementation called TWS for solving single nonlinear PDEs are presented. TWS is implemented in MAPLE 10. It turns out that, for PDEs whose balancing numbers are not positive integers, TWS works much better than existing packages. Furthermore, TWS obtains more solutions than existing packages for most cases. Program summaryProgram title:TWS Catalogue identifier:AEAM_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEAM_v1_0.html Program obtainable from:CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions:Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.:1250 No. of bytes in distributed program, including test data, etc.:78 101 Distribution format:tar.gz Programming language:Maple 10 Computer:A laptop with 1.6 GHz Pentium CPU Operating system:Windows XP Professional RAM:760 Mbytes Classification:5 Nature of problem:Finding the travelling wave solutions to single nonlinear PDEs. Solution method:Based on tanh-function method. Restrictions:The current version of this package can only deal with single autonomous PDEs or ODEs, not systems of PDEs or ODEs. However, the PDEs can have any finite number of independent space variables in addition to time t. Unusual features:For PDEs whose balancing numbers are not positive integers, TWS works much better than existing packages. Furthermore, TWS obtains more solutions than existing packages for most cases. Additional comments:It is easy to use. Running time:Less than 20 seconds for most cases, between 20 to 100 seconds for some cases, over 100 seconds for few cases. References: [1] E.S. Cheb-Terrab, K. von Bulow, Comput. Phys. Comm. 90 (1995) 102. [2] S.A. Elwakil, S.K. El-Labany, M.A. Zahran, R. Sabry, Phys. Lett. A 299 (2002) 179. [3] E. Fan, Phys. Lett. 277 (2000) 212. [4] W. Malfliet, Amer. J. Phys. 60 (1992) 650. [5] W. Malfliet, W. Hereman, Phys. Scripta 54 (1996) 563. [6] E.J. Parkes, B.R. Duffy, Comput. Phys. Comm. 98 (1996) 288.

Model's sparse representation based on reduced mixed GMsFE basis methods

NASA Astrophysics Data System (ADS)

Jiang, Lijian; Li, Qiuqi

2017-06-01

In this paper, we propose a model's sparse representation based on reduced mixed generalized multiscale finite element (GMsFE) basis methods for elliptic PDEs with random inputs. A typical application for the elliptic PDEs is the flow in heterogeneous random porous media. Mixed generalized multiscale finite element method (GMsFEM) is one of the accurate and efficient approaches to solve the flow problem in a coarse grid and obtain the velocity with local mass conservation. When the inputs of the PDEs are parameterized by the random variables, the GMsFE basis functions usually depend on the random parameters. This leads to a large number degree of freedoms for the mixed GMsFEM and substantially impacts on the computation efficiency. In order to overcome the difficulty, we develop reduced mixed GMsFE basis methods such that the multiscale basis functions are independent of the random parameters and span a low-dimensional space. To this end, a greedy algorithm is used to find a set of optimal samples from a training set scattered in the parameter space. Reduced mixed GMsFE basis functions are constructed based on the optimal samples using two optimal sampling strategies: basis-oriented cross-validation and proper orthogonal decomposition. Although the dimension of the space spanned by the reduced mixed GMsFE basis functions is much smaller than the dimension of the original full order model, the online computation still depends on the number of coarse degree of freedoms. To significantly improve the online computation, we integrate the reduced mixed GMsFE basis methods with sparse tensor approximation and obtain a sparse representation for the model's outputs. The sparse representation is very efficient for evaluating the model's outputs for many instances of parameters. To illustrate the efficacy of the proposed methods, we present a few numerical examples for elliptic PDEs with multiscale and random inputs. In particular, a two-phase flow model in random porous media is simulated by the proposed sparse representation method.

Model's sparse representation based on reduced mixed GMsFE basis methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Lijian, E-mail: ljjiang@hnu.edu.cn; Li, Qiuqi, E-mail: qiuqili@hnu.edu.cn

2017-06-01

In this paper, we propose a model's sparse representation based on reduced mixed generalized multiscale finite element (GMsFE) basis methods for elliptic PDEs with random inputs. A typical application for the elliptic PDEs is the flow in heterogeneous random porous media. Mixed generalized multiscale finite element method (GMsFEM) is one of the accurate and efficient approaches to solve the flow problem in a coarse grid and obtain the velocity with local mass conservation. When the inputs of the PDEs are parameterized by the random variables, the GMsFE basis functions usually depend on the random parameters. This leads to a largemore » number degree of freedoms for the mixed GMsFEM and substantially impacts on the computation efficiency. In order to overcome the difficulty, we develop reduced mixed GMsFE basis methods such that the multiscale basis functions are independent of the random parameters and span a low-dimensional space. To this end, a greedy algorithm is used to find a set of optimal samples from a training set scattered in the parameter space. Reduced mixed GMsFE basis functions are constructed based on the optimal samples using two optimal sampling strategies: basis-oriented cross-validation and proper orthogonal decomposition. Although the dimension of the space spanned by the reduced mixed GMsFE basis functions is much smaller than the dimension of the original full order model, the online computation still depends on the number of coarse degree of freedoms. To significantly improve the online computation, we integrate the reduced mixed GMsFE basis methods with sparse tensor approximation and obtain a sparse representation for the model's outputs. The sparse representation is very efficient for evaluating the model's outputs for many instances of parameters. To illustrate the efficacy of the proposed methods, we present a few numerical examples for elliptic PDEs with multiscale and random inputs. In particular, a two-phase flow model in random porous media is simulated by the proposed sparse representation method.« less

High-order fractional partial differential equation transform for molecular surface construction.

PubMed

Hu, Langhua; Chen, Duan; Wei, Guo-Wei

2013-01-01

Fractional derivative or fractional calculus plays a significant role in theoretical modeling of scientific and engineering problems. However, only relatively low order fractional derivatives are used at present. In general, it is not obvious what role a high fractional derivative can play and how to make use of arbitrarily high-order fractional derivatives. This work introduces arbitrarily high-order fractional partial differential equations (PDEs) to describe fractional hyperdiffusions. The fractional PDEs are constructed via fractional variational principle. A fast fractional Fourier transform (FFFT) is proposed to numerically integrate the high-order fractional PDEs so as to avoid stringent stability constraints in solving high-order evolution PDEs. The proposed high-order fractional PDEs are applied to the surface generation of proteins. We first validate the proposed method with a variety of test examples in two and three-dimensional settings. The impact of high-order fractional derivatives to surface analysis is examined. We also construct fractional PDE transform based on arbitrarily high-order fractional PDEs. We demonstrate that the use of arbitrarily high-order derivatives gives rise to time-frequency localization, the control of the spectral distribution, and the regulation of the spatial resolution in the fractional PDE transform. Consequently, the fractional PDE transform enables the mode decomposition of images, signals, and surfaces. The effect of the propagation time on the quality of resulting molecular surfaces is also studied. Computational efficiency of the present surface generation method is compared with the MSMS approach in Cartesian representation. We further validate the present method by examining some benchmark indicators of macromolecular surfaces, i.e., surface area, surface enclosed volume, surface electrostatic potential and solvation free energy. Extensive numerical experiments and comparison with an established surface model indicate that the proposed high-order fractional PDEs are robust, stable and efficient for biomolecular surface generation.

Simplified Least Squares Shadowing sensitivity analysis for chaotic ODEs and PDEs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chater, Mario, E-mail: chaterm@mit.edu; Ni, Angxiu, E-mail: niangxiu@mit.edu; Wang, Qiqi, E-mail: qiqi@mit.edu

This paper develops a variant of the Least Squares Shadowing (LSS) method, which has successfully computed the derivative for several chaotic ODEs and PDEs. The development in this paper aims to simplify Least Squares Shadowing method by improving how time dilation is treated. Instead of adding an explicit time dilation term as in the original method, the new variant uses windowing, which can be more efficient and simpler to implement, especially for PDEs.

Preliminary Study of Turbulence for a Lobed Body in Hypersonic Flight

DTIC Science & Technology

2013-02-22

physics. Modest improvements in numerical algorithms, particularly those for solving partial differential equations ( PDEs ), can now be fully...dramatically.[7] In slower speed flow fields, this energy is absorbed mostly in molecular translational and rotational modes, but for hypersonic...REFERENCES 1. Génin, F., Fryxell, B. and Menon, S., “Simulation of Detonation Propagation in Turbulent Gas- Solid Reactive Mixtures”, 41 st

Program Code Generator for Cardiac Electrophysiology Simulation with Automatic PDE Boundary Condition Handling

PubMed Central

Punzalan, Florencio Rusty; Kunieda, Yoshitoshi; Amano, Akira

2015-01-01

Clinical and experimental studies involving human hearts can have certain limitations. Methods such as computer simulations can be an important alternative or supplemental tool. Physiological simulation at the tissue or organ level typically involves the handling of partial differential equations (PDEs). Boundary conditions and distributed parameters, such as those used in pharmacokinetics simulation, add to the complexity of the PDE solution. These factors can tailor PDE solutions and their corresponding program code to specific problems. Boundary condition and parameter changes in the customized code are usually prone to errors and time-consuming. We propose a general approach for handling PDEs and boundary conditions in computational models using a replacement scheme for discretization. This study is an extension of a program generator that we introduced in a previous publication. The program generator can generate code for multi-cell simulations of cardiac electrophysiology. Improvements to the system allow it to handle simultaneous equations in the biological function model as well as implicit PDE numerical schemes. The replacement scheme involves substituting all partial differential terms with numerical solution equations. Once the model and boundary equations are discretized with the numerical solution scheme, instances of the equations are generated to undergo dependency analysis. The result of the dependency analysis is then used to generate the program code. The resulting program code are in Java or C programming language. To validate the automatic handling of boundary conditions in the program code generator, we generated simulation code using the FHN, Luo-Rudy 1, and Hund-Rudy cell models and run cell-to-cell coupling and action potential propagation simulations. One of the simulations is based on a published experiment and simulation results are compared with the experimental data. We conclude that the proposed program code generator can be used to generate code for physiological simulations and provides a tool for studying cardiac electrophysiology. PMID:26356082

Maximum-entropy reconstruction method for moment-based solution of the Boltzmann equation

NASA Astrophysics Data System (ADS)

Summy, Dustin; Pullin, Dale

2013-11-01

We describe a method for a moment-based solution of the Boltzmann equation. This starts with moment equations for a 10 + 9 N , N = 0 , 1 , 2 . . . -moment representation. The partial-differential equations (PDEs) for these moments are unclosed, containing both higher-order moments and molecular-collision terms. These are evaluated using a maximum-entropy construction of the velocity distribution function f (c , x , t) , using the known moments, within a finite-box domain of single-particle-velocity (c) space. Use of a finite-domain alleviates known problems (Junk and Unterreiter, Continuum Mech. Thermodyn., 2002) concerning existence and uniqueness of the reconstruction. Unclosed moments are evaluated with quadrature while collision terms are calculated using a Monte-Carlo method. This allows integration of the moment PDEs in time. Illustrative examples will include zero-space- dimensional relaxation of f (c , t) from a Mott-Smith-like initial condition toward equilibrium and one-space dimensional, finite Knudsen number, planar Couette flow. Comparison with results using the direct-simulation Monte-Carlo method will be presented.

Optimal control of coupled parabolic-hyperbolic non-autonomous PDEs: infinite-dimensional state-space approach

NASA Astrophysics Data System (ADS)

Aksikas, I.; Moghadam, A. Alizadeh; Forbes, J. F.

2018-04-01

This paper deals with the design of an optimal state-feedback linear-quadratic (LQ) controller for a system of coupled parabolic-hypebolic non-autonomous partial differential equations (PDEs). The infinite-dimensional state space representation and the corresponding operator Riccati differential equation are used to solve the control problem. Dynamical properties of the coupled system of interest are analysed to guarantee the existence and uniqueness of the solution of the LQ-optimal control problem and also to guarantee the exponential stability of the closed-loop system. Thanks to the eigenvalues and eigenfunctions of the parabolic operator and also the fact that the hyperbolic-associated operator Riccati differential equation can be converted to a scalar Riccati PDE, an algorithm to solve the LQ control problem has been presented. The results are applied to a non-isothermal packed-bed catalytic reactor. The LQ optimal controller designed in the early portion of the paper is implemented for the original non-linear model. Numerical simulations are performed to show the controller performances.

Fractional modeling of viscoelasticity in 3D cerebral arteries and aneurysms

NASA Astrophysics Data System (ADS)

Yu, Yue; Perdikaris, Paris; Karniadakis, George Em

2016-10-01

We develop efficient numerical methods for fractional order PDEs, and employ them to investigate viscoelastic constitutive laws for arterial wall mechanics. Recent simulations using one-dimensional models [1] have indicated that fractional order models may offer a more powerful alternative for modeling the arterial wall response, exhibiting reduced sensitivity to parametric uncertainties compared with the integer-calculus-based models. Here, we study three-dimensional (3D) fractional PDEs that naturally model the continuous relaxation properties of soft tissue, and for the first time employ them to simulate flow structure interactions for patient-specific brain aneurysms. To deal with the high memory requirements and in order to accelerate the numerical evaluation of hereditary integrals, we employ a fast convolution method [2] that reduces the memory cost to O (log ⁡ (N)) and the computational complexity to O (Nlog ⁡ (N)). Furthermore, we combine the fast convolution with high-order backward differentiation to achieve third-order time integration accuracy. We confirm that in 3D viscoelastic simulations, the integer order models strongly depends on the relaxation parameters, while the fractional order models are less sensitive. As an application to long-time simulations in complex geometries, we also apply the method to modeling fluid-structure interaction of a 3D patient-specific compliant cerebral artery with an aneurysm. Taken together, our findings demonstrate that fractional calculus can be employed effectively in modeling complex behavior of materials in realistic 3D time-dependent problems if properly designed efficient algorithms are employed to overcome the extra memory requirements and computational complexity associated with the non-local character of fractional derivatives.

Fractional modeling of viscoelasticity in 3D cerebral arteries and aneurysms

PubMed Central

Perdikaris, Paris; Karniadakis, George Em

2017-01-01

We develop efficient numerical methods for fractional order PDEs, and employ them to investigate viscoelastic constitutive laws for arterial wall mechanics. Recent simulations using one-dimensional models [1] have indicated that fractional order models may offer a more powerful alternative for modeling the arterial wall response, exhibiting reduced sensitivity to parametric uncertainties compared with the integer-calculus-based models. Here, we study three-dimensional (3D) fractional PDEs that naturally model the continuous relaxation properties of soft tissue, and for the first time employ them to simulate flow structure interactions for patient-specific brain aneurysms. To deal with the high memory requirements and in order to accelerate the numerical evaluation of hereditary integrals, we employ a fast convolution method [2] that reduces the memory cost to O(log(N)) and the computational complexity to O(N log(N)). Furthermore, we combine the fast convolution with high-order backward differentiation to achieve third-order time integration accuracy. We confirm that in 3D viscoelastic simulations, the integer order models strongly depends on the relaxation parameters, while the fractional order models are less sensitive. As an application to long-time simulations in complex geometries, we also apply the method to modeling fluid–structure interaction of a 3D patient-specific compliant cerebral artery with an aneurysm. Taken together, our findings demonstrate that fractional calculus can be employed effectively in modeling complex behavior of materials in realistic 3D time-dependent problems if properly designed efficient algorithms are employed to overcome the extra memory requirements and computational complexity associated with the non-local character of fractional derivatives. PMID:29104310

PDEs on moving surfaces via the closest point method and a modified grid based particle method

NASA Astrophysics Data System (ADS)

Petras, A.; Ruuth, S. J.

2016-05-01

Partial differential equations (PDEs) on surfaces arise in a wide range of applications. The closest point method (Ruuth and Merriman (2008) [20]) is a recent embedding method that has been used to solve a variety of PDEs on smooth surfaces using a closest point representation of the surface and standard Cartesian grid methods in the embedding space. The original closest point method (CPM) was designed for problems posed on static surfaces, however the solution of PDEs on moving surfaces is of considerable interest as well. Here we propose solving PDEs on moving surfaces using a combination of the CPM and a modification of the grid based particle method (Leung and Zhao (2009) [12]). The grid based particle method (GBPM) represents and tracks surfaces using meshless particles and an Eulerian reference grid. Our modification of the GBPM introduces a reconstruction step into the original method to ensure that all the grid points within a computational tube surrounding the surface are active. We present a number of examples to illustrate the numerical convergence properties of our combined method. Experiments for advection-diffusion equations that are strongly coupled to the velocity of the surface are also presented.

Partial differential equation models in macroeconomics.

PubMed

Achdou, Yves; Buera, Francisco J; Lasry, Jean-Michel; Lions, Pierre-Louis; Moll, Benjamin

2014-11-13

The purpose of this article is to get mathematicians interested in studying a number of partial differential equations (PDEs) that naturally arise in macroeconomics. These PDEs come from models designed to study some of the most important questions in economics. At the same time, they are highly interesting for mathematicians because their structure is often quite difficult. We present a number of examples of such PDEs, discuss what is known about their properties, and list some open questions for future research. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

High-order fractional partial differential equation transform for molecular surface construction

PubMed Central

Hu, Langhua; Chen, Duan; Wei, Guo-Wei

2013-01-01

Fractional derivative or fractional calculus plays a significant role in theoretical modeling of scientific and engineering problems. However, only relatively low order fractional derivatives are used at present. In general, it is not obvious what role a high fractional derivative can play and how to make use of arbitrarily high-order fractional derivatives. This work introduces arbitrarily high-order fractional partial differential equations (PDEs) to describe fractional hyperdiffusions. The fractional PDEs are constructed via fractional variational principle. A fast fractional Fourier transform (FFFT) is proposed to numerically integrate the high-order fractional PDEs so as to avoid stringent stability constraints in solving high-order evolution PDEs. The proposed high-order fractional PDEs are applied to the surface generation of proteins. We first validate the proposed method with a variety of test examples in two and three-dimensional settings. The impact of high-order fractional derivatives to surface analysis is examined. We also construct fractional PDE transform based on arbitrarily high-order fractional PDEs. We demonstrate that the use of arbitrarily high-order derivatives gives rise to time-frequency localization, the control of the spectral distribution, and the regulation of the spatial resolution in the fractional PDE transform. Consequently, the fractional PDE transform enables the mode decomposition of images, signals, and surfaces. The effect of the propagation time on the quality of resulting molecular surfaces is also studied. Computational efficiency of the present surface generation method is compared with the MSMS approach in Cartesian representation. We further validate the present method by examining some benchmark indicators of macromolecular surfaces, i.e., surface area, surface enclosed volume, surface electrostatic potential and solvation free energy. Extensive numerical experiments and comparison with an established surface model indicate that the proposed high-order fractional PDEs are robust, stable and efficient for biomolecular surface generation. PMID:24364020

Numerical simulations of earthquakes and the dynamics of fault systems using the Finite Element method.

NASA Astrophysics Data System (ADS)

Kettle, L. M.; Mora, P.; Weatherley, D.; Gross, L.; Xing, H.

2006-12-01

Simulations using the Finite Element method are widely used in many engineering applications and for the solution of partial differential equations (PDEs). Computational models based on the solution of PDEs play a key role in earth systems simulations. We present numerical modelling of crustal fault systems where the dynamic elastic wave equation is solved using the Finite Element method. This is achieved using a high level computational modelling language, escript, available as open source software from ACcESS (Australian Computational Earth Systems Simulator), the University of Queensland. Escript is an advanced geophysical simulation software package developed at ACcESS which includes parallel equation solvers, data visualisation and data analysis software. The escript library was implemented to develop a flexible Finite Element model which reliably simulates the mechanism of faulting and the physics of earthquakes. Both 2D and 3D elastodynamic models are being developed to study the dynamics of crustal fault systems. Our final goal is to build a flexible model which can be applied to any fault system with user-defined geometry and input parameters. To study the physics of earthquake processes, two different time scales must be modelled, firstly the quasi-static loading phase which gradually increases stress in the system (~100years), and secondly the dynamic rupture process which rapidly redistributes stress in the system (~100secs). We will discuss the solution of the time-dependent elastic wave equation for an arbitrary fault system using escript. This involves prescribing the correct initial stress distribution in the system to simulate the quasi-static loading of faults to failure; determining a suitable frictional constitutive law which accurately reproduces the dynamics of the stick/slip instability at the faults; and using a robust time integration scheme. These dynamic models generate data and information that can be used for earthquake forecasting.

Accelerated Simulation of Kinetic Transport Using Variational Principles and Sparsity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caflisch, Russel

This project is centered on the development and application of techniques of sparsity and compressed sensing for variational principles, PDEs and physics problems, in particular for kinetic transport. This included derivation of sparse modes for elliptic and parabolic problems coming from variational principles. The research results of this project are on methods for sparsity in differential equations and their applications and on application of sparsity ideas to kinetic transport of plasmas.

Some recent developments of the immersed interface method for flow simulation

NASA Astrophysics Data System (ADS)

Xu, Sheng

2017-11-01

The immersed interface method is a general methodology for solving PDEs subject to interfaces. In this talk, I will give an overview of some recent developments of the method toward the enhancement of its robustness for flow simulation. In particular, I will present with numerical results how to capture boundary conditions on immersed rigid objects, how to adopt interface triangulation in the method, and how to parallelize the method for flow with moving objects. With these developments, the immersed interface method can achieve accurate and efficient simulation of a flow involving multiple moving complex objects. Thanks to NSF for the support of this work under Grant NSF DMS 1320317.

Pencil It in: Exploring the Feasibility of Hand-Drawn Pencil Electrochemical Sensors and Their Direct Comparison to Screen-Printed Electrodes

PubMed Central

Bernalte, Elena; Foster, Christopher W.; Brownson, Dale A.C.; Mosna, Morgane; Smith, Graham C.; Banks, Craig E.

2016-01-01

We explore the fabrication, physicochemical characterisation (SEM, Raman, EDX and XPS) and electrochemical application of hand-drawn pencil electrodes (PDEs) upon an ultra-flexible polyester substrate; investigating the number of draws (used for their fabrication), the pencil grade utilised (HB to 9B) and the electrochemical properties of an array of batches (i.e, pencil boxes). Electrochemical characterisation of the PDEs, using different batches of HB grade pencils, is undertaken using several inner- and outer-sphere redox probes and is critically compared to screen-printed electrodes (SPEs). Proof-of-concept is demonstrated for the electrochemical sensing of dopamine and acetaminophen using PDEs, which are found to exhibit competitive limits of detection (3σ) upon comparison to SPEs. Nonetheless, it is important to note that a clear lack of reproducibility was demonstrated when utilising these PDEs fabricated using the HB pencils from different batches. We also explore the suitability and feasibility of a pencil-drawn reference electrode compared to screen-printed alternatives, to see if one can draw the entire sensing platform. This article reports a critical assessment of these PDEs against that of its screen-printed competitors, questioning the overall feasibility of PDEs’ implementation as a sensing platform. PMID:27589815

Identification of cytosolic phosphodiesterases in the erythrocyte: A possible role for PDE5

PubMed Central

Adderley, Shaquria P.; Thuet, Kelly M.; Sridharan, Meera; Bowles, Elizabeth A.; Stephenson, Alan H.; Ellsworth, Mary L.; Sprague, Randy S.

2011-01-01

Summary Background Within erythrocytes (RBCs), cAMP levels are regulated by phosphodiesterases (PDEs). Increases in cAMP and ATP release associated with activation of β-adrenergic receptors (βARs) and prostacyclin receptors (IPRs) are regulated by PDEs 2, 4 and PDE 3, respectively. Here we establish the presence of cytosolic PDEs in RBCs and determine a role for PDE5 in regulating levels of cGMP. Material/Methods Purified cytosolic proteins were obtained from isolated human RBCs and western analysis was performed using antibodies against PDEs 3A, 4 and 5. Rabbit RBCs were incubated with dbcGMP, a cGMP analog, to determine the effect of cGMP on cAMP levels. To determine if cGMP affects receptor-mediated increases in cAMP, rabbit RBCs were incubated with dbcGMP prior to addition of isoproterenol (ISO), a βAR receptor agonist. To demonstrate that endogenous cGMP produces the same effect, rabbit and human RBCs were incubated with SpNONOate (SpNO), a nitric oxide donor, and YC1, a direct activator of soluble guanylyl cyclase (sGC), in the absence and presence of a selective PDE5 inhibitor, zaprinast (ZAP). Results Western analysis identified PDEs 3A, 4D and 5A. dbcGMP produced a concentration dependent increase in cAMP and ISO-induced increases in cAMP were potentiated by dbcGMP. In addition, incubation with YC1 and SpNO in the presence of ZAP potentiated βAR-induced increases in cAMP. Conclusions PDEs 2, 3A and 5 are present in the cytosol of human RBCs. PDE5 activity in RBCs regulates cGMP levels. Increases in intracellular cGMP augment cAMP levels. These studies suggest a novel role for PDE5 in erythrocytes. PMID:21525805

Enhanced Elliptic Grid Generation

NASA Technical Reports Server (NTRS)

Kaul, Upender K.

2007-01-01

An enhanced method of elliptic grid generation has been invented. Whereas prior methods require user input of certain grid parameters, this method provides for these parameters to be determined automatically. "Elliptic grid generation" signifies generation of generalized curvilinear coordinate grids through solution of elliptic partial differential equations (PDEs). Usually, such grids are fitted to bounding bodies and used in numerical solution of other PDEs like those of fluid flow, heat flow, and electromagnetics. Such a grid is smooth and has continuous first and second derivatives (and possibly also continuous higher-order derivatives), grid lines are appropriately stretched or clustered, and grid lines are orthogonal or nearly so over most of the grid domain. The source terms in the grid-generating PDEs (hereafter called "defining" PDEs) make it possible for the grid to satisfy requirements for clustering and orthogonality properties in the vicinity of specific surfaces in three dimensions or in the vicinity of specific lines in two dimensions. The grid parameters in question are decay parameters that appear in the source terms of the inhomogeneous defining PDEs. The decay parameters are characteristic lengths in exponential- decay factors that express how the influences of the boundaries decrease with distance from the boundaries. These terms govern the rates at which distance between adjacent grid lines change with distance from nearby boundaries. Heretofore, users have arbitrarily specified decay parameters. However, the characteristic lengths are coupled with the strengths of the source terms, such that arbitrary specification could lead to conflicts among parameter values. Moreover, the manual insertion of decay parameters is cumbersome for static grids and infeasible for dynamically changing grids. In the present method, manual insertion and user specification of decay parameters are neither required nor allowed. Instead, the decay parameters are determined automatically as part of the solution of the defining PDEs. Depending on the shape of the boundary segments and the physical nature of the problem to be solved on the grid, the solution of the defining PDEs may provide for rates of decay to vary along and among the boundary segments and may lend itself to interpretation in terms of one or more physical quantities associated with the problem.

Efficient Development of High Fidelity Structured Volume Grids for Hypersonic Flow Simulations

NASA Technical Reports Server (NTRS)

Alter, Stephen J.

2003-01-01

A new technique for the control of grid line spacing and intersection angles of a structured volume grid, using elliptic partial differential equations (PDEs) is presented. Existing structured grid generation algorithms make use of source term hybridization to provide control of grid lines, imposing orthogonality implicitly at the boundary and explicitly on the interior of the domain. A bridging function between the two types of grid line control is typically used to blend the different orthogonality formulations. It is shown that utilizing such a bridging function with source term hybridization can result in the excessive use of computational resources and diminishes robustness. A new approach, Anisotropic Lagrange Based Trans-Finite Interpolation (ALBTFI), is offered as a replacement to source term hybridization. The ALBTFI technique captures the essence of the desired grid controls while improving the convergence rate of the elliptic PDEs when compared with source term hybridization. Grid generation on a blunt cone and a Shuttle Orbiter is used to demonstrate and assess the ALBTFI technique, which is shown to be as much as 50% faster, more robust, and produces higher quality grids than source term hybridization.

Analysis of nonlocal neural fields for both general and gamma-distributed connectivities

NASA Astrophysics Data System (ADS)

Hutt, Axel; Atay, Fatihcan M.

2005-04-01

This work studies the stability of equilibria in spatially extended neuronal ensembles. We first derive the model equation from statistical properties of the neuron population. The obtained integro-differential equation includes synaptic and space-dependent transmission delay for both general and gamma-distributed synaptic connectivities. The latter connectivity type reveals infinite, finite, and vanishing self-connectivities. The work derives conditions for stationary and nonstationary instabilities for both kernel types. In addition, a nonlinear analysis for general kernels yields the order parameter equation of the Turing instability. To compare the results to findings for partial differential equations (PDEs), two typical PDE-types are derived from the examined model equation, namely the general reaction-diffusion equation and the Swift-Hohenberg equation. Hence, the discussed integro-differential equation generalizes these PDEs. In the case of the gamma-distributed kernels, the stability conditions are formulated in terms of the mean excitatory and inhibitory interaction ranges. As a novel finding, we obtain Turing instabilities in fields with local inhibition-lateral excitation, while wave instabilities occur in fields with local excitation and lateral inhibition. Numerical simulations support the analytical results.

A substrate selectivity and inhibitor design lesson from the PDE10-cAMP crystal structure: a computational study.

PubMed

Lau, Justin Kai-Chi; Li, Xiao-Bo; Cheng, Yuen-Kit

2010-04-22

Phosphodiesterases (PDEs) catalyze the hydrolysis of second messengers cAMP and cGMP in regulating many important cellular signals and have been recognized as important drug targets. Experimentally, a range of specificity/selectivity toward cAMP and cGMP is well-known for the individual PDE families. The study reported here reveals that PDEs might also exhibit selectivity toward conformations of the endogenous substrates cAMP and cGMP. Molecular dynamics simulations and free energy study have been applied to study the binding of the cAMP torsional conformers about the glycosyl bond in PDE10A2. The computational results elucidated that PDE10A2 is energetically more favorable in complex with the syn cAMP conformer (as reported in the crystal structure) and the binding of anti cAMP to PDE10A2 would lead to either a nonreactive configuration or significant perturbation on the catalytic pocket of the enzyme. This experimentally inaccessible information provides important molecular insights for the development of effective PDE10 ligands.

A novel method for identification of lithium-ion battery equivalent circuit model parameters considering electrochemical properties

NASA Astrophysics Data System (ADS)

Zhang, Xi; Lu, Jinling; Yuan, Shifei; Yang, Jun; Zhou, Xuan

2017-03-01

This paper proposes a novel parameter identification method for the lithium-ion (Li-ion) battery equivalent circuit model (ECM) considering the electrochemical properties. An improved pseudo two-dimension (P2D) model is established on basis of partial differential equations (PDEs), since the electrolyte potential is simplified from the nonlinear to linear expression while terminal voltage can be divided into the electrolyte potential, open circuit voltage (OCV), overpotential of electrodes, internal resistance drop, and so on. The model order reduction process is implemented by the simplification of the PDEs using the Laplace transform, inverse Laplace transform, Pade approximation, etc. A unified second order transfer function between cell voltage and current is obtained for the comparability with that of ECM. The final objective is to obtain the relationship between the ECM resistances/capacitances and electrochemical parameters such that in various conditions, ECM precision could be improved regarding integration of battery interior properties for further applications, e.g., SOC estimation. Finally simulation and experimental results prove the correctness and validity of the proposed methodology.

A hybrid algorithm for coupling partial differential equation and compartment-based dynamics.

PubMed

Harrison, Jonathan U; Yates, Christian A

2016-09-01

Stochastic simulation methods can be applied successfully to model exact spatio-temporally resolved reaction-diffusion systems. However, in many cases, these methods can quickly become extremely computationally intensive with increasing particle numbers. An alternative description of many of these systems can be derived in the diffusive limit as a deterministic, continuum system of partial differential equations (PDEs). Although the numerical solution of such PDEs is, in general, much more efficient than the full stochastic simulation, the deterministic continuum description is generally not valid when copy numbers are low and stochastic effects dominate. Therefore, to take advantage of the benefits of both of these types of models, each of which may be appropriate in different parts of a spatial domain, we have developed an algorithm that can be used to couple these two types of model together. This hybrid coupling algorithm uses an overlap region between the two modelling regimes. By coupling fluxes at one end of the interface and using a concentration-matching condition at the other end, we ensure that mass is appropriately transferred between PDE- and compartment-based regimes. Our methodology gives notable reductions in simulation time in comparison with using a fully stochastic model, while maintaining the important stochastic features of the system and providing detail in appropriate areas of the domain. We test our hybrid methodology robustly by applying it to several biologically motivated problems including diffusion and morphogen gradient formation. Our analysis shows that the resulting error is small, unbiased and does not grow over time. © 2016 The Authors.

A hybrid algorithm for coupling partial differential equation and compartment-based dynamics

PubMed Central

Yates, Christian A.

2016-01-01

Stochastic simulation methods can be applied successfully to model exact spatio-temporally resolved reaction–diffusion systems. However, in many cases, these methods can quickly become extremely computationally intensive with increasing particle numbers. An alternative description of many of these systems can be derived in the diffusive limit as a deterministic, continuum system of partial differential equations (PDEs). Although the numerical solution of such PDEs is, in general, much more efficient than the full stochastic simulation, the deterministic continuum description is generally not valid when copy numbers are low and stochastic effects dominate. Therefore, to take advantage of the benefits of both of these types of models, each of which may be appropriate in different parts of a spatial domain, we have developed an algorithm that can be used to couple these two types of model together. This hybrid coupling algorithm uses an overlap region between the two modelling regimes. By coupling fluxes at one end of the interface and using a concentration-matching condition at the other end, we ensure that mass is appropriately transferred between PDE- and compartment-based regimes. Our methodology gives notable reductions in simulation time in comparison with using a fully stochastic model, while maintaining the important stochastic features of the system and providing detail in appropriate areas of the domain. We test our hybrid methodology robustly by applying it to several biologically motivated problems including diffusion and morphogen gradient formation. Our analysis shows that the resulting error is small, unbiased and does not grow over time. PMID:27628171

Ab Initio QM/MM Study Shows a Highly Dissociated SN2 Hydrolysis Mechanism for the cGMP-Specific Phosphodiesterase-5.

PubMed

Li, Zhe; Wu, Yinuo; Feng, Ling-Jun; Wu, Ruibo; Luo, Hai-Bin

2014-12-09

Phosphodiesterases (PDEs) are the sole enzymes hydrolyzing the important second messengers cGMP and cAMP and have been identified as therapeutic targets for several diseases. The most successful examples are PDE5 inhibitors (i.e., sildenafil and tadalafil), which have been approved for the treatment of male erectile dysfunction and pulmonary hypertension. However, the side effects mostly due to nonselective inhibition toward other PDE isoforms, set back the clinical usage of PDE5 inhibitors. Until now, the exact catalytic mechanism of the substrate cGMP by PDE5 is still unclear. Herein, the first computational study on the catalytic hydrolysis mechanism of cGMP for PDE5 (catalytic domain) is performed by employing the state-of-the-art ab initio quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations. Our simulations show a SN2 type reaction procedure via a highly dissociated transition state with a reaction barrier of 8.88 kcal/mol, which is quite different from the previously suggested hydrolysis mechanism of cAMP for PDE4. Furthermore, the subsequent ligand exchange and the release of the product GMP have also been investigated by binding energy analysis and MD simulations. It is deduced that ligand exchange would be the rate-determining step of the whole reaction, which is consistent with many previous experimental results. The obtained mechanistic insights should be valuable for not only the rational design of more specific inhibitors toward PDE5 but also understanding the general hydrolysis mechanism of cGMP-specific PDEs.

Numerical Simulation for the Unsteady MHD Flow and Heat Transfer of Couple Stress Fluid over a Rotating Disk

PubMed Central

2014-01-01

The present work is devoted to study the numerical simulation for unsteady MHD flow and heat transfer of a couple stress fluid over a rotating disk. A similarity transformation is employed to reduce the time dependent system of nonlinear partial differential equations (PDEs) to ordinary differential equations (ODEs). The Runge-Kutta method and shooting technique are employed for finding the numerical solution of the governing system. The influences of governing parameters viz. unsteadiness parameter, couple stress and various physical parameters on velocity, temperature and pressure profiles are analyzed graphically and discussed in detail. PMID:24835274

Photocatalytic Oxidation of Low-Level Airborne 2-Propanol and Trichloroethylene over Titania Irradiated with Bulb-Type Light-Emitting Diodes.

PubMed

Jo, Wan-Kuen

2013-01-18

This study examined the photocatalytic oxidation of gas-phase trichloroethylene (TCE) and 2-propanol, at indoor levels, over titanium dioxide (TiO₂) irradiated with light-emitting diodes (LED) under different operational conditions. TiO₂ powder baked at 450 °C exhibited the highest photocatalytic decomposition efficiency (PDE) for TCE, while all photocatalysts baked at different temperatures showed similar PDEs for 2-propanol. The average PDEs of TCE over a three hour period were four, four, five, and 51% for TiO₂ powders baked at 150, 250, 350, and 450 °C, respectively. The average PDEs of 2-propanol were 95, 97, 98, and 96% for TiO₂ powders baked at 150, 250, 350, and 450 °C, respectively. The ratio of anatase at 2θ = 25.2° to rutile at 2θ = 27.4° was lowest for the TiO₂ powder baked at 450 °C. Although the LED-irradiated TiO₂ system revealed lower PDEs of TCE and 2-propanol when compared to those of the eight watt, black-light lamp-irradiated TiO₂ system, the results for the PDEs normalized to the energy consumption were reversed. Other operational parameters, such as relative humidity, input concentrations, flow rate, and feeding type were also found to influence the photocatalytic performance of the UV LED-irradiated TiO₂ system when applied to the cleaning of TCE and 2-propanol at indoor air levels.

Seeking Space Aliens and the Strong Approximation Property: A (disjoint) Study in Dust Plumes on Planetary Satellites and Nonsymmetric Algebraic Multigrid

NASA Astrophysics Data System (ADS)

Southworth, Benjamin Scott

PART I: One of the most fascinating questions to humans has long been whether life exists outside of our planet. To our knowledge, water is a fundamental building block of life, which makes liquid water on other bodies in the universe a topic of great interest. In fact, there are large bodies of water right here in our solar system, underneath the icy crust of moons around Saturn and Jupiter. The NASA-ESA Cassini Mission spent two decades studying the Saturnian system. One of the many exciting discoveries was a "plume" on the south pole of Enceladus, emitting hundreds of kg/s of water vapor and frozen water-ice particles from Enceladus' subsurface ocean. It has since been determined that Enceladus likely has a global liquid water ocean separating its rocky core from icy surface, with conditions that are relatively favorable to support life. The plume is of particular interest because it gives direct access to ocean particles from space, by flying through the plume. Recently, evidence has been found for similar geological activity occurring on Jupiter's moon Europa, long considered one of the most likely candidate bodies to support life in our solar system. Here, a model for plume-particle dynamics is developed based on studies of the Enceladus plume and data from the Cassini Cosmic Dust Analyzer. A C++, OpenMP/MPI parallel software package is then built to run large scale simulations of dust plumes on planetary satellites. In the case of Enceladus, data from simulations and the Cassini mission provide insight into the structure of emissions on the surface, the total mass production of the plume, and the distribution of particles being emitted. Each of these are fundamental to understanding the plume and, for Europa and Enceladus, simulation data provide important results for the planning of future missions to these icy moons. In particular, this work has contributed to the Europa Clipper mission and proposed Enceladus Life Finder. PART II: Solving large, sparse linear systems arises often in the modeling of biological and physical phenomenon, data analysis through graphs and networks, and other scientific applications. This work focuses primarily on linear systems resulting from the discretization of partial differential equations (PDEs). Because solving linear systems is the bottleneck of many large simulation codes, there is a rich field of research in developing "fast" solvers, with the ultimate goal being a method that solves an n x n linear system in O(n) operations. One of the most effective classes of solvers is algebraic multigrid (AMG), which is a multilevel iterative method based on projecting the problem into progressively smaller spaces, and scales like O(n) or O(nlog n) for certain classes of problems. The field of AMG is well-developed for symmetric positive definite matrices, and is typically most effective on linear systems resulting from the discretization of scalar elliptic PDEs, such as the heat equation. Systems of PDEs can add additional difficulties, but the underlying linear algebraic theory is consistent and, in many cases, an elliptic system of PDEs can be handled well by AMG with appropriate modifications of the solver. Solving general, nonsymmetric linear systems remains the wild west of AMG (and other fast solvers), lacking significant results in convergence theory as well as robust methods. Here, we develop new theoretical motivation and practical variations of AMG to solve nonsymmetric linear systems, often resulting from the discretization of hyperbolic PDEs. In particular, multilevel convergence of AMG for nonsymmetric systems is proven for the first time. A new nonsymmetric AMG solver is also developed based on an approximate ideal restriction, referred to as AIR, which is able to solve advection-dominated, hyperbolic-type problems that are outside the scope of existing AMG solvers and other fast iterative methods. AIR demonstrates scalable convergence on unstructured meshes, in multiple dimensions, and with high-order finite elements, expanding the applicability of AMG to a new class of problems.

Considerations for the Development and Implementation of PDES (Product Data Exchange Specification) within a Government Environment

DTIC Science & Technology

1989-02-01

definition and manipulation languages. TECHNOLOGY TRANSFER: Contractor Personnel Actively Participate in PDES Activities: Yes, (Althoff & Chia Hui Shih...ORGANIZATION I) (2 (3) Mr. Bill Alzheimer Sandia National Labs X X Mr. Jeff Arthurs NAVSEA CEL-PA X Mr. Howard Bloom Nat’l Inst of Stds & Tech X LCDR

Parallels between control PDE's (Partial Differential Equations) and systems of ODE's (Ordinary Differential Equations)

NASA Technical Reports Server (NTRS)

Hunt, L. R.; Villarreal, Ramiro

1987-01-01

System theorists understand that the same mathematical objects which determine controllability for nonlinear control systems of ordinary differential equations (ODEs) also determine hypoellipticity for linear partial differentail equations (PDEs). Moreover, almost any study of ODE systems begins with linear systems. It is remarkable that Hormander's paper on hypoellipticity of second order linear p.d.e.'s starts with equations due to Kolmogorov, which are shown to be analogous to the linear PDEs. Eigenvalue placement by state feedback for a controllable linear system can be paralleled for a Kolmogorov equation if an appropriate type of feedback is introduced. Results concerning transformations of nonlinear systems to linear systems are similar to results for transforming a linear PDE to a Kolmogorov equation.

Advances in targeting cyclic nucleotide phosphodiesterases

PubMed Central

Maurice, Donald H.; Ke, Hengming; Ahmad, Faiyaz; Wang, Yousheng; Chung, Jay; Manganiello, Vincent C.

2014-01-01

Cyclic nucleotide phosphodiesterases (PDEs) catalyse the hydrolysis of cyclic AMP and cyclic GMP, thereby regulating the intracellular concentrations of these cyclic nucleotides, their signalling pathways and, consequently, myriad biological responses in health and disease. Currently, a small number of PDE inhibitors are used clinically for treating the pathophysiological dysregulation of cyclic nucleotide signalling in several disorders, including erectile dysfunction, pulmonary hypertension, acute refractory cardiac failure, intermittent claudication and chronic obstructive pulmonary disease. However, pharmaceutical interest in PDEs has been reignited by the increasing understanding of the roles of individual PDEs in regulating the subcellular compartmentalization of specific cyclic nucleotide signalling pathways, by the structure-based design of novel specific inhibitors and by the development of more sophisticated strategies to target individual PDE variants. PMID:24687066

BOOK REVIEW: Advanced Topics in Computational Partial Differential Equations: Numerical Methods and Diffpack Programming

NASA Astrophysics Data System (ADS)

Katsaounis, T. D.

2005-02-01

The scope of this book is to present well known simple and advanced numerical methods for solving partial differential equations (PDEs) and how to implement these methods using the programming environment of the software package Diffpack. A basic background in PDEs and numerical methods is required by the potential reader. Further, a basic knowledge of the finite element method and its implementation in one and two space dimensions is required. The authors claim that no prior knowledge of the package Diffpack is required, which is true, but the reader should be at least familiar with an object oriented programming language like C++ in order to better comprehend the programming environment of Diffpack. Certainly, a prior knowledge or usage of Diffpack would be a great advantage to the reader. The book consists of 15 chapters, each one written by one or more authors. Each chapter is basically divided into two parts: the first part is about mathematical models described by PDEs and numerical methods to solve these models and the second part describes how to implement the numerical methods using the programming environment of Diffpack. Each chapter closes with a list of references on its subject. The first nine chapters cover well known numerical methods for solving the basic types of PDEs. Further, programming techniques on the serial as well as on the parallel implementation of numerical methods are also included in these chapters. The last five chapters are dedicated to applications, modelled by PDEs, in a variety of fields. The first chapter is an introduction to parallel processing. It covers fundamentals of parallel processing in a simple and concrete way and no prior knowledge of the subject is required. Examples of parallel implementation of basic linear algebra operations are presented using the Message Passing Interface (MPI) programming environment. Here, some knowledge of MPI routines is required by the reader. Examples solving in parallel simple PDEs using Diffpack and MPI are also presented. Chapter 2 presents the overlapping domain decomposition method for solving PDEs. It is well known that these methods are suitable for parallel processing. The first part of the chapter covers the mathematical formulation of the method as well as algorithmic and implementational issues. The second part presents a serial and a parallel implementational framework within the programming environment of Diffpack. The chapter closes by showing how to solve two application examples with the overlapping domain decomposition method using Diffpack. Chapter 3 is a tutorial about how to incorporate the multigrid solver in Diffpack. The method is illustrated by examples such as a Poisson solver, a general elliptic problem with various types of boundary conditions and a nonlinear Poisson type problem. In chapter 4 the mixed finite element is introduced. Technical issues concerning the practical implementation of the method are also presented. The main difficulties of the efficient implementation of the method, especially in two and three space dimensions on unstructured grids, are presented and addressed in the framework of Diffpack. The implementational process is illustrated by two examples, namely the system formulation of the Poisson problem and the Stokes problem. Chapter 5 is closely related to chapter 4 and addresses the problem of how to solve efficiently the linear systems arising by the application of the mixed finite element method. The proposed method is block preconditioning. Efficient techniques for implementing the method within Diffpack are presented. Optimal block preconditioners are used to solve the system formulation of the Poisson problem, the Stokes problem and the bidomain model for the electrical activity in the heart. The subject of chapter 6 is systems of PDEs. Linear and nonlinear systems are discussed. Fully implicit and operator splitting methods are presented. Special attention is paid to how existing solvers for scalar equations in Diffpack can be used to derive fully implicit solvers for systems. The proposed techniques are illustrated in terms of two applications, namely a system of PDEs modelling pipeflow and a two-phase porous media flow. Stochastic PDEs is the topic of chapter 7. The first part of the chapter is a simple introduction to stochastic PDEs; basic analytical properties are presented for simple models like transport phenomena and viscous drag forces. The second part considers the numerical solution of stochastic PDEs. Two basic techniques are presented, namely Monte Carlo and perturbation methods. The last part explains how to implement and incorporate these solvers into Diffpack. Chapter 8 describes how to operate Diffpack from Python scripts. The main goal here is to provide all the programming and technical details in order to glue the programming environment of Diffpack with visualization packages through Python and in general take advantage of the Python interfaces. Chapter 9 attempts to show how to use numerical experiments to measure the performance of various PDE solvers. The authors gathered a rather impressive list, a total of 14 PDE solvers. Solvers for problems like Poisson, Navier--Stokes, elasticity, two-phase flows and methods such as finite difference, finite element, multigrid, and gradient type methods are presented. The authors provide a series of numerical results combining various solvers with various methods in order to gain insight into their computational performance and efficiency. In Chapter 10 the authors consider a computationally challenging problem, namely the computation of the electrical activity of the human heart. After a brief introduction on the biology of the problem the authors present the mathematical models involved and a numerical method for solving them within the framework of Diffpack. Chapter 11 and 12 are closely related; actually they could have been combined in a single chapter. Chapter 11 introduces several mathematical models used in finance, based on the Black--Scholes equation. Chapter 12 considers several numerical methods like Monte Carlo, lattice methods, finite difference and finite element methods. Implementation of these methods within Diffpack is presented in the last part of the chapter. Chapter 13 presents how the finite element method is used for the modelling and analysis of elastic structures. The authors describe the structural elements of Diffpack which include popular elements such as beams and plates and examples are presented on how to use them to simulate elastic structures. Chapter 14 describes an application problem, namely the extrusion of aluminum. This is a rather\\endcolumn complicated process which involves non-Newtonian flow, heat transfer and elasticity. The authors describe the systems of PDEs modelling the underlying process and use a finite element method to obtain a numerical solution. The implementation of the numerical method in Diffpack is presented along with some applications. The last chapter, chapter 15, focuses on mathematical and numerical models of systems of PDEs governing geological processes in sedimentary basins. The underlying mathematical model is solved using the finite element method within a fully implicit scheme. The authors discuss the implementational issues involved within Diffpack and they present results from several examples. In summary, the book focuses on the computational and implementational issues involved in solving partial differential equations. The potential reader should have a basic knowledge of PDEs and the finite difference and finite element methods. The examples presented are solved within the programming framework of Diffpack and the reader should have prior experience with the particular software in order to take full advantage of the book. Overall the book is well written, the subject of each chapter is well presented and can serve as a reference for graduate students, researchers and engineers who are interested in the numerical solution of partial differential equations modelling various applications.

Highly Scalable Asynchronous Computing Method for Partial Differential Equations: A Path Towards Exascale

NASA Astrophysics Data System (ADS)

Konduri, Aditya

Many natural and engineering systems are governed by nonlinear partial differential equations (PDEs) which result in a multiscale phenomena, e.g. turbulent flows. Numerical simulations of these problems are computationally very expensive and demand for extreme levels of parallelism. At realistic conditions, simulations are being carried out on massively parallel computers with hundreds of thousands of processing elements (PEs). It has been observed that communication between PEs as well as their synchronization at these extreme scales take up a significant portion of the total simulation time and result in poor scalability of codes. This issue is likely to pose a bottleneck in scalability of codes on future Exascale systems. In this work, we propose an asynchronous computing algorithm based on widely used finite difference methods to solve PDEs in which synchronization between PEs due to communication is relaxed at a mathematical level. We show that while stability is conserved when schemes are used asynchronously, accuracy is greatly degraded. Since message arrivals at PEs are random processes, so is the behavior of the error. We propose a new statistical framework in which we show that average errors drop always to first-order regardless of the original scheme. We propose new asynchrony-tolerant schemes that maintain accuracy when synchronization is relaxed. The quality of the solution is shown to depend, not only on the physical phenomena and numerical schemes, but also on the characteristics of the computing machine. A novel algorithm using remote memory access communications has been developed to demonstrate excellent scalability of the method for large-scale computing. Finally, we present a path to extend this method in solving complex multi-scale problems on Exascale machines.

Operational Characteristics of a Rotating Detonation Engine Using Hydrogen and Air

DTIC Science & Technology

2011-06-01

Naval Research Laboratory PDE Pulsed detonation engine RDE Rotating detonation engine TDW Transverse detonation wave Symbols [SI units...primarily been on pulsed detonation engines ( PDEs ). Recently, however, detonation research has begun to also focus on rotating , or continuous... rotating detonation engines have been studied, however, more progress was initially made regarding PDEs . Recently, though, there has been a renewed

Hyperbolic Method for Dispersive PDEs: Same High-Order of Accuracy for Solution, Gradient, and Hessian

NASA Technical Reports Server (NTRS)

Mazaheri, Alireza; Ricchiuto, Mario; Nishikawa, Hiroaki

2016-01-01

In this paper, we introduce a new hyperbolic first-order system for general dispersive partial differential equations (PDEs). We then extend the proposed system to general advection-diffusion-dispersion PDEs. We apply the fourth-order RD scheme of Ref. 1 to the proposed hyperbolic system, and solve time-dependent dispersive equations, including the classical two-soliton KdV and a dispersive shock case. We demonstrate that the predicted results, including the gradient and Hessian (second derivative), are in a very good agreement with the exact solutions. We then show that the RD scheme applied to the proposed system accurately captures dispersive shocks without numerical oscillations. We also verify that the solution, gradient and Hessian are predicted with equal order of accuracy.

Solution of elliptic PDEs by fast Poisson solvers using a local relaxation factor

NASA Technical Reports Server (NTRS)

Chang, Sin-Chung

1986-01-01

A large class of two- and three-dimensional, nonseparable elliptic partial differential equations (PDEs) is presently solved by means of novel one-step (D'Yakanov-Gunn) and two-step (accelerated one-step) iterative procedures, using a local, discrete Fourier analysis. In addition to being easily implemented and applicable to a variety of boundary conditions, these procedures are found to be computationally efficient on the basis of the results of numerical comparison with other established methods, which lack the present one's: (1) insensitivity to grid cell size and aspect ratio, and (2) ease of convergence rate estimation by means of the coefficient of the PDE being solved. The two-step procedure is numerically demonstrated to outperform the one-step procedure in the case of PDEs with variable coefficients.

Modeling and simulation of high dimensional stochastic multiscale PDE systems at the exascale

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zabaras, Nicolas J.

2016-11-08

Predictive Modeling of multiscale and Multiphysics systems requires accurate data driven characterization of the input uncertainties, and understanding of how they propagate across scales and alter the final solution. This project develops a rigorous mathematical framework and scalable uncertainty quantification algorithms to efficiently construct realistic low dimensional input models, and surrogate low complexity systems for the analysis, design, and control of physical systems represented by multiscale stochastic PDEs. The work can be applied to many areas including physical and biological processes, from climate modeling to systems biology.

MOOSE: A parallel computational framework for coupled systems of nonlinear equations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Derek Gaston; Chris Newman; Glen Hansen

Systems of coupled, nonlinear partial differential equations (PDEs) often arise in simulation of nuclear processes. MOOSE: Multiphysics Object Oriented Simulation Environment, a parallel computational framework targeted at the solution of such systems, is presented. As opposed to traditional data-flow oriented computational frameworks, MOOSE is instead founded on the mathematical principle of Jacobian-free Newton-Krylov (JFNK) solution methods. Utilizing the mathematical structure present in JFNK, physics expressions are modularized into `Kernels,'' allowing for rapid production of new simulation tools. In addition, systems are solved implicitly and fully coupled, employing physics based preconditioning, which provides great flexibility even with large variance in timemore » scales. A summary of the mathematics, an overview of the structure of MOOSE, and several representative solutions from applications built on the framework are presented.« less

(N+1)-dimensional fractional reduced differential transform method for fractional order partial differential equations

NASA Astrophysics Data System (ADS)

Arshad, Muhammad; Lu, Dianchen; Wang, Jun

2017-07-01

In this paper, we pursue the general form of the fractional reduced differential transform method (DTM) to (N+1)-dimensional case, so that fractional order partial differential equations (PDEs) can be resolved effectively. The most distinct aspect of this method is that no prescribed assumptions are required, and the huge computational exertion is reduced and round-off errors are also evaded. We utilize the proposed scheme on some initial value problems and approximate numerical solutions of linear and nonlinear time fractional PDEs are obtained, which shows that the method is highly accurate and simple to apply. The proposed technique is thus an influential technique for solving the fractional PDEs and fractional order problems occurring in the field of engineering, physics etc. Numerical results are obtained for verification and demonstration purpose by using Mathematica software.

Automating Embedded Analysis Capabilities and Managing Software Complexity in Multiphysics Simulation, Part II: Application to Partial Differential Equations

DOE PAGES

Pawlowski, Roger P.; Phipps, Eric T.; Salinger, Andrew G.; ...

2012-01-01

A template-based generic programming approach was presented in Part I of this series of papers [Sci. Program. 20 (2012), 197–219] that separates the development effort of programming a physical model from that of computing additional quantities, such as derivatives, needed for embedded analysis algorithms. In this paper, we describe the implementation details for using the template-based generic programming approach for simulation and analysis of partial differential equations (PDEs). We detail several of the hurdles that we have encountered, and some of the software infrastructure developed to overcome them. We end with a demonstration where we present shape optimization and uncertaintymore » quantification results for a 3D PDE application.« less

Build Up and Operation of an Axial Turbine Driven by a Rotary Detonation Engine

DTIC Science & Technology

2012-03-01

RDEs) offer advantages over pulsed detonation engines ( PDEs ) due to a steadier exhaust and fewer total system losses. All previous research on...turbine integration with detonation combustors has focused on utilizing PDEs to drive axial and centrifugal turbines. The objective of this thesis was... detonation engine ............................................. 5 Figure 4. Schematic of the rotating detonation wave structure for an unwrapped view of an

Cyclic Nucleotide Phosphodiesterases: important signaling modulators and therapeutic targets

PubMed Central

Ahmad, Faiyaz; Murata, Taku; Simizu, Kasumi; Degerman, Eva; Maurice, Donald; Manganiello, Vincent

2014-01-01

By catalyzing hydrolysis of cAMP and cGMP, cyclic nucleotide phosphodiesterases are critical regulators of their intracellular concentrations and their biological effects. Since these intracellular second messengers control many cellular homeostatic processes, dysregulation of their signals and signaling pathways initiate or modulate pathophysiological pathways related to various disease states, including erectile dysfunction, pulmonary hypertension, acute refractory cardiac failure, intermittent claudication, chronic obstructive pulmonary disease, and psoriasis. Alterations in expression of PDEs and PDE-gene mutations (especially mutations in PDE6, PDE8B, PDE11A and PDE4) have been implicated in various diseases and cancer pathologies. PDEs also play important role in formation and function of multi-molecular signaling/regulatory complexes called signalosomes. At specific intracellular locations, individual PDEs, together with pathway-specific signaling molecules, regulators, and effectors, are incorporated into specific signalosomes, where they facilitate and regulate compartmentalization of cyclic nucleotide signaling pathways and specific cellular functions. Currently, only a limited number of PDE inhibitors (PDE3, PDE4, PDE5 inhibitors) are used in clinical practice. Future paths to novel drug discovery include the crystal structure-based design approach, which has resulted in generation of more effective family-selective inhibitors, as well as burgeoning development of strategies to alter compartmentalized cyclic nucleotide signaling pathways by selectively targeting individual PDEs and their signalosome partners. PMID:25056711

An Artificial Neural Networks Method for Solving Partial Differential Equations

NASA Astrophysics Data System (ADS)

Alharbi, Abir

2010-09-01

While there already exists many analytical and numerical techniques for solving PDEs, this paper introduces an approach using artificial neural networks. The approach consists of a technique developed by combining the standard numerical method, finite-difference, with the Hopfield neural network. The method is denoted Hopfield-finite-difference (HFD). The architecture of the nets, energy function, updating equations, and algorithms are developed for the method. The HFD method has been used successfully to approximate the solution of classical PDEs, such as the Wave, Heat, Poisson and the Diffusion equations, and on a system of PDEs. The software Matlab is used to obtain the results in both tabular and graphical form. The results are similar in terms of accuracy to those obtained by standard numerical methods. In terms of speed, the parallel nature of the Hopfield nets methods makes them easier to implement on fast parallel computers while some numerical methods need extra effort for parallelization.

Flexible Automatic Discretization for Finite Differences: Eliminating the Human Factor

NASA Astrophysics Data System (ADS)

Pranger, Casper

2017-04-01

In the geophysical numerical modelling community, finite differences are (in part due to their small footprint) a popular spatial discretization method for PDEs in the regular-shaped continuum that is the earth. However, they rapidly become prone to programming mistakes when physics increase in complexity. To eliminate opportunities for human error, we have designed an automatic discretization algorithm using Wolfram Mathematica, in which the user supplies symbolic PDEs, the number of spatial dimensions, and a choice of symbolic boundary conditions, and the script transforms this information into matrix- and right-hand-side rules ready for use in a C++ code that will accept them. The symbolic PDEs are further used to automatically develop and perform manufactured solution benchmarks, ensuring at all stages physical fidelity while providing pragmatic targets for numerical accuracy. We find that this procedure greatly accelerates code development and provides a great deal of flexibility in ones choice of physics.

Regulation of Endothelial Barrier Function by Cyclic Nucleotides: The Role of Phosphodiesterases

PubMed Central

Surapisitchat, James

2014-01-01

The endothelium plays an important role in maintaining normal vascular function. Endothelial barrier dysfunction leading to increased permeability and vascular leakage is associated with several pathological conditions such as edema and sepsis. Thus, the development of drugs that improve endothelial barrier function is an active area of research. In this chapter, the current knowledge concerning the signaling pathways regulating endothelial barrier function is discussed with a focus on cyclic nucleotide second messengers (cAMP and cGMP) and cyclic nucleotide phosphodiesterases (PDEs). Both cAMP and cGMP have been shown to have differential effects on endothelial permeability in part due to the various effector molecules, crosstalk, and compartmentalization of cyclic nucleotide signaling. PDEs, by controlling the amplitude, duration, and localization of cyclic nucleotides, have been shown to play a critical role in regulating endothelial barrier function. Thus, PDEs are attractive drug targets for the treatment of disease states involving endothelial barrier dysfunction. PMID:21695641

Regulation of endothelial barrier function by cyclic nucleotides: the role of phosphodiesterases.

PubMed

Surapisitchat, James; Beavo, Joseph A

2011-01-01

The endothelium plays an important role in maintaining normal vascular function. Endothelial barrier dysfunction leading to increased permeability and vascular leakage is associated with several pathological conditions such as edema and sepsis. Thus, the development of drugs that improve endothelial barrier function is an active area of research. In this chapter, the current knowledge concerning the signaling pathways regulating endothelial barrier function is discussed with a focus on cyclic nucleotide second messengers (cAMP and cGMP) and cyclic nucleotide phosphodiesterases (PDEs). Both cAMP and cGMP have been shown to have differential effects on endothelial permeability in part due to the various effector molecules, crosstalk, and compartmentalization of cyclic nucleotide signaling. PDEs, by controlling the amplitude, duration, and localization of cyclic nucleotides, have been shown to play a critical role in regulating endothelial barrier function. Thus, PDEs are attractive drug targets for the treatment of disease states involving endothelial barrier dysfunction.

Backstepping boundary control: an application to the suppression of flexible beam vibration

NASA Astrophysics Data System (ADS)

Boonkumkrong, Nipon; Asadamongkon, Pichai; Chinvorarat, Sinchai

2018-01-01

This paper presents a backstepping boundary control for vibration suppression of flexible beam. The applications are such as industrial robotic arms, space structures, etc. Most slender beams can be modelled using a shear beam. The shear beam is more complex than the conventional Euler-Bernoulli beam in that a shear deformation is additionally taken into account. At present, the application of this method in industry is rather limited, because the application of controllers to the beam is difficult. In this research, we use the shear beam with moving base as a model. The beam is cantilever type. This design method allows us to deal directly with the beam’s partial differential equations (PDEs) without resorting to approximations. An observer is used to estimate the deflections along the beam. Gain kernel of the system is calculated and then used in the control law design. The control setup is anti-collocation, i.e. a sensor is placed at the beam tip and an actuator is placed at the beam moving base. Finite difference equations are used to solve the PDEs and the partial integro-differential equations (PIDEs). Control parameters are varied to see their influences that affect the control performance. The results of the control are presented via computer simulation to verify that the control scheme is effective.

Novel Numerical Approaches to Loop Quantum Cosmology

NASA Astrophysics Data System (ADS)

Diener, Peter

2015-04-01

Loop Quantum Gravity (LQG) is an (as yet incomplete) approach to the quantization of gravity. When applied to symmetry reduced cosmological spacetimes (Loop Quantum Cosmology or LQC) one of the predictions of the theory is that the Big Bang is replaced by a Big Bounce, i.e. a previously existing contracting universe underwent a bounce at finite volume before becoming our expanding universe. The evolution equations of LQC take the form of difference equations (with the discretization given by the theory) that in the large volume limit can be approximated by partial differential equations (PDEs). In this talk I will first discuss some of the unique challenges encountered when trying to numerically solve these difference equations. I will then present some of the novel approaches that have been employed to overcome the challenges. I will here focus primarily on the Chimera scheme that takes advantage of the fact that the LQC difference equations can be approximated by PDEs in the large volume limit. I will finally also briefly discuss some of the results that have been obtained using these numerical techniques by performing simulations in regions of parameter space that were previously unreachable. This work is supported by a grant from the John Templeton Foundation and by NSF grant PHYS1068743.

Discontinuous Galerkin methods for Hamiltonian ODEs and PDEs

NASA Astrophysics Data System (ADS)

Tang, Wensheng; Sun, Yajuan; Cai, Wenjun

2017-02-01

In this article, we present a unified framework of discontinuous Galerkin (DG) discretizations for Hamiltonian ODEs and PDEs. We show that with appropriate numerical fluxes the numerical algorithms deduced from DG discretizations can be combined with the symplectic methods in time to derive the multi-symplectic PRK schemes. The resulting numerical discretizations are applied to the linear and nonlinear Schrödinger equations. Some conservative properties of the numerical schemes are investigated and confirmed in the numerical experiments.

Crystal Structure of the Leishmania Major Phosphodiesterase LmjPDEB1 and Insight into the Design of hte Parasite-Selective Inhibitors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang,H.; Yan, Z.; Geng, J.

2007-01-01

Human leishmaniasis is a major public health problem in many countries, but chemotherapy is in an unsatisfactory state. Leishmania major phosphodiesterases (LmjPDEs) have been shown to play important roles in cell proliferation and apoptosis of the parasite. Thus LmjPDE inhibitors may potentially represent a novel class of drugs for the treatment of leishmaniasis. Reported here are the kinetic characterization of the LmjPDEB1 catalytic domain and its crystal structure as a complex with 3-isobutyl-1-methylxanthine (IBMX) at 1.55 Angstroms resolution. The structure of LmjPDEB1 is similar to that of human PDEs. IBMX stacks against the conserved phenylalanine and forms a hydrogen bondmore » with the invariant glutamine, in a pattern common to most inhibitors bound to human PDEs. However, an extensive structural comparison reveals subtle, but significant differences between the active sites of LmjPDEB1 and human PDEs. In addition, a pocket next to the inhibitor binding site is found to be unique to LmjPDEB1. This pocket is isolated by two gating residues in human PDE families, but constitutes a natural expansion of the inhibitor binding pocket in LmjPDEB1. The structure particularity might be useful for the development of parasite-selective inhibitors for the treatment of leishmaniasis.« less

Identification of New Signaling Components in the Sensory Epithelium of Human Saccule

PubMed Central

Degerman, Eva; Rauch, Uwe; Göransson, Olga; Lindberg, Sven; Hultgårdh, Anna; Magnusson, Måns

2011-01-01

Objective: To locate components and target proteins of relevance for the cAMP and cGMP signaling networks including cAMP and cGMP phosphodiesterases (PDEs), salt-inducible kinases (SIKs), subunits of Na+, K+-ATPases, and aquaporins (AQPs) in the human saccule. Methods: The human saccule was dissected out during the removal of vestibular schwannoma via the translabyrinthine approach and immediately fixed. Immunohistochemistry was performed using PDE, SIK, Na+, K+-ATPase, and AQP antibodies. Results: PDEs selective for cAMP (PDE4A, PDE4D, and PDE8A) and cGMP (PDE9A) as well a dual specificity PDE (PDE10A) were detected in the sensory epithelium of the saccule. Furthermore, AQP2, 4, and 9, SIK1 and the α-1 subunit of the Na+, K+-ATPase were detected. Conclusion: cAMP and cGMP are important regulators of ion and water homeostasis in the inner ear. The identification of PDEs and SIK1 in the vestibular system offers new treatment targets for endolymphatic hydrops. Exactly how the PDEs are connected to SIK1 and the SIK1 substrate Na+, K+-ATPase and to AQPs 2, 4, 9 remains to be elucidated. The dissection of the signaling networks utilizing these components and evaluating their roles will add new basic knowledge regarding inner ear physiology. PMID:21886636

A novel poly(deep eutectic solvent)-based magnetic silica composite for solid-phase extraction of trypsin.

PubMed

Xu, Kaijia; Wang, Yuzhi; Li, Yixue; Lin, Yunxuan; Zhang, Haibao; Zhou, Yigang

2016-11-23

Novel poly(deep eutectic solvent) grafted silica-coated magnetic microspheres (Fe 3 O 4 @SiO 2 -MPS@PDES) were prepared by polymerization of choline chloride-itaconic acid (ChCl-IA) and γ-MPS-modified magnetic silica composites, and were characterized by vibrating sample magnetometer (VSM), Fourier transform infrared spectrometry (FT-IR), X-ray photoelectron spectra (XPS), thermal gravimetric analysis (TGA) and transmission electron microscope (TEM). Then the synthetic Fe 3 O 4 @SiO 2 -MPS@PDES microspheres were applied for the magnetic solid-phase extraction (MSPE) of trypsin for the first time. After extraction, the concentration of trypsin in the supernatant was determined by a UV-vis spectrophotometer. Single factor experiments were carried out to investigate the effects of the extraction process, including the concentration of trypsin, the ionic strength, the pH value, the extraction time and the temperature. Experimental results showed the extraction capacity could reach up to 287.5 mg/g under optimized conditions. In comparison with Fe 3 O 4 @SiO 2 -MPS, Fe 3 O 4 @SiO 2 -MPS@PDES displayed higher extraction capacity and selectivity for trypsin. According to the regeneration studies, Fe 3 O 4 @SiO 2 -MPS@PDES microspheres can be recycled six times without significant loss of its extraction capacity, and retained a high extraction capacity of 233 mg/g after eight cycles. Besides, the activity studies also demonstrated that the activity of the extracted trypsin was well retained. Furthermore, the analysis of real sample revealed that the prepared magnetic microspheres can be used to purify trypsin in crude bovine pancreas extract. These results highlight the potential of the proposed Fe 3 O 4 @SiO 2 -MPS@PDES-MSPE method in separation of biomolecules. Copyright © 2016 Elsevier B.V. All rights reserved.

Entropy Viscosity and L1-based Approximations of PDEs: Exploiting Sparsity

DTIC Science & Technology

2015-10-23

AFRL-AFOSR-VA-TR-2015-0337 Entropy Viscosity and L1-based Approximations of PDEs: Exploiting Sparsity Jean-Luc Guermond TEXAS A & M UNIVERSITY 750...REPORT DATE (DD-MM-YYYY) 09-05-2015 2. REPORT TYPE Final report 3. DATES COVERED (From - To) 01-07-2012 - 30-06-2015 4. TITLE AND SUBTITLE Entropy ...conservation equations can be stabilized by using the so-called entropy viscosity method and we proposed to to investigate this new technique. We

Investigation of the Stability of POD-Galerkin Techniques for Reduced Order Model Development

DTIC Science & Technology

2016-01-09

symmetrizing the higher- order PDE with a preconditioning matrix. Rowley et al. also pointed out that defining a proper inner product can be important when...equations. The ROM is obtained by employing Galerkin’s method to reduce the high-order PDEs to a lower-order ODE system by means of POD eigen-bases...employing Galerkin’s method to reduce the high-order PDEs to a lower-order ODE system by means of POD eigen-bases. Possible solutions of the ROM stability

Exploration of POD-Galerkin Techniques for Developing Reduced Order Models of the Euler Equations

DTIC Science & Technology

2015-07-01

modes [1]. Barone et al [15, 16] proposed to stabilize the reduced system by symmetrizing the higher-order PDE with a preconditioning matrix. Rowley et...advection scalar equation. The ROM is obtained by employing Galerkin’s method to reduce the high-order PDEs to a lower- order ODE system by means of POD...high-order PDEs to a lower-order ODE system by means of POD eigen-bases. For purposes of this study, a linearized version of the Euler equations is

EXPONENTIAL TIME DIFFERENCING FOR HODGKIN–HUXLEY-LIKE ODES

PubMed Central

Börgers, Christoph; Nectow, Alexander R.

2013-01-01

Several authors have proposed the use of exponential time differencing (ETD) for Hodgkin–Huxley-like partial and ordinary differential equations (PDEs and ODEs). For Hodgkin–Huxley-like PDEs, ETD is attractive because it can deal effectively with the stiffness issues that diffusion gives rise to. However, large neuronal networks are often simulated assuming “space-clamped” neurons, i.e., using the Hodgkin–Huxley ODEs, in which there are no diffusion terms. Our goal is to clarify whether ETD is a good idea even in that case. We present a numerical comparison of first- and second-order ETD with standard explicit time-stepping schemes (Euler’s method, the midpoint method, and the classical fourth-order Runge–Kutta method). We find that in the standard schemes, the stable computation of the very rapid rising phase of the action potential often forces time steps of a small fraction of a millisecond. This can result in an expensive calculation yielding greater overall accuracy than needed. Although it is tempting at first to try to address this issue with adaptive or fully implicit time-stepping, we argue that neither is effective here. The main advantage of ETD for Hodgkin–Huxley-like systems of ODEs is that it allows underresolution of the rising phase of the action potential without causing instability, using time steps on the order of one millisecond. When high quantitative accuracy is not necessary and perhaps, because of modeling inaccuracies, not even useful, ETD allows much faster simulations than standard explicit time-stepping schemes. The second-order ETD scheme is found to be substantially more accurate than the first-order one even for large values of Δt. PMID:24058276

A Solution Space for a System of Null-State Partial Differential Equations: Part 1

NASA Astrophysics Data System (ADS)

Flores, Steven M.; Kleban, Peter

2015-01-01

This article is the first of four that completely and rigorously characterize a solution space for a homogeneous system of 2 N + 3 linear partial differential equations (PDEs) in 2 N variables that arises in conformal field theory (CFT) and multiple Schramm-Löwner evolution (SLE). In CFT, these are null-state equations and conformal Ward identities. They govern partition functions for the continuum limit of a statistical cluster or loop-gas model, such as percolation, or more generally the Potts models and O( n) models, at the statistical mechanical critical point. (SLE partition functions also satisfy these equations.) For such a lattice model in a polygon with its 2 N sides exhibiting a free/fixed side-alternating boundary condition , this partition function is proportional to the CFT correlation function where the w i are the vertices of and where is a one-leg corner operator. (Partition functions for "crossing events" in which clusters join the fixed sides of in some specified connectivity are linear combinations of such correlation functions.) When conformally mapped onto the upper half-plane, methods of CFT show that this correlation function satisfies the system of PDEs that we consider. In this first article, we use methods of analysis to prove that the dimension of this solution space is no more than C N , the Nth Catalan number. While our motivations are based in CFT, our proofs are completely rigorous. This proof is contained entirely within this article, except for the proof of Lemma 14, which constitutes the second article (Flores and Kleban, in Commun Math Phys, arXiv:1404.0035, 2014). In the third article (Flores and Kleban, in Commun Math Phys, arXiv:1303.7182, 2013), we use the results of this article to prove that the solution space of this system of PDEs has dimension C N and is spanned by solutions constructed with the CFT Coulomb gas (contour integral) formalism. In the fourth article (Flores and Kleban, in Commun Math Phys, arXiv:1405.2747, 2014), we prove further CFT-related properties about these solutions, some useful for calculating cluster-crossing probabilities of critical lattice models in polygons.

Optimizing some 3-stage W-methods for the time integration of PDEs

NASA Astrophysics Data System (ADS)

Gonzalez-Pinto, S.; Hernandez-Abreu, D.; Perez-Rodriguez, S.

2017-07-01

The optimization of some W-methods for the time integration of time-dependent PDEs in several spatial variables is considered. In [2, Theorem 1] several three-parametric families of three-stage W-methods for the integration of IVPs in ODEs were studied. Besides, the optimization of several specific methods for PDEs when the Approximate Matrix Factorization Splitting (AMF) is used to define the approximate Jacobian matrix (W ≈ fy(yn)) was carried out. Also, some convergence and stability properties were presented [2]. The derived methods were optimized on the base that the underlying explicit Runge-Kutta method is the one having the largest Monotonicity interval among the thee-stage order three Runge-Kutta methods [1]. Here, we propose an optimization of the methods by imposing some additional order condition [7] to keep order three for parabolic PDE problems [6] but at the price of reducing substantially the length of the nonlinear Monotonicity interval of the underlying explicit Runge-Kutta method.

Phosphodiesterase from Daboia russelli russelli venom: purification, partial characterization and inhibition of platelet aggregation.

PubMed

Mitra, Jyotirmoy; Bhattacharyya, Debasish

2014-09-01

Phosphodiesterases (PDEs) belong to a super-family of enzymes that have multiple roles in the metabolism of extracellular nucleotides and regulation of nucleotide-based intercellular signalling. A PDE from Russell's viper (Daboia russelli russelli) venom (DR-PDE) was purified by gel filtration, ion exchange and affinity chromatographies. Homogeneity of the preparation was verified by SDS-PAGE, SE-HPLC and mass spectrometry. It was free from 5'-nucleotidase, alkaline phosphatase and protease activities. Identity of the enzyme was ensured from partial sequence homology with other PDEs. DR-PDE was inactivated by polyvalent anti-venom serum and metal chelators. The enzyme was partially inhibited by the root extracts of four medicinal plants but remained unaffected by inhibitors of intracellular PDEs. DR-PDE hydrolyses ADP and thus, strongly inhibits ADP-induced platelet aggregation in human platelet rich plasma. This study leads to better understanding of a component of Russell's viper venom that affects homoeostatic system of the victim. Copyright © 2014 Elsevier Ltd. All rights reserved.

DNN-state identification of 2D distributed parameter systems

NASA Astrophysics Data System (ADS)

Chairez, I.; Fuentes, R.; Poznyak, A.; Poznyak, T.; Escudero, M.; Viana, L.

2012-02-01

There are many examples in science and engineering which are reduced to a set of partial differential equations (PDEs) through a process of mathematical modelling. Nevertheless there exist many sources of uncertainties around the aforementioned mathematical representation. Moreover, to find exact solutions of those PDEs is not a trivial task especially if the PDE is described in two or more dimensions. It is well known that neural networks can approximate a large set of continuous functions defined on a compact set to an arbitrary accuracy. In this article, a strategy based on the differential neural network (DNN) for the non-parametric identification of a mathematical model described by a class of two-dimensional (2D) PDEs is proposed. The adaptive laws for weights ensure the 'practical stability' of the DNN-trajectories to the parabolic 2D-PDE states. To verify the qualitative behaviour of the suggested methodology, here a non-parametric modelling problem for a distributed parameter plant is analysed.

Unsteady Solution of Non-Linear Differential Equations Using Walsh Function Series

NASA Technical Reports Server (NTRS)

Gnoffo, Peter A.

2015-01-01

Walsh functions form an orthonormal basis set consisting of square waves. The discontinuous nature of square waves make the system well suited for representing functions with discontinuities. The product of any two Walsh functions is another Walsh function - a feature that can radically change an algorithm for solving non-linear partial differential equations (PDEs). The solution algorithm of non-linear differential equations using Walsh function series is unique in that integrals and derivatives may be computed using simple matrix multiplication of series representations of functions. Solutions to PDEs are derived as functions of wave component amplitude. Three sample problems are presented to illustrate the Walsh function series approach to solving unsteady PDEs. These include an advection equation, a Burgers equation, and a Riemann problem. The sample problems demonstrate the use of the Walsh function solution algorithms, exploiting Fast Walsh Transforms in multi-dimensions (O(Nlog(N))). Details of a Fast Walsh Reciprocal, defined here for the first time, enable inversion of aWalsh Symmetric Matrix in O(Nlog(N)) operations. Walsh functions have been derived using a fractal recursion algorithm and these fractal patterns are observed in the progression of pairs of wave number amplitudes in the solutions. These patterns are most easily observed in a remapping defined as a fractal fingerprint (FFP). A prolongation of existing solutions to the next highest order exploits these patterns. The algorithms presented here are considered a work in progress that provide new alternatives and new insights into the solution of non-linear PDEs.

On multilevel RBF collocation to solve nonlinear PDEs arising from endogenous stochastic volatility models

NASA Astrophysics Data System (ADS)

Bastani, Ali Foroush; Dastgerdi, Maryam Vahid; Mighani, Abolfazl

2018-06-01

The main aim of this paper is the analytical and numerical study of a time-dependent second-order nonlinear partial differential equation (PDE) arising from the endogenous stochastic volatility model, introduced in [Bensoussan, A., Crouhy, M. and Galai, D., Stochastic equity volatility related to the leverage effect (I): equity volatility behavior. Applied Mathematical Finance, 1, 63-85, 1994]. As the first step, we derive a consistent set of initial and boundary conditions to complement the PDE, when the firm is financed by equity and debt. In the sequel, we propose a Newton-based iteration scheme for nonlinear parabolic PDEs which is an extension of a method for solving elliptic partial differential equations introduced in [Fasshauer, G. E., Newton iteration with multiquadrics for the solution of nonlinear PDEs. Computers and Mathematics with Applications, 43, 423-438, 2002]. The scheme is based on multilevel collocation using radial basis functions (RBFs) to solve the resulting locally linearized elliptic PDEs obtained at each level of the Newton iteration. We show the effectiveness of the resulting framework by solving a prototypical example from the field and compare the results with those obtained from three different techniques: (1) a finite difference discretization; (2) a naive RBF collocation and (3) a benchmark approximation, introduced for the first time in this paper. The numerical results confirm the robustness, higher convergence rate and good stability properties of the proposed scheme compared to other alternatives. We also comment on some possible research directions in this field.

Estimating varying coefficients for partial differential equation models.

PubMed

Zhang, Xinyu; Cao, Jiguo; Carroll, Raymond J

2017-09-01

Partial differential equations (PDEs) are used to model complex dynamical systems in multiple dimensions, and their parameters often have important scientific interpretations. In some applications, PDE parameters are not constant but can change depending on the values of covariates, a feature that we call varying coefficients. We propose a parameter cascading method to estimate varying coefficients in PDE models from noisy data. Our estimates of the varying coefficients are shown to be consistent and asymptotically normally distributed. The performance of our method is evaluated by a simulation study and by an empirical study estimating three varying coefficients in a PDE model arising from LIDAR data. © 2017, The International Biometric Society.

Parallel Computation of Flow in Heterogeneous Media Modelled by Mixed Finite Elements

NASA Astrophysics Data System (ADS)

Cliffe, K. A.; Graham, I. G.; Scheichl, R.; Stals, L.

2000-11-01

In this paper we describe a fast parallel method for solving highly ill-conditioned saddle-point systems arising from mixed finite element simulations of stochastic partial differential equations (PDEs) modelling flow in heterogeneous media. Each realisation of these stochastic PDEs requires the solution of the linear first-order velocity-pressure system comprising Darcy's law coupled with an incompressibility constraint. The chief difficulty is that the permeability may be highly variable, especially when the statistical model has a large variance and a small correlation length. For reasonable accuracy, the discretisation has to be extremely fine. We solve these problems by first reducing the saddle-point formulation to a symmetric positive definite (SPD) problem using a suitable basis for the space of divergence-free velocities. The reduced problem is solved using parallel conjugate gradients preconditioned with an algebraically determined additive Schwarz domain decomposition preconditioner. The result is a solver which exhibits a good degree of robustness with respect to the mesh size as well as to the variance and to physically relevant values of the correlation length of the underlying permeability field. Numerical experiments exhibit almost optimal levels of parallel efficiency. The domain decomposition solver (DOUG, http://www.maths.bath.ac.uk/~parsoft) used here not only is applicable to this problem but can be used to solve general unstructured finite element systems on a wide range of parallel architectures.

Dissolution enhancement and mathematical modeling of removal of residual trichloroethene in sands by ozonation during flushing with micro-nano-bubble solution

NASA Astrophysics Data System (ADS)

Sung, Menghau; Teng, Chun-Hao; Yang, Tsung-Hsien

2017-07-01

Soil flushing using micro-nano-sized bubbles (MNB) in water as the flushing solution was tested in laboratory sand columns for the cleanup of residual trichloroethene (TCE) non-aqueous-phase-liquid (NAPL). Experiments considering flushing with MNB as well as ozone MNB (OZMNB) in water to treat soils contaminated with residual TCE liquid were conducted to examine effects of ozone on dissolution enhancement. The degrees of residual TCE saturation in soils, ranging from 0.44% to 7.6%, were tested. During flushings, aqueous TCE concentrations at the column exit were monitored and TCE masses remained in the columns after flushing were determined. Experimental results between runs with MNB and OZMNB in water revealed that dissolution enhancement was dependent on residual saturation conditions, and the maximum enhancement was around 9%. Governing equations consisting of three coupled partial differential equations (PDEs) were developed to model the system, and high-order finite difference (HOFD) method was employed to solve these PDEs. From mathematical modeling of reactive mass transfer under low residual saturation conditions (0.44% and 1.9%), experimental data were simulated and important controlling mechanisms were identified. It was concluded that a specific parameter pertinent to NAPL-water interfacial area in the Sherwood number had to be modified to satisfactorily describe the dissolution of TCE in the presence of MNB in water.

Diffusion approximation of the radiative-conductive heat transfer model with Fresnel matching conditions

NASA Astrophysics Data System (ADS)

Chebotarev, Alexander Yu.; Grenkin, Gleb V.; Kovtanyuk, Andrey E.; Botkin, Nikolai D.; Hoffmann, Karl-Heinz

2018-04-01

The paper is concerned with a problem of diffraction type. The study starts with equations of complex (radiative and conductive) heat transfer in a multicomponent domain with Fresnel matching conditions at the interfaces. Applying the diffusion, P1, approximation yields a pair of coupled nonlinear PDEs describing the radiation intensity and temperature for each component of the domain. Matching conditions for these PDEs, imposed at the interfaces between the domain components, are derived. The unique solvability of the obtained problem is proven, and numerical experiments are conducted.

Scheduled Relaxation Jacobi method: Improvements and applications

NASA Astrophysics Data System (ADS)

Adsuara, J. E.; Cordero-Carrión, I.; Cerdá-Durán, P.; Aloy, M. A.

2016-09-01

Elliptic partial differential equations (ePDEs) appear in a wide variety of areas of mathematics, physics and engineering. Typically, ePDEs must be solved numerically, which sets an ever growing demand for efficient and highly parallel algorithms to tackle their computational solution. The Scheduled Relaxation Jacobi (SRJ) is a promising class of methods, atypical for combining simplicity and efficiency, that has been recently introduced for solving linear Poisson-like ePDEs. The SRJ methodology relies on computing the appropriate parameters of a multilevel approach with the goal of minimizing the number of iterations needed to cut down the residuals below specified tolerances. The efficiency in the reduction of the residual increases with the number of levels employed in the algorithm. Applying the original methodology to compute the algorithm parameters with more than 5 levels notably hinders obtaining optimal SRJ schemes, as the mixed (non-linear) algebraic-differential system of equations from which they result becomes notably stiff. Here we present a new methodology for obtaining the parameters of SRJ schemes that overcomes the limitations of the original algorithm and provide parameters for SRJ schemes with up to 15 levels and resolutions of up to 215 points per dimension, allowing for acceleration factors larger than several hundreds with respect to the Jacobi method for typical resolutions and, in some high resolution cases, close to 1000. Most of the success in finding SRJ optimal schemes with more than 10 levels is based on an analytic reduction of the complexity of the previously mentioned system of equations. Furthermore, we extend the original algorithm to apply it to certain systems of non-linear ePDEs.

IGA-ADS: Isogeometric analysis FEM using ADS solver

NASA Astrophysics Data System (ADS)

Łoś, Marcin M.; Woźniak, Maciej; Paszyński, Maciej; Lenharth, Andrew; Hassaan, Muhamm Amber; Pingali, Keshav

2017-08-01

In this paper we present a fast explicit solver for solution of non-stationary problems using L2 projections with isogeometric finite element method. The solver has been implemented within GALOIS framework. It enables parallel multi-core simulations of different time-dependent problems, in 1D, 2D, or 3D. We have prepared the solver framework in a way that enables direct implementation of the selected PDE and corresponding boundary conditions. In this paper we describe the installation, implementation of exemplary three PDEs, and execution of the simulations on multi-core Linux cluster nodes. We consider three case studies, including heat transfer, linear elasticity, as well as non-linear flow in heterogeneous media. The presented package generates output suitable for interfacing with Gnuplot and ParaView visualization software. The exemplary simulations show near perfect scalability on Gilbert shared-memory node with four Intel® Xeon® CPU E7-4860 processors, each possessing 10 physical cores (for a total of 40 cores).

Robust, heat-resistant and multifunctional superhydrophobic coating of carbon microflowers with molybdenum trioxide nanoparticles.

PubMed

Wu, Yang; Zhao, Meiyun; Guo, Zhiguang

2017-11-15

Superhydrophobic materials have triggered large interest due to their widespread applications, such as self-cleaning, corrosion resistance, anti-icing, and oil/water separation. However, suffering from weak mechanical strength, plenty of superhydrophobic materials are limited in practical application. Herein, we prepared hierarchical carbon microflowers (CMF) dispersed with molybdenum trioxide (MoO 3 ) nanoparticles (MoO 3 /CMF) via a two-step preparation method. Taking advantage of high-adhesion epoxy resin and the modification with 1H,1H,2H,2H-perfluorodecyltriethoxysilane (PDES), the modified MoO 3 /CMF (PDES-MoO 3 /CMF) coating on various substrates shows great waterproof ability, excellent chemical stability, good mechanical durability, and self-cleaning property. More significantly, the prepared PDES-MoO 3 /CMF powder with high thermal stability (250°C) can be used for oil/water separation due to its special flower-like structure and superhydrophobicity/superoleophilicity. All of these advantages endow the superhydrophobic powders with huge potential in the practical applications. Copyright © 2017 Elsevier Inc. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tian, Yuanyuan; Cui, Wenjun; Huang, Manna

Cyclic nucleotide phosphodiesterases (PDEs) decompose second messengers cAMP and cGMP that play critical roles in many physiological processes. PDE1 of Saccharomyces cerevisiae has been subcloned and expressed in Escherichia coli. Recombinant yPDE1 has a K M of 110 μM and a k cat of 16.9 s⁻¹ for cAMP and a K M of 105 μM and a k cat of 11.8 s₅⁻¹ for cGMP. Thus, the specificity constant (k cat/K McAMP)/(k cat/K M cGMP) of 1.4 indicates a dual specificity of yPDE1 for hydrolysis of both cAMP and cGMP. The crystal structures of unliganded yPDE1 and its complex with GMPmore » at 1.31 Å resolution reveal a new structural folding that is different from those of human PDEs but is partially similar to that of some other metalloenzymes such as metallo-β-lactamase. In spite of their different structures and divalent metals, yPDE1 and human PDEs may share a common mechanism for hydrolysis of cAMP and cGMP.« less

Algorithmic framework for group analysis of differential equations and its application to generalized Zakharov-Kuznetsov equations

NASA Astrophysics Data System (ADS)

Huang, Ding-jiang; Ivanova, Nataliya M.

2016-02-01

In this paper, we explain in more details the modern treatment of the problem of group classification of (systems of) partial differential equations (PDEs) from the algorithmic point of view. More precisely, we revise the classical Lie algorithm of construction of symmetries of differential equations, describe the group classification algorithm and discuss the process of reduction of (systems of) PDEs to (systems of) equations with smaller number of independent variables in order to construct invariant solutions. The group classification algorithm and reduction process are illustrated by the example of the generalized Zakharov-Kuznetsov (GZK) equations of form ut +(F (u)) xxx +(G (u)) xyy +(H (u)) x = 0. As a result, a complete group classification of the GZK equations is performed and a number of new interesting nonlinear invariant models which have non-trivial invariance algebras are obtained. Lie symmetry reductions and exact solutions for two important invariant models, i.e., the classical and modified Zakharov-Kuznetsov equations, are constructed. The algorithmic framework for group analysis of differential equations presented in this paper can also be applied to other nonlinear PDEs.

Dual-shaped offset reflector antenna designs from solutions of the geometrical optics first-order partial differential equations

NASA Technical Reports Server (NTRS)

Galindo-Israel, V.; Imbriale, W.; Shogen, K.; Mittra, R.

1990-01-01

In obtaining solutions to the first-order nonlinear partial differential equations (PDEs) for synthesizing offset dual-shaped reflectors, it is found that previously observed computational problems can be avoided if the integration of the PDEs is started from an inner projected perimeter and integrated outward rather than starting from an outer projected perimeter and integrating inward. This procedure, however, introduces a new parameter, the main reflector inner perimeter radius p(o), when given a subreflector inner angle 0(o). Furthermore, a desired outer projected perimeter (e.g., a circle) is no longer guaranteed. Stability of the integration is maintained if some of the initial parameters are determined first from an approximate solution to the PDEs. A one-, two-, or three-parameter optimization algorithm can then be used to obtain a best set of parameters yielding a close fit to the desired projected outer rim. Good low cross-polarization mapping functions are also obtained. These methods are illustrated by synthesis of a high-gain offset-shaped Cassegrainian antenna and a low-noise offset-shaped Gregorian antenna.

New algorithms for field-theoretic block copolymer simulations: Progress on using adaptive-mesh refinement and sparse matrix solvers in SCFT calculations

NASA Astrophysics Data System (ADS)

Sides, Scott; Jamroz, Ben; Crockett, Robert; Pletzer, Alexander

2012-02-01

Self-consistent field theory (SCFT) for dense polymer melts has been highly successful in describing complex morphologies in block copolymers. Field-theoretic simulations such as these are able to access large length and time scales that are difficult or impossible for particle-based simulations such as molecular dynamics. The modified diffusion equations that arise as a consequence of the coarse-graining procedure in the SCF theory can be efficiently solved with a pseudo-spectral (PS) method that uses fast-Fourier transforms on uniform Cartesian grids. However, PS methods can be difficult to apply in many block copolymer SCFT simulations (eg. confinement, interface adsorption) in which small spatial regions might require finer resolution than most of the simulation grid. Progress on using new solver algorithms to address these problems will be presented. The Tech-X Chompst project aims at marrying the best of adaptive mesh refinement with linear matrix solver algorithms. The Tech-X code PolySwift++ is an SCFT simulation platform that leverages ongoing development in coupling Chombo, a package for solving PDEs via block-structured AMR calculations and embedded boundaries, with PETSc, a toolkit that includes a large assortment of sparse linear solvers.

The Cauchy problem for the Pavlov equation

NASA Astrophysics Data System (ADS)

Grinevich, P. G.; Santini, P. M.; Wu, D.

2015-10-01

Commutation of multidimensional vector fields leads to integrable nonlinear dispersionless PDEs that arise in various problems of mathematical physics and have been intensively studied in recent literature. This report aims to solve the scattering and inverse scattering problem for integrable dispersionless PDEs, recently introduced just at a formal level, concentrating on the prototypical example of the Pavlov equation, and to justify an existence theorem for global bounded solutions of the associated Cauchy problem with small data. An essential part of this work was made during the visit of the three authors to the Centro Internacional de Ciencias in Cuernavaca, Mexico in November-December 2012.

Non-autonomous Hénon--Heiles systems

NASA Astrophysics Data System (ADS)

Hone, Andrew N. W.

1998-07-01

Scaling similarity solutions of three integrable PDEs, namely the Sawada-Kotera, fifth order KdV and Kaup-Kupershmidt equations, are considered. It is shown that the resulting ODEs may be written as non-autonomous Hamiltonian equations, which are time-dependent generalizations of the well-known integrable Hénon-Heiles systems. The (time-dependent) Hamiltonians are given by logarithmic derivatives of the tau-functions (inherited from the original PDEs). The ODEs for the similarity solutions also have inherited Bäcklund transformations, which may be used to generate sequences of rational solutions as well as other special solutions related to the first Painlevé transcendent.

Mapping implicit spectral methods to distributed memory architectures

NASA Technical Reports Server (NTRS)

Overman, Andrea L.; Vanrosendale, John

1991-01-01

Spectral methods were proven invaluable in numerical simulation of PDEs (Partial Differential Equations), but the frequent global communication required raises a fundamental barrier to their use on highly parallel architectures. To explore this issue, a 3-D implicit spectral method was implemented on an Intel hypercube. Utilization of about 50 percent was achieved on a 32 node iPSC/860 hypercube, for a 64 x 64 x 64 Fourier-spectral grid; finer grids yield higher utilizations. Chebyshev-spectral grids are more problematic, since plane-relaxation based multigrid is required. However, by using a semicoarsening multigrid algorithm, and by relaxing all multigrid levels concurrently, relatively high utilizations were also achieved in this harder case.

Second-order oriented partial-differential equations for denoising in electronic-speckle-pattern interferometry fringes.

PubMed

Tang, Chen; Han, Lin; Ren, Hongwei; Zhou, Dongjian; Chang, Yiming; Wang, Xiaohang; Cui, Xiaolong

2008-10-01

We derive the second-order oriented partial-differential equations (PDEs) for denoising in electronic-speckle-pattern interferometry fringe patterns from two points of view. The first is based on variational methods, and the second is based on controlling diffusion direction. Our oriented PDE models make the diffusion along only the fringe orientation. The main advantage of our filtering method, based on oriented PDE models, is that it is very easy to implement compared with the published filtering methods along the fringe orientation. We demonstrate the performance of our oriented PDE models via application to two computer-simulated and experimentally obtained speckle fringes and compare with related PDE models.

The pseudo-compartment method for coupling partial differential equation and compartment-based models of diffusion.

PubMed

Yates, Christian A; Flegg, Mark B

2015-05-06

Spatial reaction-diffusion models have been employed to describe many emergent phenomena in biological systems. The modelling technique most commonly adopted in the literature implements systems of partial differential equations (PDEs), which assumes there are sufficient densities of particles that a continuum approximation is valid. However, owing to recent advances in computational power, the simulation and therefore postulation, of computationally intensive individual-based models has become a popular way to investigate the effects of noise in reaction-diffusion systems in which regions of low copy numbers exist. The specific stochastic models with which we shall be concerned in this manuscript are referred to as 'compartment-based' or 'on-lattice'. These models are characterized by a discretization of the computational domain into a grid/lattice of 'compartments'. Within each compartment, particles are assumed to be well mixed and are permitted to react with other particles within their compartment or to transfer between neighbouring compartments. Stochastic models provide accuracy, but at the cost of significant computational resources. For models that have regions of both low and high concentrations, it is often desirable, for reasons of efficiency, to employ coupled multi-scale modelling paradigms. In this work, we develop two hybrid algorithms in which a PDE in one region of the domain is coupled to a compartment-based model in the other. Rather than attempting to balance average fluxes, our algorithms answer a more fundamental question: 'how are individual particles transported between the vastly different model descriptions?' First, we present an algorithm derived by carefully redefining the continuous PDE concentration as a probability distribution. While this first algorithm shows very strong convergence to analytical solutions of test problems, it can be cumbersome to simulate. Our second algorithm is a simplified and more efficient implementation of the first, it is derived in the continuum limit over the PDE region alone. We test our hybrid methods for functionality and accuracy in a variety of different scenarios by comparing the averaged simulations with analytical solutions of PDEs for mean concentrations. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Parameter Estimation of Partial Differential Equation Models.

PubMed

Xun, Xiaolei; Cao, Jiguo; Mallick, Bani; Carroll, Raymond J; Maity, Arnab

2013-01-01

Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown, and need to be estimated from the measurements of the dynamic system in the present of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE, and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from LIDAR data.

Ramp Technology and Intelligent Processing in Small Manufacturing

NASA Technical Reports Server (NTRS)

Rentz, Richard E.

1992-01-01

To address the issues of excessive inventories and increasing procurement lead times, the Navy is actively pursuing flexible computer integrated manufacturing (FCIM) technologies, integrated by communication networks to respond rapidly to its requirements for parts. The Rapid Acquisition of Manufactured Parts (RAMP) program, initiated in 1986, is an integral part of this effort. The RAMP program's goal is to reduce the current average production lead times experienced by the Navy's inventory control points by a factor of 90 percent. The manufacturing engineering component of the RAMP architecture utilizes an intelligent processing technology built around a knowledge-based shell provided by ICAD, Inc. Rules and data bases in the software simulate an expert manufacturing planner's knowledge of shop processes and equipment. This expert system can use Product Data Exchange using STEP (PDES) data to determine what features the required part has, what material is required to manufacture it, what machines and tools are needed, and how the part should be held (fixtured) for machining, among other factors. The program's rule base then indicates, for example, how to make each feature, in what order to make it, and to which machines on the shop floor the part should be routed for processing. This information becomes part of the shop work order. The process planning function under RAMP greatly reduces the time and effort required to complete a process plan. Since the PDES file that drives the intelligent processing is 100 percent complete and accurate to start with, the potential for costly errors is greatly diminished.

Aeroelastic oscillations of a cantilever with structural nonlinearities: theory and numerical simulation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robinson, Brandon; Rocha da Costa, Leandro Jose; Poirel, Dominique

Our study details the derivation of the nonlinear equations of motion for the axial, biaxial bending and torsional vibrations of an aeroelastic cantilever undergoing rigid body (pitch) rotation at the base. The primary attenstion is focussed on the geometric nonlinearities of the system, whereby the aeroelastic load is modeled by the theory of linear quasisteady aerodynamics. This modelling effort is intended to mimic the wind-tunnel experimental setup at the Royal Military College of Canada. While the derivation closely follows the work of Hodges and Dowell [1] for rotor blades, this aeroelastic system contains new inertial terms which stem from themore » fundamentally different kinematics than those exhibited by helicopter or wind turbine blades. Using the Hamilton’s principle, a set of coupled nonlinear partial differential equations (PDEs) and an ordinary differential equation (ODE) are derived which describes the coupled axial-bending-bending-torsion-pitch motion of the aeroelastic cantilever with the pitch rotation. The finite dimensional approximation of the coupled system of PDEs are obtained using the Galerkin projection, leading to a coupled system of ODEs. Subsequently, these nonlinear ODEs are solved numerically using the built-in MATLAB implicit ODE solver and the associated numerical results are compared with those obtained using Houbolt’s method. It is demonstrated that the system undergoes coalescence flutter, leading to a limit cycle oscillation (LCO) due to coupling between the rigid body pitching mode and teh flexible mode arising from the flapwise bending motion.« less

Ramp technology and intelligent processing in small manufacturing

NASA Astrophysics Data System (ADS)

Rentz, Richard E.

1992-04-01

To address the issues of excessive inventories and increasing procurement lead times, the Navy is actively pursuing flexible computer integrated manufacturing (FCIM) technologies, integrated by communication networks to respond rapidly to its requirements for parts. The Rapid Acquisition of Manufactured Parts (RAMP) program, initiated in 1986, is an integral part of this effort. The RAMP program's goal is to reduce the current average production lead times experienced by the Navy's inventory control points by a factor of 90 percent. The manufacturing engineering component of the RAMP architecture utilizes an intelligent processing technology built around a knowledge-based shell provided by ICAD, Inc. Rules and data bases in the software simulate an expert manufacturing planner's knowledge of shop processes and equipment. This expert system can use Product Data Exchange using STEP (PDES) data to determine what features the required part has, what material is required to manufacture it, what machines and tools are needed, and how the part should be held (fixtured) for machining, among other factors. The program's rule base then indicates, for example, how to make each feature, in what order to make it, and to which machines on the shop floor the part should be routed for processing. This information becomes part of the shop work order. The process planning function under RAMP greatly reduces the time and effort required to complete a process plan. Since the PDES file that drives the intelligent processing is 100 percent complete and accurate to start with, the potential for costly errors is greatly diminished.

A paradigm for modeling and computation of gas dynamics

NASA Astrophysics Data System (ADS)

Xu, Kun; Liu, Chang

2017-02-01

In the continuum flow regime, the Navier-Stokes (NS) equations are usually used for the description of gas dynamics. On the other hand, the Boltzmann equation is applied for the rarefied flow. These two equations are based on distinguishable modeling scales for flow physics. Fortunately, due to the scale separation, i.e., the hydrodynamic and kinetic ones, both the Navier-Stokes equations and the Boltzmann equation are applicable in their respective domains. However, in real science and engineering applications, they may not have such a distinctive scale separation. For example, around a hypersonic flying vehicle, the flow physics at different regions may correspond to different regimes, where the local Knudsen number can be changed significantly in several orders of magnitude. With a variation of flow physics, theoretically a continuous governing equation from the kinetic Boltzmann modeling to the hydrodynamic Navier-Stokes dynamics should be used for its efficient description. However, due to the difficulties of a direct modeling of flow physics in the scale between the kinetic and hydrodynamic ones, there is basically no reliable theory or valid governing equations to cover the whole transition regime, except resolving flow physics always down to the mean free path scale, such as the direct Boltzmann solver and the Direct Simulation Monte Carlo (DSMC) method. In fact, it is an unresolved problem about the exact scale for the validity of the NS equations, especially in the small Reynolds number cases. The computational fluid dynamics (CFD) is usually based on the numerical solution of partial differential equations (PDEs), and it targets on the recovering of the exact solution of the PDEs as mesh size and time step converging to zero. This methodology can be hardly applied to solve the multiple scale problem efficiently because there is no such a complete PDE for flow physics through a continuous variation of scales. For the non-equilibrium flow study, the direct modeling methods, such as DSMC, particle in cell, and smooth particle hydrodynamics, play a dominant role to incorporate the flow physics into the algorithm construction directly. It is fully legitimate to combine the modeling and computation together without going through the process of constructing PDEs. In other words, the CFD research is not only to obtain the numerical solution of governing equations but to model flow dynamics as well. This methodology leads to the unified gas-kinetic scheme (UGKS) for flow simulation in all flow regimes. Based on UGKS, the boundary for the validation of the Navier-Stokes equations can be quantitatively evaluated. The combination of modeling and computation provides a paradigm for the description of multiscale transport process.

Partial differential equation models in the socio-economic sciences.

PubMed

Burger, Martin; Caffarelli, Luis; Markowich, Peter A

2014-11-13

Mathematical models based on partial differential equations (PDEs) have become an integral part of quantitative analysis in most branches of science and engineering, recently expanding also towards biomedicine and socio-economic sciences. The application of PDEs in the latter is a promising field, but widely quite open and leading to a variety of novel mathematical challenges. In this introductory article of the Theme Issue, we will provide an overview of the field and its recent boosting topics. Moreover, we will put the contributions to the Theme Issue in an appropriate perspective. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

An RBF-FD closest point method for solving PDEs on surfaces

NASA Astrophysics Data System (ADS)

Petras, A.; Ling, L.; Ruuth, S. J.

2018-10-01

Partial differential equations (PDEs) on surfaces appear in many applications throughout the natural and applied sciences. The classical closest point method (Ruuth and Merriman (2008) [17]) is an embedding method for solving PDEs on surfaces using standard finite difference schemes. In this paper, we formulate an explicit closest point method using finite difference schemes derived from radial basis functions (RBF-FD). Unlike the orthogonal gradients method (Piret (2012) [22]), our proposed method uses RBF centers on regular grid nodes. This formulation not only reduces the computational cost but also avoids the ill-conditioning from point clustering on the surface and is more natural to couple with a grid based manifold evolution algorithm (Leung and Zhao (2009) [26]). When compared to the standard finite difference discretization of the closest point method, the proposed method requires a smaller computational domain surrounding the surface, resulting in a decrease in the number of sampling points on the surface. In addition, higher-order schemes can easily be constructed by increasing the number of points in the RBF-FD stencil. Applications to a variety of examples are provided to illustrate the numerical convergence of the method.

A finite elements method to solve the Bloch-Torrey equation applied to diffusion magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Nguyen, Dang Van; Li, Jing-Rebecca; Grebenkov, Denis; Le Bihan, Denis

2014-04-01

The complex transverse water proton magnetization subject to diffusion-encoding magnetic field gradient pulses in a heterogeneous medium can be modeled by the multiple compartment Bloch-Torrey partial differential equation (PDE). In addition, steady-state Laplace PDEs can be formulated to produce the homogenized diffusion tensor that describes the diffusion characteristics of the medium in the long time limit. In spatial domains that model biological tissues at the cellular level, these two types of PDEs have to be completed with permeability conditions on the cellular interfaces. To solve these PDEs, we implemented a finite elements method that allows jumps in the solution at the cell interfaces by using double nodes. Using a transformation of the Bloch-Torrey PDE we reduced oscillations in the searched-for solution and simplified the implementation of the boundary conditions. The spatial discretization was then coupled to the adaptive explicit Runge-Kutta-Chebyshev time-stepping method. Our proposed method is second order accurate in space and second order accurate in time. We implemented this method on the FEniCS C++ platform and show time and spatial convergence results. Finally, this method is applied to study some relevant questions in diffusion MRI.

Dual specificity and novel structural folding of yeast phosphodiesterase-1 for hydrolysis of second messengers cyclic adenosine and guanosine 3',5'-Monophosphate

DOE PAGES

Tian, Yuanyuan; Cui, Wenjun; Huang, Manna; ...

2014-08-05

Cyclic nucleotide phosphodiesterases (PDEs) decompose second messengers cAMP and cGMP that play critical roles in many physiological processes. PDE1 of Saccharomyces cerevisiae has been subcloned and expressed in Escherichia coli. Recombinant yPDE1 has a K M of 110 μM and a k cat of 16.9 s⁻¹ for cAMP and a K M of 105 μM and a k cat of 11.8 s₅⁻¹ for cGMP. Thus, the specificity constant (k cat/K McAMP)/(k cat/K M cGMP) of 1.4 indicates a dual specificity of yPDE1 for hydrolysis of both cAMP and cGMP. The crystal structures of unliganded yPDE1 and its complex with GMPmore » at 1.31 Å resolution reveal a new structural folding that is different from those of human PDEs but is partially similar to that of some other metalloenzymes such as metallo-β-lactamase. In spite of their different structures and divalent metals, yPDE1 and human PDEs may share a common mechanism for hydrolysis of cAMP and cGMP.« less

Atrazine acts as an endocrine disrupter by inhibiting cAMP-specific phosphodiesterase-4

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kucka, Marek; Pogrmic-Majkic, Kristina; Fa, Svetlana

2012-11-15

Atrazine, one of the most commonly used herbicides worldwide, acts as an endocrine disruptor, but the mechanism of its action has not been characterized. In this study, we show that atrazine rapidly increases cAMP levels in cultured rat pituitary and testicular Leydig cells in a concentration-dependent manner, but less effectively than 3-isobutyl-1-methylxanthine, a competitive non-specific inhibitor of phosphodiesterases (PDEs). In forskolin (an activator of adenylyl cyclase)- and probenecid (an inhibitor of cyclic nucleotide transporters)-treated cells, but not in 3-isobutyl-1-methylxanthine-treated cells, atrazine further increased cAMP levels, indicating that inhibition of PDEs accounts for accumulation of cAMP. In contrast to cAMP, atrazinemore » did not alter cGMP levels, further indicating that it inhibits cAMP-specific PDEs. Atrazine-induced changes in cAMP levels were sufficient to stimulate prolactin release in pituitary cells and androgen production in Leydig cells, indicating that it acts as an endocrine disrupter both in cells that secrete by exocytosis of prestored hormones and in cells that secrete by de novo hormone synthesis. Rolipram abolished the stimulatory effect of atrazine on cAMP release in both cell types, suggesting that it acts as an inhibitor of PDE4s, isoforms whose mRNA transcripts dominate in pituitary and Leydig cells together with mRNA for PDE8A. In contrast, immortalized lacto-somatotrophs showed low expression of these mRNA transcripts and several fold higher cAMP levels compared to normal pituitary cells, and atrazine was unable to further increase cAMP levels. These results indicate that atrazine acts as a general endocrine disrupter by inhibiting cAMP-specific PDE4s. -- Highlights: ► Atrazine stimulates cAMP accumulation in pituitary and Leydig cells. ► Atrazine also stimulates PRL and androgens secretion. ► Stimulatory effects of atrazine were abolished in cells with IBMX-inhibited PDEs. ► Atrazine specificity toward cAMP-specific PDEs was indicated by no changes in cGMP. ► Rolipram, a specific PDE4 inhibitor, also prevents stimulatory effects of atrazine. ► Atrazine acts as an endocrine disrupter by inhibiting cAMP-specific PDE4.« less

Climate science in the tropics: waves, vortices and PDEs

NASA Astrophysics Data System (ADS)

Khouider, Boualem; Majda, Andrew J.; Stechmann, Samuel N.

2013-01-01

Clouds in the tropics can organize the circulation on planetary scales and profoundly impact long range seasonal forecasting and climate on the entire globe, yet contemporary operational computer models are often deficient in representing these phenomena. On the other hand, contemporary observations reveal remarkably complex coherent waves and vortices in the tropics interacting across a bewildering range of scales from kilometers to ten thousand kilometers. This paper reviews the interdisciplinary contributions over the last decade through the modus operandi of applied mathematics to these important scientific problems. Novel physical phenomena, new multiscale equations, novel PDEs, and numerical algorithms are presented here with the goal of attracting mathematicians and physicists to this exciting research area.

Optoelectronic imaging of speckle using image processing method

NASA Astrophysics Data System (ADS)

Wang, Jinjiang; Wang, Pengfei

2018-01-01

A detailed image processing of laser speckle interferometry is proposed as an example for the course of postgraduate student. Several image processing methods were used together for dealing with optoelectronic imaging system, such as the partial differential equations (PDEs) are used to reduce the effect of noise, the thresholding segmentation also based on heat equation with PDEs, the central line is extracted based on image skeleton, and the branch is removed automatically, the phase level is calculated by spline interpolation method, and the fringe phase can be unwrapped. Finally, the imaging processing method was used to automatically measure the bubble in rubber with negative pressure which could be used in the tire detection.

Registration of cortical surfaces using sulcal landmarks for group analysis of MEG data☆

PubMed Central

Joshi, Anand A.; Shattuck, David W.; Thompson, Paul M.; Leahy, Richard M.

2010-01-01

We present a method to register individual cortical surfaces to a surface-based brain atlas or canonical template using labeled sulcal curves as landmark constraints. To map one cortex smoothly onto another, we minimize a thin-plate spline energy defined on the surface by solving the associated partial differential equations (PDEs). By using covariant derivatives in solving these PDEs, we compute the bending energy with respect to the intrinsic geometry of the 3D surface rather than evaluating it in the flattened metric of the 2D parameter space. This covariant approach greatly reduces the confounding effects of the surface parameterization on the resulting registration. PMID:20824115

Semi-analytic valuation of stock loans with finite maturity

NASA Astrophysics Data System (ADS)

Lu, Xiaoping; Putri, Endah R. M.

2015-10-01

In this paper we study stock loans of finite maturity with different dividend distributions semi-analytically using the analytical approximation method in Zhu (2006). Stock loan partial differential equations (PDEs) are established under Black-Scholes framework. Laplace transform method is used to solve the PDEs. Optimal exit price and stock loan value are obtained in Laplace space. Values in the original time space are recovered by numerical Laplace inversion. To demonstrate the efficiency and accuracy of our semi-analytic method several examples are presented, the results are compared with those calculated using existing methods. We also present a calculation of fair service fee charged by the lender for different loan parameters.

BioFVM: an efficient, parallelized diffusive transport solver for 3-D biological simulations

PubMed Central

Ghaffarizadeh, Ahmadreza; Friedman, Samuel H.; Macklin, Paul

2016-01-01

Motivation: Computational models of multicellular systems require solving systems of PDEs for release, uptake, decay and diffusion of multiple substrates in 3D, particularly when incorporating the impact of drugs, growth substrates and signaling factors on cell receptors and subcellular systems biology. Results: We introduce BioFVM, a diffusive transport solver tailored to biological problems. BioFVM can simulate release and uptake of many substrates by cell and bulk sources, diffusion and decay in large 3D domains. It has been parallelized with OpenMP, allowing efficient simulations on desktop workstations or single supercomputer nodes. The code is stable even for large time steps, with linear computational cost scalings. Solutions are first-order accurate in time and second-order accurate in space. The code can be run by itself or as part of a larger simulator. Availability and implementation: BioFVM is written in C ++ with parallelization in OpenMP. It is maintained and available for download at http://BioFVM.MathCancer.org and http://BioFVM.sf.net under the Apache License (v2.0). Contact: paul.macklin@usc.edu. Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26656933

A finite elements method to solve the Bloch–Torrey equation applied to diffusion magnetic resonance imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nguyen, Dang Van; NeuroSpin, Bat145, Point Courrier 156, CEA Saclay Center, 91191 Gif-sur-Yvette Cedex; Li, Jing-Rebecca, E-mail: jingrebecca.li@inria.fr

2014-04-15

The complex transverse water proton magnetization subject to diffusion-encoding magnetic field gradient pulses in a heterogeneous medium can be modeled by the multiple compartment Bloch–Torrey partial differential equation (PDE). In addition, steady-state Laplace PDEs can be formulated to produce the homogenized diffusion tensor that describes the diffusion characteristics of the medium in the long time limit. In spatial domains that model biological tissues at the cellular level, these two types of PDEs have to be completed with permeability conditions on the cellular interfaces. To solve these PDEs, we implemented a finite elements method that allows jumps in the solution atmore » the cell interfaces by using double nodes. Using a transformation of the Bloch–Torrey PDE we reduced oscillations in the searched-for solution and simplified the implementation of the boundary conditions. The spatial discretization was then coupled to the adaptive explicit Runge–Kutta–Chebyshev time-stepping method. Our proposed method is second order accurate in space and second order accurate in time. We implemented this method on the FEniCS C++ platform and show time and spatial convergence results. Finally, this method is applied to study some relevant questions in diffusion MRI.« less

Cloning and characterization of a cAMP-specific phosphodiesterase (TbPDE2B) from Trypanosoma brucei

PubMed Central

Rascón, Ana; Soderling, Scott H.; Schaefer, Jonathan B.; Beavo, Joseph A.

2002-01-01

Here we report the cloning, expression, and characterization of a cAMP-specific phosphodiesterase (PDE) from Trypanosoma brucei (TbPDE2B). Using a bioinformatic approach, two different expressed sequence tag clones were identified and used to isolate the complete sequence of two identical PDE genes arranged in tandem. Each gene consists of 2,793 bases that predict a protein of 930 aa with a molecular mass of 103.2 kDa. Two GAF (for cGMP binding and stimulated PDEs, Anabaena adenylyl cyclases, and Escherichia coli FhlA) domains, similar to those contained in many signaling molecules including mammalian PDE2, PDE5, PDE6, PDE10, and PDE11, were located N-terminal to a consensus PDE catalytic domain. The catalytic domain is homologous to the catalytic domain of all 11 mammalian PDEs, the Dictyostelium discoideum RegA, and a probable PDE from Caenorhabditis elegans. It is most similar to the T. brucei PDE2A (89% identity). TbPDE2B has substrate specificity for cAMP with a Km of 2.4 μM. cGMP is not hydrolyzed by TbPDE2B nor does this cyclic nucleotide modulate cAMP PDE activity. The nonselective PDE inhibitors 3-isobutyl-1-methylxanthine, papaverine and pentoxifyline are poor inhibitors of TbPDE2B. Similarly, PDE inhibitors selective for the mammalian PDE families 2, 3, 5, and 6 (erythro-9-[3-(2-hydroxynonyl)]-adenine, enoximone, zaprinast, and sildenafil) were also unable to inhibit this enzyme. However, dipyridamole was a reasonably good inhibitor of this enzyme with an IC50 of 27 μM. cAMP plays key roles in cell growth and differentiation in this parasite, and PDEs are responsible for the hydrolysis of this important second messenger. Therefore, parasite PDEs, including this one, have the potential to be attractive targets for selective drug design. PMID:11930017

Operator splitting method for simulation of dynamic flows in natural gas pipeline networks

DOE PAGES

Dyachenko, Sergey A.; Zlotnik, Anatoly; Korotkevich, Alexander O.; ...

2017-09-19

Here, we develop an operator splitting method to simulate flows of isothermal compressible natural gas over transmission pipelines. The method solves a system of nonlinear hyperbolic partial differential equations (PDEs) of hydrodynamic type for mass flow and pressure on a metric graph, where turbulent losses of momentum are modeled by phenomenological Darcy-Weisbach friction. Mass flow balance is maintained through the boundary conditions at the network nodes, where natural gas is injected or withdrawn from the system. Gas flow through the network is controlled by compressors boosting pressure at the inlet of the adjoint pipe. Our operator splitting numerical scheme ismore » unconditionally stable and it is second order accurate in space and time. The scheme is explicit, and it is formulated to work with general networks with loops. We test the scheme over range of regimes and network configurations, also comparing its performance with performance of two other state of the art implicit schemes.« less

AdS6 solutions of type II supergravity

NASA Astrophysics Data System (ADS)

Apruzzi, Fabio; Fazzi, Marco; Passias, Achilleas; Rosa, Dario; Tomasiello, Alessandro

2014-11-01

Very few AdS6 × M 4 supersymmetric solutions are known: one in massive IIA, and two IIB solutions dual to it. The IIA solution is known to be unique; in this paper, we use the pure spinor approach to give a classification for IIB supergravity. We reduce the problem to two PDEs on a two-dimensional space Σ. M 4 is then a fibration of S 2 over Σ; the metric and fluxes are completely determined in terms of the solution to the PDEs. The results seem likely to accommodate near-horizon limits of ( p, q)-fivebrane webs studied in the literature as a source of CFT5's. We also show that there are no AdS6 solutions in eleven-dimensional supergravity.

Presymplectic current and the inverse problem of the calculus of variations

NASA Astrophysics Data System (ADS)

Khavkine, Igor

2013-11-01

The inverse problem of the calculus of variations asks whether a given system of partial differential equations (PDEs) admits a variational formulation. We show that the existence of a presymplectic form in the variational bicomplex, when horizontally closed on solutions, allows us to construct a variational formulation for a subsystem of the given PDE. No constraints on the differential order or number of dependent or independent variables are assumed. The proof follows a recent observation of Bridges, Hydon, and Lawson [Math. Proc. Cambridge Philos. Soc. 148(01), 159-178 (2010)] and generalizes an older result of Henneaux [Ann. Phys. 140(1), 45-64 (1982)] from ordinary differential equations (ODEs) to PDEs. Uniqueness of the variational formulation is also discussed.

Recurrence relations for orthogonal polynomials for PDEs in polar and cylindrical geometries.

PubMed

Richardson, Megan; Lambers, James V

2016-01-01

This paper introduces two families of orthogonal polynomials on the interval (-1,1), with weight function [Formula: see text]. The first family satisfies the boundary condition [Formula: see text], and the second one satisfies the boundary conditions [Formula: see text]. These boundary conditions arise naturally from PDEs defined on a disk with Dirichlet boundary conditions and the requirement of regularity in Cartesian coordinates. The families of orthogonal polynomials are obtained by orthogonalizing short linear combinations of Legendre polynomials that satisfy the same boundary conditions. Then, the three-term recurrence relations are derived. Finally, it is shown that from these recurrence relations, one can efficiently compute the corresponding recurrences for generalized Jacobi polynomials that satisfy the same boundary conditions.

Clawpack: Building an open source ecosystem for solving hyperbolic PDEs

USGS Publications Warehouse

Iverson, Richard M.; Mandli, K.T.; Ahmadia, Aron J.; Berger, M.J.; Calhoun, Donna; George, David L.; Hadjimichael, Y.; Ketcheson, David I.; Lemoine, Grady L.; LeVeque, Randall J.

2016-01-01

Clawpack is a software package designed to solve nonlinear hyperbolic partial differential equations using high-resolution finite volume methods based on Riemann solvers and limiters. The package includes a number of variants aimed at different applications and user communities. Clawpack has been actively developed as an open source project for over 20 years. The latest major release, Clawpack 5, introduces a number of new features and changes to the code base and a new development model based on GitHub and Git submodules. This article provides a summary of the most significant changes, the rationale behind some of these changes, and a description of our current development model. Clawpack: building an open source ecosystem for solving hyperbolic PDEs.

Energy-optimal path planning in the coastal ocean

NASA Astrophysics Data System (ADS)

Subramani, Deepak N.; Haley, Patrick J.; Lermusiaux, Pierre F. J.

2017-05-01

We integrate data-driven ocean modeling with the stochastic Dynamically Orthogonal (DO) level-set optimization methodology to compute and study energy-optimal paths, speeds, and headings for ocean vehicles in the Middle-Atlantic Bight (MAB) region. We hindcast the energy-optimal paths from among exact time-optimal paths for the period 28 August 2006 to 9 September 2006. To do so, we first obtain a data-assimilative multiscale reanalysis, combining ocean observations with implicit two-way nested multiresolution primitive-equation simulations of the tidal-to-mesoscale dynamics in the region. Second, we solve the reduced-order stochastic DO level-set partial differential equations (PDEs) to compute the joint probability of minimum arrival time, vehicle-speed time series, and total energy utilized. Third, for each arrival time, we select the vehicle-speed time series that minimize the total energy utilization from the marginal probability of vehicle-speed and total energy. The corresponding energy-optimal path and headings are obtained through the exact particle-backtracking equation. Theoretically, the present methodology is PDE-based and provides fundamental energy-optimal predictions without heuristics. Computationally, it is 3-4 orders of magnitude faster than direct Monte Carlo methods. For the missions considered, we analyze the effects of the regional tidal currents, strong wind events, coastal jets, shelfbreak front, and other local circulations on the energy-optimal paths. Results showcase the opportunities for vehicles that intelligently utilize the ocean environment to minimize energy usage, rigorously integrating ocean forecasting with optimal control of autonomous vehicles.

Multi-Dimensional Quantum Effect Simulation Using a Density-Gradient Model and Script-Level Programming Techniques

NASA Technical Reports Server (NTRS)

Rafferty, Connor S.; Biegel, Bryan A.; Yu, Zhi-Ping; Ancona, Mario G.; Bude, J.; Dutton, Robert W.; Saini, Subhash (Technical Monitor)

1998-01-01

A density-gradient (DG) model is used to calculate quantum-mechanical corrections to classical carrier transport in MOS (Metal Oxide Semiconductor) inversion/accumulation layers. The model is compared to measured data and to a fully self-consistent coupled Schrodinger and Poisson equation (SCSP) solver. Good agreement is demonstrated for MOS capacitors with gate oxide as thin as 21 A. It is then applied to study carrier distribution in ultra short MOSFETs (Metal Oxide Semiconductor Field Effect Transistor) with surface roughness. This work represents the first implementation of the DG formulation on multidimensional unstructured meshes. It was enabled by a powerful scripting approach which provides an easy-to-use and flexible framework for solving the fourth-order PDEs (Partial Differential Equation) of the DG model.

Modeling of Multi-Tube Pulse Detonation Engine Operation

NASA Technical Reports Server (NTRS)

Ebrahimi, Houshang B.; Mohanraj, Rajendran; Merkle, Charles L.

2001-01-01

The present paper explores some preliminary issues concerning the operational characteristics of multiple-tube pulsed detonation engines (PDEs). The study is based on a two-dimensional analysis of the first-pulse operation of two detonation tubes exhausting through a common nozzle. Computations are first performed to assess isolated tube behavior followed by results for multi-tube flow phenomena. The computations are based on an eight-species, finite-rate transient flow-field model. The results serve as an important precursor to understanding appropriate propellant fill procedures and shock wave propagation in multi-tube, multi-dimensional simulations. Differences in behavior between single and multi-tube PDE models are discussed, The influence of multi-tube geometry and the preferred times for injecting the fresh propellant mixture during multi-tube PDE operation are studied.

Existence and Optimality Conditions for Risk-Averse PDE-Constrained Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kouri, Drew Philip; Surowiec, Thomas M.

Uncertainty is ubiquitous in virtually all engineering applications, and, for such problems, it is inadequate to simulate the underlying physics without quantifying the uncertainty in unknown or random inputs, boundary and initial conditions, and modeling assumptions. Here in this paper, we introduce a general framework for analyzing risk-averse optimization problems constrained by partial differential equations (PDEs). In particular, we postulate conditions on the random variable objective function as well as the PDE solution that guarantee existence of minimizers. Furthermore, we derive optimality conditions and apply our results to the control of an environmental contaminant. Lastly, we introduce a new riskmore » measure, called the conditional entropic risk, that fuses desirable properties from both the conditional value-at-risk and the entropic risk measures.« less

Existence and Optimality Conditions for Risk-Averse PDE-Constrained Optimization

DOE PAGES

Kouri, Drew Philip; Surowiec, Thomas M.

2018-06-05

Uncertainty is ubiquitous in virtually all engineering applications, and, for such problems, it is inadequate to simulate the underlying physics without quantifying the uncertainty in unknown or random inputs, boundary and initial conditions, and modeling assumptions. Here in this paper, we introduce a general framework for analyzing risk-averse optimization problems constrained by partial differential equations (PDEs). In particular, we postulate conditions on the random variable objective function as well as the PDE solution that guarantee existence of minimizers. Furthermore, we derive optimality conditions and apply our results to the control of an environmental contaminant. Lastly, we introduce a new riskmore » measure, called the conditional entropic risk, that fuses desirable properties from both the conditional value-at-risk and the entropic risk measures.« less

A numerical solution for a variable-order reaction-diffusion model by using fractional derivatives with non-local and non-singular kernel

NASA Astrophysics Data System (ADS)

Coronel-Escamilla, A.; Gómez-Aguilar, J. F.; Torres, L.; Escobar-Jiménez, R. F.

2018-02-01

A reaction-diffusion system can be represented by the Gray-Scott model. The reaction-diffusion dynamic is described by a pair of time and space dependent Partial Differential Equations (PDEs). In this paper, a generalization of the Gray-Scott model by using variable-order fractional differential equations is proposed. The variable-orders were set as smooth functions bounded in (0 , 1 ] and, specifically, the Liouville-Caputo and the Atangana-Baleanu-Caputo fractional derivatives were used to express the time differentiation. In order to find a numerical solution of the proposed model, the finite difference method together with the Adams method were applied. The simulations results showed the chaotic behavior of the proposed model when different variable-orders are applied.

Differential morphology and image processing.

PubMed

Maragos, P

1996-01-01

Image processing via mathematical morphology has traditionally used geometry to intuitively understand morphological signal operators and set or lattice algebra to analyze them in the space domain. We provide a unified view and analytic tools for morphological image processing that is based on ideas from differential calculus and dynamical systems. This includes ideas on using partial differential or difference equations (PDEs) to model distance propagation or nonlinear multiscale processes in images. We briefly review some nonlinear difference equations that implement discrete distance transforms and relate them to numerical solutions of the eikonal equation of optics. We also review some nonlinear PDEs that model the evolution of multiscale morphological operators and use morphological derivatives. Among the new ideas presented, we develop some general 2-D max/min-sum difference equations that model the space dynamics of 2-D morphological systems (including the distance computations) and some nonlinear signal transforms, called slope transforms, that can analyze these systems in a transform domain in ways conceptually similar to the application of Fourier transforms to linear systems. Thus, distance transforms are shown to be bandpass slope filters. We view the analysis of the multiscale morphological PDEs and of the eikonal PDE solved via weighted distance transforms as a unified area in nonlinear image processing, which we call differential morphology, and briefly discuss its potential applications to image processing and computer vision.

Universal and integrable nonlinear evolution systems of equations in 2+1 dimensions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maccari, A.

1997-08-01

Integrable systems of nonlinear partial differential equations (PDEs) are obtained from integrable equations in 2+1 dimensions, by means of a reduction method of broad applicability based on Fourier expansion and spatio{endash}temporal rescalings, which is asymptotically exact in the limit of weak nonlinearity. The integrability by the spectral transform is explicitly demonstrated, because the corresponding Lax pairs have been derived, applying the same reduction method to the Lax pair of the initial equation. These systems of nonlinear PDEs are likely to be of applicative relevance and have a {open_quotes}universal{close_quotes} character, inasmuch as they may be derived from a very large classmore » of nonlinear evolution equations with a linear dispersive part. {copyright} {ital 1997 American Institute of Physics.}« less

Algebraic Construction of Exact Difference Equations from Symmetry of Equations

NASA Astrophysics Data System (ADS)

Itoh, Toshiaki

2009-09-01

Difference equations or exact numerical integrations, which have general solutions, are treated algebraically. Eliminating the symmetries of the equation, we can construct difference equations (DCE) or numerical integrations equivalent to some ODEs or PDEs that means both have the same solution functions. When arbitrary functions are given, whether we can construct numerical integrations that have solution functions equal to given function or not are treated in this work. Nowadays, Lie's symmetries solver for ODE and PDE has been implemented in many symbolic software. Using this solver we can construct algebraic DCEs or numerical integrations which are correspond to some ODEs or PDEs. In this work, we treated exact correspondence between ODE or PDE and DCE or numerical integration with Gröbner base and Janet base from the view of Lie's symmetries.

Presymplectic current and the inverse problem of the calculus of variations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khavkine, Igor, E-mail: i.khavkine@uu.nl

2013-11-15

The inverse problem of the calculus of variations asks whether a given system of partial differential equations (PDEs) admits a variational formulation. We show that the existence of a presymplectic form in the variational bicomplex, when horizontally closed on solutions, allows us to construct a variational formulation for a subsystem of the given PDE. No constraints on the differential order or number of dependent or independent variables are assumed. The proof follows a recent observation of Bridges, Hydon, and Lawson [Math. Proc. Cambridge Philos. Soc. 148(01), 159–178 (2010)] and generalizes an older result of Henneaux [Ann. Phys. 140(1), 45–64 (1982)]more » from ordinary differential equations (ODEs) to PDEs. Uniqueness of the variational formulation is also discussed.« less

Compatible Spatial Discretizations for Partial Differential Equations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arnold, Douglas, N, ed.

From May 11--15, 2004, the Institute for Mathematics and its Applications held a hot topics workshop on Compatible Spatial Discretizations for Partial Differential Equations. The numerical solution of partial differential equations (PDE) is a fundamental task in science and engineering. The goal of the workshop was to bring together a spectrum of scientists at the forefront of the research in the numerical solution of PDEs to discuss compatible spatial discretizations. We define compatible spatial discretizations as those that inherit or mimic fundamental properties of the PDE such as topology, conservation, symmetries, and positivity structures and maximum principles. A wide varietymore » of discretization methods applied across a wide range of scientific and engineering applications have been designed to or found to inherit or mimic intrinsic spatial structure and reproduce fundamental properties of the solution of the continuous PDE model at the finite dimensional level. A profusion of such methods and concepts relevant to understanding them have been developed and explored: mixed finite element methods, mimetic finite differences, support operator methods, control volume methods, discrete differential forms, Whitney forms, conservative differencing, discrete Hodge operators, discrete Helmholtz decomposition, finite integration techniques, staggered grid and dual grid methods, etc. This workshop seeks to foster communication among the diverse groups of researchers designing, applying, and studying such methods as well as researchers involved in practical solution of large scale problems that may benefit from advancements in such discretizations; to help elucidate the relations between the different methods and concepts; and to generally advance our understanding in the area of compatible spatial discretization methods for PDE. Particular points of emphasis included: + Identification of intrinsic properties of PDE models that are critical for the fidelity of numerical simulations. + Identification and design of compatible spatial discretizations of PDEs, their classification, analysis, and relations. + Relationships between different compatible spatial discretization methods and concepts which have been developed; + Impact of compatible spatial discretizations upon physical fidelity, verification and validation of simulations, especially in large-scale, multiphysics settings. + How solvers address the demands placed upon them by compatible spatial discretizations. This report provides information about the program and abstracts of all the presentations.« less

Concurrent Engineering through Product Data Standards

DTIC Science & Technology

1991-05-01

standards, represents the power of a new industrial revolution . The role of the NIST National PDES testbed, technical leadership and a testing-based foundation for the development of STEP, is described.

Construction of energy-stable Galerkin reduced order models.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kalashnikova, Irina; Barone, Matthew Franklin; Arunajatesan, Srinivasan

2013-05-01

This report aims to unify several approaches for building stable projection-based reduced order models (ROMs). Attention is focused on linear time-invariant (LTI) systems. The model reduction procedure consists of two steps: the computation of a reduced basis, and the projection of the governing partial differential equations (PDEs) onto this reduced basis. Two kinds of reduced bases are considered: the proper orthogonal decomposition (POD) basis and the balanced truncation basis. The projection step of the model reduction can be done in two ways: via continuous projection or via discrete projection. First, an approach for building energy-stable Galerkin ROMs for linear hyperbolicmore » or incompletely parabolic systems of PDEs using continuous projection is proposed. The idea is to apply to the set of PDEs a transformation induced by the Lyapunov function for the system, and to build the ROM in the transformed variables. The resulting ROM will be energy-stable for any choice of reduced basis. It is shown that, for many PDE systems, the desired transformation is induced by a special weighted L2 inner product, termed the %E2%80%9Csymmetry inner product%E2%80%9D. Attention is then turned to building energy-stable ROMs via discrete projection. A discrete counterpart of the continuous symmetry inner product, a weighted L2 inner product termed the %E2%80%9CLyapunov inner product%E2%80%9D, is derived. The weighting matrix that defines the Lyapunov inner product can be computed in a black-box fashion for a stable LTI system arising from the discretization of a system of PDEs in space. It is shown that a ROM constructed via discrete projection using the Lyapunov inner product will be energy-stable for any choice of reduced basis. Connections between the Lyapunov inner product and the inner product induced by the balanced truncation algorithm are made. Comparisons are also made between the symmetry inner product and the Lyapunov inner product. The performance of ROMs constructed using these inner products is evaluated on several benchmark test cases.« less

Using cellular automata to simulate forest fire propagation in Portugal

NASA Astrophysics Data System (ADS)

Freire, Joana; daCamara, Carlos

2017-04-01

Wildfires in the Mediterranean region have severe damaging effects mainly due to large fire events [1, 2]. When restricting to Portugal, wildfires have burned over 1:4 million ha in the last decade. Considering the increasing tendency in the extent and severity of wildfires [1, 2], the availability of modeling tools of fire episodes is of crucial importance. Two main types of mathematical models are generally available, namely deterministic and stochastic models. Deterministic models attempt a description of fires, fuel and atmosphere as multiphase continua prescribing mass, momentum and energy conservation, which typically leads to systems of coupled PDEs to be solved numerically on a grid. Simpler descriptions, such as FARSITE, neglect the interaction with atmosphere and propagate the fire front using wave techniques. One of the most important stochastic models are Cellular Automata (CA), in which space is discretized into cells, and physical quantities take on a finite set of values at each cell. The cells evolve in discrete time according to a set of transition rules, and the states of the neighboring cells. In the present work, we implement and then improve a simple and fast CA model designed to operationally simulate wildfires in Portugal. The reference CA model chosen [3] has the advantage of having been applied successfully in other Mediterranean ecosystems, namely to historical fires in Greece. The model is defined on a square grid with propagation to 8 nearest and next-nearest neighbors, where each cell is characterized by 4 possible discrete states, corresponding to burning, not-yet burned, fuel-free and completely burned cells, with 4 possible rules of evolution which take into account fuel properties, meteorological conditions, and topography. As a CA model, it offers the possibility to run a very high number of simulations in order to verify and apply the model, and is easily modified by implementing additional variables and different rules for the evolution of the fire spread. We present and discuss the application of the CA model to the "Tavira wildfire" in which approximately 24,800ha were burned. The event took place in summer 2012, between July 18 and 21, and spread in the Tavira and São Brás de Alportel municipalities of Algarve, a province in the southern coast of Portugal. [1] DaCamara et. al. (2014), International Journal of Wildland Fire 23. [2] Amraoui et. al. (2013), Forest Ecology and Management 294. [3] Alexandridis et. al. (2008), Applied Mathematics and Computation 204.

Optimal linear-quadratic control of coupled parabolic-hyperbolic PDEs

NASA Astrophysics Data System (ADS)

Aksikas, I.; Moghadam, A. Alizadeh; Forbes, J. F.

2017-10-01

This paper focuses on the optimal control design for a system of coupled parabolic-hypebolic partial differential equations by using the infinite-dimensional state-space description and the corresponding operator Riccati equation. Some dynamical properties of the coupled system of interest are analysed to guarantee the existence and uniqueness of the solution of the linear-quadratic (LQ)-optimal control problem. A state LQ-feedback operator is computed by solving the operator Riccati equation, which is converted into a set of algebraic and differential Riccati equations, thanks to the eigenvalues and the eigenvectors of the parabolic operator. The results are applied to a non-isothermal packed-bed catalytic reactor. The LQ-optimal controller designed in the early portion of the paper is implemented for the original nonlinear model. Numerical simulations are performed to show the controller performances.

Computationally efficient statistical differential equation modeling using homogenization

USGS Publications Warehouse

Hooten, Mevin B.; Garlick, Martha J.; Powell, James A.

2013-01-01

Statistical models using partial differential equations (PDEs) to describe dynamically evolving natural systems are appearing in the scientific literature with some regularity in recent years. Often such studies seek to characterize the dynamics of temporal or spatio-temporal phenomena such as invasive species, consumer-resource interactions, community evolution, and resource selection. Specifically, in the spatial setting, data are often available at varying spatial and temporal scales. Additionally, the necessary numerical integration of a PDE may be computationally infeasible over the spatial support of interest. We present an approach to impose computationally advantageous changes of support in statistical implementations of PDE models and demonstrate its utility through simulation using a form of PDE known as “ecological diffusion.” We also apply a statistical ecological diffusion model to a data set involving the spread of mountain pine beetle (Dendroctonus ponderosae) in Idaho, USA.

Birkhoff Normal Form for Some Nonlinear PDEs

NASA Astrophysics Data System (ADS)

Bambusi, Dario

We consider the problem of extending to PDEs Birkhoff normal form theorem on Hamiltonian systems close to nonresonant elliptic equilibria. As a model problem we take the nonlinear wave equation with Dirichlet boundary conditions on [0,π] g is an analytic skewsymmetric function which vanishes for u=0 and is periodic with period 2π in the x variable. We prove, under a nonresonance condition which is fulfilled for most g's, that for any integer M there exists a canonical transformation that puts the Hamiltonian in Birkhoff normal form up to a reminder of order M. The canonical transformation is well defined in a neighbourhood of the origin of a Sobolev type phase space of sufficiently high order. Some dynamical consequences are obtained. The technique of proof is applicable to quite general semilinear equations in one space dimension.

Fast RBF OGr for solving PDEs on arbitrary surfaces

NASA Astrophysics Data System (ADS)

Piret, Cécile; Dunn, Jarrett

2016-10-01

The Radial Basis Functions Orthogonal Gradients method (RBF-OGr) was introduced in [1] to discretize differential operators defined on arbitrary manifolds defined only by a point cloud. We take advantage of the meshfree character of RBFs, which give us a high accuracy and the flexibility to represent complex geometries in any spatial dimension. A large limitation of the RBF-OGr method was its large computational complexity, which greatly restricted the size of the point cloud. In this paper, we apply the RBF-Finite Difference (RBF-FD) technique to the RBF-OGr method for building sparse differentiation matrices discretizing continuous differential operators such as the Laplace-Beltrami operator. This method can be applied to solving PDEs on arbitrary surfaces embedded in ℛ3. We illustrate the accuracy of our new method by solving the heat equation on the unit sphere.

Brain Surface Conformal Parameterization Using Riemann Surface Structure

PubMed Central

Wang, Yalin; Lui, Lok Ming; Gu, Xianfeng; Hayashi, Kiralee M.; Chan, Tony F.; Toga, Arthur W.; Thompson, Paul M.; Yau, Shing-Tung

2011-01-01

In medical imaging, parameterized 3-D surface models are useful for anatomical modeling and visualization, statistical comparisons of anatomy, and surface-based registration and signal processing. Here we introduce a parameterization method based on Riemann surface structure, which uses a special curvilinear net structure (conformal net) to partition the surface into a set of patches that can each be conformally mapped to a parallelogram. The resulting surface subdivision and the parameterizations of the components are intrinsic and stable (their solutions tend to be smooth functions and the boundary conditions of the Dirichlet problem can be enforced). Conformal parameterization also helps transform partial differential equations (PDEs) that may be defined on 3-D brain surface manifolds to modified PDEs on a two-dimensional parameter domain. Since the Jacobian matrix of a conformal parameterization is diagonal, the modified PDE on the parameter domain is readily solved. To illustrate our techniques, we computed parameterizations for several types of anatomical surfaces in 3-D magnetic resonance imaging scans of the brain, including the cerebral cortex, hippocampi, and lateral ventricles. For surfaces that are topologically homeomorphic to each other and have similar geometrical structures, we show that the parameterization results are consistent and the subdivided surfaces can be matched to each other. Finally, we present an automatic sulcal landmark location algorithm by solving PDEs on cortical surfaces. The landmark detection results are used as constraints for building conformal maps between surfaces that also match explicitly defined landmarks. PMID:17679336

Control of cardiac alternans by mechanical and electrical feedback.

PubMed

Yapari, Felicia; Deshpande, Dipen; Belhamadia, Youssef; Dubljevic, Stevan

2014-07-01

A persistent alternation in the cardiac action potential duration has been linked to the onset of ventricular arrhythmia, which may lead to sudden cardiac death. A coupling between these cardiac alternans and the intracellular calcium dynamics has also been identified in previous studies. In this paper, the system of PDEs describing the small amplitude of alternans and the alternation of peak intracellular Ca(2+) are stabilized by optimal boundary and spatially distributed actuation. A simulation study demonstrating the successful annihilation of both alternans on a one-dimensional cable of cardiac cells by utilizing the full-state feedback controller is presented. Complimentary to these studies, a three variable Nash-Panfilov model is used to investigate alternans annihilation via mechanical (or stretch) perturbations. The coupled model includes the active stress which defines the mechanical properties of the tissue and is utilized in the feedback algorithm as an independent input from the pacing based controller realization in alternans annihilation. Simulation studies of both control methods demonstrate that the proposed methods can successfully annihilate alternans in cables that are significantly longer than 1 cm, thus overcoming the limitations of earlier control efforts.

Master equations and the theory of stochastic path integrals

NASA Astrophysics Data System (ADS)

Weber, Markus F.; Frey, Erwin

2017-04-01

This review provides a pedagogic and self-contained introduction to master equations and to their representation by path integrals. Since the 1930s, master equations have served as a fundamental tool to understand the role of fluctuations in complex biological, chemical, and physical systems. Despite their simple appearance, analyses of master equations most often rely on low-noise approximations such as the Kramers-Moyal or the system size expansion, or require ad-hoc closure schemes for the derivation of low-order moment equations. We focus on numerical and analytical methods going beyond the low-noise limit and provide a unified framework for the study of master equations. After deriving the forward and backward master equations from the Chapman-Kolmogorov equation, we show how the two master equations can be cast into either of four linear partial differential equations (PDEs). Three of these PDEs are discussed in detail. The first PDE governs the time evolution of a generalized probability generating function whose basis depends on the stochastic process under consideration. Spectral methods, WKB approximations, and a variational approach have been proposed for the analysis of the PDE. The second PDE is novel and is obeyed by a distribution that is marginalized over an initial state. It proves useful for the computation of mean extinction times. The third PDE describes the time evolution of a ‘generating functional’, which generalizes the so-called Poisson representation. Subsequently, the solutions of the PDEs are expressed in terms of two path integrals: a ‘forward’ and a ‘backward’ path integral. Combined with inverse transformations, one obtains two distinct path integral representations of the conditional probability distribution solving the master equations. We exemplify both path integrals in analysing elementary chemical reactions. Moreover, we show how a well-known path integral representation of averaged observables can be recovered from them. Upon expanding the forward and the backward path integrals around stationary paths, we then discuss and extend a recent method for the computation of rare event probabilities. Besides, we also derive path integral representations for processes with continuous state spaces whose forward and backward master equations admit Kramers-Moyal expansions. A truncation of the backward expansion at the level of a diffusion approximation recovers a classic path integral representation of the (backward) Fokker-Planck equation. One can rewrite this path integral in terms of an Onsager-Machlup function and, for purely diffusive Brownian motion, it simplifies to the path integral of Wiener. To make this review accessible to a broad community, we have used the language of probability theory rather than quantum (field) theory and do not assume any knowledge of the latter. The probabilistic structures underpinning various technical concepts, such as coherent states, the Doi-shift, and normal-ordered observables, are thereby made explicit.

Master equations and the theory of stochastic path integrals.

PubMed

Weber, Markus F; Frey, Erwin

2017-04-01

This review provides a pedagogic and self-contained introduction to master equations and to their representation by path integrals. Since the 1930s, master equations have served as a fundamental tool to understand the role of fluctuations in complex biological, chemical, and physical systems. Despite their simple appearance, analyses of master equations most often rely on low-noise approximations such as the Kramers-Moyal or the system size expansion, or require ad-hoc closure schemes for the derivation of low-order moment equations. We focus on numerical and analytical methods going beyond the low-noise limit and provide a unified framework for the study of master equations. After deriving the forward and backward master equations from the Chapman-Kolmogorov equation, we show how the two master equations can be cast into either of four linear partial differential equations (PDEs). Three of these PDEs are discussed in detail. The first PDE governs the time evolution of a generalized probability generating function whose basis depends on the stochastic process under consideration. Spectral methods, WKB approximations, and a variational approach have been proposed for the analysis of the PDE. The second PDE is novel and is obeyed by a distribution that is marginalized over an initial state. It proves useful for the computation of mean extinction times. The third PDE describes the time evolution of a 'generating functional', which generalizes the so-called Poisson representation. Subsequently, the solutions of the PDEs are expressed in terms of two path integrals: a 'forward' and a 'backward' path integral. Combined with inverse transformations, one obtains two distinct path integral representations of the conditional probability distribution solving the master equations. We exemplify both path integrals in analysing elementary chemical reactions. Moreover, we show how a well-known path integral representation of averaged observables can be recovered from them. Upon expanding the forward and the backward path integrals around stationary paths, we then discuss and extend a recent method for the computation of rare event probabilities. Besides, we also derive path integral representations for processes with continuous state spaces whose forward and backward master equations admit Kramers-Moyal expansions. A truncation of the backward expansion at the level of a diffusion approximation recovers a classic path integral representation of the (backward) Fokker-Planck equation. One can rewrite this path integral in terms of an Onsager-Machlup function and, for purely diffusive Brownian motion, it simplifies to the path integral of Wiener. To make this review accessible to a broad community, we have used the language of probability theory rather than quantum (field) theory and do not assume any knowledge of the latter. The probabilistic structures underpinning various technical concepts, such as coherent states, the Doi-shift, and normal-ordered observables, are thereby made explicit.

A resilient domain decomposition polynomial chaos solver for uncertain elliptic PDEs

NASA Astrophysics Data System (ADS)

Mycek, Paul; Contreras, Andres; Le Maître, Olivier; Sargsyan, Khachik; Rizzi, Francesco; Morris, Karla; Safta, Cosmin; Debusschere, Bert; Knio, Omar

2017-07-01

A resilient method is developed for the solution of uncertain elliptic PDEs on extreme scale platforms. The method is based on a hybrid domain decomposition, polynomial chaos (PC) framework that is designed to address soft faults. Specifically, parallel and independent solves of multiple deterministic local problems are used to define PC representations of local Dirichlet boundary-to-boundary maps that are used to reconstruct the global solution. A LAD-lasso type regression is developed for this purpose. The performance of the resulting algorithm is tested on an elliptic equation with an uncertain diffusivity field. Different test cases are considered in order to analyze the impacts of correlation structure of the uncertain diffusivity field, the stochastic resolution, as well as the probability of soft faults. In particular, the computations demonstrate that, provided sufficiently many samples are generated, the method effectively overcomes the occurrence of soft faults.

Asynchronous multilevel adaptive methods for solving partial differential equations on multiprocessors - Performance results

NASA Technical Reports Server (NTRS)

Mccormick, S.; Quinlan, D.

1989-01-01

The fast adaptive composite grid method (FAC) is an algorithm that uses various levels of uniform grids (global and local) to provide adaptive resolution and fast solution of PDEs. Like all such methods, it offers parallelism by using possibly many disconnected patches per level, but is hindered by the need to handle these levels sequentially. The finest levels must therefore wait for processing to be essentially completed on all the coarser ones. A recently developed asynchronous version of FAC, called AFAC, completely eliminates this bottleneck to parallelism. This paper describes timing results for AFAC, coupled with a simple load balancing scheme, applied to the solution of elliptic PDEs on an Intel iPSC hypercube. These tests include performance of certain processes necessary in adaptive methods, including moving grids and changing refinement. A companion paper reports on numerical and analytical results for estimating convergence factors of AFAC applied to very large scale examples.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dyachenko, Sergey A.; Zlotnik, Anatoly; Korotkevich, Alexander O.

Here, we develop an operator splitting method to simulate flows of isothermal compressible natural gas over transmission pipelines. The method solves a system of nonlinear hyperbolic partial differential equations (PDEs) of hydrodynamic type for mass flow and pressure on a metric graph, where turbulent losses of momentum are modeled by phenomenological Darcy-Weisbach friction. Mass flow balance is maintained through the boundary conditions at the network nodes, where natural gas is injected or withdrawn from the system. Gas flow through the network is controlled by compressors boosting pressure at the inlet of the adjoint pipe. Our operator splitting numerical scheme ismore » unconditionally stable and it is second order accurate in space and time. The scheme is explicit, and it is formulated to work with general networks with loops. We test the scheme over range of regimes and network configurations, also comparing its performance with performance of two other state of the art implicit schemes.« less

Coupling Osmolarity Dynamics within Human Tear Film on an Eye-Shaped Domain

NASA Astrophysics Data System (ADS)

Li, Longfei; Braun, R. J.; Driscoll, T. A.; Henshaw, W. D.; Banks, J. W.; King-Smith, P. E.

2013-11-01

The concentration of ions in the tear film (osmolarity) is a key variable in understanding dry eye symptoms and disease. We derived a mathematical model that couples osmolarity (treated as a single solute) and fluid dynamics within the tear film on a 2D eye-shaped domain. The model concerns the physical effects of evaporation, surface tension, viscosity, ocular surface wettability, osmolarity, osmosis and tear fluid supply and drainage. We solved the governing system of coupled nonlinear PDEs using the Overture computational framework developed at LLNL, together with a new hybrid time stepping scheme (using variable step BDF and RKC) that was added to the framework. Results of our numerical simulations show good agreement with existing 1D models (for both tear film and osmolarity dynamics) and provide new insight about the osmolarity distribution over the ocular surface during the interblink.

Automating the solution of PDEs on the sphere and other manifolds in FEniCS 1.2

NASA Astrophysics Data System (ADS)

Rognes, M. E.; Ham, D. A.; Cotter, C. J.; McRae, A. T. T.

2013-12-01

Differential equations posed over immersed manifolds are of particular importance in studying geophysical flows; for instance, ocean and atmosphere simulations crucially rely on the capability to solve equations over the sphere. This paper presents the extension of the FEniCS software components to the automated solution of finite element formulations of differential equations defined over general, immersed manifolds. We describe the implementation and, in particular detail, how the required extensions essentially reduce to the extension of the FEniCS form compiler to cover this case. The resulting implementation has all the properties of the FEniCS pipeline and we demonstrate its flexibility by an extensive range of numerical examples covering a number of geophysical benchmark examples and test cases. The results are all in agreement with the expected values. The description here relates to DOLFIN/FEniCS 1.2.

Automating the solution of PDEs on the sphere and other manifolds in FEniCS 1.2

NASA Astrophysics Data System (ADS)

Rognes, M. E.; Ham, D. A.; Cotter, C. J.; McRae, A. T. T.

2013-07-01

Differential equations posed over immersed manifolds are of particular importance in studying geophysical flows; for instance, ocean and atmosphere simulations crucially rely on the capability to solve equations over the sphere. This paper presents the extension of the FEniCS software components to the automated solution of finite element formulations of differential equations defined over general, immersed manifolds. We describe the implementation and in particular detail how the required extensions essentially reduce to the extension of the FEniCS form compiler to cover this case. The resulting implementation has all the properties of the FEniCS pipeline and we demonstrate its flexibility by an extensive range of numerical examples covering a number of geophysical benchmark examples and test cases. The results are all in agreement with the expected values. The description here relates to DOLFIN/FEniCS 1.2.

Precision measurement of the photon detection efficiency of silicon photomultipliers using two integrating spheres.

PubMed

Yang, Seul Ki; Lee, J; Kim, Sug-Whan; Lee, Hye-Young; Jeon, Jin-A; Park, I H; Yoon, Jae-Ryong; Baek, Yang-Sik

2014-01-13

We report a new and improved photon counting method for the precision PDE measurement of SiPM detectors, utilizing two integrating spheres connected serially and calibrated reference detectors. First, using a ray tracing simulation and irradiance measurement results with a reference photodiode, we investigated irradiance characteristics of the measurement instrument, and analyzed dominating systematic uncertainties in PDE measurement. Two SiPM detectors were then used for PDE measurements between wavelengths of 368 and 850 nm and for bias voltages varying from around 70V. The resulting PDEs of the SiPMs show good agreement with those from other studies, yet with an improved accuracy of 1.57% (1σ). This was achieved by the simultaneous measurement with the NIST calibrated reference detectors, which suppressed the time dependent variation of source light. The technical details of the instrumentation, measurement results and uncertainty analysis are reported together with their implications.

Uncertainty quantification in Eulerian-Lagrangian models for particle-laden flows

NASA Astrophysics Data System (ADS)

Fountoulakis, Vasileios; Jacobs, Gustaaf; Udaykumar, Hs

2017-11-01

A common approach to ameliorate the computational burden in simulations of particle-laden flows is to use a point-particle based Eulerian-Lagrangian model, which traces individual particles in their Lagrangian frame and models particles as mathematical points. The particle motion is determined by Stokes drag law, which is empirically corrected for Reynolds number, Mach number and other parameters. The empirical corrections are subject to uncertainty. Treating them as random variables renders the coupled system of PDEs and ODEs stochastic. An approach to quantify the propagation of this parametric uncertainty to the particle solution variables is proposed. The approach is based on averaging of the governing equations and allows for estimation of the first moments of the quantities of interest. We demonstrate the feasibility of our proposed methodology of uncertainty quantification of particle-laden flows on one-dimensional linear and nonlinear Eulerian-Lagrangian systems. This research is supported by AFOSR under Grant FA9550-16-1-0008.

A Fast and Scalable Method for A-Optimal Design of Experiments for Infinite-dimensional Bayesian Nonlinear Inverse Problems with Application to Porous Medium Flow

NASA Astrophysics Data System (ADS)

Petra, N.; Alexanderian, A.; Stadler, G.; Ghattas, O.

2015-12-01

We address the problem of optimal experimental design (OED) for Bayesian nonlinear inverse problems governed by partial differential equations (PDEs). The inverse problem seeks to infer a parameter field (e.g., the log permeability field in a porous medium flow model problem) from synthetic observations at a set of sensor locations and from the governing PDEs. The goal of the OED problem is to find an optimal placement of sensors so as to minimize the uncertainty in the inferred parameter field. We formulate the OED objective function by generalizing the classical A-optimal experimental design criterion using the expected value of the trace of the posterior covariance. This expected value is computed through sample averaging over the set of likely experimental data. Due to the infinite-dimensional character of the parameter field, we seek an optimization method that solves the OED problem at a cost (measured in the number of forward PDE solves) that is independent of both the parameter and the sensor dimension. To facilitate this goal, we construct a Gaussian approximation to the posterior at the maximum a posteriori probability (MAP) point, and use the resulting covariance operator to define the OED objective function. We use randomized trace estimation to compute the trace of this covariance operator. The resulting OED problem includes as constraints the system of PDEs characterizing the MAP point, and the PDEs describing the action of the covariance (of the Gaussian approximation to the posterior) to vectors. We control the sparsity of the sensor configurations using sparsifying penalty functions, and solve the resulting penalized bilevel optimization problem via an interior-point quasi-Newton method, where gradient information is computed via adjoints. We elaborate our OED method for the problem of determining the optimal sensor configuration to best infer the log permeability field in a porous medium flow problem. Numerical results show that the number of PDE solves required for the evaluation of the OED objective function and its gradient is essentially independent of both the parameter dimension and the sensor dimension (i.e., the number of candidate sensor locations). The number of quasi-Newton iterations for computing an OED also exhibits the same dimension invariance properties.

Numerical approaches to model perturbation fire in turing pattern formations

NASA Astrophysics Data System (ADS)

Campagna, R.; Brancaccio, M.; Cuomo, S.; Mazzoleni, S.; Russo, L.; Siettos, K.; Giannino, F.

2017-11-01

Turing patterns were observed in chemical, physical and biological systems described by coupled reaction-diffusion equations. Several models have been formulated proposing the water as the causal mechanism of vegetation pattern formation, but this isn't an exhaustive hypothesis in some natural environments. An alternative explanation has been related to the plant-soil negative feedback. In Marasco et al. [1] the authors explored the hypothesis that both mechanisms contribute in the formation of regular and irregular vegetation patterns. The mathematical model consists in three partial differential equations (PDEs) that take into account for a dynamic balance between biomass, water and toxic compounds. A numerical approach is mandatory also to investigate on the predictions of this kind of models. In this paper we start from the mathematical model described in [1], set the model parameters such that the biomass reaches a stable spatial pattern (spots) and present preliminary studies about the occurrence of perturbing events, such as wildfire, that can affect the regularity of the biomass configuration.

Fracture and healing of elastomers: A phase-transition theory and numerical implementation

NASA Astrophysics Data System (ADS)

Kumar, Aditya; Francfort, Gilles A.; Lopez-Pamies, Oscar

2018-03-01

A macroscopic theory is proposed to describe, explain, and predict the nucleation and propagation of fracture and healing in elastomers undergoing arbitrarily large quasistatic deformations. The theory, which can be viewed as a natural generalization of the phase-field approximation of the variational theory of brittle fracture of Francfort and Marigo (1998) to account for physical attributes innate to elastomers that have been recently unveiled by experiments at high spatio-temporal resolution, rests on two central ideas. The first one is to view elastomers as solids capable to undergo finite elastic deformations and capable also to phase transition to another solid of vanishingly small stiffness: the forward phase transition serves to model the nucleation and propagation of fracture while the reverse phase transition models the possible healing. The second central idea is to take the phase transition to be driven by the competition between a combination of strain energy and hydrostatic stress concentration in the bulk and surface energy on the created/healed new surfaces in the elastomer. From an applications point of view, the proposed theory amounts to solving a system of two coupled and nonlinear PDEs for the deformation field and an order parameter, or phase field. A numerical scheme is presented to generate solutions for these PDEs in N = 2 and 3 space dimensions. This is based on an efficient non-conforming finite-element discretization, which remains stable for large deformations and elastomers of any compressibility, together with an implicit gradient flow solver, which is able to deal with the large changes in the deformation field that can ensue locally in space and time from the nucleation of fracture. The last part of this paper is devoted to presenting sample simulations of the so-called Gent-Park experiment. Those are confronted with recent experimental results for various types of silicone elastomers.

Bounding the electrostatic free energies associated with linear continuum models of molecular solvation.

PubMed

Bardhan, Jaydeep P; Knepley, Matthew G; Anitescu, Mihai

2009-03-14

The importance of electrostatic interactions in molecular biology has driven extensive research toward the development of accurate and efficient theoretical and computational models. Linear continuum electrostatic theory has been surprisingly successful, but the computational costs associated with solving the associated partial differential equations (PDEs) preclude the theory's use in most dynamical simulations. Modern generalized-Born models for electrostatics can reproduce PDE-based calculations to within a few percent and are extremely computationally efficient but do not always faithfully reproduce interactions between chemical groups. Recent work has shown that a boundary-integral-equation formulation of the PDE problem leads naturally to a new approach called boundary-integral-based electrostatics estimation (BIBEE) to approximate electrostatic interactions. In the present paper, we prove that the BIBEE method can be used to rigorously bound the actual continuum-theory electrostatic free energy. The bounds are validated using a set of more than 600 proteins. Detailed numerical results are presented for structures of the peptide met-enkephalin taken from a molecular-dynamics simulation. These bounds, in combination with our demonstration that the BIBEE methods accurately reproduce pairwise interactions, suggest a new approach toward building a highly accurate yet computationally tractable electrostatic model.

Bounding the electrostatic free energies associated with linear continuum models of molecular solvation

NASA Astrophysics Data System (ADS)

Bardhan, Jaydeep P.; Knepley, Matthew G.; Anitescu, Mihai

2009-03-01

The importance of electrostatic interactions in molecular biology has driven extensive research toward the development of accurate and efficient theoretical and computational models. Linear continuum electrostatic theory has been surprisingly successful, but the computational costs associated with solving the associated partial differential equations (PDEs) preclude the theory's use in most dynamical simulations. Modern generalized-Born models for electrostatics can reproduce PDE-based calculations to within a few percent and are extremely computationally efficient but do not always faithfully reproduce interactions between chemical groups. Recent work has shown that a boundary-integral-equation formulation of the PDE problem leads naturally to a new approach called boundary-integral-based electrostatics estimation (BIBEE) to approximate electrostatic interactions. In the present paper, we prove that the BIBEE method can be used to rigorously bound the actual continuum-theory electrostatic free energy. The bounds are validated using a set of more than 600 proteins. Detailed numerical results are presented for structures of the peptide met-enkephalin taken from a molecular-dynamics simulation. These bounds, in combination with our demonstration that the BIBEE methods accurately reproduce pairwise interactions, suggest a new approach toward building a highly accurate yet computationally tractable electrostatic model.

Dynamic least-squares kernel density modeling of Fokker-Planck equations with application to neural population.

PubMed

Shotorban, Babak

2010-04-01

The dynamic least-squares kernel density (LSQKD) model [C. Pantano and B. Shotorban, Phys. Rev. E 76, 066705 (2007)] is used to solve the Fokker-Planck equations. In this model the probability density function (PDF) is approximated by a linear combination of basis functions with unknown parameters whose governing equations are determined by a global least-squares approximation of the PDF in the phase space. In this work basis functions are set to be Gaussian for which the mean, variance, and covariances are governed by a set of partial differential equations (PDEs) or ordinary differential equations (ODEs) depending on what phase-space variables are approximated by Gaussian functions. Three sample problems of univariate double-well potential, bivariate bistable neurodynamical system [G. Deco and D. Martí, Phys. Rev. E 75, 031913 (2007)], and bivariate Brownian particles in a nonuniform gas are studied. The LSQKD is verified for these problems as its results are compared against the results of the method of characteristics in nondiffusive cases and the stochastic particle method in diffusive cases. For the double-well potential problem it is observed that for low to moderate diffusivity the dynamic LSQKD well predicts the stationary PDF for which there is an exact solution. A similar observation is made for the bistable neurodynamical system. In both these problems least-squares approximation is made on all phase-space variables resulting in a set of ODEs with time as the independent variable for the Gaussian function parameters. In the problem of Brownian particles in a nonuniform gas, this approximation is made only for the particle velocity variable leading to a set of PDEs with time and particle position as independent variables. Solving these PDEs, a very good performance by LSQKD is observed for a wide range of diffusivities.

A numerical technique for linear elliptic partial differential equations in polygonal domains.

PubMed

Hashemzadeh, P; Fokas, A S; Smitheman, S A

2015-03-08

Integral representations for the solution of linear elliptic partial differential equations (PDEs) can be obtained using Green's theorem. However, these representations involve both the Dirichlet and the Neumann values on the boundary, and for a well-posed boundary-value problem (BVPs) one of these functions is unknown. A new transform method for solving BVPs for linear and integrable nonlinear PDEs usually referred to as the unified transform ( or the Fokas transform ) was introduced by the second author in the late Nineties. For linear elliptic PDEs, this method can be considered as the analogue of Green's function approach but now it is formulated in the complex Fourier plane instead of the physical plane. It employs two global relations also formulated in the Fourier plane which couple the Dirichlet and the Neumann boundary values. These relations can be used to characterize the unknown boundary values in terms of the given boundary data, yielding an elegant approach for determining the Dirichlet to Neumann map . The numerical implementation of the unified transform can be considered as the counterpart in the Fourier plane of the well-known boundary integral method which is formulated in the physical plane. For this implementation, one must choose (i) a suitable basis for expanding the unknown functions and (ii) an appropriate set of complex values, which we refer to as collocation points, at which to evaluate the global relations. Here, by employing a variety of examples we present simple guidelines of how the above choices can be made. Furthermore, we provide concrete rules for choosing the collocation points so that the condition number of the matrix of the associated linear system remains low.

Fast Time and Space Parallel Algorithms for Solution of Parabolic Partial Differential Equations

NASA Technical Reports Server (NTRS)

Fijany, Amir

1993-01-01

In this paper, fast time- and Space -Parallel agorithms for solution of linear parabolic PDEs are developed. It is shown that the seemingly strictly serial iterations of the time-stepping procedure for solution of the problem can be completed decoupled.

Divergent expansion, Borel summability and three-dimensional Navier-Stokes equation.

PubMed

Costin, Ovidiu; Luo, Guo; Tanveer, Saleh

2008-08-13

We describe how the Borel summability of a divergent asymptotic expansion can be expanded and applied to nonlinear partial differential equations (PDEs). While Borel summation does not apply for non-analytic initial data, the present approach generates an integral equation (IE) applicable to much more general data. We apply these concepts to the three-dimensional Navier-Stokes (NS) system and show how the IE approach can give rise to local existence proofs. In this approach, the global existence problem in three-dimensional NS systems, for specific initial condition and viscosity, becomes a problem of asymptotics in the variable p (dual to 1/t or some positive power of 1/t). Furthermore, the errors in numerical computations in the associated IE can be controlled rigorously, which is very important for nonlinear PDEs such as NS when solutions are not known to exist globally.Moreover, computation of the solution of the IE over an interval [0,p0] provides sharper control of its p-->infinity behaviour. Preliminary numerical computations give encouraging results.

αAMG based on Weighted Matching for Systems of Elliptic PDEs Arising From Displacement and Mixed Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

D'Ambra, P.; Vassilevski, P. S.

2014-05-30

Adaptive Algebraic Multigrid (or Multilevel) Methods (αAMG) are introduced to improve robustness and efficiency of classical algebraic multigrid methods in dealing with problems where no a-priori knowledge or assumptions on the near-null kernel of the underlined matrix are available. Recently we proposed an adaptive (bootstrap) AMG method, αAMG, aimed to obtain a composite solver with a desired convergence rate. Each new multigrid component relies on a current (general) smooth vector and exploits pairwise aggregation based on weighted matching in a matrix graph to define a new automatic, general-purpose coarsening process, which we refer to as “the compatible weighted matching”. Inmore » this work, we present results that broaden the applicability of our method to different finite element discretizations of elliptic PDEs. In particular, we consider systems arising from displacement methods in linear elasticity problems and saddle-point systems that appear in the application of the mixed method to Darcy problems.« less

Phosphodiesterases regulate airway smooth muscle function in health and disease.

PubMed

Krymskaya, Vera P; Panettieri, Reynold A

2007-01-01

On the basis of structure, regulation, and kinetic properties, phosphodiesterases (PDEs) represent a superfamily of enzymes divided into 11 subfamilies that catalyze cytosolic levels of 3',5'-cyclic adenosine monophosphate (cAMP) or 3',5'-cyclic guanosine monophosphate (cGMP) to 5'-AMP or 5'-GMP, respectively. PDE4 represents the major PDE expressed in inflammatory cells as well as airway smooth muscle (ASM), and selective PDE4 inhibitors provide a broad spectrum of anti-inflammatory effects such as abrogating cytokine and chemokine release from inflammatory cells and inhibiting inflammatory cell trafficking. Due to cell- and tissue-specific gene expression and regulation, PDEs modulate unique organ-based functions. New tools or compounds that selectively inhibit PDE subfamilies and genetically engineered mice deficient in selective isoforms have greatly enhanced our understanding of PDE function in airway inflammation and resident cell function. This chapter will focus on recent advances in our understanding of the role of PDE in regulating ASM function.

Concentration-driven models revisited: towards a unified framework to model settling tanks in water resource recovery facilities.

PubMed

Torfs, Elena; Martí, M Carmen; Locatelli, Florent; Balemans, Sophie; Bürger, Raimund; Diehl, Stefan; Laurent, Julien; Vanrolleghem, Peter A; François, Pierre; Nopens, Ingmar

2017-02-01

A new perspective on the modelling of settling behaviour in water resource recovery facilities is introduced. The ultimate goal is to describe in a unified way the processes taking place both in primary settling tanks (PSTs) and secondary settling tanks (SSTs) for a more detailed operation and control. First, experimental evidence is provided, pointing out distributed particle properties (such as size, shape, density, porosity, and flocculation state) as an important common source of distributed settling behaviour in different settling unit processes and throughout different settling regimes (discrete, hindered and compression settling). Subsequently, a unified model framework that considers several particle classes is proposed in order to describe distributions in settling behaviour as well as the effect of variations in particle properties on the settling process. The result is a set of partial differential equations (PDEs) that are valid from dilute concentrations, where they correspond to discrete settling, to concentrated suspensions, where they correspond to compression settling. Consequently, these PDEs model both PSTs and SSTs.

One shot methods for optimal control of distributed parameter systems 1: Finite dimensional control

NASA Technical Reports Server (NTRS)

Taasan, Shlomo

1991-01-01

The efficient numerical treatment of optimal control problems governed by elliptic partial differential equations (PDEs) and systems of elliptic PDEs, where the control is finite dimensional is discussed. Distributed control as well as boundary control cases are discussed. The main characteristic of the new methods is that they are designed to solve the full optimization problem directly, rather than accelerating a descent method by an efficient multigrid solver for the equations involved. The methods use the adjoint state in order to achieve efficient smoother and a robust coarsening strategy. The main idea is the treatment of the control variables on appropriate scales, i.e., control variables that correspond to smooth functions are solved for on coarse grids depending on the smoothness of these functions. Solution of the control problems is achieved with the cost of solving the constraint equations about two to three times (by a multigrid solver). Numerical examples demonstrate the effectiveness of the method proposed in distributed control case, pointwise control and boundary control problems.

Homology modeling, docking studies and molecular dynamic simulations using graphical processing unit architecture to probe the type-11 phosphodiesterase catalytic site: a computational approach for the rational design of selective inhibitors.

PubMed

Cichero, Elena; D'Ursi, Pasqualina; Moscatelli, Marco; Bruno, Olga; Orro, Alessandro; Rotolo, Chiara; Milanesi, Luciano; Fossa, Paola

2013-12-01

Phosphodiesterase 11 (PDE11) is the latest isoform of the PDEs family to be identified, acting on both cyclic adenosine monophosphate and cyclic guanosine monophosphate. The initial reports of PDE11 found evidence for PDE11 expression in skeletal muscle, prostate, testis, and salivary glands; however, the tissue distribution of PDE11 still remains a topic of active study and some controversy. Given the sequence similarity between PDE11 and PDE5, several PDE5 inhibitors have been shown to cross-react with PDE11. Accordingly, many non-selective inhibitors, such as IBMX, zaprinast, sildenafil, and dipyridamole, have been documented to inhibit PDE11. Only recently, a series of dihydrothieno[3,2-d]pyrimidin-4(3H)-one derivatives proved to be selective toward the PDE11 isoform. In the absence of experimental data about PDE11 X-ray structures, we found interesting to gain a better understanding of the enzyme-inhibitor interactions using in silico simulations. In this work, we describe a computational approach based on homology modeling, docking, and molecular dynamics simulation to derive a predictive 3D model of PDE11. Using a Graphical Processing Unit architecture, it is possible to perform long simulations, find stable interactions involved in the complex, and finally to suggest guideline for the identification and synthesis of potent and selective inhibitors. © 2013 John Wiley & Sons A/S.

Towards Integrated Pulse Detonation Propulsion and MHD Power

NASA Technical Reports Server (NTRS)

Litchford, Ron J.; Thompson, Bryan R.; Lineberry, John T.

1999-01-01

The interest in pulse detonation engines (PDE) arises primarily from the advantages that accrue from the significant combustion pressure rise that is developed in the detonation process. Conventional rocket engines, for example, must obtain all of their compression from the turbopumps, while the PDE provides additional compression in the combustor. Thus PDE's are expected to achieve higher I(sub sp) than conventional rocket engines and to require smaller turbopumps. The increase in I(sub sp) and the decrease in turbopump capacity must be traded off against each other. Additional advantages include the ability to vary thrust level by adjusting the firing rate rather than throttling the flow through injector elements. The common conclusion derived from these aggregated performance attributes is that PDEs should result in engines which are smaller, lower in cost, and lighter in weight than conventional engines. Unfortunately, the analysis of PDEs is highly complex due to their unsteady operation and non-ideal processes. Although the feasibility of the basic PDE concept has been proven in several experimental and theoretical efforts, the implied performance improvements have yet to be convincingly demonstrated. Also, there are certain developmental issues affecting the practical application of pulse detonation propulsion systems which are yet to be fully resolved. Practical detonation combustion engines, for example, require a repetitive cycle of charge induction, mixing, initiation/propagation of the detonation wave, and expulsion/scavenging of the combustion product gases. Clearly, the performance and power density of such a device depends upon the maximum rate at which this cycle can be successfully implemented. In addition, the electrical energy required for direct detonation initiation can be significant, and a means for direct electrical power production is needed to achieve self-sustained engine operation. This work addresses the technological issues associated with PDEs for integrated aerospace propulsion and MHD power. An effort is made to estimate the energy requirements for direct detonation initiation of potential fuel/oxidizer mixtures and to determine the electrical power requirements. This requirement is evaluated in terms of the possibility for MHD power generation using the combustion detonation wave. Small scale laboratory experiments were conducted using stoichiometric mixtures of acetylene and oxygen with an atomized spray of cesium hydroxide dissolved in alcohol as an ionization seed in the active MHD region. Time resolved thrust and MHD power generation measurements were performed. These results show that PDEs yield higher I(sub sp) levels than a comparable rocket engine and that MHD power generation is viable candidate for achieving self-excited engine operation.

PDES Application Protocol Suite for Composites (PAS-C). Functional Needs Report for the PAS-C Program

DTIC Science & Technology

1991-09-01

103 A2352344 Layup Cover Sheets/Inspect ............................. 103 A2352345 Perform Automated Tape Laying operations...A2352345 Perform Automated Tape Laying operations/Inspect The tape is layed in 3-12 inch strips along the surface of the bond mold. The NC program is

The development of the deterministic nonlinear PDEs in particle physics to stochastic case

NASA Astrophysics Data System (ADS)

Abdelrahman, Mahmoud A. E.; Sohaly, M. A.

2018-06-01

In the present work, accuracy method called, Riccati-Bernoulli Sub-ODE technique is used for solving the deterministic and stochastic case of the Phi-4 equation and the nonlinear Foam Drainage equation. Also, the control on the randomness input is studied for stability stochastic process solution.

Ideal cycle analysis of a regenerative pulse detonation engine for power production

NASA Astrophysics Data System (ADS)

Bellini, Rafaela

Over the last few decades, considerable research has been focused on pulse detonation engines (PDEs) as a promising replacement for existing propulsion systems with potential applications in aircraft ranging from the subsonic to the lower hypersonic regimes. On the other hand, very little attention has been given to applying detonation for electric power production. One method for assessing the performance of a PDE is through thermodynamic cycle analysis. Earlier works have adopted a thermodynamic cycle for the PDE that was based on the assumption that the detonation process could be approximated by a constant volume process, called the Humphrey cycle. The Fickett-Jacob cycle, which uses the one--dimensional Chapman--Jouguet (CJ) theory of detonation, has also been used to model the PDE cycle. However, an ideal PDE cycle must include a detonation based compression and heat release processes with a finite chemical reaction rate that is accounted for in the Zeldovich -- von Neumann -- Doring model of detonation where the shock is considered a discontinuous jump and is followed by a finite exothermic reaction zone. This work presents a thermodynamic cycle analysis for an ideal PDE cycle for power production. A code has been written that takes only one input value, namely the heat of reaction of a fuel-oxidizer mixture, based on which the program computes all the points on the ZND cycle (both p--v and T--s plots), including the von Neumann spike and the CJ point along with all the non-dimensionalized state properties at each point. In addition, the program computes the points on the Humphrey and Brayton cycles for the same input value. Thus, the thermal efficiencies of the various cycles can be calculated and compared. The heat release of combustion is presented in a generic form to make the program usable with a wide variety of fuels and oxidizers and also allows for its use in a system for the real time monitoring and control of a PDE in which the heat of reaction can be obtained as a function of fuel-oxidizer ratio. The Humphrey and ZND cycles are studied in comparison with the Brayton cycle for different fuel-air mixtures such as methane, propane and hydrogen. The validity and limitations of the ZND and Humphrey cycles related to the detonation process are discussed and the criteria for the selection of the best model for the PDE cycle are explained. It is seen that the ZND cycle is a more appropriate representation of the PDE cycle. Next, the thermal and electrical power generation efficiencies for the PDE are compared with those of the deflagration based Brayton cycle. While the Brayton cycle shows an efficiency of 0 at a compressor pressure ratio of 1, the thermal efficiency for the ZND cycle starts out at 42% for hydrogen--air and then climbs to a peak of 66% at a compression ratio of 7 before falling slowly for higher compression ratios. The Brayton cycle efficiency rises above the PDEs for compression ratios above 23. This finding supports the theoretical advantage of PDEs over the gas turbines because PDEs only require a fan or only a few compressor stages, thereby eliminating the need for heavy compressor machinery, making the PDEs less complex and therefore more cost effective than other engines. Lastly, a regeneration study is presented to analyze how the use of exhaust gases can improve the performance of the system. The thermal efficiencies for the regenerative ZND cycle are compared with the efficiencies for the non--regenerative cycle. For a hydrogen--air mixture the thermal efficiency increases from 52%, for a cycle without regeneration, to 78%, for the regenerative cycle. The efficiency is compared with the Carnot efficiency of 84% which is the maximum possible theoretical efficiency of the cycle. When compared to the Brayton cycle thermal efficiencies, the regenerative cycle shows efficiencies that are always higher for the pressure ratio studied of 5 ≤ pic ≤ 25, where pi c the compressor pressure ratio of the cycle. This observation strengthens the idea of using regeneration on PDEs.

Multiscale Modeling of Angiogenesis and Predictive Capacity

NASA Astrophysics Data System (ADS)

Pillay, Samara; Byrne, Helen; Maini, Philip

Tumors induce the growth of new blood vessels from existing vasculature through angiogenesis. Using an agent-based approach, we model the behavior of individual endothelial cells during angiogenesis. We incorporate crowding effects through volume exclusion, motility of cells through biased random walks, and include birth and death-like processes. We use the transition probabilities associated with the discrete model and a discrete conservation equation for cell occupancy to determine collective cell behavior, in terms of partial differential equations (PDEs). We derive three PDE models incorporating single, multi-species and no volume exclusion. By fitting the parameters in our PDE models and other well-established continuum models to agent-based simulations during a specific time period, and then comparing the outputs from the PDE models and agent-based model at later times, we aim to determine how well the PDE models predict the future behavior of the agent-based model. We also determine whether predictions differ across PDE models and the significance of those differences. This may impact drug development strategies based on PDE models.

Dynamic Analysis of a Reaction-Diffusion Rumor Propagation Model

NASA Astrophysics Data System (ADS)

Zhao, Hongyong; Zhu, Linhe

2016-06-01

The rapid development of the Internet, especially the emergence of the social networks, leads rumor propagation into a new media era. Rumor propagation in social networks has brought new challenges to network security and social stability. This paper, based on partial differential equations (PDEs), proposes a new SIS rumor propagation model by considering the effect of the communication between the different rumor infected users on rumor propagation. The stabilities of a nonrumor equilibrium point and a rumor-spreading equilibrium point are discussed by linearization technique and the upper and lower solutions method, and the existence of a traveling wave solution is established by the cross-iteration scheme accompanied by the technique of upper and lower solutions and Schauder’s fixed point theorem. Furthermore, we add the time delay to rumor propagation and deduce the conditions of Hopf bifurcation and stability switches for the rumor-spreading equilibrium point by taking the time delay as the bifurcation parameter. Finally, numerical simulations are performed to illustrate the theoretical results.

THREE-POINT BACKWARD FINITE DIFFERENCE METHOD FOR SOLVING A SYSTEM OF MIXED HYPERBOLIC-PARABOLIC PARTIAL DIFFERENTIAL EQUATIONS. (R825549C019)

EPA Science Inventory

A three-point backward finite-difference method has been derived for a system of mixed hyperbolic_¯¯parabolic (convection_¯¯diffusion) partial differential equations (mixed PDEs). The method resorts to the three-point backward differenci...

Roles of A-Kinase Anchoring Proteins and Phosphodiesterases in the Cardiovascular System

PubMed Central

Ercu, Maria; Klussmann, Enno

2018-01-01

A-kinase anchoring proteins (AKAPs) and cyclic nucleotide phosphodiesterases (PDEs) are essential enzymes in the cyclic adenosine 3′-5′ monophosphate (cAMP) signaling cascade. They establish local cAMP pools by controlling the intensity, duration and compartmentalization of cyclic nucleotide-dependent signaling. Various members of the AKAP and PDE families are expressed in the cardiovascular system and direct important processes maintaining homeostatic functioning of the heart and vasculature, e.g., the endothelial barrier function and excitation-contraction coupling. Dysregulation of AKAP and PDE function is associated with pathophysiological conditions in the cardiovascular system including heart failure, hypertension and atherosclerosis. A number of diseases, including autosomal dominant hypertension with brachydactyly (HTNB) and type I long-QT syndrome (LQT1), result from mutations in genes encoding for distinct members of the two classes of enzymes. This review provides an overview over the AKAPs and PDEs relevant for cAMP compartmentalization in the heart and vasculature and discusses their pathophysiological role as well as highlights the potential benefits of targeting these proteins and their protein-protein interactions for the treatment of cardiovascular diseases. PMID:29461511

Assessment of the further improved (G'/G)-expansion method and the extended tanh-method in probing exact solutions of nonlinear PDEs.

PubMed

Akbar, M Ali; Ali, Norhashidah Hj Mohd; Mohyud-Din, Syed Tauseef

2013-01-01

The (G'/G)-expansion method is one of the most direct and effective method for obtaining exact solutions of nonlinear partial differential equations (PDEs). In the present article, we construct the exact traveling wave solutions of nonlinear evolution equations in mathematical physics via the (2 + 1)-dimensional breaking soliton equation by using two methods: namely, a further improved (G'/G)-expansion method, where G(ξ) satisfies the auxiliary ordinary differential equation (ODE) [G'(ξ)](2) = p G (2)(ξ) + q G (4)(ξ) + r G (6)(ξ); p, q and r are constants and the well known extended tanh-function method. We demonstrate, nevertheless some of the exact solutions bring out by these two methods are analogous, but they are not one and the same. It is worth mentioning that the first method has not been exercised anybody previously which gives further exact solutions than the second one. PACS numbers 02.30.Jr, 05.45.Yv, 02.30.Ik.

Preface of the "Symposium on Mathematical Models and Methods to investigate Heterogeneity in Cell and Cell Population Biology"

NASA Astrophysics Data System (ADS)

Clairambault, Jean

2016-06-01

This session investigates hot topics related to mathematical representations of cell and cell population dynamics in biology and medicine, in particular, but not only, with applications to cancer. Methods in mathematical modelling and analysis, and in statistical inference using single-cell and cell population data, should contribute to focus this session on heterogeneity in cell populations. Among other methods are proposed: a) Intracellular protein dynamics and gene regulatory networks using ordinary/partial/delay differential equations (ODEs, PDEs, DDEs); b) Representation of cell population dynamics using agent-based models (ABMs) and/or PDEs; c) Hybrid models and multiscale models to integrate single-cell dynamics into cell population behaviour; d) Structured cell population dynamics and asymptotic evolution w.r.t. relevant traits; e) Heterogeneity in cancer cell populations: origin, evolution, phylogeny and methods of reconstruction; f) Drug resistance as an evolutionary phenotype: predicting and overcoming it in therapeutics; g) Theoretical therapeutic optimisation of combined drug treatments in cancer cell populations and in populations of other organisms, such as bacteria.

Pressure and Thrust Measurements of a High-Frequency Pulsed-Detonation Actuator

NASA Technical Reports Server (NTRS)

Nguyen, Namtran C.; Cutler, Andrew D.

2008-01-01

This paper describes the development of a small-scale, high-frequency pulsed detonation actuator. The device utilized a fuel mixture of H2 and air, which was injected into the device at frequencies of up to 1200 Hz. Pulsed detonations were demonstrated in an 8-inch long combustion volume, at approx.600 Hz, for the lambda/4 mode. The primary objective of this experiment was to measure the generated thrust. A mean value of thrust was measured up to 6.0 lb, corresponding to specific impulse of 2611 s. This value is comparable to other H2-fueled pulsed detonation engines (PDEs) experiments. The injection and detonation frequency for this new experimental case was approx.600 Hz, and was much higher than typical PDEs, where frequencies are usually less than 100 Hz. The compact size of the model and high frequency of detonation yields a thrust-per-unit-volume of approximately 2.0 lb/cu in, and compares favorably with other experiments, which typically have thrust-per-unit-volume values of approximately 0.01 lb/cu in.

Drop Spreading with Random Viscosity

NASA Astrophysics Data System (ADS)

Xu, Feng; Jensen, Oliver

2016-11-01

Airway mucus acts as a barrier to protect the lung. However as a biological material, its physical properties are known imperfectly and can be spatially heterogeneous. In this study we assess the impact of these uncertainties on the rate of spreading of a drop (representing an inhaled aerosol) over a mucus film. We model the film as Newtonian, having a viscosity that depends linearly on the concentration of a passive solute (a crude proxy for mucin proteins). Given an initial random solute (and hence viscosity) distribution, described as a Gaussian random field with a given correlation structure, we seek to quantify the uncertainties in outcomes as the drop spreads. Using lubrication theory, we describe the spreading of the drop in terms of a system of coupled nonlinear PDEs governing the evolution of film height and the vertically-averaged solute concentration. We perform Monte Carlo simulations to predict the variability in the drop centre location and width (1D) or area (2D). We show how simulation results are well described (at much lower computational cost) by a low-order model using a weak disorder expansion. Our results show for example how variability in the drop location is a non-monotonic function of the solute correlation length increases. Engineering and Physical Sciences Research Council.

Implementing a bar-code assisted medication administration system: effects on the dispensing process and user perceptions.

PubMed

Samaranayake, N R; Cheung, S T D; Cheng, K; Lai, K; Chui, W C M; Cheung, B M Y

2014-06-01

We assessed the effects of a bar-code assisted medication administration system used without the support of computerised prescribing (stand-alone BCMA), on the dispensing process and its users. The stand-alone BCMA system was implemented in one ward of a teaching hospital. The number of dispensing steps, dispensing time and potential dispensing errors (PDEs) were directly observed one month before and eight months after the intervention. Attitudes of pharmacy and nursing staff were assessed using a questionnaire (Likert scale) and interviews. Among 1291 and 471 drug items observed before and after the introduction of the technology respectively, the number of dispensing steps increased from five to eight and time (standard deviation) to dispense one drug item by one staff personnel increased from 0.8 (0.09) to 1.5 (0.12) min. Among 2828 and 471 drug items observed before and after the intervention respectively, the number of PDEs increased significantly (P<0.001). 'Procedural errors' and 'missing drug items' were the frequently observed PDEs in the after study. 'Perceived usefulness' and 'job relevance' of the technology decreased significantly (P=0.003 and P=0.004 respectively) among users who participated in the before (N=16) and after (N=16) questionnaires surveys. Among the interviewees, pharmacy staff felt that the system offered less benefit to the dispensing process (9/16). Nursing staff perceived the system as useful in improving the accuracy of drug administration (7/10). Implementing a stand-alone BCMA system may slow down and complicate the dispensing process. Nursing staff believe the stand-alone BCMA system could improve the drug administration process but pharmacy staff believes the technology would be more helpful if supported by computerised prescribing. However, periodical assessments are needed to identify weaknesses in the process after implementation, and all users should be educated on the benefits of using this technology. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

c-di-GMP Turn-Over in Clostridium difficile Is Controlled by a Plethora of Diguanylate Cyclases and Phosphodiesterases

PubMed Central

Bordeleau, Eric; Fortier, Louis-Charles; Malouin, François; Burrus, Vincent

2011-01-01

Clostridium difficile infections have become a major healthcare concern in the last decade during which the emergence of new strains has underscored this bacterium's capacity to cause persistent epidemics. c-di-GMP is a bacterial second messenger regulating diverse bacterial phenotypes, notably motility and biofilm formation, in proteobacteria such as Vibrio cholerae, Pseudomonas aeruginosa, and Salmonella. c-di-GMP is synthesized by diguanylate cyclases (DGCs) that contain a conserved GGDEF domain. It is degraded by phosphodiesterases (PDEs) that contain either an EAL or an HD-GYP conserved domain. Very little is known about the role of c-di-GMP in the regulation of phenotypes of Gram-positive or fastidious bacteria. Herein, we exposed the main components of c-di-GMP signalling in 20 genomes of C. difficile, revealed their prevalence, and predicted their enzymatic activity. Ectopic expression of 31 of these conserved genes was carried out in V. cholerae to evaluate their effect on motility and biofilm formation, two well-characterized phenotype alterations associated with intracellular c-di-GMP variation in this bacterium. Most of the predicted DGCs and PDEs were found to be active in the V. cholerae model. Expression of truncated versions of CD0522, a protein with two GGDEF domains and one EAL domain, suggests that it can act alternatively as a DGC or a PDE. The activity of one purified DGC (CD1420) and one purified PDE (CD0757) was confirmed by in vitro enzymatic assays. GTP was shown to be important for the PDE activity of CD0757. Our results indicate that, in contrast to most Gram-positive bacteria including its closest relatives, C. difficile encodes a large assortment of functional DGCs and PDEs, revealing that c-di-GMP signalling is an important and well-conserved signal transduction system in this human pathogen. PMID:21483756

Relaxation of isolated guinea-pig trachea by apigenin, a constituent of celery, via inhibition of phosphodiesterase.

PubMed

Chen, Junn-Lain; Ko, Wun-Chang

2017-09-15

Apigenin, was reported to have vasodilatory effects by inhibiting Ca 2+ influx through both voltage- and receptor-operated calcium channels, but not by inhibiting cAMP- or cGMP-phosphodiesterases (PDEs) in rat thoracic aorta. However, apigenin was reported to inhibit PDE1, 2 and 3 in guinea-pig lung and heart. The aim of this study was to clarify that guinea-pig tracheal relaxation by apigenin whether via PDE inhibition. We isometrically recorded the tension of isolated guinea-pig tracheal segments on a polygraph. Antagonistic effects of apigenin against cumulative contractile agents or Ca 2+ induced contractions of the trachealis in normal or isotonic high-K + , Ca 2+ -free Krebs solution, respectively. Effects of apigenin (15 and 30μM) on the cumulative forskolin- and nitroprusside-induced relaxations to histamine (30μM)-induced precontraction were performed. The inhibitory effects of 30-300μM apigenin and 3-isobutyl-1-methylxanthine (IBMX, positive control) on the cAMP- and cGMP-PDEs were determined. Apigenin concentration-dependently but non-competitively inhibited cumulative histamine-, carbachol- or Ca 2+ -induced contractions in normal or in the depolarized (K + , 60mM) trachealis, suggesting that Ca 2+ influx through voltage-dependent calcium channels is inhibited. However, apigenin (15-30μM) parallel leftward shifted the concentration-response curves of forskolin and nitroprusside, and significantly increased the pD 2 values of these two cyclase activators. Both apigenin and IBMX, a reference drug, concentration (10-300μM)-dependently and significantly, but non-selectively inhibited the activities of cAMP- and cGMP-PDEs in the trachealis. In conclusion, the relaxant effect of apigenin may be due to inhibition of both enzyme activities and reduction of intracellular Ca 2+ by inhibiting Ca 2+ influx in the trachealis. Copyright © 2017 Elsevier B.V. All rights reserved.

Genome-Based Comparison of Cyclic Di-GMP Signaling in Pathogenic and Commensal Escherichia coli Strains

PubMed Central

Povolotsky, Tatyana L.

2015-01-01

ABSTRACT The ubiquitous bacterial second messenger cyclic di-GMP (c-di-GMP) has recently become prominent as a trigger for biofilm formation in many bacteria. It is generated by diguanylate cyclases (DGCs; with GGDEF domains) and degraded by specific phosphodiesterases (PDEs; containing either EAL or HD-GYP domains). Most bacterial species contain multiples of these proteins with some having specific functions that are based on direct molecular interactions in addition to their enzymatic activities. Escherichia coli K-12 laboratory strains feature 29 genes encoding GGDEF and/or EAL domains, resulting in a set of 12 DGCs, 13 PDEs, and four enzymatically inactive “degenerate” proteins that act by direct macromolecular interactions. We present here a comparative analysis of GGDEF/EAL domain-encoding genes in 61 genomes of pathogenic, commensal, and probiotic E. coli strains (including enteric pathogens such as enteroaggregative, enterohemorrhagic, enteropathogenic, enterotoxigenic, and adherent and invasive Escherichia coli and the 2011 German outbreak O104:H4 strain, as well as extraintestinal pathogenic E. coli, such as uropathogenic and meningitis-associated E. coli). We describe additional genes for two membrane-associated DGCs (DgcX and DgcY) and four PDEs (the membrane-associated PdeT, as well as the EAL domain-only proteins PdeW, PdeX, and PdeY), thus showing the pangenome of E. coli to contain at least 35 GGDEF/EAL domain proteins. A core set of only eight proteins is absolutely conserved in all 61 strains: DgcC (YaiC), DgcI (YliF), PdeB (YlaB), PdeH (YhjH), PdeK (YhjK), PdeN (Rtn), and the degenerate proteins CsrD and CdgI (YeaI). In all other GGDEF/EAL domain genes, diverse point and frameshift mutations, as well as small or large deletions, were discovered in various strains. IMPORTANCE Our analysis reveals interesting trends in pathogenic Escherichia coli that could reflect different host cell adherence mechanisms. These may either benefit from or be counteracted by the c-di-GMP-stimulated production of amyloid curli fibers and cellulose. Thus, EAEC, which adhere in a “stacked brick” biofilm mode, have a potential for high c-di-GMP accumulation due to DgcX, a strongly expressed additional DGC. In contrast, EHEC and UPEC, which use alternative adherence mechanisms, tend to have extra PDEs, suggesting that low cellular c-di-GMP levels are crucial for these strains under specific conditions. Overall, our study also indicates that GGDEF/EAL domain proteins evolve rapidly and thereby contribute to adaptation to host-specific and environmental niches of various types of E. coli. PMID:26303830

Genome-Based Comparison of Cyclic Di-GMP Signaling in Pathogenic and Commensal Escherichia coli Strains.

PubMed

Povolotsky, Tatyana L; Hengge, Regine

2016-01-01

The ubiquitous bacterial second messenger cyclic di-GMP (c-di-GMP) has recently become prominent as a trigger for biofilm formation in many bacteria. It is generated by diguanylate cyclases (DGCs; with GGDEF domains) and degraded by specific phosphodiesterases (PDEs; containing either EAL or HD-GYP domains). Most bacterial species contain multiples of these proteins with some having specific functions that are based on direct molecular interactions in addition to their enzymatic activities. Escherichia coli K-12 laboratory strains feature 29 genes encoding GGDEF and/or EAL domains, resulting in a set of 12 DGCs, 13 PDEs, and four enzymatically inactive "degenerate" proteins that act by direct macromolecular interactions. We present here a comparative analysis of GGDEF/EAL domain-encoding genes in 61 genomes of pathogenic, commensal, and probiotic E. coli strains (including enteric pathogens such as enteroaggregative, enterohemorrhagic, enteropathogenic, enterotoxigenic, and adherent and invasive Escherichia coli and the 2011 German outbreak O104:H4 strain, as well as extraintestinal pathogenic E. coli, such as uropathogenic and meningitis-associated E. coli). We describe additional genes for two membrane-associated DGCs (DgcX and DgcY) and four PDEs (the membrane-associated PdeT, as well as the EAL domain-only proteins PdeW, PdeX, and PdeY), thus showing the pangenome of E. coli to contain at least 35 GGDEF/EAL domain proteins. A core set of only eight proteins is absolutely conserved in all 61 strains: DgcC (YaiC), DgcI (YliF), PdeB (YlaB), PdeH (YhjH), PdeK (YhjK), PdeN (Rtn), and the degenerate proteins CsrD and CdgI (YeaI). In all other GGDEF/EAL domain genes, diverse point and frameshift mutations, as well as small or large deletions, were discovered in various strains. Our analysis reveals interesting trends in pathogenic Escherichia coli that could reflect different host cell adherence mechanisms. These may either benefit from or be counteracted by the c-di-GMP-stimulated production of amyloid curli fibers and cellulose. Thus, EAEC, which adhere in a "stacked brick" biofilm mode, have a potential for high c-di-GMP accumulation due to DgcX, a strongly expressed additional DGC. In contrast, EHEC and UPEC, which use alternative adherence mechanisms, tend to have extra PDEs, suggesting that low cellular c-di-GMP levels are crucial for these strains under specific conditions. Overall, our study also indicates that GGDEF/EAL domain proteins evolve rapidly and thereby contribute to adaptation to host-specific and environmental niches of various types of E. coli. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Ferrofluids: Modeling, numerical analysis, and scientific computation

NASA Astrophysics Data System (ADS)

Tomas, Ignacio

This dissertation presents some developments in the Numerical Analysis of Partial Differential Equations (PDEs) describing the behavior of ferrofluids. The most widely accepted PDE model for ferrofluids is the Micropolar model proposed by R.E. Rosensweig. The Micropolar Navier-Stokes Equations (MNSE) is a subsystem of PDEs within the Rosensweig model. Being a simplified version of the much bigger system of PDEs proposed by Rosensweig, the MNSE are a natural starting point of this thesis. The MNSE couple linear velocity u, angular velocity w, and pressure p. We propose and analyze a first-order semi-implicit fully-discrete scheme for the MNSE, which decouples the computation of the linear and angular velocities, is unconditionally stable and delivers optimal convergence rates under assumptions analogous to those used for the Navier-Stokes equations. Moving onto the much more complex Rosensweig's model, we provide a definition (approximation) for the effective magnetizing field h, and explain the assumptions behind this definition. Unlike previous definitions available in the literature, this new definition is able to accommodate the effect of external magnetic fields. Using this definition we setup the system of PDEs coupling linear velocity u, pressure p, angular velocity w, magnetization m, and magnetic potential ϕ We show that this system is energy-stable and devise a numerical scheme that mimics the same stability property. We prove that solutions of the numerical scheme always exist and, under certain simplifying assumptions, that the discrete solutions converge. A notable outcome of the analysis of the numerical scheme for the Rosensweig's model is the choice of finite element spaces that allow the construction of an energy-stable scheme. Finally, with the lessons learned from Rosensweig's model, we develop a diffuse-interface model describing the behavior of two-phase ferrofluid flows and present an energy-stable numerical scheme for this model. For a simplified version of this model and the corresponding numerical scheme we prove (in addition to stability) convergence and existence of solutions as by-product . Throughout this dissertation, we will provide numerical experiments, not only to validate mathematical results, but also to help the reader gain a qualitative understanding of the PDE models analyzed in this dissertation (the MNSE, the Rosenweig's model, and the Two-phase model). In addition, we also provide computational experiments to illustrate the potential of these simple models and their ability to capture basic phenomenological features of ferrofluids, such as the Rosensweig instability for the case of the two-phase model. In this respect, we highlight the incisive numerical experiments with the two-phase model illustrating the critical role of the demagnetizing field to reproduce physically realistic behavior of ferrofluids.

3D Orthorhombic Elastic Wave Propagation Pre-Test Simulation of SPE DAG-1 Test

NASA Astrophysics Data System (ADS)

Jensen, R. P.; Preston, L. A.

2017-12-01

A more realistic representation of many geologic media can be characterized as a dense system of vertically-aligned microfractures superimposed on a finely-layered horizontal geology found in shallow crustal rocks. This seismic anisotropy representation lends itself to being modeled as an orthorhombic elastic medium comprising three mutually orthogonal symmetry planes containing nine independent moduli. These moduli can be determined by observing (or prescribing) nine independent P-wave and S-wave phase speeds along different propagation directions. We have developed an explicit time-domain finite-difference (FD) algorithm for simulating 3D elastic wave propagation in a heterogeneous orthorhombic medium. The components of the particle velocity vector and the stress tensor are governed by a set of nine, coupled, first-order, linear, partial differential equations (PDEs) called the velocity-stress system. All time and space derivatives are discretized with centered and staggered FD operators possessing second- and fourth-order numerical accuracy, respectively. Additionally, we have implemented novel perfectly matched layer (PML) absorbing boundary conditions, specifically designed for orthorhombic media, to effectively suppress grid boundary reflections. In support of the Source Physics Experiment (SPE) Phase II, a series of underground chemical explosions at the Nevada National Security Site, the code has been used to perform pre-test estimates of the Dry Alluvium Geology - Experiment 1 (DAG-1). Based on literature searches, realistic geologic structure and values for orthorhombic P-wave and S-wave speeds have been estimated. Results and predictions from the simulations are presented.

Nonlinear Stochastic PDEs: Analysis and Approximations

DTIC Science & Technology

2016-05-23

numerical performance. Main theoretical and experimental advances include: 1.Introduction of a number of effective approaches to numerical analysis of...Stokes and Euler SPDEs, quasi -geostrophic SPDE, Ginzburg-Landau SPDE and Duffing oscillator REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT...compare their numerical performance. Main theoretical and experimental advances include: 1.Introduction of a number of effective approaches to

On a Parabolic-Elliptic system with chemotaxis and logistic type growth

NASA Astrophysics Data System (ADS)

Galakhov, Evgeny; Salieva, Olga; Tello, J. Ignacio

2016-10-01

We consider a nonlinear PDEs system of two equations of Parabolic-Elliptic type with chemotactic terms. The system models the movement of a biological population ;u; towards a higher concentration of a chemical agent ;w; in a bounded and regular domain Ω ⊂RN for arbitrary N ∈ N. After normalization, the system is as follows

77 FR 58830 - State Program Requirements; Application To Administer Partial National Pollutant Discharge...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-24

... Pollutant Discharge Elimination System (AgPDES) program pursuant to Section 402(b) of the Clean Water Act... Discharge Elimination System (NPDES) permit program under Section 402(n)(3) of the Act for all discharges of... through Friday, excluding legal holidays, at EPA Region 6, 1445 Ross Ave., Dallas, Texas 75202. A copy of...

Synchronous Parallel Emulation and Discrete Event Simulation System with Self-Contained Simulation Objects and Active Event Objects

NASA Technical Reports Server (NTRS)

Steinman, Jeffrey S. (Inventor)

1998-01-01

The present invention is embodied in a method of performing object-oriented simulation and a system having inter-connected processor nodes operating in parallel to simulate mutual interactions of a set of discrete simulation objects distributed among the nodes as a sequence of discrete events changing state variables of respective simulation objects so as to generate new event-defining messages addressed to respective ones of the nodes. The object-oriented simulation is performed at each one of the nodes by assigning passive self-contained simulation objects to each one of the nodes, responding to messages received at one node by generating corresponding active event objects having user-defined inherent capabilities and individual time stamps and corresponding to respective events affecting one of the passive self-contained simulation objects of the one node, restricting the respective passive self-contained simulation objects to only providing and receiving information from die respective active event objects, requesting information and changing variables within a passive self-contained simulation object by the active event object, and producing corresponding messages specifying events resulting therefrom by the active event objects.

Operationalizing Healthcare Simulation Psychological Safety: A Descriptive Analysis of an Intervention.

PubMed

Henricksen, Jared W; Altenburg, Catherine; Reeder, Ron W

2017-10-01

Despite efforts to prepare a psychologically safe environment, simulation participants are occasionally psychologically distressed. Instructing simulation educators about participant psychological risks and having a participant psychological distress action plan available to simulation educators may assist them as they seek to keep all participants psychologically safe. A Simulation Participant Psychological Safety Algorithm was designed to aid simulation educators as they debrief simulation participants perceived to have psychological distress and categorize these events as mild (level 1), moderate (level 2), or severe (level 3). A prebrief dedicated to creating a psychologically safe learning environment was held constant. The algorithm was used for 18 months in an active pediatric simulation program. Data collected included level of participant psychological distress as perceived and categorized by the simulation team using the algorithm, type of simulation that participants went through, who debriefed, and timing of when psychological distress was perceived to occur during the simulation session. The Kruskal-Wallis test was used to evaluate the relationship between events and simulation type, events and simulation educator team who debriefed, and timing of event during the simulation session. A total of 3900 participants went through 399 simulation sessions between August 1, 2014, and January 26, 2016. Thirty-four (<1%) simulation participants from 27 sessions (7%) were perceived to have an event. One participant was perceived to have a severe (level 3) psychological distress event. Events occurred more commonly in high-intensity simulations, with novice learners and with specific educator teams. Simulation type and simulation educator team were associated with occurrence of events (P < 0.001). There was no association between event timing and event level. Severe psychological distress as categorized by simulation personnel using the Simulation Participant Psychological Safety Algorithm is rare, with mild and moderate events being more common. The algorithm was used to teach simulation educators how to assist a participant who may be psychologically distressed and document perceived event severity.

A Simulation of Alternatives for Wholesale Inventory Replenishment

DTIC Science & Technology

2016-03-01

algorithmic details. The last method is a mixed-integer, linear optimization model. Comparative Inventory Simulation, a discrete event simulation model, is...simulation; event graphs; reorder point; fill-rate; backorder; discrete event simulation; wholesale inventory optimization model 15. NUMBER OF PAGES...model. Comparative Inventory Simulation, a discrete event simulation model, is designed to find fill rates achieved for each National Item

Long-term Stable Conservative Multiscale Methods for Vortex Flows

DTIC Science & Technology

2017-10-31

Computational and Applied Mathematics and Engeneering, Eccomas 2016 (Crete, June, 2016) - M. A. Olshanskii, Scientific computing seminar of Math ...UMass Dartmouth (October 2015) - L. Rebholz, Applied Math Seminar Talk, University of Alberta (October 2015) - L. Rebholz, Colloquium Talk, Scientific...Colloquium, (November 2016) - L. Rebholz, Joint Math Meetings 2017, Special session on recent advances in numerical analysis of PDEs, Atlanta GA

L1-Based Approximations of PDEs and Applications

DTIC Science & Technology

2012-09-05

the analysis of the Navier-Stokes equations. The early versions of artificial vis- cosities being overly dissipative, the interest for these technique ...Guermond, and B. Popov. Stability analysis of explicit en- tropy viscosity methods for non-linear scalar conservation equations. Math. Comp., 2012... methods for solv- ing mathematical models of nonlinear phenomena such as nonlinear conservation laws, surface/image/data reconstruction problems

Convergence Rates of Best N-term Galerkin Approximations for a Class of Elliptic sPDEs

DTIC Science & Technology

2010-05-31

Todor , Karhúnen-Loève Approximation of Random Fields by General- ized Fast Multipole Methods, Journal of Computational Physics 217(2006), 100–122. [19...20] R. Todor , Robust eigenvalue computation for smoothing operators, SIAM J. Num. Anal. 44(2006), 865–878. 29 [21] R. Todor and Ch. Schwab, Convergence

Characterization of Transient Plasma Ignition Flame Kernel Growth for Varying Inlet Conditions

DTIC Science & Technology

2009-12-01

unlimited 12b. DISTRIBUTION CODE A 13. ABSTRACT (maximum 200 words) Pulse detonation engines ( PDEs ) have the...Instruments NPS - Naval Postgraduate School PDC - Pulse Detonation Combustor PDE - Pulse Detonation Engine Phi The Greek letter Φ PSIA...produced little to no new chemical propulsion developments; only improvements to existing architectures. The Pulse Detonation Engine ( PDE ) is a

N Termini of apPDE4 Isoforms Are Responsible for Targeting the Isoforms to Different Cellular Membranes

ERIC Educational Resources Information Center

Jang, Deok-Jin; Park, Soo-Won; Lee, Jin-A; Lee, Changhoon; Chae, Yeon-Su; Park, Hyungju; Kim, Min-Jeong; Choi, Sun-Lim; Lee, Nuribalhae; Kim, Hyoung; Kaang, Bong-Kiun

2010-01-01

Phosphodiesterases (PDEs) are known to play a key role in the compartmentalization of cAMP signaling; however, the molecular mechanisms underlying intracellular localization of different PDE isoforms are not understood. In this study, we have found that each of the supershort, short, and long forms of apPDE4 showed distinct localization in the…

Synchronization Of Parallel Discrete Event Simulations

NASA Technical Reports Server (NTRS)

Steinman, Jeffrey S.

1992-01-01

Adaptive, parallel, discrete-event-simulation-synchronization algorithm, Breathing Time Buckets, developed in Synchronous Parallel Environment for Emulation and Discrete Event Simulation (SPEEDES) operating system. Algorithm allows parallel simulations to process events optimistically in fluctuating time cycles that naturally adapt while simulation in progress. Combines best of optimistic and conservative synchronization strategies while avoiding major disadvantages. Algorithm processes events optimistically in time cycles adapting while simulation in progress. Well suited for modeling communication networks, for large-scale war games, for simulated flights of aircraft, for simulations of computer equipment, for mathematical modeling, for interactive engineering simulations, and for depictions of flows of information.

Interface modeling in incompressible media using level sets in Escript

NASA Astrophysics Data System (ADS)

Gross, L.; Bourgouin, L.; Hale, A. J.; Mühlhaus, H.-B.

2007-08-01

We use a finite element (FEM) formulation of the level set method to model geological fluid flow problems involving interface propagation. Interface problems are ubiquitous in geophysics. Here we focus on a Rayleigh-Taylor instability, namely mantel plumes evolution, and the growth of lava domes. Both problems require the accurate description of the propagation of an interface between heavy and light materials (plume) or between high viscous lava and low viscous air (lava dome), respectively. The implementation of the models is based on Escript which is a Python module for the solution of partial differential equations (PDEs) using spatial discretization techniques such as FEM. It is designed to describe numerical models in the language of PDEs while using computational components implemented in C and C++ to achieve high performance for time-intensive, numerical calculations. A critical step in the solution geological flow problems is the solution of the velocity-pressure problem. We describe how the Escript module can be used for a high-level implementation of an efficient variant of the well-known Uzawa scheme. We begin with a brief outline of the Escript modules and then present illustrations of its usage for the numerical solutions of the problems mentioned above.

Modified method of simplest equation: Powerful tool for obtaining exact and approximate traveling-wave solutions of nonlinear PDEs

NASA Astrophysics Data System (ADS)

Vitanov, Nikolay K.

2011-03-01

We discuss the class of equations ∑i,j=0mAij(u){∂iu}/{∂ti}∂+∑k,l=0nBkl(u){∂ku}/{∂xk}∂=C(u) where Aij( u), Bkl( u) and C( u) are functions of u( x, t) as follows: (i) Aij, Bkl and C are polynomials of u; or (ii) Aij, Bkl and C can be reduced to polynomials of u by means of Taylor series for small values of u. For these two cases the above-mentioned class of equations consists of nonlinear PDEs with polynomial nonlinearities. We show that the modified method of simplest equation is powerful tool for obtaining exact traveling-wave solution of this class of equations. The balance equations for the sub-class of traveling-wave solutions of the investigated class of equations are obtained. We illustrate the method by obtaining exact traveling-wave solutions (i) of the Swift-Hohenberg equation and (ii) of the generalized Rayleigh equation for the cases when the extended tanh-equation or the equations of Bernoulli and Riccati are used as simplest equations.

PDE-based geophysical modelling using finite elements: examples from 3D resistivity and 2D magnetotellurics

NASA Astrophysics Data System (ADS)

Schaa, R.; Gross, L.; du Plessis, J.

2016-04-01

We present a general finite-element solver, escript, tailored to solve geophysical forward and inverse modeling problems in terms of partial differential equations (PDEs) with suitable boundary conditions. Escript’s abstract interface allows geoscientists to focus on solving the actual problem without being experts in numerical modeling. General-purpose finite element solvers have found wide use especially in engineering fields and find increasing application in the geophysical disciplines as these offer a single interface to tackle different geophysical problems. These solvers are useful for data interpretation and for research, but can also be a useful tool in educational settings. This paper serves as an introduction into PDE-based modeling with escript where we demonstrate in detail how escript is used to solve two different forward modeling problems from applied geophysics (3D DC resistivity and 2D magnetotellurics). Based on these two different cases, other geophysical modeling work can easily be realized. The escript package is implemented as a Python library and allows the solution of coupled, linear or non-linear, time-dependent PDEs. Parallel execution for both shared and distributed memory architectures is supported and can be used without modifications to the scripts.

Inversion of potential field data using the finite element method on parallel computers

NASA Astrophysics Data System (ADS)

Gross, L.; Altinay, C.; Shaw, S.

2015-11-01

In this paper we present a formulation of the joint inversion of potential field anomaly data as an optimization problem with partial differential equation (PDE) constraints. The problem is solved using the iterative Broyden-Fletcher-Goldfarb-Shanno (BFGS) method with the Hessian operator of the regularization and cross-gradient component of the cost function as preconditioner. We will show that each iterative step requires the solution of several PDEs namely for the potential fields, for the adjoint defects and for the application of the preconditioner. In extension to the traditional discrete formulation the BFGS method is applied to continuous descriptions of the unknown physical properties in combination with an appropriate integral form of the dot product. The PDEs can easily be solved using standard conforming finite element methods (FEMs) with potentially different resolutions. For two examples we demonstrate that the number of PDE solutions required to reach a given tolerance in the BFGS iteration is controlled by weighting regularization and cross-gradient but is independent of the resolution of PDE discretization and that as a consequence the method is weakly scalable with the number of cells on parallel computers. We also show a comparison with the UBC-GIF GRAV3D code.

Phosphodiesterase Inhibitors as a Therapeutic Approach to Neuroprotection and Repair

PubMed Central

Knott, Eric P.; Assi, Mazen; Rao, Sudheendra N. R.; Ghosh, Mousumi; Pearse, Damien D.

2017-01-01

A wide diversity of perturbations of the central nervous system (CNS) result in structural damage to the neuroarchitecture and cellular defects, which in turn are accompanied by neurological dysfunction and abortive endogenous neurorepair. Altering intracellular signaling pathways involved in inflammation and immune regulation, neural cell death, axon plasticity and remyelination has shown therapeutic benefit in experimental models of neurological disease and trauma. The second messengers, cyclic adenosine monophosphate (cyclic AMP) and cyclic guanosine monophosphate (cyclic GMP), are two such intracellular signaling targets, the elevation of which has produced beneficial cellular effects within a range of CNS pathologies. The only known negative regulators of cyclic nucleotides are a family of enzymes called phosphodiesterases (PDEs) that hydrolyze cyclic nucleotides into adenosine monophosphate (AMP) or guanylate monophosphate (GMP). Herein, we discuss the structure and physiological function as well as the roles PDEs play in pathological processes of the diseased or injured CNS. Further we review the approaches that have been employed therapeutically in experimental paradigms to block PDE expression or activity and in turn elevate cyclic nucleotide levels to mediate neuroprotection or neurorepair as well as discuss both the translational pathway and current limitations in moving new PDE-targeted therapies to the clinic. PMID:28338622

Metabolic benefits of inhibiting cAMP-PDEs with resveratrol.

PubMed

Chung, Jay H

2012-10-01

Calorie restriction (CR) extends lifespan in species ranging from yeast to mammals. There is evidence that CR also protects against aging-related diseases in non-human primates. This has led to an intense interest in the development of CR-mimetics to harness the beneficial effects of CR to treat aging-related diseases. One CR-mimetic that has received a great deal of attention is resveratrol. Resveratrol extends the lifespan of obese mice and protects against obesity-related diseases such as type 2 diabetes. The specific mechanism of resveratrol action has been difficult to elucidate because resveratrol has a promiscuous target profile. A recent finding indicates that the metabolic effects of resveratrol may result from competitive inhibition of cAMP-degrading phosphodiesterases (PDEs), which increases cAMP levels. The cAMP-dependent pathways activate AMP-activated protein kinase (AMPK), which is essential for the metabolic effects of resveratrol. Inhibiting PDE4 with rolipram reproduces all of the metabolic benefits of resveratrol, including protection against diet-induced obesity and an increase in mitochondrial function, physical stamina and glucose tolerance in mice. This discovery suggests that PDE inhibitors may be useful for treating metabolic diseases associated with aging.

Correspondence between discrete and continuous models of excitable media: trigger waves

NASA Technical Reports Server (NTRS)

Chernyak, Y. B.; Feldman, A. B.; Cohen, R. J.

1997-01-01

We present a theoretical framework for relating continuous partial differential equation (PDE) models of excitable media to discrete cellular automata (CA) models on a randomized lattice. These relations establish a quantitative link between the CA model and the specific physical system under study. We derive expressions for the CA model's plane wave speed, critical curvature, and effective diffusion constant in terms of the model's internal parameters (the interaction radius, excitation threshold, and time step). We then equate these expressions to the corresponding quantities obtained from solution of the PDEs (for a fixed excitability). This yields a set of coupled equations with a unique solution for the required CA parameter values. Here we restrict our analysis to "trigger" wave solutions obtained in the limiting case of a two-dimensional excitable medium with no recovery processes. We tested the correspondence between our CA model and two PDE models (the FitzHugh-Nagumo medium and a medium with a "sawtooth" nonlinear reaction source) and found good agreement with the numerical solutions of the PDEs. Our results suggest that the behavior of trigger waves is actually controlled by a small number of parameters.

Fast Maximum Entropy Moment Closure Approach to Solving the Boltzmann Equation

NASA Astrophysics Data System (ADS)

Summy, Dustin; Pullin, Dale

2015-11-01

We describe a method for a moment-based solution of the Boltzmann Equation (BE). This is applicable to an arbitrary set of velocity moments whose transport is governed by partial-differential equations (PDEs) derived from the BE. The equations are unclosed, containing both higher-order moments and molecular-collision terms. These are evaluated using a maximum-entropy reconstruction of the velocity distribution function f (c , x , t) , from the known moments, within a finite-box domain of single-particle velocity (c) space. Use of a finite-domain alleviates known problems (Junk and Unterreiter, Continuum Mech. Thermodyn., 2002) concerning existence and uniqueness of the reconstruction. Unclosed moments are evaluated with quadrature while collision terms are calculated using any desired method. This allows integration of the moment PDEs in time. The high computational cost of the general method is greatly reduced by careful choice of the velocity moments, allowing the necessary integrals to be reduced from three- to one-dimensional in the case of strictly 1D flows. A method to extend this enhancement to fully 3D flows is discussed. Comparison with relaxation and shock-wave problems using the DSMC method will be presented. Partially supported by NSF grant DMS-1418903.

Modulation of kinetic Alfvén waves in an intermediate low-beta magnetoplasma

NASA Astrophysics Data System (ADS)

Chatterjee, Debjani; Misra, A. P.

2018-05-01

We study the amplitude modulation of nonlinear kinetic Alfvén waves (KAWs) in an intermediate low-beta magnetoplasma. Starting from a set of fluid equations coupled to the Maxwell's equations, we derive a coupled set of nonlinear partial differential equations (PDEs) which govern the evolution of KAW envelopes in the plasma. The modulational instability (MI) of such KAW envelopes is then studied by a nonlinear Schrödinger equation derived from the coupled PDEs. It is shown that the KAWs can evolve into bright envelope solitons or can undergo damping depending on whether the characteristic ratio ( α ) of the Alfvén to ion-acoustic speeds remains above or below a critical value. The parameter α is also found to shift the MI domains around the k x k z plane, where k x ( k z ) is the KAW number perpendicular (parallel) to the external magnetic field. The growth rate of MI, as well as the frequency shift and the energy transfer rate, are obtained and analyzed. The results can be useful for understanding the existence and formation of bright and dark envelope solitons, or damping of KAW envelopes in space plasmas, e.g., interplanetary space, solar winds, etc.

Infiltration on sloping terrain and its role on runoff generation and slope stability

NASA Astrophysics Data System (ADS)

Loáiciga, Hugo A.; Johnson, J. Michael

2018-06-01

A modified Green-and-Ampt model is formulated to quantify infiltration on sloping terrain underlain by homogeneous soil wetted by surficial water application. This paper's theory for quantifying infiltration relies on the mathematical statement of the coupled partial differential equations (pdes) governing infiltration and runoff. These pdes are solved by employing an explicit finite-difference numerical method that yields the infiltration, the infiltration rate, the depth to the wetting front, the rate of runoff, and the depth of runoff everywhere on the slope during external wetting. Data inputs consist of a water application rate or the rainfall hyetograph of a storm of arbitrary duration, soil hydraulic characteristics and antecedent moisture, and the slope's hydraulic and geometric characteristics. The presented theory predicts the effect an advancing wetting front has on slope stability with respect to translational sliding. This paper's theory also develops the 1D pde governing suspended sediment transport and slope degradation caused by runoff influenced by infiltration. Three examples illustrate the application of the developed theory to calculate infiltration and runoff on a slope and their role on the stability of cohesive and cohesionless soils forming sloping terrain.

Numerical Coupling and Simulation of Point-Mass System with the Turbulent Fluid Flow

NASA Astrophysics Data System (ADS)

Gao, Zheng

A computational framework that combines the Eulerian description of the turbulence field with a Lagrangian point-mass ensemble is proposed in this dissertation. Depending on the Reynolds number, the turbulence field is simulated using Direct Numerical Simulation (DNS) or eddy viscosity model. In the meanwhile, the particle system, such as spring-mass system and cloud droplets, are modeled using the ordinary differential system, which is stiff and hence poses a challenge to the stability of the entire system. This computational framework is applied to the numerical study of parachute deceleration and cloud microphysics. These two distinct problems can be uniformly modeled with Partial Differential Equations (PDEs) and Ordinary Differential Equations (ODEs), and numerically solved in the same framework. For the parachute simulation, a novel porosity model is proposed to simulate the porous effects of the parachute canopy. This model is easy to implement with the projection method and is able to reproduce Darcy's law observed in the experiment. Moreover, the impacts of using different versions of k-epsilon turbulence model in the parachute simulation have been investigated and conclude that the standard and Re-Normalisation Group (RNG) model may overestimate the turbulence effects when Reynolds number is small while the Realizable model has a consistent performance with both large and small Reynolds number. For another application, cloud microphysics, the cloud entrainment-mixing problem is studied in the same numerical framework. Three sets of DNS are carried out with both decaying and forced turbulence. The numerical result suggests a new way parameterize the cloud mixing degree using the dynamical measures. The numerical experiments also verify the negative relationship between the droplets number concentration and the vorticity field. The results imply that the gravity has fewer impacts on the forced turbulence than the decaying turbulence. In summary, the proposed framework can be used to solve a physics problem that involves turbulence field and point-mass system, and therefore has a broad application.

Local polynomial chaos expansion for linear differential equations with high dimensional random inputs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yi; Jakeman, John; Gittelson, Claude

2015-01-08

In this paper we present a localized polynomial chaos expansion for partial differential equations (PDE) with random inputs. In particular, we focus on time independent linear stochastic problems with high dimensional random inputs, where the traditional polynomial chaos methods, and most of the existing methods, incur prohibitively high simulation cost. Furthermore, the local polynomial chaos method employs a domain decomposition technique to approximate the stochastic solution locally. In each subdomain, a subdomain problem is solved independently and, more importantly, in a much lower dimensional random space. In a postprocesing stage, accurate samples of the original stochastic problems are obtained frommore » the samples of the local solutions by enforcing the correct stochastic structure of the random inputs and the coupling conditions at the interfaces of the subdomains. Overall, the method is able to solve stochastic PDEs in very large dimensions by solving a collection of low dimensional local problems and can be highly efficient. In our paper we present the general mathematical framework of the methodology and use numerical examples to demonstrate the properties of the method.« less

New preconditioning strategy for Jacobian-free solvers for variably saturated flows with Richards’ equation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lipnikov, Konstantin; Moulton, David; Svyatskiy, Daniil

2016-04-29

We develop a new approach for solving the nonlinear Richards’ equation arising in variably saturated flow modeling. The growing complexity of geometric models for simulation of subsurface flows leads to the necessity of using unstructured meshes and advanced discretization methods. Typically, a numerical solution is obtained by first discretizing PDEs and then solving the resulting system of nonlinear discrete equations with a Newton-Raphson-type method. Efficiency and robustness of the existing solvers rely on many factors, including an empiric quality control of intermediate iterates, complexity of the employed discretization method and a customized preconditioner. We propose and analyze a new preconditioningmore » strategy that is based on a stable discretization of the continuum Jacobian. We will show with numerical experiments for challenging problems in subsurface hydrology that this new preconditioner improves convergence of the existing Jacobian-free solvers 3-20 times. Furthermore, we show that the Picard method with this preconditioner becomes a more efficient nonlinear solver than a few widely used Jacobian-free solvers.« less

Spectral Upscaling for Graph Laplacian Problems with Application to Reservoir Simulation

DOE PAGES

Barker, Andrew T.; Lee, Chak S.; Vassilevski, Panayot S.

2017-10-26

Here, we consider coarsening procedures for graph Laplacian problems written in a mixed saddle-point form. In that form, in addition to the original (vertex) degrees of freedom (dofs), we also have edge degrees of freedom. We extend previously developed aggregation-based coarsening procedures applied to both sets of dofs to now allow more than one coarse vertex dof per aggregate. Those dofs are selected as certain eigenvectors of local graph Laplacians associated with each aggregate. Additionally, we coarsen the edge dofs by using traces of the discrete gradients of the already constructed coarse vertex dofs. These traces are defined on themore » interface edges that connect any two adjacent aggregates. The overall procedure is a modification of the spectral upscaling procedure developed in for the mixed finite element discretization of diffusion type PDEs which has the important property of maintaining inf-sup stability on coarse levels and having provable approximation properties. We consider applications to partitioning a general graph and to a finite volume discretization interpreted as a graph Laplacian, developing consistent and accurate coarse-scale models of a fine-scale problem.« less

Output Feedback-Based Boundary Control of Uncertain Coupled Semilinear Parabolic PDE Using Neurodynamic Programming.

PubMed

Talaei, Behzad; Jagannathan, Sarangapani; Singler, John

2018-04-01

In this paper, neurodynamic programming-based output feedback boundary control of distributed parameter systems governed by uncertain coupled semilinear parabolic partial differential equations (PDEs) under Neumann or Dirichlet boundary control conditions is introduced. First, Hamilton-Jacobi-Bellman (HJB) equation is formulated in the original PDE domain and the optimal control policy is derived using the value functional as the solution of the HJB equation. Subsequently, a novel observer is developed to estimate the system states given the uncertain nonlinearity in PDE dynamics and measured outputs. Consequently, the suboptimal boundary control policy is obtained by forward-in-time estimation of the value functional using a neural network (NN)-based online approximator and estimated state vector obtained from the NN observer. Novel adaptive tuning laws in continuous time are proposed for learning the value functional online to satisfy the HJB equation along system trajectories while ensuring the closed-loop stability. Local uniformly ultimate boundedness of the closed-loop system is verified by using Lyapunov theory. The performance of the proposed controller is verified via simulation on an unstable coupled diffusion reaction process.

Numerical modeling of the debris flows runout

NASA Astrophysics Data System (ADS)

Federico, Francesco; Cesali, Chiara

2017-06-01

Rapid debris flows are identified among the most dangerous of all landslides. Due to their destructive potential, the runout length has to be predicted to define the hazardous areas and design safeguarding measures. To this purpose, a continuum model to predict the debris flows mobility is developed. It is based on the well known depth-integrated avalanche model proposed by Savage and Hutter (S&H model) to simulate the dry granular materials flows. Conservation of mass and momentum equations, describing the evolving geometry and the depth averaged velocity distribution, are re-written taking into account the effects of the interstitial pressures and the possible variation of mass along the motion due to erosion/deposition processes. Furthermore, the mechanical behaviour of the debris flow is described by a recently developed rheological law, which allows to take into account the dissipative effects of the grain inelastic collisions and friction, simultaneously acting within a `shear layer', typically at the base of the debris flows. The governing PDEs are solved by applying the finite difference method. The analysis of a documented case is finally carried out.

State-of-charge estimation in lithium-ion batteries: A particle filter approach

NASA Astrophysics Data System (ADS)

Tulsyan, Aditya; Tsai, Yiting; Gopaluni, R. Bhushan; Braatz, Richard D.

2016-11-01

The dynamics of lithium-ion batteries are complex and are often approximated by models consisting of partial differential equations (PDEs) relating the internal ionic concentrations and potentials. The Pseudo two-dimensional model (P2D) is one model that performs sufficiently accurately under various operating conditions and battery chemistries. Despite its widespread use for prediction, this model is too complex for standard estimation and control applications. This article presents an original algorithm for state-of-charge estimation using the P2D model. Partial differential equations are discretized using implicit stable algorithms and reformulated into a nonlinear state-space model. This discrete, high-dimensional model (consisting of tens to hundreds of states) contains implicit, nonlinear algebraic equations. The uncertainty in the model is characterized by additive Gaussian noise. By exploiting the special structure of the pseudo two-dimensional model, a novel particle filter algorithm that sweeps in time and spatial coordinates independently is developed. This algorithm circumvents the degeneracy problems associated with high-dimensional state estimation and avoids the repetitive solution of implicit equations by defining a 'tether' particle. The approach is illustrated through extensive simulations.

Minimizing finite-volume discretization errors on polyhedral meshes

NASA Astrophysics Data System (ADS)

Mouly, Quentin; Evrard, Fabien; van Wachem, Berend; Denner, Fabian

2017-11-01

Tetrahedral meshes are widely used in CFD to simulate flows in and around complex geometries, as automatic generation tools now allow tetrahedral meshes to represent arbitrary domains in a relatively accessible manner. Polyhedral meshes, however, are an increasingly popular alternative. While tetrahedron have at most four neighbours, the higher number of neighbours per polyhedral cell leads to a more accurate evaluation of gradients, essential for the numerical resolution of PDEs. The use of polyhedral meshes, nonetheless, introduces discretization errors for finite-volume methods: skewness and non-orthogonality, which occur with all sorts of unstructured meshes, as well as errors due to non-planar faces, specific to polygonal faces with more than three vertices. Indeed, polyhedral mesh generation algorithms cannot, in general, guarantee to produce meshes free of non-planar faces. The presented work focuses on the quantification and optimization of discretization errors on polyhedral meshes in the context of finite-volume methods. A quasi-Newton method is employed to optimize the relevant mesh quality measures. Various meshes are optimized and CFD results of cases with known solutions are presented to assess the improvements the optimization approach can provide.

Koopman decomposition of Burgers' equation: What can we learn?

NASA Astrophysics Data System (ADS)

Page, Jacob; Kerswell, Rich

2017-11-01

Burgers' equation is a well known 1D model of the Navier-Stokes equations and admits a selection of equilibria and travelling wave solutions. A series of Burgers' trajectories are examined with Dynamic Mode Decomposition (DMD) to probe the capability of the method to extract coherent structures from ``run-down'' simulations. The performance of the method depends critically on the choice of observable. We use the Cole-Hopf transformation to derive an observable which has linear, autonomous dynamics and for which the DMD modes overlap exactly with Koopman modes. This observable can accurately predict the flow evolution beyond the time window of the data used in the DMD, and in that sense outperforms other observables motivated by the nonlinearity in the governing equation. The linearizing observable also allows us to make informed decisions about often ambiguous choices in nonlinear problems, such as rank truncation and snapshot spacing. A number of rules of thumb for connecting DMD with the Koopman operator for nonlinear PDEs are distilled from the results. Related problems in low Reynolds number fluid turbulence are also discussed.

Parallel adaptive wavelet collocation method for PDEs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nejadmalayeri, Alireza, E-mail: Alireza.Nejadmalayeri@gmail.com; Vezolainen, Alexei, E-mail: Alexei.Vezolainen@Colorado.edu; Brown-Dymkoski, Eric, E-mail: Eric.Browndymkoski@Colorado.edu

2015-10-01

A parallel adaptive wavelet collocation method for solving a large class of Partial Differential Equations is presented. The parallelization is achieved by developing an asynchronous parallel wavelet transform, which allows one to perform parallel wavelet transform and derivative calculations with only one data synchronization at the highest level of resolution. The data are stored using tree-like structure with tree roots starting at a priori defined level of resolution. Both static and dynamic domain partitioning approaches are developed. For the dynamic domain partitioning, trees are considered to be the minimum quanta of data to be migrated between the processes. This allowsmore » fully automated and efficient handling of non-simply connected partitioning of a computational domain. Dynamic load balancing is achieved via domain repartitioning during the grid adaptation step and reassigning trees to the appropriate processes to ensure approximately the same number of grid points on each process. The parallel efficiency of the approach is discussed based on parallel adaptive wavelet-based Coherent Vortex Simulations of homogeneous turbulence with linear forcing at effective non-adaptive resolutions up to 2048{sup 3} using as many as 2048 CPU cores.« less

Dual Dynamically Orthogonal approximation of incompressible Navier Stokes equations with random boundary conditions

NASA Astrophysics Data System (ADS)

Musharbash, Eleonora; Nobile, Fabio

2018-02-01

In this paper we propose a method for the strong imposition of random Dirichlet boundary conditions in the Dynamical Low Rank (DLR) approximation of parabolic PDEs and, in particular, incompressible Navier Stokes equations. We show that the DLR variational principle can be set in the constrained manifold of all S rank random fields with a prescribed value on the boundary, expressed in low rank format, with rank smaller then S. We characterize the tangent space to the constrained manifold by means of a Dual Dynamically Orthogonal (Dual DO) formulation, in which the stochastic modes are kept orthonormal and the deterministic modes satisfy suitable boundary conditions, consistent with the original problem. The Dual DO formulation is also convenient to include the incompressibility constraint, when dealing with incompressible Navier Stokes equations. We show the performance of the proposed Dual DO approximation on two numerical test cases: the classical benchmark of a laminar flow around a cylinder with random inflow velocity, and a biomedical application for simulating blood flow in realistic carotid artery reconstructed from MRI data with random inflow conditions coming from Doppler measurements.

Event-driven simulation in SELMON: An overview of EDSE

NASA Technical Reports Server (NTRS)

Rouquette, Nicolas F.; Chien, Steve A.; Charest, Leonard, Jr.

1992-01-01

EDSE (event-driven simulation engine), a model-based event-driven simulator implemented for SELMON, a tool for sensor selection and anomaly detection in real-time monitoring is described. The simulator is used in conjunction with a causal model to predict future behavior of the model from observed data. The behavior of the causal model is interpreted as equivalent to the behavior of the physical system being modeled. An overview of the functionality of the simulator and the model-based event-driven simulation paradigm on which it is based is provided. Included are high-level descriptions of the following key properties: event consumption and event creation, iterative simulation, synchronization and filtering of monitoring data from the physical system. Finally, how EDSE stands with respect to the relevant open issues of discrete-event and model-based simulation is discussed.

Switching waves dynamics in optical bistable cavity-free system at femtosecond laser pulse propagation in semiconductor under light diffraction

NASA Astrophysics Data System (ADS)

Trofimov, Vyacheslav A.; Egorenkov, Vladimir A.; Loginova, Maria M.

2018-02-01

We consider a propagation of laser pulse in a semiconductor under the conditions of an occurrence of optical bistability, which appears due to a nonlinear absorption of the semiconductor. As a result, the domains of high concentration of free charged particles (electrons and ionized donors) occur if an intensity of the incident optical pulse is greater than certain intensity. As it is well-known, that an optical beam must undergo a diffraction on (or reflection from) the domains boundaries. Usually, the beam diffraction along a coordinate of the optical pulse propagation does not take into account by using the slowly varying envelope approximation for the laser pulse interaction with optical bistable element. Therefore, a reflection of the beam from the domains with abrupt boundary does not take into account under computer simulation of the laser pulse propagation. However, the optical beams, reflected from nonhomogeneities caused by the domains of high concentration of free-charged particles, can essentially influence on a formation of switching waves in a semiconductor. We illustrate this statement by computer simulation results provided on the base of nonlinear Schrödinger equation and a set of PDEs, which describe an evolution of the semiconductor characteristics (concentrations of free-charged particles and potential of an electric field strength), and taking into account the longitudinal and transverse diffraction effects.

An assessment of CFD-based wall heat transfer models in piston engines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sircar, Arpan; Paul, Chandan; Ferreyro-Fernandez, Sebastian

The lack of accurate submodels for in-cylinder heat transfer has been identified as a key shortcoming in developing truly predictive, physics-based computational fluid dynamics (CFD) models that can be used to develop combustion systems for advanced high-efficiency, low-emissions engines. Only recently have experimental methods become available that enable accurate near-wall measurements to enhance simulation capability via advancing models. Initial results show crank-angle dependent discrepancies with respect to previously used boundary-layer models of up to 100%. However, available experimental data is quite sparse (only few data points on engine walls) and limited (available measurements are those of heat flux only). Predictivemore » submodels are needed for medium-resolution ("engineering") LES and for unsteady Reynolds-averaged simulations (URANS). Recently, some research groups have performed DNS studies on engine-relevant conditions using simple geometries. These provide very useful data for benchmarking wall heat transfer models under such conditions. Further, a number of new and more sophisticated models have also become available in the literature which account for these engine-like conditions. Some of these have been incorporated while others of a more complex nature, which include solving additional partial differential equations (PDEs) within the thin boundary layer near the wall, are underway. These models will then be tested against the available DNS/experimental data in both SI (spark-ignition) and CI (compression-ignition) engines.« less

Synchronous parallel system for emulation and discrete event simulation

NASA Technical Reports Server (NTRS)

Steinman, Jeffrey S. (Inventor)

1992-01-01

A synchronous parallel system for emulation and discrete event simulation having parallel nodes responds to received messages at each node by generating event objects having individual time stamps, stores only the changes to state variables of the simulation object attributable to the event object, and produces corresponding messages. The system refrains from transmitting the messages and changing the state variables while it determines whether the changes are superseded, and then stores the unchanged state variables in the event object for later restoral to the simulation object if called for. This determination preferably includes sensing the time stamp of each new event object and determining which new event object has the earliest time stamp as the local event horizon, determining the earliest local event horizon of the nodes as the global event horizon, and ignoring the events whose time stamps are less than the global event horizon. Host processing between the system and external terminals enables such a terminal to query, monitor, command or participate with a simulation object during the simulation process.

Synchronous Parallel System for Emulation and Discrete Event Simulation

NASA Technical Reports Server (NTRS)

Steinman, Jeffrey S. (Inventor)

2001-01-01

A synchronous parallel system for emulation and discrete event simulation having parallel nodes responds to received messages at each node by generating event objects having individual time stamps, stores only the changes to the state variables of the simulation object attributable to the event object and produces corresponding messages. The system refrains from transmitting the messages and changing the state variables while it determines whether the changes are superseded, and then stores the unchanged state variables in the event object for later restoral to the simulation object if called for. This determination preferably includes sensing the time stamp of each new event object and determining which new event object has the earliest time stamp as the local event horizon, determining the earliest local event horizon of the nodes as the global event horizon, and ignoring events whose time stamps are less than the global event horizon. Host processing between the system and external terminals enables such a terminal to query, monitor, command or participate with a simulation object during the simulation process.

Creating Weather System Ensembles Through Synergistic Process Modeling and Machine Learning

NASA Astrophysics Data System (ADS)

Chen, B.; Posselt, D. J.; Nguyen, H.; Wu, L.; Su, H.; Braverman, A. J.

2017-12-01

Earth's weather and climate are sensitive to a variety of control factors (e.g., initial state, forcing functions, etc). Characterizing the response of the atmosphere to a change in initial conditions or model forcing is critical for weather forecasting (ensemble prediction) and climate change assessment. Input - response relationships can be quantified by generating an ensemble of multiple (100s to 1000s) realistic realizations of weather and climate states. Atmospheric numerical models generate simulated data through discretized numerical approximation of the partial differential equations (PDEs) governing the underlying physics. However, the computational expense of running high resolution atmospheric state models makes generation of more than a few simulations infeasible. Here, we discuss an experiment wherein we approximate the numerical PDE solver within the Weather Research and Forecasting (WRF) Model using neural networks trained on a subset of model run outputs. Once trained, these neural nets can produce large number of realization of weather states from a small number of deterministic simulations with speeds that are orders of magnitude faster than the underlying PDE solver. Our neural network architecture is inspired by the governing partial differential equations. These equations are location-invariant, and consist of first and second derivations. As such, we use a 3x3 lon-lat grid of atmospheric profiles as the predictor in the neural net to provide the network the information necessary to compute the first and second moments. Results indicate that the neural network algorithm can approximate the PDE outputs with high degree of accuracy (less than 1% error), and that this error increases as a function of the prediction time lag.

Student Solution Manual for Essential Mathematical Methods for the Physical Sciences

NASA Astrophysics Data System (ADS)

Riley, K. F.; Hobson, M. P.

2011-02-01

1. Matrices and vector spaces; 2. Vector calculus; 3. Line, surface and volume integrals; 4. Fourier series; 5. Integral transforms; 6. Higher-order ODEs; 7. Series solutions of ODEs; 8. Eigenfunction methods; 9. Special functions; 10. Partial differential equations; 11. Solution methods for PDEs; 12. Calculus of variations; 13. Integral equations; 14. Complex variables; 15. Applications of complex variables; 16. Probability; 17. Statistics.

Essential Mathematical Methods for the Physical Sciences

NASA Astrophysics Data System (ADS)

Riley, K. F.; Hobson, M. P.

2011-02-01

1. Matrices and vector spaces; 2. Vector calculus; 3. Line, surface and volume integrals; 4. Fourier series; 5. Integral transforms; 6. Higher-order ODEs; 7. Series solutions of ODEs; 8. Eigenfunction methods; 9. Special functions; 10. Partial differential equations; 11. Solution methods for PDEs; 12. Calculus of variations; 13. Integral equations; 14. Complex variables; 15. Applications of complex variables; 16. Probability; 17. Statistics; Appendices; Index.

Rotating Detonation Engine Operation (Preprint)

DTIC Science & Technology

2012-01-01

MdotH2 = mass flow of hydrogen MdotAir = mass flow of air PCB = Piezoelectric Pressure Sensor PDE = Pulsed Detonation Engine RDE = Rotating ...and unsteady thrust output of PDEs . One of the new designs was the Rotating Detonation Engine (RDE). An RDE operates by exhausting an initial...AFRL-RZ-WP-TP-2012-0003 ROTATING DETONATION ENGINE OPERATION (PREPRINT) James A. Suchocki and Sheng-Tao John Yu The Ohio State

Overdetermined elliptic problems in topological disks

NASA Astrophysics Data System (ADS)

Mira, Pablo

2018-06-01

We introduce a method, based on the Poincaré-Hopf index theorem, to classify solutions to overdetermined problems for fully nonlinear elliptic equations in domains diffeomorphic to a closed disk. Applications to some well-known nonlinear elliptic PDEs are provided. Our result can be seen as the analogue of Hopf's uniqueness theorem for constant mean curvature spheres, but for the general analytic context of overdetermined elliptic problems.

Discovery and Optimization of Low-Storage Runge-Kutta Methods

DTIC Science & Technology

2015-06-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS DISCOVERY AND OPTIMIZATION OF LOW-STORAGE RUNGE-KUTTA METHODS by Matthew T. Fletcher June 2015... methods are an important family of iterative methods for approximating the solutions of ordinary differential equations (ODEs) and differential...algebraic equations (DAEs). It is common to use an RK method to discretize in time when solving time dependent partial differential equations (PDEs) with a

Nitric oxide-induced changes in endothelial expression of phosphodiesterases 2, 3, and 5.

PubMed

Schankin, Christoph J; Kruse, Lars S; Reinisch, Veronika M; Jungmann, Steffen; Kristensen, Julie C; Grau, Stefan; Ferrari, Uta; Sinicina, Inga; Goldbrunner, Roland; Straube, Andreas; Kruuse, Christina

2010-03-01

To investigate nitric oxide (NO)-mediated changes in expression of cyclic nucleotide degrading phosphodiesterases 2A (PDE2A), PDE3B, and PDE5A in human endothelial cells. Nitric oxide induces production of cyclic guanosine monophosphate (cGMP), which along with cyclic adenosine monophosphate (cAMP) is degraded by PDEs. NO donors and selective inhibitors of PDE3 and PDE5 induce migraine-like headache and play a role in endothelial dysfunction during stroke. The current study investigates possible NO modulation of cGMP-related PDEs relevant to headache induction in a cell line containing such PDEs. Real time polymerase chain reaction and Western blots were used to show expression of PDE2A, PDE3B, and PDE5A in a stable cell line of human brain microvascular endothelial cells. Effects of NO on PDE expression were analyzed at specific time intervals after continued DETA NONOate administration. This study shows the expression of PDE2A, PDE3B, and PDE5A mRNA and PDE3B and PDE5A protein in human cerebral endothelial cells. Long-term DETA NONOate administration induced an immediate mRNA up-regulation of PDE5A (1.9-fold, 0.5 hour), an early peak of PDE2A (1.4-fold, 1 and 2 hours) and later up-regulation of both PDE3B (1.6-fold, 4 hours) and PDE2A (1.7-fold, 8 hours and 1.2-fold after 24 hours). Such changes were, however, not translated into significant changes in protein expression indicating few, if any, functional effects. Long-term NO stimulation modulated PDE3 and PDE5 mRNA expression in endothelial cells. However, PDE3 and PDE5 protein levels were unaffected by NO. The presence of PDE3 or PDE5 in endothelial cells indicates that selective inhibitors may have functional effects in such cells. A complex interaction of cGMP and cAMP in response to NO administration may take place if the mRNA translates into active protein. Whether or not this plays a role in the headache mechanisms remains to be investigated.

OPC-13013, a cyclic nucleotide phosphodiesterase type III, inhibitor, inhibits cell proliferation and transdifferentiation of cultured rat hepatic stellate cells.

PubMed

Shimizu, E; Kobayashi, Y; Oki, Y; Kawasaki, T; Yoshimi, T; Nakamura, H

1999-01-01

Activated hepatic stellate cells (HSC; lipocytes; Ito cells) proliferate and are responsible for extracellular matrix synthesis during hepatic fibrogenesis. During activation, HSC undergo transdifferentiation into myofibroblasts expressing alpha-smooth muscle actin (alpha-SMA). Adenosine 3', 5'-cyclic monophosphate (cyclic AMP) is an ubiquitous intracellular signaling molecule, and is upregulated by the activation of adenylate cyclase and downregulated via hydrolysis by cyclic nucleotide phosphodiesterases (PDEs). Recently, increased intracellular cyclic AMP has been shown to inhibit HSC activation. The aim of the current study was to determine the effects of inhibition of PDEs on cell proliferation and transdifferentiation in cultured rat HSC. Cell proliferation was determined by [3H]thymidine incorporation, and Western blot analysis was performed for detection of alpha-SMA, a phenotypic marker of transdifferentiation into myofibroblast. When the cells were exposed to 3-isobutyl-1-methylxanthine (IBMX; 50-1000 microM), a nonselective PDE inhibitor, serum-stimulated [3H]thymidine incorporation was suppressed in a dose-dependent manner with a maximum inhibition of 66% at a concentration of 500 microM OPC-13013 (1-60 microM), a selective PDE III isoenzyme inhibitor, induced a dose-dependent inhibitory effect on serum-stimulated DNA synthesis that reached a maximum inhibition of 95% at a concentration of 60 microM, while neither 8-methoxymethyl-3-isobutyl-1-methylxanthine (8-MMX), a PDE I isoenzyme inhibitor, nor Ro-20-1724, a PDE IV isoenzyme inhibitor, had an inhibitory effect. Western blot analysis revealed that IBMX or OPC-13013 decreased alpha-SMA expression, while other selective PDE isoenzyme inhibitors did not have a suppressive effect. IBMX, OPC-13013 or Ro-20-1724, but not 8-MMX augmented forskolin-induced increase in intracellular cyclic AMP levels although cyclic AMP levels were not affected by treatment with any of these PDE inhibitors alone. These data indicate that inhibition of PDEs, especially PDE III isoenzyme, can produce an inhibitory effect on HSC activation. The PDE III isoenzyme may contribute to the regulation of HSC activation during fibrogenesis. In addition, OPC-13013 may have the potential to inhibit initiation and progression of hepatic fibrosis by interfering with HSC activation.

Biomolecular surface construction by PDE transform

PubMed Central

Zheng, Qiong; Yang, Siyang; Wei, Guo-Wei

2011-01-01

This work proposes a new framework for the surface generation based on the partial differential equation (PDE) transform. The PDE transform has recently been introduced as a general approach for the mode decomposition of images, signals, and data. It relies on the use of arbitrarily high order PDEs to achieve the time-frequency localization, control the spectral distribution, and regulate the spatial resolution. The present work provides a new variational derivation of high order PDE transforms. The fast Fourier transform is utilized to accomplish the PDE transform so as to avoid stringent stability constraints in solving high order PDEs. As a consequence, the time integration of high order PDEs can be done efficiently with the fast Fourier transform. The present approach is validated with a variety of test examples in two and three-dimensional settings. We explore the impact of the PDE transform parameters, such as the PDE order and propagation time, on the quality of resulting surfaces. Additionally, we utilize a set of 10 proteins to compare the computational efficiency of the present surface generation method and the MSMS approach in Cartesian meshes. Moreover, we analyze the present method by examining some benchmark indicators of biomolecular surface, i.e., surface area, surface enclosed volume, solvation free energy and surface electrostatic potential. A test set of 13 protein molecules is used in the present investigation. The electrostatic analysis is carried out via the Poisson-Boltzmann equation model. To further demonstrate the utility of the present PDE transform based surface method, we solve the Poisson-Nernst-Planck (PNP) equations with a PDE transform surface of a protein. Second order convergence is observed for the electrostatic potential and concentrations. Finally, to test the capability and efficiency of the present PDE transform based surface generation method, we apply it to the construction of an excessively large biomolecule, a virus surface capsid. Virus surface morphologies of different resolutions are attained by adjusting the propagation time. Therefore, the present PDE transform provides a multiresolution analysis in the surface visualization. Extensive numerical experiment and comparison with an established surface model indicate that the present PDE transform is a robust, stable and efficient approach for biomolecular surface generation in Cartesian meshes. PMID:22582140

An approach to rogue waves through the cnoidal equation

NASA Astrophysics Data System (ADS)

Lechuga, Antonio

2014-05-01

Lately it has been realized the importance of rogue waves in some events happening in open seas. Extreme waves and extreme weather could explain some accidents, but not all of them. Every now and then inflicted damages on ships only can be reported to be caused by anomalous and elusive waves, such as rogue waves. That's one of the reason why they continue attracting considerable interest among researchers. In the frame of the Nonlinear Schrödinger equation(NLS), Witham(1974) and Dingemans and Otta (2001)gave asymptotic solutions in moving coordinates that transformed the NLS equation in a ordinary differential equation that is the Duffing or cnoidal wave equation. Applying the Zakharov equation, Stiassnie and Shemer(2004) and Shemer(2010)got also a similar equation. It's well known that this ordinary equation can be solved in elliptic functions. The main aim of this presentation is to sort out the domains of the solutions of this equation, that, of course, are linked to the corresponding solutions of the partial differential equations(PDEs). That being, Lechuga(2007),a simple way to look for anomalous waves as it's the case with some "chaotic" solutions of the Duffing equation.

Reduced-order model for dynamic optimization of pressure swing adsorption processes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agarwal, A.; Biegler, L.; Zitney, S.

2007-01-01

Over the past decades, pressure swing adsorption (PSA) processes have been widely used as energy-efficient gas and liquid separation techniques, especially for high purity hydrogen purification from refinery gases. The separation processes are based on solid-gas equilibrium and operate under periodic transient conditions. Models for PSA processes are therefore multiple instances of partial differential equations (PDEs) in time and space with periodic boundary conditions that link the processing steps together. The solution of this coupled stiff PDE system is governed by steep concentrations and temperature fronts moving with time. As a result, the optimization of such systems for either designmore » or operation represents a significant computational challenge to current differential algebraic equation (DAE) optimization techniques and nonlinear programming algorithms. Model reduction is one approach to generate cost-efficient low-order models which can be used as surrogate models in the optimization problems. The study develops a reduced-order model (ROM) based on proper orthogonal decomposition (POD), which is a low-dimensional approximation to a dynamic PDE-based model. Initially, a representative ensemble of solutions of the dynamic PDE system is constructed by solving a higher-order discretization of the model using the method of lines, a two-stage approach that discretizes the PDEs in space and then integrates the resulting DAEs over time. Next, the ROM method applies the Karhunen-Loeve expansion to derive a small set of empirical eigenfunctions (POD modes) which are used as basis functions within a Galerkin's projection framework to derive a low-order DAE system that accurately describes the dominant dynamics of the PDE system. The proposed method leads to a DAE system of significantly lower order, thus replacing the one obtained from spatial discretization before and making optimization problem computationally-efficient. The method has been applied to the dynamic coupled PDE-based model of a two-bed four-step PSA process for separation of hydrogen from methane. Separate ROMs have been developed for each operating step with different POD modes for each of them. A significant reduction in the order of the number of states has been achieved. The gas-phase mole fraction, solid-state loading and temperature profiles from the low-order ROM and from the high-order simulations have been compared. Moreover, the profiles for a different set of inputs and parameter values fed to the same ROM were compared with the accurate profiles from the high-order simulations. Current results indicate the proposed ROM methodology as a promising surrogate modeling technique for cost-effective optimization purposes. Moreover, deviations from the ROM for different set of inputs and parameters suggest that a recalibration of the model is required for the optimization studies. Results for these will also be presented with the aforementioned results.« less

Heat Transfer Experiments on a Pulse Detonation Driven Combustor

DTIC Science & Technology

2011-03-01

steps that need to take place before such a hybrid is successfully developed. PDEs obtain their increased efficiency by means of detonation , a pressure...combustion in the Brayton cycle. A PDE utilizes detonations , which offer much higher pressures at the site of fuel ignition, generating less...HEAT TRANSFER EXPERIMENTS ON A PULSE DETONATION DRIVEN COMBUSTOR THESIS Nicholas C. Longo, Captain, USAF AFIT/GAE/ENY/11-M18

Heat Exchanger Design and Testing for a 6-Inch Rotating Detonation Engine

DTIC Science & Technology

2013-03-01

Engine Research Facility HHV Higher heating value LHV Lower heating value PDE Pulsed detonation engine RDE Rotating detonation engine RTD...the combustion community are pulse detonation engines ( PDEs ) and rotating detonation engines (RDEs). 1.1 Differences between Pulsed and Rotating ...steadier than that of a PDE (2, 3). (2) (3) Figure 1. Unrolled rotating detonation wave from high-speed video (4) Another difference that

Initiation Mechanisms of Low-loss Swept-ramp Obstacles for Deflagration to Detonation Transition in Pulse Detonation Combustors

DTIC Science & Technology

2009-12-01

minimal pressure losses. 15. NUMBER OF PAGES 113 14. SUBJECT TERMS Pulse Detonation Combustors, PDC, Pulse Detonation Engines, PDE , PDE ...Postgraduate School PDC Pulse Detonation Combustor PDE Pulse Detonation Engine RAM Random Access Memory RDT Research, Design and Test RPL...inhibiting the implementation of this advanced propulsion system. The primary advantage offered by pulse detonation engines ( PDEs ) is the high efficiency

Comment on "Applications of homogenous balanced principle on investigating exact solutions to a series of time fractional nonlinear PDEs", [Commun Nonlinear Sci Numer Simulat 47 (2017) 253-266

NASA Astrophysics Data System (ADS)

Li, Xiangzheng

2018-06-01

A counterexample is given to show that the product rule of the Caputo fractional derivatives does not hold except on a special point. The function-expansion method of separation variable proposed by Rui[Commun Nonlinear Sci Numer Simulat 47 (2017) 253-266] based on the product rule must be modified.

Reconfigurable Analog PDE computation for Baseband and RFComputation

DTIC Science & Technology

2017-03-01

waveguiding PDEs. One-dimensional ladder topologies enable linear delays, linear-phase analog filters , as well as analog beamforming, potentially at RF...performance. This discussion focuses on ODE / PDE analog computation available in SoC FPAA structures. One such computation is a ladder filter (Fig...Implementation of a one-dimensional ladder filter for computing inductor (L) and capacitor (C) lines. These components can be implemented in CABs or as

Towards a rational theory for CFD global stability

NASA Technical Reports Server (NTRS)

Baker, A. J.; Iannelli, G. S.

1989-01-01

The fundamental notion of the consistent stability of semidiscrete analogues of evolution PDEs is explored. Lyapunov's direct method is used to develop CFD semidiscrete algorithms which yield the TVD constraint as a special case. A general formula for supplying dissipation parameters for arbitrary multidimensional conservation law systems is proposed. The reliability of the method is demonstrated by the results of two numerical tests for representative Euler shocked flows.

Rapid Prototyping of Application Specific Signal Processors (RASSP) program - Study Phase

DTIC Science & Technology

1992-10-12

in the quantitative evaluaion of desip ltenatlves. To make sysmms such as IDAS mor effective for...steps, and should invest in the standardization of data models that meet these needs. PDES and CFI are likely to offer the most payoff for such an...provides a bigger picture of the ATR roadmap. It attempts to lay out the projected progress of the ATR technologies and applications, both in the

A comparison of Redlich-Kister polynomial and cubic spline representations of the chemical potential in phase field computations

DOE PAGES

Teichert, Gregory H.; Gunda, N. S. Harsha; Rudraraju, Shiva; ...

2016-12-18

Free energies play a central role in many descriptions of equilibrium and non-equilibrium properties of solids. Continuum partial differential equations (PDEs) of atomic transport, phase transformations and mechanics often rely on first and second derivatives of a free energy function. The stability, accuracy and robustness of numerical methods to solve these PDEs are sensitive to the particular functional representations of the free energy. In this communication we investigate the influence of different representations of thermodynamic data on phase field computations of diffusion and two-phase reactions in the solid state. First-principles statistical mechanics methods were used to generate realistic free energymore » data for HCP titanium with interstitially dissolved oxygen. While Redlich-Kister polynomials have formed the mainstay of thermodynamic descriptions of multi-component solids, they require high order terms to fit oscillations in chemical potentials around phase transitions. Here, we demonstrate that high fidelity fits to rapidly fluctuating free energy functions are obtained with spline functions. As a result, spline functions that are many degrees lower than Redlich-Kister polynomials provide equal or superior fits to chemical potential data and, when used in phase field computations, result in solution times approaching an order of magnitude speed up relative to the use of Redlich-Kister polynomials.« less

Inactivation of Pde8b enhances memory, motor performance, and protects against age-induced motor coordination decay

PubMed Central

Tsai, Li-Chun Lisa; Chan, Guy Chiu-Kai; Nangle, Shannon N.; Shimizu-Albergine, Masami; Jones, Graham; Storm, Daniel R.; Beavo, Joseph A.; Zweifel, Larry S.

2012-01-01

Phosphodiesterases (PDEs) are critical regulatory enzymes in cyclic nucleotide signaling. PDEs have diverse expression patterns within the central nervous system (CNS), show differing affinities for cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP), and regulate a vast array of behaviors. Here, we investigated the expression profile of the PDE8 gene family members Pde8a and Pde8b in the mouse brain. We find that Pde8a expression is largely absent in the CNS; by contrast, Pde8b is expressed in select regions of the hippocampus, ventral striatum, and cerebellum. Behavioral analysis of mice with Pde8b gene inactivation (PDE8B KO) demonstrate an enhancement in contextual fear, spatial memory, performance in an appetitive instrumental conditioning task, motor-coordination, and have an attenuation of age-induced motor coordination decline. In addition to improvements observed in select behaviors, we find basal anxiety levels to be increased in PDE8B KO mice. These findings indicate that selective antagonism of PDE8B may be an attractive target for enhancement of cognitive and motor functions; however, possible alterations in affective state will need to be weighed against potential therapeutic value. PMID:22925203

An improved numerical method for the kernel density functional estimation of disperse flow

NASA Astrophysics Data System (ADS)

Smith, Timothy; Ranjan, Reetesh; Pantano, Carlos

2014-11-01

We present an improved numerical method to solve the transport equation for the one-point particle density function (pdf), which can be used to model disperse flows. The transport equation, a hyperbolic partial differential equation (PDE) with a source term, is derived from the Lagrangian equations for a dilute particle system by treating position and velocity as state-space variables. The method approximates the pdf by a discrete mixture of kernel density functions (KDFs) with space and time varying parameters and performs a global Rayleigh-Ritz like least-square minimization on the state-space of velocity. Such an approximation leads to a hyperbolic system of PDEs for the KDF parameters that cannot be written completely in conservation form. This system is solved using a numerical method that is path-consistent, according to the theory of non-conservative hyperbolic equations. The resulting formulation is a Roe-like update that utilizes the local eigensystem information of the linearized system of PDEs. We will present the formulation of the base method, its higher-order extension and further regularization to demonstrate that the method can predict statistics of disperse flows in an accurate, consistent and efficient manner. This project was funded by NSF Project NSF-DMS 1318161.

Three-dimensional inverse problem of geometrical optics: a mathematical comparison between Fermat's principle and the eikonal equation.

PubMed

Borghero, Francesco; Demontis, Francesco

2016-09-01

In the framework of geometrical optics, we consider the following inverse problem: given a two-parameter family of curves (congruence) (i.e., f(x,y,z)=c₁,g(x,y,z)=c₂), construct the refractive-index distribution function n=n(x,y,z) of a 3D continuous transparent inhomogeneous isotropic medium, allowing for the creation of the given congruence as a family of monochromatic light rays. We solve this problem by following two different procedures: 1. By applying Fermat's principle, we establish a system of two first-order linear nonhomogeneous PDEs in the unique unknown function n=n(x,y,z) relating the assigned congruence of rays with all possible refractive-index profiles compatible with this family. Moreover, we furnish analytical proof that the family of rays must be a normal congruence. 2. By applying the eikonal equation, we establish a second system of two first-order linear homogeneous PDEs whose solutions give the equation S(x,y,z)=const. of the geometric wavefronts and, consequently, all pertinent refractive-index distribution functions n=n(x,y,z). Finally, we make a comparison between the two procedures described above, discussing appropriate examples having exact solutions.

Towards selective phosphodiesterase 2A (PDE2A) inhibitors: a patent review (2010 - present).

PubMed

Trabanco, Andrés A; Buijnsters, Peter; Rombouts, Frederik J R

2016-08-01

The cyclic nucleotides cAMP and cGMP are ubiquitous intracellular second messengers regulating a large variety of biological processes. The intracellular concentration of these biologically relevant molecules is modulated by the activity of phosphodiesterases (PDEs), a class of enzymes that is grouped in 11 families. The expression of PDEs is tissue- and cell-specific allowing spatiotemporal integration of multiple signaling cascades. PDE2A is a dual substrate enzyme and is expressed in both the periphery and in the central nervous system, however its expression is highest in the brain, where it is mainly localized in the cortex, hippocampus, and striatum. This suggests that this enzyme may regulate intraneuronal cGMP and cAMP levels in brain areas involved in emotion, perception, concentration, learning and memory. This review covers the patent applications published between January 2010 and February 2016 on phosphodiesterase 2A inhibitors. Recent publications in the literature and in filed patent applications demonstrate the interest of pharmaceutical companies for PDE2A. This has increased the insights of its possible therapeutic role but the few clinical trials were terminated. Based on the ongoing interest in the field it is likely that new clinical trials can be expected and will unravel the therapeutic potential of PDE2A inhibition.

The EAL domain protein YciR acts as a trigger enzyme in a c-di-GMP signalling cascade in E. coli biofilm control

PubMed Central

Lindenberg, Sandra; Klauck, Gisela; Pesavento, Christina; Klauck, Eberhard; Hengge, Regine

2013-01-01

C-di-GMP—which is produced by diguanylate cyclases (DGC) and degraded by specific phosphodiesterases (PDEs)—is a ubiquitous second messenger in bacterial biofilm formation. In Escherichia coli, several DGCs (YegE, YdaM) and PDEs (YhjH, YciR) and the MerR-like transcription factor MlrA regulate the transcription of csgD, which encodes a biofilm regulator essential for producing amyloid curli fibres of the biofilm matrix. Here, we demonstrate that this system operates as a signalling cascade, in which c-di-GMP controlled by the DGC/PDE pair YegE/YhjH (module I) regulates the activity of the YdaM/YciR pair (module II). Via multiple direct interactions, the two module II proteins form a signalling complex with MlrA. YciR acts as a connector between modules I and II and functions as a trigger enzyme: its direct inhibition of the DGC YdaM is relieved when it binds and degrades c-di-GMP generated by module I. As a consequence, YdaM then generates c-di-GMP and—by direct and specific interaction—activates MlrA to stimulate csgD transcription. Trigger enzymes may represent a general principle in local c-di-GMP signalling. PMID:23708798

Evaluating average and atypical response in radiation effects simulations

NASA Astrophysics Data System (ADS)

Weller, R. A.; Sternberg, A. L.; Massengill, L. W.; Schrimpf, R. D.; Fleetwood, D. M.

2003-12-01

We examine the limits of performing single-event simulations using pre-averaged radiation events. Geant4 simulations show the necessity, for future devices, to supplement current methods with ensemble averaging of device-level responses to physically realistic radiation events. Initial Monte Carlo simulations have generated a significant number of extremal events in local energy deposition. These simulations strongly suggest that proton strikes of sufficient energy, even those that initiate purely electronic interactions, can initiate device response capable in principle of producing single event upset or microdose damage in highly scaled devices.

The Programming Language Python In Earth System Simulations

NASA Astrophysics Data System (ADS)

Gross, L.; Imranullah, A.; Mora, P.; Saez, E.; Smillie, J.; Wang, C.

2004-12-01

Mathematical models in earth sciences base on the solution of systems of coupled, non-linear, time-dependent partial differential equations (PDEs). The spatial and time-scale vary from a planetary scale and million years for convection problems to 100km and 10 years for fault systems simulations. Various techniques are in use to deal with the time dependency (e.g. Crank-Nicholson), with the non-linearity (e.g. Newton-Raphson) and weakly coupled equations (e.g. non-linear Gauss-Seidel). Besides these high-level solution algorithms discretization methods (e.g. finite element method (FEM), boundary element method (BEM)) are used to deal with spatial derivatives. Typically, large-scale, three dimensional meshes are required to resolve geometrical complexity (e.g. in the case of fault systems) or features in the solution (e.g. in mantel convection simulations). The modelling environment escript allows the rapid implementation of new physics as required for the development of simulation codes in earth sciences. Its main object is to provide a programming language, where the user can define new models and rapidly develop high-level solution algorithms. The current implementation is linked with the finite element package finley as a PDE solver. However, the design is open and other discretization technologies such as finite differences and boundary element methods could be included. escript is implemented as an extension of the interactive programming environment python (see www.python.org). Key concepts introduced are Data objects, which are holding values on nodes or elements of the finite element mesh, and linearPDE objects, which are defining linear partial differential equations to be solved by the underlying discretization technology. In this paper we will show the basic concepts of escript and will show how escript is used to implement a simulation code for interacting fault systems. We will show some results of large-scale, parallel simulations on an SGI Altix system. Acknowledgements: Project work is supported by Australian Commonwealth Government through the Australian Computational Earth Systems Simulator Major National Research Facility, Queensland State Government Smart State Research Facility Fund, The University of Queensland and SGI.

USMC Inventory Control Using Optimization Modeling and Discrete Event Simulation

DTIC Science & Technology

2016-09-01

release. Distribution is unlimited. USMC INVENTORY CONTROL USING OPTIMIZATION MODELING AND DISCRETE EVENT SIMULATION by Timothy A. Curling...USING OPTIMIZATION MODELING AND DISCRETE EVENT SIMULATION 5. FUNDING NUMBERS 6. AUTHOR(S) Timothy A. Curling 7. PERFORMING ORGANIZATION NAME(S...optimization and discrete -event simulation. This construct can potentially provide an effective means in improving order management decisions. However

ANALYSIS OF INPATIENT HOSPITAL STAFF MENTAL WORKLOAD BY MEANS OF DISCRETE-EVENT SIMULATION

DTIC Science & Technology

2016-03-24

ANALYSIS OF INPATIENT HOSPITAL STAFF MENTAL WORKLOAD BY MEANS OF DISCRETE -EVENT SIMULATION...in the United States. AFIT-ENV-MS-16-M-166 ANALYSIS OF INPATIENT HOSPITAL STAFF MENTAL WORKLOAD BY MEANS OF DISCRETE -EVENT SIMULATION...UNLIMITED. AFIT-ENV-MS-16-M-166 ANALYSIS OF INPATIENT HOSPITAL STAFF MENTAL WORKLOAD BY MEANS OF DISCRETE -EVENT SIMULATION Erich W

An Empirical Study of Combining Communicating Processes in a Parallel Discrete Event Simulation

DTIC Science & Technology

1990-12-01

dynamics of the cost/performance criteria which typically made up computer resource acquisition decisions . offering a broad range of tradeoffs in the way... prcesses has a significant impact on simulation performance. It is the hypothesis of this 3-4 SYSTEM DECOMPOSITION PHYSICAL SYSTEM 1: N PHYSICAL PROCESS 1...EMPTY)) next-event = pop(next-event-queue); lp-clock = next-event - time; Simulate next event departure- consume event-enqueue new event end while; If no

The Time Dependent Propensity Function for Acceleration of Spatial Stochastic Simulation of Reaction-Diffusion Systems

PubMed Central

Wu, Sheng; Li, Hong; Petzold, Linda R.

2015-01-01

The inhomogeneous stochastic simulation algorithm (ISSA) is a fundamental method for spatial stochastic simulation. However, when diffusion events occur more frequently than reaction events, simulating the diffusion events by ISSA is quite costly. To reduce this cost, we propose to use the time dependent propensity function in each step. In this way we can avoid simulating individual diffusion events, and use the time interval between two adjacent reaction events as the simulation stepsize. We demonstrate that the new algorithm can achieve orders of magnitude efficiency gains over widely-used exact algorithms, scales well with increasing grid resolution, and maintains a high level of accuracy. PMID:26609185

Program For Simulation Of Trajectories And Events

NASA Technical Reports Server (NTRS)

Gottlieb, Robert G.

1992-01-01

Universal Simulation Executive (USE) program accelerates and eases generation of application programs for numerical simulation of continuous trajectories interrupted by or containing discrete events. Developed for simulation of multiple spacecraft trajectories with events as one spacecraft crossing the equator, two spacecraft meeting or parting, or firing rocket engine. USE also simulates operation of chemical batch processing factory. Written in Ada.

Some remarks on the numerical solution of parabolic partial differential equations

NASA Astrophysics Data System (ADS)

Campagna, R.; Cuomo, S.; Leveque, S.; Toraldo, G.; Giannino, F.; Severino, G.

2017-11-01

Numerous environmental/engineering applications relying upon the theory of diffusion phenomena into chaotic environments have recently stimulated the interest toward the numerical solution of parabolic partial differential equations (PDEs). In the present paper, we outline a formulation of the mathematical problem underlying a quite general diffusion mechanism in the natural environments, and we shortly emphasize some remarks concerning the applicability of the (straightforward) finite difference method. An illustration example is also presented.

Vibrational and Rotational CARS Measurements of Nitrogen in Afterglow of Streamer Discharge in Atmospheric Pressure Fuel/Air Mixtures

DTIC Science & Technology

2012-01-01

in a variety of different ignition regimes, including pulsed detonation engines ( PDEs ) and automobile engines, with experiments demonstrating TPI to...Vibrational and rotational CARS measurements of nitrogen in afterglow of streamer discharge in atmospheric pressure fuel/air mixtures This article...DATE 2012 2. REPORT TYPE 3. DATES COVERED 00-00-2012 to 00-00-2012 4. TITLE AND SUBTITLE Vibrational and rotational CARS measurements of

Observability of discretized partial differential equations

NASA Technical Reports Server (NTRS)

Cohn, Stephen E.; Dee, Dick P.

1988-01-01

It is shown that complete observability of the discrete model used to assimilate data from a linear partial differential equation (PDE) system is necessary and sufficient for asymptotic stability of the data assimilation process. The observability theory for discrete systems is reviewed and applied to obtain simple observability tests for discretized constant-coefficient PDEs. Examples are used to show how numerical dispersion can result in discrete dynamics with multiple eigenvalues, thereby detracting from observability.

Tailoring High Order Time Discretizations for Use with Spatial Discretizations of Hyperbolic PDEs

DTIC Science & Technology

2015-05-19

Duration of Grant Sigal Gottlieb, Professor of Mathematics, UMass Dartmouth. Daniel Higgs , Graduate Student, UMass Dartmouth. Zachary Grant, Undergraduate...Grant, and D. Higgs , “Optimal Explicit Strong Stability Preserving Runge– Kutta Methods with High Linear Order and optimal Nonlinear Order.” Accepted...for publica- tion in Mathematics of Computation. Available on Arxiv at http://arxiv.org/abs/1403. 6519 4. C. Bresten, S. Gottlieb, Z. Grant, D. Higgs

Digital Representation for Communication of Product Definition Data. Revision

DTIC Science & Technology

1990-04-30

Treuhandgesellschaft Electrical Thomas C . Estervog Boeing Computer Services John C . Faulkner S D R C Ayron L. Fears IBM Corp. ix MEMBERS OF THE IGES/PDES...Force Eugene F. Gurga Computervision C . Hayden Hamilton III PDA Engineering William Hammon Tandem Computer Yosef Haridim Boeing Electronics Co. C ...British Aerospace Raphael McBain General Dynamics Corp. Dennis McBurney L-ueing Military Airplane Co Patrick McFadden Boeing Computer Services C . Kevin

Simulation of a master-slave event set processor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Comfort, J.C.

1984-03-01

Event set manipulation may consume a considerable amount of the computation time spent in performing a discrete-event simulation. One way of minimizing this time is to allow event set processing to proceed in parallel with the remainder of the simulation computation. The paper describes a multiprocessor simulation computer, in which all non-event set processing is performed by the principal processor (called the host). Event set processing is coordinated by a front end processor (the master) and actually performed by several other functionally identical processors (the slaves). A trace-driven simulation program modeling this system was constructed, and was run with tracemore » output taken from two different simulation programs. Output from this simulation suggests that a significant reduction in run time may be realized by this approach. Sensitivity analysis was performed on the significant parameters to the system (number of slave processors, relative processor speeds, and interprocessor communication times). A comparison between actual and simulation run times for a one-processor system was used to assist in the validation of the simulation. 7 references.« less

Parallel discrete event simulation: A shared memory approach

NASA Technical Reports Server (NTRS)

Reed, Daniel A.; Malony, Allen D.; Mccredie, Bradley D.

1987-01-01

With traditional event list techniques, evaluating a detailed discrete event simulation model can often require hours or even days of computation time. Parallel simulation mimics the interacting servers and queues of a real system by assigning each simulated entity to a processor. By eliminating the event list and maintaining only sufficient synchronization to insure causality, parallel simulation can potentially provide speedups that are linear in the number of processors. A set of shared memory experiments is presented using the Chandy-Misra distributed simulation algorithm to simulate networks of queues. Parameters include queueing network topology and routing probabilities, number of processors, and assignment of network nodes to processors. These experiments show that Chandy-Misra distributed simulation is a questionable alternative to sequential simulation of most queueing network models.

Parallel discrete event simulation using shared memory

NASA Technical Reports Server (NTRS)

Reed, Daniel A.; Malony, Allen D.; Mccredie, Bradley D.

1988-01-01

With traditional event-list techniques, evaluating a detailed discrete-event simulation-model can often require hours or even days of computation time. By eliminating the event list and maintaining only sufficient synchronization to ensure causality, parallel simulation can potentially provide speedups that are linear in the numbers of processors. A set of shared-memory experiments, using the Chandy-Misra distributed-simulation algorithm, to simulate networks of queues is presented. Parameters of the study include queueing network topology and routing probabilities, number of processors, and assignment of network nodes to processors. These experiments show that Chandy-Misra distributed simulation is a questionable alternative to sequential-simulation of most queueing network models.

An adaptive moving finite volume scheme for modeling flood inundation over dry and complex topography

NASA Astrophysics Data System (ADS)

Zhou, Feng; Chen, Guoxian; Huang, Yuefei; Yang, Jerry Zhijian; Feng, Hui

2013-04-01

A new geometrical conservative interpolation on unstructured meshes is developed for preserving still water equilibrium and positivity of water depth at each iteration of mesh movement, leading to an adaptive moving finite volume (AMFV) scheme for modeling flood inundation over dry and complex topography. Unlike traditional schemes involving position-fixed meshes, the iteration process of the AFMV scheme moves a fewer number of the meshes adaptively in response to flow variables calculated in prior solutions and then simulates their posterior values on the new meshes. At each time step of the simulation, the AMFV scheme consists of three parts: an adaptive mesh movement to shift the vertices position, a geometrical conservative interpolation to remap the flow variables by summing the total mass over old meshes to avoid the generation of spurious waves, and a partial differential equations(PDEs) discretization to update the flow variables for a new time step. Five different test cases are presented to verify the computational advantages of the proposed scheme over nonadaptive methods. The results reveal three attractive features: (i) the AMFV scheme could preserve still water equilibrium and positivity of water depth within both mesh movement and PDE discretization steps; (ii) it improved the shock-capturing capability for handling topographic source terms and wet-dry interfaces by moving triangular meshes to approximate the spatial distribution of time-variant flood processes; (iii) it was able to solve the shallow water equations with a relatively higher accuracy and spatial-resolution with a lower computational cost.

Final Report, DOE Early Career Award: Predictive modeling of complex physical systems: new tools for statistical inference, uncertainty quantification, and experimental design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marzouk, Youssef

Predictive simulation of complex physical systems increasingly rests on the interplay of experimental observations with computational models. Key inputs, parameters, or structural aspects of models may be incomplete or unknown, and must be developed from indirect and limited observations. At the same time, quantified uncertainties are needed to qualify computational predictions in the support of design and decision-making. In this context, Bayesian statistics provides a foundation for inference from noisy and limited data, but at prohibitive computional expense. This project intends to make rigorous predictive modeling *feasible* in complex physical systems, via accelerated and scalable tools for uncertainty quantification, Bayesianmore » inference, and experimental design. Specific objectives are as follows: 1. Develop adaptive posterior approximations and dimensionality reduction approaches for Bayesian inference in high-dimensional nonlinear systems. 2. Extend accelerated Bayesian methodologies to large-scale {\\em sequential} data assimilation, fully treating nonlinear models and non-Gaussian state and parameter distributions. 3. Devise efficient surrogate-based methods for Bayesian model selection and the learning of model structure. 4. Develop scalable simulation/optimization approaches to nonlinear Bayesian experimental design, for both parameter inference and model selection. 5. Demonstrate these inferential tools on chemical kinetic models in reacting flow, constructing and refining thermochemical and electrochemical models from limited data. Demonstrate Bayesian filtering on canonical stochastic PDEs and in the dynamic estimation of inhomogeneous subsurface properties and flow fields.« less

Hydrologic modeling of two glaciated watersheds in Northeast Pennsylvania

USGS Publications Warehouse

Srinivasan, M.S.; Hamlett, J.M.; Day, R.L.; Sams, J.I.; Petersen, G.W.

1998-01-01

A hydrologic modeling study, using the Hydrologic Simulation Program - FORTRAN (HSPF), was conducted in two glaciated watersheds, Purdy Creek and Ariel Creek in northeastern Pennsylvania. Both watersheds have wetlands and poorly drained soils due to low hydraulic conductivity and presence of fragipans. The HSPF model was calibrated in the Purdy Creek watershed and verified in the Ariel Creek watershed for June 1992 to December 1993 period. In Purdy Creek, the total volume of observed streamflow during the entire simulation period was 13.36 x 106 m3 and the simulated streamflow volume was 13.82 x 106 m3 (5 percent difference). For the verification simulation in Ariel Creek, the difference between the total observed and simulated flow volumes was 17 percent. Simulated peak flow discharges were within two hours of the observed for 30 of 46 peak flow events (discharge greater than 0.1 m3/sec) in Purdy Creek and 27 of 53 events in Ariel Creek. For 22 of the 46 events in Purdy Creek and 24 of 53 in Ariel Creek, the differences between the observed and simulated peak discharge rates were less than 30 percent. These 22 events accounted for 63 percent of total volume of streamflow observed during the selected 46 peak flow events in Purdy Creek. In Ariel Creek, these 24 peak flow events accounted for 62 percent of the total flow observed during all peak flow events. Differences in observed and simulated peak flow rates and volumes (on a percent basis) were greater during the snowmelt runoff events and summer periods than for other times.A hydrologic modeling study, using the Hydrologic Simulation Program - FORTRAN (HSPF), was conducted in two glaciated watersheds, Purdy Creek and Ariel Creek in northeastern Pennsylvania. Both watersheds have wetlands and poorly drained soils due to low hydraulic conductivity and presence of fragipans. The HSPF model was calibrated in the Purdy Creek watershed and verified in the Ariel Creek watershed for June 1992 to December 1993 period. In Purdy Creek, the total volume of observed streamflow during the entire simulation period was 13.36??106 m3 and the simulated streamflow volume was 13.82??106 m3 (5 percent difference). For the verification simulation in Ariel Creek, the difference between the total observed and simulated flow volumes was 17 percent. Simulated peak flow discharges were within two hours of the observed for 30 of 46 peak flow events (discharge greater than 0.1 m3/sec) in Purdy Creek and 27 of 53 events in Ariel Creek. For 22 of the 46 events in Purdy Creek and 24 of 53 in Ariel Creek, the differences between the observed and simulated peak discharge rates were less than 30 percent. These 22 events accounted for 63 percent of total volume of streamflow observed during the selected 46 peak flow events in Purdy Creek. In Ariel Creek, these 24 peak flow events accounted for 62 percent of the total flow observed during all peak flow events. Differences in observed and simulated peak flow rates and volumes (on a percent basis) were greater during the snowmelt runoff events and summer periods than for other times.

Ensemble Grouping Strategies for Embedded Stochastic Collocation Methods Applied to Anisotropic Diffusion Problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

D'Elia, M.; Edwards, H. C.; Hu, J.

Previous work has demonstrated that propagating groups of samples, called ensembles, together through forward simulations can dramatically reduce the aggregate cost of sampling-based uncertainty propagation methods [E. Phipps, M. D'Elia, H. C. Edwards, M. Hoemmen, J. Hu, and S. Rajamanickam, SIAM J. Sci. Comput., 39 (2017), pp. C162--C193]. However, critical to the success of this approach when applied to challenging problems of scientific interest is the grouping of samples into ensembles to minimize the total computational work. For example, the total number of linear solver iterations for ensemble systems may be strongly influenced by which samples form the ensemble whenmore » applying iterative linear solvers to parameterized and stochastic linear systems. In this paper we explore sample grouping strategies for local adaptive stochastic collocation methods applied to PDEs with uncertain input data, in particular canonical anisotropic diffusion problems where the diffusion coefficient is modeled by truncated Karhunen--Loève expansions. Finally, we demonstrate that a measure of the total anisotropy of the diffusion coefficient is a good surrogate for the number of linear solver iterations for each sample and therefore provides a simple and effective metric for grouping samples.« less

Nonlinear unsteady convection on micro and nanofluids with Cattaneo-Christov heat flux

NASA Astrophysics Data System (ADS)

Mamatha Upadhya, S.; Raju, C. S. K.; Mahesha; Saleem, S.

2018-06-01

This is a theoretical study of unsteady nonlinear convection on magnetohydrodynamic fluid in a suspension of dust and graphene nanoparticles. For boosting the heat transport phenomena we consider the Cattaneo-Christov heat flux and thermal radiation. Dispersal of graphene nanoparticles in dusty fluids finds applications in biocompatibility, bio-imaging, biosensors, detection and cancer treatment, in monitoring stem cells differentiation etc. Initially the simulation is performed by amalgamation of dust (micron size) and nanoparticles into base fluid. Primarily existing partial differential system (PDEs) is changed to ordinary differential system (ODEs) with the support of usual similarity transformations. Consequently, the highly nonlinear ODEs are solved numerically through Runge-Kutta and Shooting method. The computational results for Non-dimensional temperature and velocity profiles are offered through graphs (ϕ = 0 and ϕ = 0.05) cases. Additionally, the numerical values of friction factor and heat transfer rate are tabulated numerically for various physical parameters obtained. We also validated the current outcomes with previously available study and found to be extremely acceptable. From this study we conclude that in the presence of nanofluid heat transfer rate and temperature distribution is higher compared to micro fluid.

Effect of asynchrony on numerical simulations of fluid flow phenomena

NASA Astrophysics Data System (ADS)

Konduri, Aditya; Mahoney, Bryan; Donzis, Diego

2015-11-01

Designing scalable CFD codes on massively parallel computers is a challenge. This is mainly due to the large number of communications between processing elements (PEs) and their synchronization, leading to idling of PEs. Indeed, communication will likely be the bottleneck in the scalability of codes on Exascale machines. Our recent work on asynchronous computing for PDEs based on finite-differences has shown that it is possible to relax synchronization between PEs at a mathematical level. Computations then proceed regardless of the status of communication, reducing the idle time of PEs and improving the scalability. However, accuracy of the schemes is greatly affected. We have proposed asynchrony-tolerant (AT) schemes to address this issue. In this work, we study the effect of asynchrony on the solution of fluid flow problems using standard and AT schemes. We show that asynchrony creates additional scales with low energy content. The specific wavenumbers affected can be shown to be due to two distinct effects: the randomness in the arrival of messages and the corresponding switching between schemes. Understanding these errors allow us to effectively control them, rendering the method's feasibility in solving turbulent flows at realistic conditions on future computing systems.

Ensemble Grouping Strategies for Embedded Stochastic Collocation Methods Applied to Anisotropic Diffusion Problems

DOE PAGES

D'Elia, M.; Edwards, H. C.; Hu, J.; ...

2018-01-18

Previous work has demonstrated that propagating groups of samples, called ensembles, together through forward simulations can dramatically reduce the aggregate cost of sampling-based uncertainty propagation methods [E. Phipps, M. D'Elia, H. C. Edwards, M. Hoemmen, J. Hu, and S. Rajamanickam, SIAM J. Sci. Comput., 39 (2017), pp. C162--C193]. However, critical to the success of this approach when applied to challenging problems of scientific interest is the grouping of samples into ensembles to minimize the total computational work. For example, the total number of linear solver iterations for ensemble systems may be strongly influenced by which samples form the ensemble whenmore » applying iterative linear solvers to parameterized and stochastic linear systems. In this paper we explore sample grouping strategies for local adaptive stochastic collocation methods applied to PDEs with uncertain input data, in particular canonical anisotropic diffusion problems where the diffusion coefficient is modeled by truncated Karhunen--Loève expansions. Finally, we demonstrate that a measure of the total anisotropy of the diffusion coefficient is a good surrogate for the number of linear solver iterations for each sample and therefore provides a simple and effective metric for grouping samples.« less

An "age"-structured model of hematopoietic stem cell organization with application to chronic myeloid leukemia.

PubMed

Roeder, Ingo; Herberg, Maria; Horn, Matthias

2009-04-01

Previously, we have modeled hematopoietic stem cell organization by a stochastic, single cell-based approach. Applications to different experimental systems demonstrated that this model consistently explains a broad variety of in vivo and in vitro data. A major advantage of the agent-based model (ABM) is the representation of heterogeneity within the hematopoietic stem cell population. However, this advantage comes at the price of time-consuming simulations if the systems become large. One example in this respect is the modeling of disease and treatment dynamics in patients with chronic myeloid leukemia (CML), where the realistic number of individual cells to be considered exceeds 10(6). To overcome this deficiency, without losing the representation of the inherent heterogeneity of the stem cell population, we here propose to approximate the ABM by a system of partial differential equations (PDEs). The major benefit of such an approach is its independence from the size of the system. Although this mean field approach includes a number of simplifying assumptions compared to the ABM, it retains the key structure of the model including the "age"-structure of stem cells. We show that the PDE model qualitatively and quantitatively reproduces the results of the agent-based approach.

Modeling Anti-Air Warfare With Discrete Event Simulation and Analyzing Naval Convoy Operations

DTIC Science & Technology

2016-06-01

WARFARE WITH DISCRETE EVENT SIMULATION AND ANALYZING NAVAL CONVOY OPERATIONS by Ali E. Opcin June 2016 Thesis Advisor: Arnold H. Buss Co...REPORT DATE June 2016 3. REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE MODELING ANTI-AIR WARFARE WITH DISCRETE EVENT...In this study, a discrete event simulation (DES) was built by modeling ships, and their sensors and weapons, to simulate convoy operations under

ATLAS Simulation using Real Data: Embedding and Overlay

NASA Astrophysics Data System (ADS)

Haas, Andrew; ATLAS Collaboration

2017-10-01

For some physics processes studied with the ATLAS detector, a more accurate simulation in some respects can be achieved by including real data into simulated events, with substantial potential improvements in the CPU, disk space, and memory usage of the standard simulation configuration, at the cost of significant database and networking challenges. Real proton-proton background events can be overlaid (at the detector digitization output stage) on a simulated hard-scatter process, to account for pileup background (from nearby bunch crossings), cavern background, and detector noise. A similar method is used to account for the large underlying event from heavy ion collisions, rather than directly simulating the full collision. Embedding replaces the muons found in Z→μμ decays in data with simulated taus at the same 4-momenta, thus preserving the underlying event and pileup from the original data event. In all these cases, care must be taken to exactly match detector conditions (beamspot, magnetic fields, alignments, dead sensors, etc.) between the real data event and the simulation. We will discuss the status of these overlay and embedding techniques within ATLAS software and computing.

Biomolecular surface construction by PDE transform.

PubMed

Zheng, Qiong; Yang, Siyang; Wei, Guo-Wei

2012-03-01

This work proposes a new framework for the surface generation based on the partial differential equation (PDE) transform. The PDE transform has recently been introduced as a general approach for the mode decomposition of images, signals, and data. It relies on the use of arbitrarily high-order PDEs to achieve the time-frequency localization, control the spectral distribution, and regulate the spatial resolution. The present work provides a new variational derivation of high-order PDE transforms. The fast Fourier transform is utilized to accomplish the PDE transform so as to avoid stringent stability constraints in solving high-order PDEs. As a consequence, the time integration of high-order PDEs can be done efficiently with the fast Fourier transform. The present approach is validated with a variety of test examples in two-dimensional and three-dimensional settings. We explore the impact of the PDE transform parameters, such as the PDE order and propagation time, on the quality of resulting surfaces. Additionally, we utilize a set of 10 proteins to compare the computational efficiency of the present surface generation method and a standard approach in Cartesian meshes. Moreover, we analyze the present method by examining some benchmark indicators of biomolecular surface, that is, surface area, surface-enclosed volume, solvation free energy, and surface electrostatic potential. A test set of 13 protein molecules is used in the present investigation. The electrostatic analysis is carried out via the Poisson-Boltzmann equation model. To further demonstrate the utility of the present PDE transform-based surface method, we solve the Poisson-Nernst-Planck equations with a PDE transform surface of a protein. Second-order convergence is observed for the electrostatic potential and concentrations. Finally, to test the capability and efficiency of the present PDE transform-based surface generation method, we apply it to the construction of an excessively large biomolecule, a virus surface capsid. Virus surface morphologies of different resolutions are attained by adjusting the propagation time. Therefore, the present PDE transform provides a multiresolution analysis in the surface visualization. Extensive numerical experiment and comparison with an established surface model indicate that the present PDE transform is a robust, stable, and efficient approach for biomolecular surface generation in Cartesian meshes. Copyright © 2012 John Wiley & Sons, Ltd.

A unified Fourier theory for time-of-flight PET data

PubMed Central

Li, Yusheng; Matej, Samuel; Metzler, Scott D

2016-01-01

Fully 3D time-of-flight (TOF) PET scanners offer the potential of previously unachievable image quality in clinical PET imaging. TOF measurements add another degree of redundancy for cylindrical PET scanners and make photon-limited TOF-PET imaging more robust than non-TOF PET imaging. The data space for 3D TOF-PET data is five-dimensional with two degrees of redundancy. Previously, consistency equations were used to characterize the redundancy of TOF-PET data. In this paper, we first derive two Fourier consistency equations and Fourier-John equation for 3D TOF PET based on the generalized projection-slice theorem; the three partial differential equations (PDEs) are the dual of the sinogram consistency equations and John's equation. We then solve the three PDEs using the method of characteristics. The two degrees of entangled redundancy of the TOF-PET data can be explicitly elicited and exploited by the solutions of the PDEs along the characteristic curves, which gives a complete understanding of the rich structure of the 3D X-ray transform with TOF measurement. Fourier rebinning equations and other mapping equations among different types of PET data are special cases of the general solutions. We also obtain new Fourier rebinning and consistency equations (FORCEs) from other special cases of the general solutions, and thus we obtain a complete scheme to convert among different types of PET data: 3D TOF, 3D non-TOF, 2D TOF and 2D non-TOF data. The new FORCEs can be used as new Fourier-based rebinning algorithms for TOF-PET data reduction, inverse rebinnings for designing fast projectors, or consistency conditions for estimating missing data. Further, we give a geometric interpretation of the general solutions—the two families of characteristic curves can be obtained by respectively changing the azimuthal and co-polar angles of the biorthogonal coordinates in Fourier space. We conclude the unified Fourier theory by showing that the Fourier consistency equations are necessary and sufficient for 3D X-ray transform with TOF measurement. Finally, we give numerical examples of inverse rebinning for a 3D TOF PET and Fourier-based rebinning for a 2D TOF PET using the FORCEs to show the efficacy of the unified Fourier solutions. PMID:26689836

A unified Fourier theory for time-of-flight PET data.

PubMed

Li, Yusheng; Matej, Samuel; Metzler, Scott D

2016-01-21

Fully 3D time-of-flight (TOF) PET scanners offer the potential of previously unachievable image quality in clinical PET imaging. TOF measurements add another degree of redundancy for cylindrical PET scanners and make photon-limited TOF-PET imaging more robust than non-TOF PET imaging. The data space for 3D TOF-PET data is five-dimensional with two degrees of redundancy. Previously, consistency equations were used to characterize the redundancy of TOF-PET data. In this paper, we first derive two Fourier consistency equations and Fourier-John equation for 3D TOF PET based on the generalized projection-slice theorem; the three partial differential equations (PDEs) are the dual of the sinogram consistency equations and John's equation. We then solve the three PDEs using the method of characteristics. The two degrees of entangled redundancy of the TOF-PET data can be explicitly elicited and exploited by the solutions of the PDEs along the characteristic curves, which gives a complete understanding of the rich structure of the 3D x-ray transform with TOF measurement. Fourier rebinning equations and other mapping equations among different types of PET data are special cases of the general solutions. We also obtain new Fourier rebinning and consistency equations (FORCEs) from other special cases of the general solutions, and thus we obtain a complete scheme to convert among different types of PET data: 3D TOF, 3D non-TOF, 2D TOF and 2D non-TOF data. The new FORCEs can be used as new Fourier-based rebinning algorithms for TOF-PET data reduction, inverse rebinnings for designing fast projectors, or consistency conditions for estimating missing data. Further, we give a geometric interpretation of the general solutions--the two families of characteristic curves can be obtained by respectively changing the azimuthal and co-polar angles of the biorthogonal coordinates in Fourier space. We conclude the unified Fourier theory by showing that the Fourier consistency equations are necessary and sufficient for 3D x-ray transform with TOF measurement. Finally, we give numerical examples of inverse rebinning for a 3D TOF PET and Fourier-based rebinning for a 2D TOF PET using the FORCEs to show the efficacy of the unified Fourier solutions.

Mean Curvature, Threshold Dynamics, and Phase Field Theory on Finite Graphs

DTIC Science & Technology

2013-06-28

of the graph in a low dimensional space . Of course, the various definitions of curvature in the ... with a velocity depending on the mean curvature of the front. Recently, there has been an increasing interest in using ideas from continuum PDEs...functions V → R and E the space of all skew-symmetric4 functions E → R. Again to simplify notation, we extend each ϕ ∈ E to a function ϕ : V 2 → R

An Overview of Advanced Concepts for Space Access (Preprint)

DTIC Science & Technology

2008-06-19

One such technology is the pulsed detonation engine ( PDE ). PDEs are conceptually simple devices. Fuel and air are mixed in the closed end of a...to form air detonations that propel the vehicle. Two types of lightcraft engines have been examined using either simple laser-thermal or more complex... detonation waves to propel the vehicle has the advantage of not having to store fuel on-board the vehicle. However as the vehicle ascends, the air

High-Order Accurate Solutions to the Helmholtz Equation in the Presence of Boundary Singularities

DTIC Science & Technology

2015-03-31

FD scheme is only consistent for classical solutions of the PDE . For this reason, we implement the method of singularity subtraction as a means for...regularity due to the boundary conditions. This is because the FD scheme is only consistent for classical solutions of the PDE . For this reason, we...Introduction In the present work, we develop a high-order numerical method for solving linear elliptic PDEs with well-behaved variable coefficients on

Dynamic grid refinement for partial differential equations on parallel computers

NASA Technical Reports Server (NTRS)

Mccormick, S.; Quinlan, D.

1989-01-01

The fast adaptive composite grid method (FAC) is an algorithm that uses various levels of uniform grids to provide adaptive resolution and fast solution of PDEs. An asynchronous version of FAC, called AFAC, that completely eliminates the bottleneck to parallelism is presented. This paper describes the advantage that this algorithm has in adaptive refinement for moving singularities on multiprocessor computers. This work is applicable to the parallel solution of two- and three-dimensional shock tracking problems.

Modern Perspectives in Applied Mathematics: Theory and Numerics of PDEs

DTIC Science & Technology

2015-04-13

Stokes-Fokker- Planck systems 09:45 – 10:25 Helena Lopes (Universidade Federal do Rio de Janeiro ) Boundary correctors and energy estimates for...Duke%University x Helena Lopes Universidade%Federal%do% Rio % de % Janeiro x x Andrew Majda New%York%University x Siddhartha Mishra ETH%Zurich x Stanley...09:00 – 09:40 Chair: Doron Levy (University of Maryland) Pierre-Louis Lions (Collège de France) 09:45 – 10:25 Andrew Majda (New York University

Pressure and Thrust Measurements of a High-Frequency Pulsed Detonation Tube

NASA Technical Reports Server (NTRS)

Nguyen, N.; Cutler, A. D.

2008-01-01

This paper describes measurements of a small-scale, high-frequency pulsed detonation tube. The device utilized a mixture of H2 fuel and air, which was injected into the device at frequencies of up to 1200 Hz. Pulsed detonations were demonstrated in an 8-inch long combustion volume, at about 600 Hz, for the quarter wave mode of resonance. The primary objective of this experiment was to measure the generated thrust. A mean value of thrust was measured up to 6.0 lb, corresponding to H2 flow based specific impulse of 2970 s. This value is comparable to measurements in H2-fueled pulsed detonation engines (PDEs). The injection and detonation frequency for this new experimental case was much higher than typical PDEs, where frequencies are usually less than 100 Hz. The compact size of the device and high frequency of detonation yields a thrust-per-unit-volume of approximately 2.0 pounds per cubic inch, and compares favorably with other experiments, which typically have thrust-per-unit-volume of order 0.01 pound per cubic inch. This much higher volumetric efficiency results in a potentially much more practical device than the typical PDE, for a wide range of potential applications, including high-speed boundary layer separation control, for example in hypersonic engine inlets, and propulsion for small aircraft and missiles.

Discrete event simulation and the resultant data storage system response in the operational mission environment of Jupiter-Saturn /Voyager/ spacecraft

NASA Technical Reports Server (NTRS)

Mukhopadhyay, A. K.

1978-01-01

The Data Storage Subsystem Simulator (DSSSIM) simulating (by ground software) occurrence of discrete events in the Voyager mission is described. Functional requirements for Data Storage Subsystems (DSS) simulation are discussed, and discrete event simulation/DSSSIM processing is covered. Four types of outputs associated with a typical DSSSIM run are presented, and DSSSIM limitations and constraints are outlined.

Improving prospective memory performance with future event simulation in traumatic brain injury patients.

PubMed

Mioni, Giovanna; Bertucci, Erica; Rosato, Antonella; Terrett, Gill; Rendell, Peter G; Zamuner, Massimo; Stablum, Franca

2017-06-01

Previous studies have shown that traumatic brain injury (TBI) patients have difficulties with prospective memory (PM). Considering that PM is closely linked to independent living it is of primary interest to develop strategies that can improve PM performance in TBI patients. This study employed Virtual Week task as a measure of PM, and we included future event simulation to boost PM performance. Study 1 evaluated the efficacy of the strategy and investigated possible practice effects. Twenty-four healthy participants performed Virtual Week in a no strategy condition, and 24 healthy participants performed it in a mixed condition (no strategy - future event simulation). In Study 2, 18 TBI patients completed the mixed condition of Virtual Week and were compared with the 24 healthy controls who undertook the mixed condition of Virtual Week in Study 1. All participants also completed a neuropsychological evaluation to characterize the groups on level of cognitive functioning. Study 1 showed that participants in the future event simulation condition outperformed participants in the no strategy condition, and these results were not attributable to practice effects. Results of Study 2 showed that TBI patients performed PM tasks less accurately than controls, but that future event simulation can substantially reduce TBI-related deficits in PM performance. The future event simulation strategy also improved the controls' PM performance. These studies showed the value of future event simulation strategy in improving PM performance in healthy participants as well as in TBI patients. TBI patients performed PM tasks less accurately than controls, confirming prospective memory impairment in these patients. Participants in the future event simulation condition out-performed participants in the no strategy condition. Future event simulation can substantially reduce TBI-related deficits in PM performance. Future event simulation strategy also improved the controls' PM performance. © 2017 The British Psychological Society.

Dynamic modeling and control of a solid-sorbent CO{sub 2} capture process with two-stage bubbling fluidized bed adsorber reactor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Modekurti, S.; Bhattacharyya, D.; Zitney, S.

2012-01-01

Solid-sorbent-based CO{sub 2} capture processes have strong potential for reducing the overall energy penalty for post-combustion capture from the flue gas of a conventional pulverized coal power plant. However, the commercial success of this technology is contingent upon it operating over a wide range of capture rates, transient events, malfunctions, and disturbances, as well as under uncertainties. To study these operational aspects, a dynamic model of a solid-sorbent-based CO{sub 2} capture process has been developed. In this work, a one-dimensional (1D), non-isothermal, dynamic model of a two-stage bubbling fluidized bed (BFB) adsorber-reactor system with overflow-type weir configuration has been developedmore » in Aspen Custom Modeler (ACM). The physical and chemical properties of the sorbent used in this study are based on a sorbent (32D) developed at National Energy Technology Laboratory (NETL). Each BFB is divided into bubble, emulsion, and cloud-wake regions with the assumptions that the bubble region is free of solids while both gas and solid phases coexist in the emulsion and cloud-wake regions. The BFB dynamic model includes 1D partial differential equations (PDEs) for mass and energy balances, along with comprehensive reaction kinetics. In addition to the two BFB models, the adsorber-reactor system includes 1D PDE-based dynamic models of the downcomer and outlet hopper, as well as models of distributors, control valves, and other pressure-drop devices. Consistent boundary and initial conditions are considered for simulating the dynamic model. Equipment items are sized and appropriate heat transfer options, wherever needed, are provided. Finally, a valid pressure-flow network is developed and a lower-level control system is designed. Using ACM, the transient responses of various process variables such as flue gas and sorbent temperatures, overall CO{sub 2} capture, level of solids in the downcomer and hopper have been studied by simulating typical disturbances such as change in the temperature, flowrate, and composition of the flue gas. To maintain the overall CO{sub 2} capture at a desired level in face of the typical disturbances, two control strategies were considered–a proportional-integral-derivative (PID)-based feedback control strategy and a feedforward-augmented feedback control strategy. Dynamic simulation results show that both the strategies result in unacceptable overshoot/undershoot and a long settling time. To improve the control system performance, a linear model predictive controller (LMPC) is designed. In summary, the overall results illustrate how optimizing the operation and control of carbon capture systems can have a significant impact on the extent and the rate at which commercial-scale capture processes will be scaled-up, deployed, and used in the years to come.« less

An extension of the OpenModelica compiler for using Modelica models in a discrete event simulation

DOE PAGES

Nutaro, James

2014-11-03

In this article, a new back-end and run-time system is described for the OpenModelica compiler. This new back-end transforms a Modelica model into a module for the adevs discrete event simulation package, thereby extending adevs to encompass complex, hybrid dynamical systems. The new run-time system that has been built within the adevs simulation package supports models with state-events and time-events and that comprise differential-algebraic systems with high index. Finally, although the procedure for effecting this transformation is based on adevs and the Discrete Event System Specification, it can be adapted to any discrete event simulation package.

The devil is in the details: Comparisons of episodic simulations of positive and negative future events.

PubMed

Puig, Vannia A; Szpunar, Karl K

2017-08-01

Over the past decade, psychologists have devoted considerable attention to episodic simulation-the ability to imagine specific hypothetical events. Perhaps one of the most consistent patterns of data to emerge from this literature is that positive simulations of the future are rated as more detailed than negative simulations of the future, a pattern of results that is commonly interpreted as evidence for a positivity bias in future thinking. In the present article, we demonstrate across two experiments that negative future events are consistently simulated in more detail than positive future events when frequency of prior thinking is taken into account as a possible confounding variable and when level of detail associated with simulated events is assessed using an objective scoring criterion. Our findings are interpreted in the context of the mobilization-minimization hypothesis of event cognition that suggests people are especially likely to devote cognitive resources to processing negative scenarios. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Repetition-Related Reductions in Neural Activity during Emotional Simulations of Future Events.

PubMed

Szpunar, Karl K; Jing, Helen G; Benoit, Roland G; Schacter, Daniel L

2015-01-01

Simulations of future experiences are often emotionally arousing, and the tendency to repeatedly simulate negative future outcomes has been identified as a predictor of the onset of symptoms of anxiety. Nonetheless, next to nothing is known about how the healthy human brain processes repeated simulations of emotional future events. In this study, we present a paradigm that can be used to study repeated simulations of the emotional future in a manner that overcomes phenomenological confounds between positive and negative events. The results show that pulvinar nucleus and orbitofrontal cortex respectively demonstrate selective reductions in neural activity in response to frequently as compared to infrequently repeated simulations of negative and positive future events. Implications for research on repeated simulations of the emotional future in both non-clinical and clinical populations are discussed.

A Simulation of Readiness-Based Sparing Policies

DTIC Science & Technology

2017-06-01

variant of a greedy heuristic algorithm to set stock levels and estimate overall WS availability. Our discrete event simulation is then used to test the...available in the optimization tools. 14. SUBJECT TERMS readiness-based sparing, discrete event simulation, optimization, multi-indenture...variant of a greedy heuristic algorithm to set stock levels and estimate overall WS availability. Our discrete event simulation is then used to test the

DOE Office of Scientific and Technical Information (OSTI.GOV)

Manzini, Gianmarco

This document contains working annotations on the Virtual Element Method (VEM) for the approximate solution of diffusion problems with variable coefficients. To read this document you are assumed to have familiarity with concepts from the numerical discretization of Partial Differential Equations (PDEs) and, in particular, the Finite Element Method (FEM). This document is not an introduction to the FEM, for which many textbooks (also free on the internet) are available. Eventually, this document is intended to evolve into a tutorial introduction to the VEM (but this is really a long-term goal).

PDES Logical Layer Initiation Task.

DTIC Science & Technology

1986-04-28

surface. We have heard such expressions as "topology sits on tcp of geometry." We choose to avoid subordinating one to the other by bringing them together...a mapping from Discipline model to Global model. 38 A~A g d ip . t ~ P A1 / /oaefZ - - 6jOM#AL Mat&mft9 We have attempted to group basqd on the...FIGURE PHASE 2: Conceptualization and Integration. In this phase conceptual entities and relationships are discovered. An integrated conceptual modelO

Stochastic Calculus and Differential Equations for Physics and Finance

NASA Astrophysics Data System (ADS)

McCauley, Joseph L.

2013-02-01

1. Random variables and probability distributions; 2. Martingales, Markov, and nonstationarity; 3. Stochastic calculus; 4. Ito processes and Fokker-Planck equations; 5. Selfsimilar Ito processes; 6. Fractional Brownian motion; 7. Kolmogorov's PDEs and Chapman-Kolmogorov; 8. Non Markov Ito processes; 9. Black-Scholes, martingales, and Feynman-Katz; 10. Stochastic calculus with martingales; 11. Statistical physics and finance, a brief history of both; 12. Introduction to new financial economics; 13. Statistical ensembles and time series analysis; 14. Econometrics; 15. Semimartingales; References; Index.

Analytic Regularity and Polynomial Approximation of Parametric and Stochastic Elliptic PDEs

DTIC Science & Technology

2010-05-31

Todor : Finite elements for elliptic problems with stochastic coefficients Comp. Meth. Appl. Mech. Engg. 194 (2005) 205-228. [14] R. Ghanem and P. Spanos...for elliptic partial differential equations with random input data SIAM J. Num. Anal. 46(2008), 2411–2442. [20] R. Todor , Robust eigenvalue computation...for smoothing operators, SIAM J. Num. Anal. 44(2006), 865– 878. [21] Ch. Schwab and R.A. Todor , Karhúnen-Loève Approximation of Random Fields by

A Model of Controlled Growth

NASA Astrophysics Data System (ADS)

Bressan, Alberto; Lewicka, Marta

2018-03-01

We consider a free boundary problem for a system of PDEs, modeling the growth of a biological tissue. A morphogen, controlling volume growth, is produced by specific cells and then diffused and absorbed throughout the domain. The geometric shape of the growing tissue is determined by the instantaneous minimization of an elastic deformation energy, subject to a constraint on the volumetric growth. For an initial domain with C}^{2,α boundary, our main result establishes the local existence and uniqueness of a classical solution, up to a rigid motion.

A Parallel Stochastic Framework for Reservoir Characterization and History Matching

DOE PAGES

Thomas, Sunil G.; Klie, Hector M.; Rodriguez, Adolfo A.; ...

2011-01-01

The spatial distribution of parameters that characterize the subsurface is never known to any reasonable level of accuracy required to solve the governing PDEs of multiphase flow or species transport through porous media. This paper presents a numerically cheap, yet efficient, accurate and parallel framework to estimate reservoir parameters, for example, medium permeability, using sensor information from measurements of the solution variables such as phase pressures, phase concentrations, fluxes, and seismic and well log data. Numerical results are presented to demonstrate the method.

Sparse Recovery via l1 and L1 Optimization

DTIC Science & Technology

2014-11-01

problem, with t being the descent direc- tion, obtaining ut = uxx + f − 1 µ p(u) (6) as an evolution equation. We can hope that these L1 regularized (or...implementation. He considered a wide class of second–order elliptic equations and, with Friedman [14], an extension to parabolic equa- tions. In [15, 16...obtaining an elliptic PDE, or by gradi- ent descent to obtain a parabolic PDE. Addition- ally, some PDEs can be rewritten using the L1 subgradient such as the

Numerical study of a matrix-free trust-region SQP method for equality constrained optimization.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heinkenschloss, Matthias; Ridzal, Denis; Aguilo, Miguel Antonio

2011-12-01

This is a companion publication to the paper 'A Matrix-Free Trust-Region SQP Algorithm for Equality Constrained Optimization' [11]. In [11], we develop and analyze a trust-region sequential quadratic programming (SQP) method that supports the matrix-free (iterative, in-exact) solution of linear systems. In this report, we document the numerical behavior of the algorithm applied to a variety of equality constrained optimization problems, with constraints given by partial differential equations (PDEs).

Building Flexible User Interfaces for Solving PDEs

NASA Astrophysics Data System (ADS)

Logg, Anders; Wells, Garth N.

2010-09-01

FEniCS is a collection of software tools for the automated solution of differential equations by finite element methods. In this note, we describe how FEniCS can be used to solve a simple nonlinear model problem with varying levels of automation. At one extreme, FEniCS provides tools for the fully automated and adaptive solution of nonlinear partial differential equations. At the other extreme, FEniCS provides a range of tools that allow the computational scientist to experiment with novel solution algorithms.

Explicit finite difference predictor and convex corrector with applications to hyperbolic partial differential equations

NASA Technical Reports Server (NTRS)

Dey, C.; Dey, S. K.

1983-01-01

An explicit finite difference scheme consisting of a predictor and a corrector has been developed and applied to solve some hyperbolic partial differential equations (PDEs). The corrector is a convex-type function which is applied at each time level and at each mesh point. It consists of a parameter which may be estimated such that for larger time steps the algorithm should remain stable and generate a fast speed of convergence to the steady-state solution. Some examples have been given.

Assessment of upper-ocean variability and the Madden-Julian Oscillation in extended-range air-ocean coupled mesoscale simulations

NASA Astrophysics Data System (ADS)

Hong, Xiaodong; Reynolds, Carolyn A.; Doyle, James D.; May, Paul; O'Neill, Larry

2017-06-01

Atmosphere-ocean interaction, particular the ocean response to strong atmospheric forcing, is a fundamental component of the Madden-Julian Oscillation (MJO). In this paper, we examine how model errors in previous Madden-Julian Oscillation (MJO) events can affect the simulation of subsequent MJO events due to increased errors that develop in the upper-ocean before the MJO initiation stage. Two fully coupled numerical simulations with 45-km and 27-km horizontal resolutions were integrated for a two-month period from November to December 2011 using the Navy's limited area Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS®). There are three MJO events that occurred subsequently in early November, mid-November, and mid-December during the simulations. The 45-km simulation shows an excessive warming of the SSTs during the suppressed phase that occurs before the initiation of the second MJO event due to erroneously strong surface net heat fluxes. The simulated second MJO event stalls over the Maritime Continent which prevents the recovery of the deep mixed layer and associated barrier layer. Cross-wavelet analysis of solar radiation and SSTs reveals that the diurnal warming is absent during the second suppressed phase after the second MJO event. The mixed layer heat budget indicates that the cooling is primarily caused by horizontal advection associated with the stalling of the second MJO event and the cool SSTs fail to initiate the third MJO event. When the horizontal resolution is increased to 27-km, three MJOs are simulated and compare well with observations on multi-month timescales. The higher-resolution simulation of the second MJO event and more-realistic upper-ocean response promote the onset of the third MJO event. Simulations performed with analyzed SSTs indicate that the stalling of the second MJO in the 45-km run is a robust feature, regardless of ocean forcing, while the diurnal cycle analysis indicates that both 45-km and 27-km ocean resolutions respond realistically when provided with realistic atmospheric forcing. Thus, the problem in the 45-km simulation appears to originate in the atmosphere. Additional simulations show that while the details of the simulations are sensitive to small changes in the initial integration time, the large differences between the 45-km and 27-km runs during the suppressed phase in early December are robust.

Synchronization of autonomous objects in discrete event simulation

NASA Technical Reports Server (NTRS)

Rogers, Ralph V.

1990-01-01

Autonomous objects in event-driven discrete event simulation offer the potential to combine the freedom of unrestricted movement and positional accuracy through Euclidean space of time-driven models with the computational efficiency of event-driven simulation. The principal challenge to autonomous object implementation is object synchronization. The concept of a spatial blackboard is offered as a potential methodology for synchronization. The issues facing implementation of a spatial blackboard are outlined and discussed.

Simulations and Characteristics of Large Solar Events Propagating Throughout the Heliosphere and Beyond (Invited)

NASA Astrophysics Data System (ADS)

Intriligator, D. S.; Sun, W.; Detman, T. R.; Dryer, Ph D., M.; Intriligator, J.; Deehr, C. S.; Webber, W. R.; Gloeckler, G.; Miller, W. D.

2015-12-01

Large solar events can have severe adverse global impacts at Earth. These solar events also can propagate throughout the heliopshere and into the interstellar medium. We focus on the July 2012 and Halloween 2003 solar events. We simulate these events starting from the vicinity of the Sun at 2.5 Rs. We compare our three dimensional (3D) time-dependent simulations to available spacecraft (s/c) observations at 1 AU and beyond. Based on the comparisons of the predictions from our simulations with in-situ measurements we find that the effects of these large solar events can be observed in the outer heliosphere, the heliosheath, and even into the interstellar medium. We use two simulation models. The HAFSS (HAF Source Surface) model is a kinematic model. HHMS-PI (Hybrid Heliospheric Modeling System with Pickup protons) is a numerical magnetohydrodynamic solar wind (SW) simulation model. Both HHMS-PI and HAFSS are ideally suited for these analyses since starting at 2.5 Rs from the Sun they model the slowly evolving background SW and the impulsive, time-dependent events associated with solar activity. Our models naturally reproduce dynamic 3D spatially asymmetric effects observed throughout the heliosphere. Pre-existing SW background conditions have a strong influence on the propagation of shock waves from solar events. Time-dependence is a crucial aspect of interpreting s/c data. We show comparisons of our simulation results with STEREO A, ACE, Ulysses, and Voyager s/c observations.

Mars Exploration Rover Terminal Descent Mission Modeling and Simulation

NASA Technical Reports Server (NTRS)

Raiszadeh, Behzad; Queen, Eric M.

2004-01-01

Because of NASA's added reliance on simulation for successful interplanetary missions, the MER mission has developed a detailed EDL trajectory modeling and simulation. This paper summarizes how the MER EDL sequence of events are modeled, verification of the methods used, and the inputs. This simulation is built upon a multibody parachute trajectory simulation tool that has been developed in POST I1 that accurately simulates the trajectory of multiple vehicles in flight with interacting forces. In this model the parachute and the suspended bodies are treated as 6 Degree-of-Freedom (6 DOF) bodies. The terminal descent phase of the mission consists of several Entry, Descent, Landing (EDL) events, such as parachute deployment, heatshield separation, deployment of the lander from the backshell, deployment of the airbags, RAD firings, TIRS firings, etc. For an accurate, reliable simulation these events need to be modeled seamlessly and robustly so that the simulations will remain numerically stable during Monte-Carlo simulations. This paper also summarizes how the events have been modeled, the numerical issues, and modeling challenges.

Computer simulation of earthquakes

NASA Technical Reports Server (NTRS)

Cohen, S. C.

1976-01-01

Two computer simulation models of earthquakes were studied for the dependence of the pattern of events on the model assumptions and input parameters. Both models represent the seismically active region by mechanical blocks which are connected to one another and to a driving plate. The blocks slide on a friction surface. In the first model elastic forces were employed and time independent friction to simulate main shock events. The size, length, and time and place of event occurrence were influenced strongly by the magnitude and degree of homogeniety in the elastic and friction parameters of the fault region. Periodically reoccurring similar events were frequently observed in simulations with near homogeneous parameters along the fault, whereas, seismic gaps were a common feature of simulations employing large variations in the fault parameters. The second model incorporated viscoelastic forces and time-dependent friction to account for aftershock sequences. The periods between aftershock events increased with time and the aftershock region was confined to that which moved in the main event.

Simulation studies on the differences between spontaneous and triggered seismicity and on foreshock probabilities

NASA Astrophysics Data System (ADS)

Zhuang, J.; Vere-Jones, D.; Ogata, Y.; Christophersen, A.; Savage, M. K.; Jackson, D. D.

2008-12-01

In this study we investigate the foreshock probabilities calculated from earthquake catalogs from Japan, Southern California and New Zealand. Unlike conventional studies on foreshocks, we use a probability-based declustering method to separate each catalog into stochastic versions of family trees, such that each event is classified as either having been triggered by a preceding event, or being a spontaneous event. The probabilities are determined from parameters that provide the best fit of the real catalogue using a space- time epidemic-type aftershock sequence (ETAS) model. The model assumes that background and triggered earthquakes have the same magnitude dependent triggering capability. A foreshock here is defined as a spontaneous event that has one or more larger descendants, and a triggered foreshock is a triggered event that has one or more larger descendants. The proportion of foreshocks in spontaneous events of each catalog is found to be lower than the proportion of triggered foreshocks in triggered events. One possibility is that this is due to different triggering productivity in spontaneous versus triggered events, i.e., a triggered event triggers more children than a spontaneous events of the same magnitude. To understand what causes the above differences between spontaneous and triggered events, we apply the same procedures to several synthetic catalogs simulated by using different models. The first simulation is done by using the ETAS model with parameters and spontaneous rate fitted from the JMA catalog. The second synthetic catalog is simulated by using an adjusted ETAS model that takes into account the triggering effect from events lower than the magnitude. That is, we simulated the catalog with a low magnitude threshold with the original ETAS model, and then we remove the events smaller than a higher magnitude threshold. The third model for simulation assumes that different triggering behaviors exist between spontaneous event and triggered events. We repeat the fitting and reconstruction procedures to all those simulated catalogs. The reconstruction results for the first synthetic catalog do not show the difference between spontaneous events and triggered event or the differences in foreshock probabilities. On the other hand, results from the synthetic catalogs simulated with the second and the third models clearly reconstruct such differences. In summary our results implies that one of the causes of such differences may be neglecting the triggering effort from events smaller than the cut-off magnitude or magnitude errors. For the objective of forecasting seismicity, we can use a clustering model in which spontaneous events trigger child events in a different way from triggered events to avoid over-predicting earthquake risks with foreshocks. To understand the physical implication of this study, we need further careful studies to compare the real seismicity and the adjusted ETAS model, which takes the triggering effect from events below the cut-off magnitude into account.

Molecular modeling study of binding to the catalytic site of PDE4 enzymes by a novel class of inhibitors

NASA Astrophysics Data System (ADS)

Lawrenz, Morgan E.; Salter, E. A.; Wierzbicki, Andrzej; Thompson, W. J.

Cyclic nucleotide phosphodiesterases (PDEs) comprise a superfamily of enzymes that hydrolyze the second messengers adenosine and guanosine 3',5'-cyclic monophosphate (cAMP and cGMP) to their noncyclic nucleotides (5'-AMP and 5'-GMP). Selective inhibitors of all 11 gene families of PDEs are being sought based on the different biochemical properties of the different isoforms, including their substrate specificities. The PDE4 gene family consists of cAMP-specific isoforms; selective PDE4 inhibitors such as rolipram have been developed, and related agents are used clinically as anti-inflammatory agents for asthma and COPD. The known crystal structures of PDE4 bound with rolipram and IBMX have allowed us to define plausible binding orientations for a novel class of benzylpyridazinone-based PDE4 inhibitors represented by EMD 94360 and EMD 95832 that are structurally distinct from rolipram. Molecular mechanics modeling with autodocking is used to explore energetically favorable binding orientations within the PDE4 catalytic site. We present two putative orientations for EMD 94360/95832 inhibitor binding. Our estimated interaction energies for rolipram, IBMX, EMD 94360, and EMD 95832 are consistent with the experimental data for their IC50 values. Key binding residues and interactions in these orientations are identified and compared with known binding motifs proposed for rolipram. The experimentally observed improved strength of inhibition exhibited by this novel class of PDE4 inhibitors is explained by the molecular modeling reported here.

Phosphodiesterase Inhibition to Target the Synaptic Dysfunction in Alzheimer's Disease

NASA Astrophysics Data System (ADS)

Bales, Kelly R.; Plath, Niels; Svenstrup, Niels; Menniti, Frank S.

Alzheimer's Disease (AD) is a disease of synaptic dysfunction that ultimately proceeds to neuronal death. There is a wealth of evidence that indicates the final common mediator of this neurotoxic process is the formation and actions on synaptotoxic b-amyloid (Aβ). The premise in this review is that synaptic dysfunction may also be an initiating factor in for AD and promote synaptotoxic Aβ formation. This latter hypothesis is consistent with the fact that the most common risk factors for AD, apolipoprotein E (ApoE) allele status, age, education, and fitness, encompass suboptimal synaptic function. Thus, the synaptic dysfunction in AD may be both cause and effect, and remediating synaptic dysfunction in AD may have acute effects on the symptoms present at the initiation of therapy and also slow disease progression. The cyclic nucleotide (cAMP and cGMP) signaling systems are intimately involved in the regulation of synaptic homeostasis. The phosphodiesterases (PDEs) are a superfamily of enzymes that critically regulate spatial and temporal aspects of cyclic nucleotide signaling through metabolic inactivation of cAMP and cGMP. Thus, targeting the PDEs to promote improved synaptic function, or 'synaptic resilience', may be an effective and facile approach to new symptomatic and disease modifying therapies for AD. There continues to be a significant drug discovery effort aimed at discovering PDE inhibitors to treat a variety of neuropsychiatric disorders. Here we review the current status of those efforts as they relate to potential new therapies for AD.

PDE and cognitive processing: beyond the memory domain.

PubMed

Heckman, P R A; Blokland, A; Ramaekers, J; Prickaerts, J

2015-03-01

Phosphodiesterase inhibitors (PDE-Is) enhance cAMP and/or cGMP signaling via reducing the degradation of these cyclic nucleotides. Both cAMP and cGMP signaling are essential for a variety of cellular functions and exert their effects both pre- and post-synaptically. Either of these second messengers relays and amplifies incoming signals at receptors on the cell surface making them important elements in signal transduction cascades and essential in cellular signaling in a variety of cell functions including neurotransmitter release and neuroprotection. Consequently, these processes can be influenced by PDE-Is as they increase cAMP and/or cGMP concentrations. PDE-Is have been considered as possible therapeutic agents to treat impaired memory function linked to several brain disorders, including depression, schizophrenia and Alzheimer's disease (AD). This review will, however, focus on the possible role of phosphodiesterases (PDEs) in cognitive decline beyond the memory domain. Here we will discuss the involvement of PDEs on three related domains: attention, information filtering (sensory- and sensorimotor gating) and response inhibition (drug-induced hyperlocomotion). Currently, these are emerging cognitive domains in the field of PDE research. Here we discuss experimental studies and the potential beneficial effects of PDE-I drugs on these cognitive domains, as effects of PDE-Is on these domains could potentially influence effects on memory performance. Overall, PDE4 seems to be the most promising target for all domains discussed in this review. Copyright © 2014 Elsevier Inc. All rights reserved.

The high-affinity phosphodiesterase PdeH regulates development and aflatoxin biosynthesis in Aspergillus flavus.

PubMed

Yang, Kunlong; Liu, Yinghang; Liang, Linlin; Li, Zhenguo; Qin, Qiuping; Nie, Xinyi; Wang, Shihua

2017-04-01

Cyclic AMP signaling controls a range of physiological processes in response to extracellular stimuli in organisms. Among the signaling cascades, cAMP, as a second messenger, is orchestrated by adenylate cyclase (biosynthesis) and cAMP phosphodiesterases (PDEs) (hydrolysis). In this study, we investigated the function of the high-affinity (PdeH) and low-affinity (PdeL) cAMP phosphodiesterase from the carcinogenic aflatoxin producing fungus Aspergillus flavus, and found that instead of PdeL, inactivation of PdeH exhibited a reduction in conidiation and sclerotia formation. However, the ΔpdeL/ΔpdeH mutant exhibited an enhanced phenotype defects, a similar phenotype defects to wild-type strain treated with exogenous cAMP. The activation of PKA activity was inhibited in the ΔpdeH or ΔpdeL/ΔpdeH mutant, both of whom exhibited increasing AF production. Further analysis by qRT-PCR revealed that pdeH had a high transcriptional level compared to pdeL in wild-type strain, and affected pdeL transcription. Green fluorescent protein tagging at the C-terminus of PDEs showed that PdeH-GFP is broadly compartmentalized in the cytosol, while PdeL-GFP localized mainly to the nucleus. Overall, our results indicated that PdeH plays a major role, but has overlapping function with PdeL, in vegetative growth, development and AF biosynthesis in A. flavus. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Equalizer technology followed by DIGE-based proteomics for detection of cellular proteins in artificial peritoneal dialysis effluents.

PubMed

Lichtenauer, Anton Michael; Herzog, Rebecca; Tarantino, Silvia; Aufricht, Christoph; Kratochwill, Klaus

2014-05-01

Peritoneal dialysis effluent (PDE) represents a rich pool of potential biomarkers for monitoring disease and therapy. Until now, proteomic studies have been hindered by the plasma-like composition of the PDE. Beads covered with a peptide library are a promising approach to remove high abundant proteins and concentrate the sample in one step. In this study, a novel approach for proteomic biomarker identification in PDEs consisting of a depletion and concentration step followed by 2D gel based protein quantification was established. To prove this experimental concept a model system of artificial PDEs was established by spiking unused peritoneal dialysis (PD) fluids with cellular proteins reflecting control conditions or cell stress. Using this procedure, we were able to reduce the amount of high abundant plasma proteins and concentrate low abundant proteins while preserving changes in abundance of proteins with cellular origin. The alterations in abundance of the investigated marker for cell stress, the heat shock proteins, showed similar abundance profiles in the artificial PDE as in pure cell culture samples. Our results demonstrate the efficacy of this system in detecting subtle changes in cellular protein expression triggered by unphysiological stress stimuli typical in PD, which could serve as biomarkers. Further studies using patients' PDE will be necessary to prove the concept in clinical PD and to assess whether this technique is also informative regarding enriching low abundant plasma derived protein biomarker in the PDE. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Direct modeling for computational fluid dynamics

NASA Astrophysics Data System (ADS)

Xu, Kun

2015-06-01

All fluid dynamic equations are valid under their modeling scales, such as the particle mean free path and mean collision time scale of the Boltzmann equation and the hydrodynamic scale of the Navier-Stokes (NS) equations. The current computational fluid dynamics (CFD) focuses on the numerical solution of partial differential equations (PDEs), and its aim is to get the accurate solution of these governing equations. Under such a CFD practice, it is hard to develop a unified scheme that covers flow physics from kinetic to hydrodynamic scales continuously because there is no such governing equation which could make a smooth transition from the Boltzmann to the NS modeling. The study of fluid dynamics needs to go beyond the traditional numerical partial differential equations. The emerging engineering applications, such as air-vehicle design for near-space flight and flow and heat transfer in micro-devices, do require further expansion of the concept of gas dynamics to a larger domain of physical reality, rather than the traditional distinguishable governing equations. At the current stage, the non-equilibrium flow physics has not yet been well explored or clearly understood due to the lack of appropriate tools. Unfortunately, under the current numerical PDE approach, it is hard to develop such a meaningful tool due to the absence of valid PDEs. In order to construct multiscale and multiphysics simulation methods similar to the modeling process of constructing the Boltzmann or the NS governing equations, the development of a numerical algorithm should be based on the first principle of physical modeling. In this paper, instead of following the traditional numerical PDE path, we introduce direct modeling as a principle for CFD algorithm development. Since all computations are conducted in a discretized space with limited cell resolution, the flow physics to be modeled has to be done in the mesh size and time step scales. Here, the CFD is more or less a direct construction of discrete numerical evolution equations, where the mesh size and time step will play dynamic roles in the modeling process. With the variation of the ratio between mesh size and local particle mean free path, the scheme will capture flow physics from the kinetic particle transport and collision to the hydrodynamic wave propagation. Based on the direct modeling, a continuous dynamics of flow motion will be captured in the unified gas-kinetic scheme. This scheme can be faithfully used to study the unexplored non-equilibrium flow physics in the transition regime.

Characterizing rare-event property distributions via replicate molecular dynamics simulations of proteins.

PubMed

Krishnan, Ranjani; Walton, Emily B; Van Vliet, Krystyn J

2009-11-01

As computational resources increase, molecular dynamics simulations of biomolecules are becoming an increasingly informative complement to experimental studies. In particular, it has now become feasible to use multiple initial molecular configurations to generate an ensemble of replicate production-run simulations that allows for more complete characterization of rare events such as ligand-receptor unbinding. However, there are currently no explicit guidelines for selecting an ensemble of initial configurations for replicate simulations. Here, we use clustering analysis and steered molecular dynamics simulations to demonstrate that the configurational changes accessible in molecular dynamics simulations of biomolecules do not necessarily correlate with observed rare-event properties. This informs selection of a representative set of initial configurations. We also employ statistical analysis to identify the minimum number of replicate simulations required to sufficiently sample a given biomolecular property distribution. Together, these results suggest a general procedure for generating an ensemble of replicate simulations that will maximize accurate characterization of rare-event property distributions in biomolecules.

Two-Dimensional Modeling of Heat and Moisture Dynamics in Swedish Roads: Model Set up and Parameter Sensitivity

NASA Astrophysics Data System (ADS)

Rasul, H.; Wu, M.; Olofsson, B.

2017-12-01

Modelling moisture and heat changes in road layers is very important to understand road hydrology and for better construction and maintenance of roads in a sustainable manner. In cold regions due to the freezing/thawing process in the partially saturated material of roads, the modeling task will become more complicated than simple model of flow through porous media without freezing/thawing pores considerations. This study is presenting a 2-D model simulation for a section of highway with considering freezing/thawing and vapor changes. Partial deferential equations (PDEs) are used in formulation of the model. Parameters are optimized from modelling results based on the measured data from test station on E18 highway near Stockholm. Impacts of phase change considerations in the modelling are assessed by comparing the modeled soil moisture with TDR-measured data. The results show that the model can be used for prediction of water and ice content in different layers of the road and at different seasons. Parameter sensitivities are analyzed by implementing a calibration strategy. In addition, the phase change consideration is evaluated in the modeling process, by comparing the PDE model with another model without considerations of freezing/thawing in roads. The PDE model shows high potential in understanding the moisture dynamics in the road system.

Stochastic Ocean Predictions with Dynamically-Orthogonal Primitive Equations

NASA Astrophysics Data System (ADS)

Subramani, D. N.; Haley, P., Jr.; Lermusiaux, P. F. J.

2017-12-01

The coastal ocean is a prime example of multiscale nonlinear fluid dynamics. Ocean fields in such regions are complex and intermittent with unstationary heterogeneous statistics. Due to the limited measurements, there are multiple sources of uncertainties, including the initial conditions, boundary conditions, forcing, parameters, and even the model parameterizations and equations themselves. For efficient and rigorous quantification and prediction of these uncertainities, the stochastic Dynamically Orthogonal (DO) PDEs for a primitive equation ocean modeling system with a nonlinear free-surface are derived and numerical schemes for their space-time integration are obtained. Detailed numerical studies with idealized-to-realistic regional ocean dynamics are completed. These include consistency checks for the numerical schemes and comparisons with ensemble realizations. As an illustrative example, we simulate the 4-d multiscale uncertainty in the Middle Atlantic/New York Bight region during the months of Jan to Mar 2017. To provide intitial conditions for the uncertainty subspace, uncertainties in the region were objectively analyzed using historical data. The DO primitive equations were subsequently integrated in space and time. The probability distribution function (pdf) of the ocean fields is compared to in-situ, remote sensing, and opportunity data collected during the coincident POSYDON experiment. Results show that our probabilistic predictions had skill and are 3- to 4- orders of magnitude faster than classic ensemble schemes.

Low-rank separated representation surrogates of high-dimensional stochastic functions: Application in Bayesian inference

NASA Astrophysics Data System (ADS)

Validi, AbdoulAhad

2014-03-01

This study introduces a non-intrusive approach in the context of low-rank separated representation to construct a surrogate of high-dimensional stochastic functions, e.g., PDEs/ODEs, in order to decrease the computational cost of Markov Chain Monte Carlo simulations in Bayesian inference. The surrogate model is constructed via a regularized alternative least-square regression with Tikhonov regularization using a roughening matrix computing the gradient of the solution, in conjunction with a perturbation-based error indicator to detect optimal model complexities. The model approximates a vector of a continuous solution at discrete values of a physical variable. The required number of random realizations to achieve a successful approximation linearly depends on the function dimensionality. The computational cost of the model construction is quadratic in the number of random inputs, which potentially tackles the curse of dimensionality in high-dimensional stochastic functions. Furthermore, this vector-valued separated representation-based model, in comparison to the available scalar-valued case, leads to a significant reduction in the cost of approximation by an order of magnitude equal to the vector size. The performance of the method is studied through its application to three numerical examples including a 41-dimensional elliptic PDE and a 21-dimensional cavity flow.

A model and variance reduction method for computing statistical outputs of stochastic elliptic partial differential equations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vidal-Codina, F., E-mail: fvidal@mit.edu; Nguyen, N.C., E-mail: cuongng@mit.edu; Giles, M.B., E-mail: mike.giles@maths.ox.ac.uk

We present a model and variance reduction method for the fast and reliable computation of statistical outputs of stochastic elliptic partial differential equations. Our method consists of three main ingredients: (1) the hybridizable discontinuous Galerkin (HDG) discretization of elliptic partial differential equations (PDEs), which allows us to obtain high-order accurate solutions of the governing PDE; (2) the reduced basis method for a new HDG discretization of the underlying PDE to enable real-time solution of the parameterized PDE in the presence of stochastic parameters; and (3) a multilevel variance reduction method that exploits the statistical correlation among the different reduced basismore » approximations and the high-fidelity HDG discretization to accelerate the convergence of the Monte Carlo simulations. The multilevel variance reduction method provides efficient computation of the statistical outputs by shifting most of the computational burden from the high-fidelity HDG approximation to the reduced basis approximations. Furthermore, we develop a posteriori error estimates for our approximations of the statistical outputs. Based on these error estimates, we propose an algorithm for optimally choosing both the dimensions of the reduced basis approximations and the sizes of Monte Carlo samples to achieve a given error tolerance. We provide numerical examples to demonstrate the performance of the proposed method.« less

Modeling hexavalent chromium removal in a Bacillus sp. fixed-film bioreactor.

PubMed

Nkhalambayausi-Chirwa, Evans M; Wang, Yi-Tin

2004-09-30

A one-dimensional diffusion-reaction model was developed to simulate Cr(VI) reduction in a Bacillus sp. pure culture biofilm reactor with glucose as a sole supplied carbon and energy source. Substrate utilization and Cr(VI) reduction in the biofilm was best represented by a system of (second-order) partial differential equations (PDEs). The PDE system was solved by the (fourth-order) Runge-Kutta method adjusted for mass transport resistance using the (second-order) Crank-Nicholson and Backward Euler finite difference methods. A heuristic procedure (genetic search algorithm) was used to find global optimum values of Cr(VI) reduction and substrate utilization rate kinetic parameters. The fixed-film bioreactor system yielded higher values of the maximum specific Cr(VI) reduction rate coefficient and Cr(VI) reduction capacity (kmc = 0.062 1/h, and Rc = 0.13 mg/mg, respectively) than previously determined in batch reactors (kmc = 0.022 1/h and Rc = 0.012 mg/mg). The model predicted effluent Cr(VI) concentration well with 98.9% confidence (sigmay2 = 2.37 mg2/L2, N = 119) and effluent glucose with 96.4 % confidence (sigmay(w)2 = 5402 mg2/L2, N = 121, w = 100) over a wide range of Cr(VI) loadings (10-498 mg Cr(VI)/L/d). Copyright 2004 Wiley Periodicals, Inc.

A non-Fourier approach towards the analysis of heat transfer enhancement with water based nanofluids through a channel

NASA Astrophysics Data System (ADS)

Dil, Taimoor; Khan, M. Sabeel

2018-05-01

In this article, a non-Fourier approach to model the heat transfer phenomenon in nanofluids having application to automotive industry is studied. In this respect, a recently proposed hyperbolic heat flux equation is embedded into the heat energy equation and thereby incorporating the effect of thermal relaxation time. Nanofluids are formed by considering copper oxide (CuO), Titanium dioxide (TiO2) and Aluminum oxide (Al2O3) nano-solid particles in the base fluid. The flow governing system of PDEs along with boundary conditions is transformed into its respective coupled system of nonlinear ODEs using suitable similarity functions. Runge-Kutta-Fehlberg (RK-5) numerical scheme embedded with shooting method is implemented and used to solve the obtained boundary value problem. Numerical simulations are performed and tabulated to analyze the influence of solid volume fraction on local coefficient of skin-friction and Nusselt number. A comparison is made between the results by Fourier and present heat flux model. We conclude that the presented new approach is more general and thus allows predicting the influence of thermal relaxation time on the heat transfer characteristics. Moreover, consideration of present model over the Fourier model helps to predict the actual temporal behavior of solution.

Emotional intensity in episodic autobiographical memory and counterfactual thinking.

PubMed

Stanley, Matthew L; Parikh, Natasha; Stewart, Gregory W; De Brigard, Felipe

2017-02-01

Episodic counterfactual thoughts-imagined alternative ways in which personal past events might have occurred-are frequently accompanied by intense emotions. Here, participants recollected positive and negative autobiographical memories and then generated better and worse episodic counterfactual events from those memories. Our results suggest that the projected emotional intensity during the simulated remembered/imagined event is significantly higher than but typically positively related to the emotional intensity while remembering/imagining the event. Furthermore, repeatedly simulating counterfactual events heightened the emotional intensity felt while simulating the counterfactual event. Finally, for both the emotional intensity accompanying the experience of remembering/imagining and the projected emotional intensity during the simulated remembered/imagined event, the emotional intensity of negative memories was greater than the emotional intensity of upward counterfactuals generated from them but lower than the emotional intensity of downward counterfactuals generated from them. These findings are discussed in relation to clinical work and functional theories of counterfactual thinking. Copyright © 2017 Elsevier Inc. All rights reserved.

Desktop Modeling and Simulation: Parsimonious, yet Effective Discrete-Event Simulation Analysis

NASA Technical Reports Server (NTRS)

Bradley, James R.

2012-01-01

This paper evaluates how quickly students can be trained to construct useful discrete-event simulation models using Excel The typical supply chain used by many large national retailers is described, and an Excel-based simulation model is constructed of it The set of programming and simulation skills required for development of that model are then determined we conclude that six hours of training are required to teach the skills to MBA students . The simulation presented here contains all fundamental functionallty of a simulation model, and so our result holds for any discrete-event simulation model. We argue therefore that Industry workers with the same technical skill set as students having completed one year in an MBA program can be quickly trained to construct simulation models. This result gives credence to the efficacy of Desktop Modeling and Simulation whereby simulation analyses can be quickly developed, run, and analyzed with widely available software, namely Excel.

Consistent simulation of direct-photon production in hadron collisions including associated two-jet production

NASA Astrophysics Data System (ADS)

Odaka, Shigeru; Kurihara, Yoshimasa

2016-05-01

We have developed an event generator for direct-photon production in hadron collisions, including associated 2-jet production in the framework of the GR@PPA event generator. The event generator consistently combines γ + 2-jet production processes with the lowest-order γ + jet and photon-radiation (fragmentation) processes from quantum chromodynamics (QCD) 2-jet production using a subtraction method. The generated events can be fed to general-purpose event generators to facilitate the addition of hadronization and decay simulations. Using the obtained event information, we can simulate photon isolation and hadron-jet reconstruction at the particle (hadron) level. The simulation reasonably reproduces measurement data obtained at the large hadron collider (LHC) concerning not only the inclusive photon spectrum, but also the correlation between the photon and jet. The simulation implies that the contribution of the γ + 2-jet is very large, especially in low photon-pT ( ≲ 50 GeV) regions. Discrepancies observed at low pT, although marginal, may indicate the necessity for the consideration of further higher-order processes. Unambiguous particle-level definition of the photon-isolation condition for the signal events is desired to be given explicitly in future measurements.

Assessment of Critical Events Corridors through Multivariate Cascading Outages Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Makarov, Yuri V.; Samaan, Nader A.; Diao, Ruisheng

2011-10-17

Massive blackouts of electrical power systems in North America over the past decade has focused increasing attention upon ways to identify and simulate network events that may potentially lead to widespread network collapse. This paper summarizes a method to simulate power-system vulnerability to cascading failures to a supplied set of initiating events synonymously termed as Extreme Events. The implemented simulation method is currently confined to simulating steady state power-system response to a set of extreme events. The outlined method of simulation is meant to augment and provide a new insight into bulk power transmission network planning that at present remainsmore » mainly confined to maintaining power system security for single and double component outages under a number of projected future network operating conditions. Although one of the aims of this paper is to demonstrate the feasibility of simulating network vulnerability to cascading outages, a more important goal has been to determine vulnerable parts of the network that may potentially be strengthened in practice so as to mitigate system susceptibility to cascading failures. This paper proposes to demonstrate a systematic approach to analyze extreme events and identify vulnerable system elements that may be contributing to cascading outages. The hypothesis of critical events corridors is proposed to represent repeating sequential outages that can occur in the system for multiple initiating events. The new concept helps to identify system reinforcements that planners could engineer in order to 'break' the critical events sequences and therefore lessen the likelihood of cascading outages. This hypothesis has been successfully validated with a California power system model.« less

The Effects of Time Advance Mechanism on Simple Agent Behaviors in Combat Simulations

DTIC Science & Technology

2011-12-01

modeling packages that illustrate the differences between discrete-time simulation (DTS) and discrete-event simulation ( DES ) methodologies. Many combat... DES ) models , often referred to as “next-event” (Law and Kelton 2000) or discrete time simulation (DTS), commonly referred to as “time-step.” DTS...discrete-time simulation (DTS) and discrete-event simulation ( DES ) methodologies. Many combat models use DTS as their simulation time advance mechanism

Teaching sexual history-taking skills using the Sexual Events Classification System.

PubMed

Fidler, Donald C; Petri, Justin Daniel; Chapman, Mark

2010-01-01

The authors review the literature about educational programs for teaching sexual history-taking skills and describe novel techniques for teaching these skills. Psychiatric residents enrolled in a brief sexual history-taking course that included instruction on the Sexual Events Classification System, feedback on residents' video-recorded interviews with simulated patients, discussion of videos that simulated bad interviews, simulated patients, and a competency scoring form to score a video of a simulated interview. After the course, residents completed an anonymous survey to assess the usefulness of the experience. After the course, most residents felt more comfortable taking sexual histories. They described the Sexual Events Classification System and simulated interviews as practical methods for teaching sexual history-taking skills. The Sexual Events Classification System and simulated patient experiences may serve as a practical model for teaching sexual history-taking skills to general psychiatric residents.

The Application of SNiPER to the JUNO Simulation

NASA Astrophysics Data System (ADS)

Lin, Tao; Zou, Jiaheng; Li, Weidong; Deng, Ziyan; Fang, Xiao; Cao, Guofu; Huang, Xingtao; You, Zhengyun; JUNO Collaboration

2017-10-01

The JUNO (Jiangmen Underground Neutrino Observatory) is a multipurpose neutrino experiment which is designed to determine neutrino mass hierarchy and precisely measure oscillation parameters. As one of the important systems, the JUNO offline software is being developed using the SNiPER software. In this proceeding, we focus on the requirements of JUNO simulation and present the working solution based on the SNiPER. The JUNO simulation framework is in charge of managing event data, detector geometries and materials, physics processes, simulation truth information etc. It glues physics generator, detector simulation and electronics simulation modules together to achieve a full simulation chain. In the implementation of the framework, many attractive characteristics of the SNiPER have been used, such as dynamic loading, flexible flow control, multiple event management and Python binding. Furthermore, additional efforts have been made to make both detector and electronics simulation flexible enough to accommodate and optimize different detector designs. For the Geant4-based detector simulation, each sub-detector component is implemented as a SNiPER tool which is a dynamically loadable and configurable plugin. So it is possible to select the detector configuration at runtime. The framework provides the event loop to drive the detector simulation and interacts with the Geant4 which is implemented as a passive service. All levels of user actions are wrapped into different customizable tools, so that user functions can be easily extended by just adding new tools. The electronics simulation has been implemented by following an event driven scheme. The SNiPER task component is used to simulate data processing steps in the electronics modules. The electronics and trigger are synchronized by triggered events containing possible physics signals. The JUNO simulation software has been released and is being used by the JUNO collaboration to do detector design optimization, event reconstruction algorithm development and physics sensitivity studies.

Comparison of ground motions from hybrid simulations to nga prediction equations

USGS Publications Warehouse

Star, L.M.; Stewart, J.P.; Graves, R.W.

2011-01-01

We compare simulated motions for a Mw 7.8 rupture scenario on the San Andreas Fault known as the ShakeOut event, two permutations with different hypocenter locations, and a Mw 7.15 Puente Hills blind thrust scenario, to median and dispersion predictions from empirical NGA ground motion prediction equations. We find the simulated motions attenuate faster with distance than is predicted by the NGA models for periods less than about 5.0 s After removing this distance attenuation bias, the average residuals of the simulated events (i.e., event terms) are generally within the scatter of empirical event terms, although the ShakeOut simulation appears to be a high static stress drop event. The intraevent dispersion in the simulations is lower than NGA values at short periods and abruptly increases at 1.0 s due to different simulation procedures at short and long periods. The simulated motions have a depth-dependent basin response similar to the NGA models, and also show complex effects in which stronger basin response occurs when the fault rupture transmits energy into a basin at low angle, which is not predicted by the NGA models. Rupture directivity effects are found to scale with the isochrone parameter ?? 2011, Earthquake Engineering Research Institute.

Repetition-related reductions in neural activity reveal component processes of mental simulation.

PubMed

Szpunar, Karl K; St Jacques, Peggy L; Robbins, Clifford A; Wig, Gagan S; Schacter, Daniel L

2014-05-01

In everyday life, people adaptively prepare for the future by simulating dynamic events about impending interactions with people, objects and locations. Previous research has consistently demonstrated that a distributed network of frontal-parietal-temporal brain regions supports this ubiquitous mental activity. Nonetheless, little is known about the manner in which specific regions of this network contribute to component features of future simulation. In two experiments, we used a functional magnetic resonance (fMR)-repetition suppression paradigm to demonstrate that distinct frontal-parietal-temporal regions are sensitive to processing the scenarios or what participants imagined was happening in an event (e.g., medial prefrontal, posterior cingulate, temporal-parietal and middle temporal cortices are sensitive to the scenarios associated with future social events), people (medial prefrontal cortex), objects (inferior frontal and premotor cortices) and locations (posterior cingulate/retrosplenial, parahippocampal and posterior parietal cortices) that typically constitute simulations of personal future events. This pattern of results demonstrates that the neural substrates of these component features of event simulations can be reliably identified in the context of a task that requires participants to simulate complex, everyday future experiences.

Necessary optimality conditions for infinite dimensional state constrained control problems

NASA Astrophysics Data System (ADS)

Frankowska, H.; Marchini, E. M.; Mazzola, M.

2018-06-01

This paper is concerned with first order necessary optimality conditions for state constrained control problems in separable Banach spaces. Assuming inward pointing conditions on the constraint, we give a simple proof of Pontryagin maximum principle, relying on infinite dimensional neighboring feasible trajectories theorems proved in [20]. Further, we provide sufficient conditions guaranteeing normality of the maximum principle. We work in the abstract semigroup setting, but nevertheless we apply our results to several concrete models involving controlled PDEs. Pointwise state constraints (as positivity of the solutions) are allowed.

Program For Parallel Discrete-Event Simulation

NASA Technical Reports Server (NTRS)

Beckman, Brian C.; Blume, Leo R.; Geiselman, John S.; Presley, Matthew T.; Wedel, John J., Jr.; Bellenot, Steven F.; Diloreto, Michael; Hontalas, Philip J.; Reiher, Peter L.; Weiland, Frederick P.

1991-01-01

User does not have to add any special logic to aid in synchronization. Time Warp Operating System (TWOS) computer program is special-purpose operating system designed to support parallel discrete-event simulation. Complete implementation of Time Warp mechanism. Supports only simulations and other computations designed for virtual time. Time Warp Simulator (TWSIM) subdirectory contains sequential simulation engine interface-compatible with TWOS. TWOS and TWSIM written in, and support simulations in, C programming language.

Design of virtual simulation experiment based on key events

NASA Astrophysics Data System (ADS)

Zhong, Zheng; Zhou, Dongbo; Song, Lingxiu

2018-06-01

Considering complex content and lacking of guidance in virtual simulation experiments, the key event technology in VR narrative theory was introduced for virtual simulation experiment to enhance fidelity and vividness process. Based on the VR narrative technology, an event transition structure was designed to meet the need of experimental operation process, and an interactive event processing model was used to generate key events in interactive scene. The experiment of" margin value of bees foraging" based on Biologic morphology was taken as an example, many objects, behaviors and other contents were reorganized. The result shows that this method can enhance the user's experience and ensure experimental process complete and effectively.

Arcus end-to-end simulations

NASA Astrophysics Data System (ADS)

Wilms, Joern; Guenther, H. Moritz; Dauser, Thomas; Huenemoerder, David P.; Ptak, Andrew; Smith, Randall; Arcus Team

2018-01-01

We present an overview of the end-to-end simulation environment that we are implementing as part of the Arcus phase A Study. With the rcus simulator, we aim to to model the imaging, detection, and event reconstruction properties of the spectrometer. The simulator uses a Monte Carlo ray-trace approach, projecting photons onto the Arcus focal plane from the silicon pore optic mirrors and critical-angle transmission gratings. We simulate the detection and read-out of the photons in the focal plane CCDs with software originally written for the eROSITA and Athena-WFI detectors; we include all relevant detector physics, such as charge splitting, and effects of the detector read-out, such as out of time events. The output of the simulation chain is an event list that closely resembles the data expected during flight. This event list is processed using a prototype event reconstruction chain for the order separation, wavelength calibration, and effective area calibration. The output is compatible with standard X-ray astronomical analysis software.During phase A, the end-to-end simulation approach is used to demonstrate the overall performance of the mission, including a full simulation of the calibration effort. Continued development during later phases of the mission will ensure that the simulator remains a faithful representation of the true mission capabilities, and will ultimately be used as the Arcus calibration model.

The added value of convection permitting simulations of extreme precipitation events over the eastern Mediterranean

NASA Astrophysics Data System (ADS)

Zittis, G.; Bruggeman, A.; Camera, C.; Hadjinicolaou, P.; Lelieveld, J.

2017-07-01

Climate change is expected to substantially influence precipitation amounts and distribution. To improve simulations of extreme rainfall events, we analyzed the performance of different convection and microphysics parameterizations of the WRF (Weather Research and Forecasting) model at very high horizontal resolutions (12, 4 and 1 km). Our study focused on the eastern Mediterranean climate change hot-spot. Five extreme rainfall events over Cyprus were identified from observations and were dynamically downscaled from the ERA-Interim (EI) dataset with WRF. We applied an objective ranking scheme, using a 1-km gridded observational dataset over Cyprus and six different performance metrics, to investigate the skill of the WRF configurations. We evaluated the rainfall timing and amounts for the different resolutions, and discussed the observational uncertainty over the particular extreme events by comparing three gridded precipitation datasets (E-OBS, APHRODITE and CHIRPS). Simulations with WRF capture rainfall over the eastern Mediterranean reasonably well for three of the five selected extreme events. For these three cases, the WRF simulations improved the ERA-Interim data, which strongly underestimate the rainfall extremes over Cyprus. The best model performance is obtained for the January 1989 event, simulated with an average bias of 4% and a modified Nash-Sutcliff of 0.72 for the 5-member ensemble of the 1-km simulations. We found overall added value for the convection-permitting simulations, especially over regions of high-elevation. Interestingly, for some cases the intermediate 4-km nest was found to outperform the 1-km simulations for low-elevation coastal parts of Cyprus. Finally, we identified significant and inconsistent discrepancies between the three, state of the art, gridded precipitation datasets for the tested events, highlighting the observational uncertainty in the region.

An Advanced Simulation Framework for Parallel Discrete-Event Simulation

NASA Technical Reports Server (NTRS)

Li, P. P.; Tyrrell, R. Yeung D.; Adhami, N.; Li, T.; Henry, H.

1994-01-01

Discrete-event simulation (DEVS) users have long been faced with a three-way trade-off of balancing execution time, model fidelity, and number of objects simulated. Because of the limits of computer processing power the analyst is often forced to settle for less than desired performances in one or more of these areas.

The cost of conservative synchronization in parallel discrete event simulations

NASA Technical Reports Server (NTRS)

Nicol, David M.

1990-01-01

The performance of a synchronous conservative parallel discrete-event simulation protocol is analyzed. The class of simulation models considered is oriented around a physical domain and possesses a limited ability to predict future behavior. A stochastic model is used to show that as the volume of simulation activity in the model increases relative to a fixed architecture, the complexity of the average per-event overhead due to synchronization, event list manipulation, lookahead calculations, and processor idle time approach the complexity of the average per-event overhead of a serial simulation. The method is therefore within a constant factor of optimal. The analysis demonstrates that on large problems--those for which parallel processing is ideally suited--there is often enough parallel workload so that processors are not usually idle. The viability of the method is also demonstrated empirically, showing how good performance is achieved on large problems using a thirty-two node Intel iPSC/2 distributed memory multiprocessor.

WE-AB-204-07: Spatiotemporal Distribution of the FDG PET Tracer in Solid Tumors: Contributions of Diffusion and Convection Mechanisms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Soltani, M; Sefidgar, M; Bazmara, H

2015-06-15

Purpose: In this study, a mathematical model is utilized to simulate FDG distribution in tumor tissue. In contrast to conventional compartmental modeling, tracer distributions across space and time are directly linked together (i.e. moving beyond ordinary differential equations (ODEs) to utilizing partial differential equations (PDEs) coupling space and time). The diffusion and convection transport mechanisms are both incorporated to model tracer distribution. We aimed to investigate the contributions of these two mechanisms on FDG distribution for various tumor geometries obtained from PET/CT images. Methods: FDG transport was simulated via a spatiotemporal distribution model (SDM). The model is based on amore » 5K compartmental model. We model the fact that tracer concentration in the second compartment (extracellular space) is modulated via convection and diffusion. Data from n=45 patients with pancreatic tumors as imaged using clinical FDG PET/CT imaging were analyzed, and geometrical information from the tumors including size, shape, and aspect ratios were classified. Tumors with varying shapes and sizes were assessed in order to investigate the effects of convection and diffusion mechanisms on FDG transport. Numerical methods simulating interstitial flow and solute transport in tissue were utilized. Results: We have shown the convection mechanism to depend on the shape and size of tumors whereas diffusion mechanism is seen to exhibit low dependency on shape and size. Results show that concentration distribution of FDG is relatively similar for the considered tumors; and that the diffusion mechanism of FDG transport significantly dominates the convection mechanism. The Peclet number which shows the ratio of convection to diffusion rates was shown to be of the order of 10−{sup 3} for all considered tumors. Conclusion: We have demonstrated that even though convection leads to varying tracer distribution profiles depending on tumor shape and size, the domination of the diffusion phenomenon prevents these factors from modulating FDG distribution.« less

Evaluation of the Navys Sea/Shore Flow Policy

DTIC Science & Technology

2016-06-01

Std. Z39.18 i Abstract CNA developed an independent Discrete -Event Simulation model to evaluate and assess the effect of...a more steady manning level, but the variability remains, even if the system is optimized. In building a Discrete -Event Simulation model, we...steady-state model. In FY 2014, CNA developed a Discrete -Event Simulation model to evaluate the impact of sea/shore flow policy (the DES-SSF model

Spiking neural network simulation: memory-optimal synaptic event scheduling.

PubMed

Stewart, Robert D; Gurney, Kevin N

2011-06-01

Spiking neural network simulations incorporating variable transmission delays require synaptic events to be scheduled prior to delivery. Conventional methods have memory requirements that scale with the total number of synapses in a network. We introduce novel scheduling algorithms for both discrete and continuous event delivery, where the memory requirement scales instead with the number of neurons. Superior algorithmic performance is demonstrated using large-scale, benchmarking network simulations.

Manual for the Jet Event and Background Simulation Library(JEBSimLib)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heinz, Matthias; Soltz, Ron; Angerami, Aaron

Jets are the collimated streams of particles resulting from hard scattering in the initial state of high-energy collisions. In heavy-ion collisions, jets interact with the quark-gluon plasma (QGP) before freezeout, providing a probe into the internal structure and properties of the QGP. In order to study jets, background must be subtracted from the measured event, potentially introducing a bias. We aim to understand and quantify this subtraction bias. PYTHIA, a library to simulate pure jet events, is used to simulate a model for a signature with one pure jet (a photon) and one quenched jet, where all quenched particle momentamore » are reduced by a user-de ned constant fraction. Background for the event is simulated using multiplicity values generated by the TRENTO initial state model of heavy-ion collisions fed into a thermal model consisting of a 3-dimensional Boltzmann distribution for particle types and momenta. Data from the simulated events is used to train a statistical model, which computes a posterior distribution of the quench factor for a data set. The model was tested rst on pure jet events and then on full events including the background. This model will allow for a quantitative determination of biases induced by various methods of background subtraction.« less

Manual for the Jet Event and Background Simulation Library

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heinz, M.; Soltz, R.; Angerami, A.

Jets are the collimated streams of particles resulting from hard scattering in the initial state of high-energy collisions. In heavy-ion collisions, jets interact with the quark-gluon plasma (QGP) before freezeout, providing a probe into the internal structure and properties of the QGP. In order to study jets, background must be subtracted from the measured event, potentially introducing a bias. We aim to understand and quantify this subtraction bias. PYTHIA, a library to simulate pure jet events, is used to simulate a model for a signature with one pure jet (a photon) and one quenched jet, where all quenched particle momentamore » are reduced by a user-de ned constant fraction. Background for the event is simulated using multiplicity values generated by the TRENTO initial state model of heavy-ion collisions fed into a thermal model consisting of a 3-dimensional Boltzmann distribution for particle types and momenta. Data from the simulated events is used to train a statistical model, which computes a posterior distribution of the quench factor for a data set. The model was tested rst on pure jet events and then on full events including the background. This model will allow for a quantitative determination of biases induced by various methods of background subtraction.« less

Event Detection and Sub-state Discovery from Bio-molecular Simulations Using Higher-Order Statistics: Application To Enzyme Adenylate Kinase

PubMed Central

Ramanathan, Arvind; Savol, Andrej J.; Agarwal, Pratul K.; Chennubhotla, Chakra S.

2012-01-01

Biomolecular simulations at milli-second and longer timescales can provide vital insights into functional mechanisms. Since post-simulation analyses of such large trajectory data-sets can be a limiting factor in obtaining biological insights, there is an emerging need to identify key dynamical events and relating these events to the biological function online, that is, as simulations are progressing. Recently, we have introduced a novel computational technique, quasi-anharmonic analysis (QAA) (PLoS One 6(1): e15827), for partitioning the conformational landscape into a hierarchy of functionally relevant sub-states. The unique capabilities of QAA are enabled by exploiting anharmonicity in the form of fourth-order statistics for characterizing atomic fluctuations. In this paper, we extend QAA for analyzing long time-scale simulations online. In particular, we present HOST4MD - a higher-order statistical toolbox for molecular dynamics simulations, which (1) identifies key dynamical events as simulations are in progress, (2) explores potential sub-states and (3) identifies conformational transitions that enable the protein to access those sub-states. We demonstrate HOST4MD on micro-second time-scale simulations of the enzyme adenylate kinase in its apo state. HOST4MD identifies several conformational events in these simulations, revealing how the intrinsic coupling between the three sub-domains (LID, CORE and NMP) changes during the simulations. Further, it also identifies an inherent asymmetry in the opening/closing of the two binding sites. We anticipate HOST4MD will provide a powerful and extensible framework for detecting biophysically relevant conformational coordinates from long time-scale simulations. PMID:22733562

Event Classification and Identification Based on the Characteristic Ellipsoid of Phasor Measurement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, Jian; Diao, Ruisheng; Makarov, Yuri V.

2011-09-23

In this paper, a method to classify and identify power system events based on the characteristic ellipsoid of phasor measurement is presented. The decision tree technique is used to perform the event classification and identification. Event types, event locations and clearance times are identified by decision trees based on the indices of the characteristic ellipsoid. A sufficiently large number of transient events were simulated on the New England 10-machine 39-bus system based on different system configurations. Transient simulations taking into account different event types, clearance times and various locations are conducted to simulate phasor measurement. Bus voltage magnitudes and recordedmore » reactive and active power flows are used to build the characteristic ellipsoid. The volume, eccentricity, center and projection of the longest axis in the parameter space coordinates of the characteristic ellipsoids are used to classify and identify events. Results demonstrate that the characteristic ellipsoid and the decision tree are capable to detect the event type, location, and clearance time with very high accuracy.« less

Hand-assisted laparoscopic sigmoid colectomy skills acquisition: augmented reality simulator versus human cadaver training models.

PubMed

Leblanc, Fabien; Senagore, Anthony J; Ellis, Clyde N; Champagne, Bradley J; Augestad, Knut M; Neary, Paul C; Delaney, Conor P

2010-01-01

The aim of this study was to compare a simulator with the human cadaver model for hand-assisted laparoscopic colorectal skills acquisition training. An observational prospective comparative study was conducted to compare the laparoscopic surgery training models. The study took place during the laparoscopic colectomy training course performed at the annual scientific meeting of the American Society of Colon and Rectal Surgeons. Thirty four practicing surgeons performed hand-assisted laparoscopic sigmoid colectomy on human cadavers (n = 7) and on an augmented reality simulator (n = 27). Prior laparoscopic colorectal experience was assessed. Trainers and trainees completed independently objective structured assessment forms. Training models were compared by trainees' technical skills scores, events scores, and satisfaction. Prior laparoscopic experience was similar in both surgeon groups. Generic and specific skills scores were similar on both training models. Generic events scores were significantly better on the cadaver model. The 2 most frequent generic events occurring on the simulator were poor hand-eye coordination and inefficient use of retraction. Specific events were scored better on the simulator and reached the significance limit (p = 0.051) for trainers. The specific events occurring on the cadaver were intestinal perforation and left ureter identification difficulties. Overall satisfaction was better for the cadaver than for the simulator model (p = 0.009). With regard to skills scores, the augmented reality simulator had adequate qualities for the hand-assisted laparoscopic colectomy training. Nevertheless, events scores highlighted weaknesses of the anatomical replication on the simulator. Although improvements likely will be required to incorporate the simulator more routinely into the colorectal training, it may be useful in its current form for more junior trainees or those early on their learning curve. Copyright 2010 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Conceptual Modeling of a Quantum Key Distribution Simulation Framework Using the Discrete Event System Specification

DTIC Science & Technology

2014-09-18

and full/scale experimental verifications towards ground/ satellite quantum key distribution0 Oat Qhotonics 4235>9+7,=5;9!អ \\58^ Zin K. Dao Z. Miu T...Conceptual Modeling of a Quantum Key Distribution Simulation Framework Using the Discrete Event System Specification DISSERTATION Jeffrey D. Morris... QUANTUM KEY DISTRIBUTION SIMULATION FRAMEWORK USING THE DISCRETE EVENT SYSTEM SPECIFICATION DISSERTATION Presented to the Faculty Department of Systems

Evaluation of the Navys Sea/Shore Flow Policy

DTIC Science & Technology

2016-06-01

CNA developed an independent Discrete -Event Simulation model to evaluate and assess the effect of alternative sea/shore flow policies. In this study...remains, even if the system is optimized. In building a Discrete -Event Simulation model, we discovered key factors that should be included in the... Discrete -Event Simulation model to evaluate the impact of sea/shore flow policy (the DES-SSF model) and compared the results with the SSFM for one

A Simbol-X Event Simulator

NASA Astrophysics Data System (ADS)

Puccetti, S.; Fiore, F.; Giommi, P.

2009-05-01

The ASI Science Data Center (ASDC) has developed an X-ray event simulator to support users (and team members) in simulation of data taken with the two cameras on board the Simbol-X X-Ray Telescope. The Simbol-X simulator is very fast and flexible, compared to ray-tracing simulator. These properties make our simulator advantageous to support the user in planning proposals and comparing real data with the theoretical expectations and for a quick detection of unexpected features. We present here the simulator outline and a few examples of simulated data.

Consistent simulation of nonresonant diphoton production in hadron collisions including associated jet production up to two jets

NASA Astrophysics Data System (ADS)

Odaka, Shigeru; Kurihara, Yoshimasa

2016-12-01

An event generator for diphoton (γ γ ) production in hadron collisions that includes associated jet production up to two jets has been developed using a subtraction method based on the limited leading-log subtraction. The parton shower (PS) simulation to restore the subtracted divergent components involves both quantum electrodynamic (QED) and quantum chromodynamic radiation, and QED radiation at very small Q2 is simulated by referring to a fragmentation function (FF). The PS/FF simulation has the ability to enforce the radiation of a given number of energetic photons. The generated events can be fed to PYTHIA to obtain particle (hadron) level event information, which enables us to perform realistic simulations of photon isolation and hadron-jet reconstruction. The simulated events, in which the loop-mediated g g →γ γ process is involved, reasonably reproduce the diphoton kinematics measured at the LHC. Using the developed simulation, we found that the two-jet processes significantly contribute to diphoton production. A large two-jet contribution can be considered as a common feature in electroweak-boson production in hadron collisions although the reason is yet to be understood. Discussion concerning the treatment of the underlying events in photon isolation is necessary for future higher precision measurements.

The development of a simulation model of the treatment of coronary heart disease.

PubMed

Cooper, Keith; Davies, Ruth; Roderick, Paul; Chase, Debbie; Raftery, James

2002-11-01

A discrete event simulation models the progress of patients who have had a coronary event, through their treatment pathways and subsequent coronary events. The main risk factors in the model are age, sex, history of previous events and the extent of the coronary vessel disease. The model parameters are based on data collected from epidemiological studies of incidence and prognosis, efficacy studies. national surveys and treatment audits. The simulation results were validated against different sources of data. The initial results show that increasing revascularisation has considerable implications for resource use but has little impact on patient mortality.

Effect of Phosphodiesterase in Regulating the Activity of Lysosomes in the HeLa Cell Line.

PubMed

Hong, Eun-Seon; Kim, Bit-Na; Kim, Yang-Hoon; Min, Jiho

2017-02-28

The transport of lysosomal enzymes into the lysosomes depends on the phosphorylation of their chains and the binding of the phosphorylated residues to mannose-6-phosphate receptors. The efficiency of separation depends more on the phosphodiesterases (PDEs) than on the activity of the phosphorylation of mannose residues and can be determined in vitro. PDEs play important roles in regulation of the activation of lysosomes. The expression of proteins was confirmed by western blotting. All PDE4 series protein expression was reduced in high concentrations of rolipram. As a result of observing the fluorescence intensity after rolipram treatment, the lysosomal enzyme was activated at low concentrations and suppressed at high concentrations. High concentrations of rolipram recovered the original function. Antimicrobial activity was not shown in either 10 or 100 µ concentrations of rolipram in treated HeLa cells in vitro. However, the higher anticancer activity at lower rolipram concentration was shown in lysosomal enzyme treated with 10 µ of rolipram. The anticancer activity was confirmed through cathepsin B and D assay. Tranfection allowed examination of the relationship between PDE4 and lysosomal activity in more detail. Protein expression was confirmed to be reduced. Fluorescence intensity showed decreased activity of lysosomes and ROS in cells transfected with the antisense sequences of PDE4 A, B, C, and D. PDE4A showed anticancer activity, whereas lysosome from cells transfected with the antisense sequences of PDE4 B, C, and D had decreased anticancer activity. These results showed the PDE4 A, B, C, and D are conjunctly related with lysosomal activity.

Cigarette Smoke Upregulates PDE3 and PDE4 to Decrease cAMP in Airway Cells.

PubMed

Zuo, Haoxiao; Han, Bing; Poppinga, Wilfred J; Ringnalda, Lennard; Kistemaker, Loes E M; Halayko, Andrew J; Gosens, Reinoud; Nikolaev, Viacheslav O; Schmidt, Martina

2018-05-03

3', 5'-cyclic adenosine monophosphate (cAMP) is a central second messenger that broadly regulates cell function and can underpin pathophysiology. In chronic obstructive pulmonary disease (COPD), a lung disease primarily provoked by cigarette smoke (CS), the induction of cAMP-dependent pathways, via inhibition of hydrolyzing phosphodiesterases (PDEs), is a prime therapeutic strategy. Mechanisms that disrupt cAMP signaling in airway cells, in particular regulation of endogenous PDEs are poorly understood. We used a novel Förster resonance energy transfer (FRET) based cAMP biosensor in mouse in vivo, ex vivo precision cut lung slices (PCLS), and in human in vitro cell models to track the effects of CS exposure. Under fenoterol stimulated conditions, FRET responses to cilostamide were significantly increased in in vivo, ex vivo PCLS exposed to CS and in human airway smooth muscle cells exposed to CS extract. FRET signals to rolipram were only increased in the in vivo CS model. Under basal conditions, FRET responses to cilostamide and rolipram were significantly increased in in vivo, ex vivo PCLS exposed to CS. Elevated FRET signals to rolipram correlated with a protein upregulation of PDE4 subtypes. In ex vivo PCLS exposed to CS extract, rolipram reversed downregulation of ciliary beating frequency, whereas only cilostamide significantly increased airway relaxation of methacholine pre-contracted airways. We show that CS upregulates expression and activity of both PDE3 and PDE4, which regulate real-time cAMP dynamics. These mechanisms determine the availability of cAMP and can contribute to CS-induced pulmonary pathophysiology. This article is protected by copyright. All rights reserved.

WEAK GALERKIN METHODS FOR SECOND ORDER ELLIPTIC INTERFACE PROBLEMS

PubMed Central

MU, LIN; WANG, JUNPING; WEI, GUOWEI; YE, XIU; ZHAO, SHAN

2013-01-01

Weak Galerkin methods refer to general finite element methods for partial differential equations (PDEs) in which differential operators are approximated by their weak forms as distributions. Such weak forms give rise to desirable flexibilities in enforcing boundary and interface conditions. A weak Galerkin finite element method (WG-FEM) is developed in this paper for solving elliptic PDEs with discontinuous coefficients and interfaces. Theoretically, it is proved that high order numerical schemes can be designed by using the WG-FEM with polynomials of high order on each element. Extensive numerical experiments have been carried to validate the WG-FEM for solving second order elliptic interface problems. High order of convergence is numerically confirmed in both L2 and L∞ norms for the piecewise linear WG-FEM. Special attention is paid to solve many interface problems, in which the solution possesses a certain singularity due to the nonsmoothness of the interface. A challenge in research is to design nearly second order numerical methods that work well for problems with low regularity in the solution. The best known numerical scheme in the literature is of order O(h) to O(h1.5) for the solution itself in L∞ norm. It is demonstrated that the WG-FEM of the lowest order, i.e., the piecewise constant WG-FEM, is capable of delivering numerical approximations that are of order O(h1.75) to O(h2) in the L∞ norm for C1 or Lipschitz continuous interfaces associated with a C1 or H2 continuous solution. PMID:24072935

Dietary flavonoid luteolin attenuates uropathogenic Escherichia. Coli invasion of the urinary bladder.

PubMed

Shen, Xiao-Fei; Teng, Yan; Sha, Kai-Hui; Wang, Xin-Yuan; Yang, Xiao-Long; Guo, Xiao-Juan; Ren, Lai-Bin; Wang, Xiao-Ying; Li, Jingyu; Huang, Ning

2016-11-12

Uropathogenic Escherichia coli (UPEC), the primary uropathogen, adhere to and invade bladder epithelial cells (BECs) to establish a successful urinary tract infection (UTI). Emerging antibiotic resistance requires novel nonantibiotic strategies. Our previous study indicated that luteolin attenuated adhesive and invasive abilities as well as cytotoxicity of UPEC on T24 BECs through down-regulating UPEC virulence factors. The aims of this study were to investigate the possible function of the flavonoid luteolin and the mechanisms by which luteolin functions in UPEC-induced bladder infection. Firstly, obvious reduction of UPEC invasion but not adhesion were observed in luteolin-pretreated 5637 and T24 BECs sa well as mice bladder via colony counting. The luteolin-mediated suppression of UPEC invasion was linked to elevated levels of intracellular cAMP induced by inhibiting the activity of cAMP-phosphodiesterases (cAMP-PDEs), which resulting activation of protein kinase A, thereby negatively regulating Rac1-GTPase-mediated actin polymerization. Furthermore, p38 MAPK was primarily and ERK1/2 was partially involved in luteolin-mediated suppression of UPEC invasion and actin polymerization, as confirmed with chemical activators of p38 MAPK and ERK1/2. These data suggest that luteolin can protect bladder epithelial cells against UPEC invasion. Therefore, luteolin or luteolin-rich products as dietary supplement may be beneficial to control the UPEC-related bladder infections, and cAMP-PDEs may be a therapy target for UTIs treatment. © 2016 BioFactors, 42(6):674-685, 2016. © 2016 International Union of Biochemistry and Molecular Biology.

Construction of energy-stable projection-based reduced order models

DOE PAGES

Kalashnikova, Irina; Barone, Matthew F.; Arunajatesan, Srinivasan; ...

2014-12-15

Our paper aims to unify and extend several approaches for building stable projection-based reduced order models (ROMs) using the energy method and the concept of “energy-stability”. Attention is focused on linear time-invariant (LTI) systems. First, an approach for building energy stable Galerkin ROMs for linear hyperbolic or incompletely parabolic systems of partial differential equations (PDEs) using continuous projection is proposed. The key idea is to apply to the system a transformation induced by the Lyapunov function for the system, and to build the ROM in the transformed variables. The result of this procedure will be a ROM that is energy-stablemore » for any choice of reduced basis. It is shown that, for many PDE systems, the desired transformation is induced by a special inner product, termed the “symmetry inner product”. Next, attention is turned to building energy-stable ROMs via discrete projection. A discrete counterpart of the continuous symmetry inner product, termed the “Lyapunov inner product”, is derived. Moreover, it is shown that the Lyapunov inner product can be computed in a black-box fashion for a stable LTI system ari sing from the discretization of a system of PDEs in space. Projection in this inner product guarantees a ROM that is energy-stable, again for any choice of reduced basis. Connections between the Lyapunov inner product and the inner product induced by the balanced truncation algorithm are made. We also made comparisons between the symmetry inner product and the Lyapunov inner product. Performance of ROMs constructed using these inner products is evaluated on several benchmark test cases.« less

An agent-based stochastic Occupancy Simulator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yixing; Hong, Tianzhen; Luo, Xuan

Occupancy has significant impacts on building performance. However, in current building performance simulation programs, occupancy inputs are static and lack diversity, contributing to discrepancies between the simulated and actual building performance. This work presents an Occupancy Simulator that simulates the stochastic behavior of occupant presence and movement in buildings, capturing the spatial and temporal occupancy diversity. Each occupant and each space in the building are explicitly simulated as an agent with their profiles of stochastic behaviors. The occupancy behaviors are represented with three types of models: (1) the status transition events (e.g., first arrival in office) simulated with probability distributionmore » model, (2) the random moving events (e.g., from one office to another) simulated with a homogeneous Markov chain model, and (3) the meeting events simulated with a new stochastic model. A hierarchical data model was developed for the Occupancy Simulator, which reduces the amount of data input by using the concepts of occupant types and space types. Finally, a case study of a small office building is presented to demonstrate the use of the Simulator to generate detailed annual sub-hourly occupant schedules for individual spaces and the whole building. The Simulator is a web application freely available to the public and capable of performing a detailed stochastic simulation of occupant presence and movement in buildings. Future work includes enhancements in the meeting event model, consideration of personal absent days, verification and validation of the simulated occupancy results, and expansion for use with residential buildings.« less

An agent-based stochastic Occupancy Simulator

DOE PAGES

Chen, Yixing; Hong, Tianzhen; Luo, Xuan

2017-06-01

Occupancy has significant impacts on building performance. However, in current building performance simulation programs, occupancy inputs are static and lack diversity, contributing to discrepancies between the simulated and actual building performance. This work presents an Occupancy Simulator that simulates the stochastic behavior of occupant presence and movement in buildings, capturing the spatial and temporal occupancy diversity. Each occupant and each space in the building are explicitly simulated as an agent with their profiles of stochastic behaviors. The occupancy behaviors are represented with three types of models: (1) the status transition events (e.g., first arrival in office) simulated with probability distributionmore » model, (2) the random moving events (e.g., from one office to another) simulated with a homogeneous Markov chain model, and (3) the meeting events simulated with a new stochastic model. A hierarchical data model was developed for the Occupancy Simulator, which reduces the amount of data input by using the concepts of occupant types and space types. Finally, a case study of a small office building is presented to demonstrate the use of the Simulator to generate detailed annual sub-hourly occupant schedules for individual spaces and the whole building. The Simulator is a web application freely available to the public and capable of performing a detailed stochastic simulation of occupant presence and movement in buildings. Future work includes enhancements in the meeting event model, consideration of personal absent days, verification and validation of the simulated occupancy results, and expansion for use with residential buildings.« less

Optimization and Control of Agent-Based Models in Biology: A Perspective.

PubMed

An, G; Fitzpatrick, B G; Christley, S; Federico, P; Kanarek, A; Neilan, R Miller; Oremland, M; Salinas, R; Laubenbacher, R; Lenhart, S

2017-01-01

Agent-based models (ABMs) have become an increasingly important mode of inquiry for the life sciences. They are particularly valuable for systems that are not understood well enough to build an equation-based model. These advantages, however, are counterbalanced by the difficulty of analyzing and using ABMs, due to the lack of the type of mathematical tools available for more traditional models, which leaves simulation as the primary approach. As models become large, simulation becomes challenging. This paper proposes a novel approach to two mathematical aspects of ABMs, optimization and control, and it presents a few first steps outlining how one might carry out this approach. Rather than viewing the ABM as a model, it is to be viewed as a surrogate for the actual system. For a given optimization or control problem (which may change over time), the surrogate system is modeled instead, using data from the ABM and a modeling framework for which ready-made mathematical tools exist, such as differential equations, or for which control strategies can explored more easily. Once the optimization problem is solved for the model of the surrogate, it is then lifted to the surrogate and tested. The final step is to lift the optimization solution from the surrogate system to the actual system. This program is illustrated with published work, using two relatively simple ABMs as a demonstration, Sugarscape and a consumer-resource ABM. Specific techniques discussed include dimension reduction and approximation of an ABM by difference equations as well systems of PDEs, related to certain specific control objectives. This demonstration illustrates the very challenging mathematical problems that need to be solved before this approach can be realistically applied to complex and large ABMs, current and future. The paper outlines a research program to address them.

Chaste: An Open Source C++ Library for Computational Physiology and Biology

PubMed Central

Mirams, Gary R.; Arthurs, Christopher J.; Bernabeu, Miguel O.; Bordas, Rafel; Cooper, Jonathan; Corrias, Alberto; Davit, Yohan; Dunn, Sara-Jane; Fletcher, Alexander G.; Harvey, Daniel G.; Marsh, Megan E.; Osborne, James M.; Pathmanathan, Pras; Pitt-Francis, Joe; Southern, James; Zemzemi, Nejib; Gavaghan, David J.

2013-01-01

Chaste — Cancer, Heart And Soft Tissue Environment — is an open source C++ library for the computational simulation of mathematical models developed for physiology and biology. Code development has been driven by two initial applications: cardiac electrophysiology and cancer development. A large number of cardiac electrophysiology studies have been enabled and performed, including high-performance computational investigations of defibrillation on realistic human cardiac geometries. New models for the initiation and growth of tumours have been developed. In particular, cell-based simulations have provided novel insight into the role of stem cells in the colorectal crypt. Chaste is constantly evolving and is now being applied to a far wider range of problems. The code provides modules for handling common scientific computing components, such as meshes and solvers for ordinary and partial differential equations (ODEs/PDEs). Re-use of these components avoids the need for researchers to ‘re-invent the wheel’ with each new project, accelerating the rate of progress in new applications. Chaste is developed using industrially-derived techniques, in particular test-driven development, to ensure code quality, re-use and reliability. In this article we provide examples that illustrate the types of problems Chaste can be used to solve, which can be run on a desktop computer. We highlight some scientific studies that have used or are using Chaste, and the insights they have provided. The source code, both for specific releases and the development version, is available to download under an open source Berkeley Software Distribution (BSD) licence at http://www.cs.ox.ac.uk/chaste, together with details of a mailing list and links to documentation and tutorials. PMID:23516352

Modeling methods of MEMS micro-speaker with electrostatic working principle

NASA Astrophysics Data System (ADS)

Tumpold, D.; Kaltenbacher, M.; Glacer, C.; Nawaz, M.; Dehé, A.

2013-05-01

The market for mobile devices like tablets, laptops or mobile phones is increasing rapidly. Device housings get thinner and energy efficiency is more and more important. Micro-Electro-Mechanical-System (MEMS) loudspeakers, fabricated in complementary metal oxide semiconductor (CMOS) compatible technology merge energy efficient driving technology with cost economical fabrication processes. In most cases, the fabrication of such devices within the design process is a lengthy and costly task. Therefore, the need for computer modeling tools capable of precisely simulating the multi-field interactions is increasing. The accurate modeling of such MEMS devices results in a system of coupled partial differential equations (PDEs) describing the interaction between the electric, mechanical and acoustic field. For the efficient and accurate solution we apply the Finite Element (FE) method. Thereby, we fully take the nonlinear effects into account: electrostatic force, charged moving body (loaded membrane) in an electric field, geometric nonlinearities and mechanical contact during the snap-in case between loaded membrane and stator. To efficiently handle the coupling between the mechanical and acoustic fields, we apply Mortar FE techniques, which allow different grid sizes along the coupling interface. Furthermore, we present a recently developed PML (Perfectly Matched Layer) technique, which allows limiting the acoustic computational domain even in the near field without getting spurious reflections. For computations towards the acoustic far field we us a Kirchhoff Helmholtz integral (e.g, to compute the directivity pattern). We will present simulations of a MEMS speaker system based on a single sided driving mechanism as well as an outlook on MEMS speakers using double stator systems (pull-pull-system), and discuss their efficiency (SPL) and quality (THD) towards the generated acoustic sound.

A discrete event simulation tool to support and predict hospital and clinic staffing.

PubMed

DeRienzo, Christopher M; Shaw, Ryan J; Meanor, Phillip; Lada, Emily; Ferranti, Jeffrey; Tanaka, David

2017-06-01

We demonstrate how to develop a simulation tool to help healthcare managers and administrators predict and plan for staffing needs in a hospital neonatal intensive care unit using administrative data. We developed a discrete event simulation model of nursing staff needed in a neonatal intensive care unit and then validated the model against historical data. The process flow was translated into a discrete event simulation model. Results demonstrated that the model can be used to give a respectable estimate of annual admissions, transfers, and deaths based upon two different staffing levels. The discrete event simulation tool model can provide healthcare managers and administrators with (1) a valid method of modeling patient mix, patient acuity, staffing needs, and costs in the present state and (2) a forecast of how changes in a unit's staffing, referral patterns, or patient mix would affect a unit in a future state.

Requirements analysis for a hardware, discrete-event, simulation engine accelerator

NASA Astrophysics Data System (ADS)

Taylor, Paul J., Jr.

1991-12-01

An analysis of a general Discrete Event Simulation (DES), executing on the distributed architecture of an eight mode Intel PSC/2 hypercube, was performed. The most time consuming portions of the general DES algorithm were determined to be the functions associated with message passing of required simulation data between processing nodes of the hypercube architecture. A behavioral description, using the IEEE standard VHSIC Hardware Description and Design Language (VHDL), for a general DES hardware accelerator is presented. The behavioral description specifies the operational requirements for a DES coprocessor to augment the hypercube's execution of DES simulations. The DES coprocessor design implements the functions necessary to perform distributed discrete event simulations using a conservative time synchronization protocol.

Simulation of the Tsunami Resulting from the M 9.2 2004 Sumatra-Andaman Earthquake - Dynamic Rupture vs. Seismic Inversion Source Model

NASA Astrophysics Data System (ADS)

Vater, Stefan; Behrens, Jörn

2017-04-01

Simulations of historic tsunami events such as the 2004 Sumatra or the 2011 Tohoku event are usually initialized using earthquake sources resulting from inversion of seismic data. Also, other data from ocean buoys etc. is sometimes included in the derivation of the source model. The associated tsunami event can often be well simulated in this way, and the results show high correlation with measured data. However, it is unclear how the derived source model compares to the particular earthquake event. In this study we use the results from dynamic rupture simulations obtained with SeisSol, a software package based on an ADER-DG discretization solving the spontaneous dynamic earthquake rupture problem with high-order accuracy in space and time. The tsunami model is based on a second-order Runge-Kutta discontinuous Galerkin (RKDG) scheme on triangular grids and features a robust wetting and drying scheme for the simulation of inundation events at the coast. Adaptive mesh refinement enables the efficient computation of large domains, while at the same time it allows for high local resolution and geometric accuracy. The results are compared to measured data and results using earthquake sources based on inversion. With the approach of using the output of actual dynamic rupture simulations, we can estimate the influence of different earthquake parameters. Furthermore, the comparison to other source models enables a thorough comparison and validation of important tsunami parameters, such as the runup at the coast. This work is part of the ASCETE (Advanced Simulation of Coupled Earthquake and Tsunami Events) project, which aims at an improved understanding of the coupling between the earthquake and the generated tsunami event.

Modeling and Simulation with INS.

ERIC Educational Resources Information Center

Roberts, Stephen D.; And Others

INS, the Integrated Network Simulation language, puts simulation modeling into a network framework and automatically performs such programming activities as placing the problem into a next event structure, coding events, collecting statistics, monitoring status, and formatting reports. To do this, INS provides a set of symbols (nodes and branches)…

SIGMA--A Graphical Approach to Teaching Simulation.

ERIC Educational Resources Information Center

Schruben, Lee W.

1992-01-01

SIGMA (Simulation Graphical Modeling and Analysis) is a computer graphics environment for building, testing, and experimenting with discrete event simulation models on personal computers. It uses symbolic representations (computer animation) to depict the logic of large, complex discrete event systems for easier understanding and has proven itself…

Hybrid Architectural Framework for C4ISR and Discrete-Event Simulation (DES) to Support Sensor-Driven Model Synthesis in Real-World Scenarios

DTIC Science & Technology

2013-09-01

which utilizes FTA and then loads it into a DES engine to generate simulation results. .......44 Figure 21. This simulation architecture is...While Discrete Event Simulation ( DES ) can provide accurate time estimation and fast simulation speed, models utilizing it often suffer...C4ISR progress in MDW is developed in this research to demonstrate the feasibility of AEMF- DES and explore its potential. The simulation (MDSIM

Event detection and sub-state discovery from biomolecular simulations using higher-order statistics: application to enzyme adenylate kinase.

PubMed

Ramanathan, Arvind; Savol, Andrej J; Agarwal, Pratul K; Chennubhotla, Chakra S

2012-11-01

Biomolecular simulations at millisecond and longer time-scales can provide vital insights into functional mechanisms. Because post-simulation analyses of such large trajectory datasets can be a limiting factor in obtaining biological insights, there is an emerging need to identify key dynamical events and relating these events to the biological function online, that is, as simulations are progressing. Recently, we have introduced a novel computational technique, quasi-anharmonic analysis (QAA) (Ramanathan et al., PLoS One 2011;6:e15827), for partitioning the conformational landscape into a hierarchy of functionally relevant sub-states. The unique capabilities of QAA are enabled by exploiting anharmonicity in the form of fourth-order statistics for characterizing atomic fluctuations. In this article, we extend QAA for analyzing long time-scale simulations online. In particular, we present HOST4MD--a higher-order statistical toolbox for molecular dynamics simulations, which (1) identifies key dynamical events as simulations are in progress, (2) explores potential sub-states, and (3) identifies conformational transitions that enable the protein to access those sub-states. We demonstrate HOST4MD on microsecond timescale simulations of the enzyme adenylate kinase in its apo state. HOST4MD identifies several conformational events in these simulations, revealing how the intrinsic coupling between the three subdomains (LID, CORE, and NMP) changes during the simulations. Further, it also identifies an inherent asymmetry in the opening/closing of the two binding sites. We anticipate that HOST4MD will provide a powerful and extensible framework for detecting biophysically relevant conformational coordinates from long time-scale simulations. Copyright © 2012 Wiley Periodicals, Inc.

BOOK REVIEW: Partial Differential Equations in General Relativity

NASA Astrophysics Data System (ADS)

Halburd, Rodney G.

2008-11-01

Although many books on general relativity contain an overview of the relevant background material from differential geometry, very little attention is usually paid to background material from the theory of differential equations. This is understandable in a first course on relativity but it often limits the kinds of problems that can be studied rigorously. Einstein's field equations lie at the heart of general relativity. They are a system of partial differential equations (PDEs) relating the curvature of spacetime to properties of matter. A central part of most problems in general relativity is to extract information about solutions of these equations. Most standard texts achieve this by studying exact solutions or numerical and analytical approximations. In the book under review, Alan Rendall emphasises the role of rigorous qualitative methods in general relativity. There has long been a need for such a book, giving a broad overview of the relevant background from the theory of partial differential equations, and not just from differential geometry. It should be noted that the book also covers the basic theory of ordinary differential equations. Although there are many good books on the rigorous theory of PDEs, methods related to the Einstein equations deserve special attention, not only because of the complexity and importance of these equations, but because these equations do not fit into any of the standard classes of equations (elliptic, parabolic, hyperbolic) that one typically encounters in a course on PDEs. Even specifying exactly what ones means by a Cauchy problem in general relativity requires considerable care. The main problem here is that the manifold on which the solution is defined is determined by the solution itself. This means that one does not simply define data on a submanifold. Rendall's book gives a good overview of applications and results from the qualitative theory of PDEs to general relativity. It would be impossible to give detailed proofs of the main results in a self-contained book of reasonable length. Instead, the author concentrates on providing key definitions together with their motivations and explaining the main results, tools and difficulties for each topic. There is a section at the end of each chapter which points the reader to appropriate literature for further details. In this way, Rendall manages to describe the central issues concerning many subjects. Each of the twelve chapters (except for one on functional analysis) contains an important application to general relativity. For example, the chapter on ODEs discusses Bianchi spacetimes and the Einstein constraint equations are discussed in the chapter on elliptic equations. In the chapter on hyperbolic equations, the Einstein dust system is considered in the context of Leray hyperbolicity and Gowdy spacetimes are analysed in the section on Fuchsian methods. The book concludes with four chapters purely on applications to general relativity, namely The Cauchy problem for the Einstein equations, Global results, The Einstein-Vlasov system and The Einstein-scalar field systems. On reading this book, someone with a basic understanding of relativity could rapidly develop a picture, painted in broad brush strokes, of the main problems and tools in the area. It would be particularly useful for someone, such as a graduate student, just entering the field, or for someone who wants a general idea of the main issues. For those who want to go further, a lot more reading will be necessary but the author has sign-posted appropriate entry points to the literature throughout the book. Ultimately, this is a very technical subject and this book can only provide an overview. I believe that Alan Rendall's book is a valuable contribution to the field of mathematical relativity.

Simulating Impacts of Disruptions to Liquid Fuels Infrastructure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilson, Michael; Corbet, Thomas F.; Baker, Arnold B.

This report presents a methodology for estimating the impacts of events that damage or disrupt liquid fuels infrastructure. The impact of a disruption depends on which components of the infrastructure are damaged, the time required for repairs, and the position of the disrupted components in the fuels supply network. Impacts are estimated for seven stressing events in regions of the United States, which were selected to represent a range of disruption types. For most of these events the analysis is carried out using the National Transportation Fuels Model (NTFM) to simulate the system-level liquid fuels sector response. Results are presentedmore » for each event, and a brief cross comparison of event simulation results is provided.« less

PyRETIS: A well-done, medium-sized python library for rare events.

PubMed

Lervik, Anders; Riccardi, Enrico; van Erp, Titus S

2017-10-30

Transition path sampling techniques are becoming common approaches in the study of rare events at the molecular scale. More efficient methods, such as transition interface sampling (TIS) and replica exchange transition interface sampling (RETIS), allow the investigation of rare events, for example, chemical reactions and structural/morphological transitions, in a reasonable computational time. Here, we present PyRETIS, a Python library for performing TIS and RETIS simulations. PyRETIS directs molecular dynamics (MD) simulations in order to sample rare events with unbiased dynamics. PyRETIS is designed to be easily interfaced with any molecular simulation package and in the present release, it has been interfaced with GROMACS and CP2K, for classical and ab initio MD simulations, respectively. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Medicanes in an ocean-atmosphere coupled regional climate model

NASA Astrophysics Data System (ADS)

Akhtar, Naveed; Brauch, Jennifer; Ahrens, Bodo

2014-05-01

So-called medicanes (Mediterranean hurricanes) are meso-scale, marine and warm core Mediterranean cyclones which exhibit some similarities with tropical cyclones. The strong cyclonic winds associated with them are a potential thread for highly populated coastal areas around the Mediterranean basin. In this study we employ an atmospheric limited-area model (COSMO-CLM) coupled with a one-dimensional ocean model (NEMO-1d) to simulate medicanes. The goal of this study is to assess the robustness of the coupled model to simulate these extreme events. For this purpose 11 historical medicane events are simulated by the atmosphere-only and the coupled models using different set-ups (horizontal grid-spacings: 0.44o, 0.22o, 0.088o; with/with-out spectral nudging). The results show that at high resolution the coupled model is not only able to simulate all medicane events but also improves the simulated track length, warm core, and wind speed of simulated medicanes compared to atmosphere-only simulations. In most of the cases the medicanes trajectories and structures are better represented in coupled simulations compared to atmosphere-only simulations. We conclude that the coupled model is a suitable tool for systemic and detailed study of historical medicane events and also for future projections.

A comparison of human cadaver and augmented reality simulator models for straight laparoscopic colorectal skills acquisition training.

PubMed

LeBlanc, Fabien; Champagne, Bradley J; Augestad, Knut M; Neary, Paul C; Senagore, Anthony J; Ellis, Clyde N; Delaney, Conor P

2010-08-01

The aim of this study was to compare the human cadaver model with an augmented reality simulator for straight laparoscopic colorectal skills acquisition. Thirty-five sigmoid colectomies were performed on a cadaver (n = 7) or an augmented reality simulator (n = 28) during a laparoscopic training course. Prior laparoscopic colorectal experience was assessed. Objective structured technical skills assessment forms were completed by trainers and trainees independently. Groups were compared according to technical skills and events scores and satisfaction with training model. Prior laparoscopic experience was similar in both groups. For trainers and trainees, technical skills scores were considerably better on the simulator than on the cadaver. For trainers, generic events score was also considerably better on the simulator than on the cadaver. The main generic event occurring on both models was errors in the use of retraction. The main specific event occurring on both models was bowel perforation. Global satisfaction was better for the cadaver than for the simulator model (p < 0.001). The human cadaver model was more difficult but better appreciated than the simulator for laparoscopic sigmoid colectomy training. Simulator training followed by cadaver training can appropriately integrate simulators into the learning curve and maintain the benefits of both training methodologies. Published by Elsevier Inc.

Modelling and Simulation as a Recognizing Method in Education

ERIC Educational Resources Information Center

Stoffa, Veronika

2004-01-01

Computer animation-simulation models of complex processes and events, which are the method of instruction, can be an effective didactic device. Gaining deeper knowledge about objects modelled helps to plan simulation experiments oriented on processes and events researched. Animation experiments realized on multimedia computers can aid easier…

New Perspectives on Long Run-out Rock Avalanches: A Dynamic Analysis of 20 Events in the Vaigat Strait, West Greenland

NASA Astrophysics Data System (ADS)

Benjamin, J.; Rosser, N. J.; Dunning, S.; Hardy, R. J.; Karim, K.; Szczucinski, W.; Norman, E. C.; Strzelecki, M.; Drewniak, M.

2014-12-01

Risk assessments of the threat posed by rock avalanches rely upon numerical modelling of potential run-out and spreading, and are contingent upon a thorough understanding of the flow dynamics inferred from deposits left by previous events. Few records exist of multiple rock avalanches with boundary conditions sufficiently consistent to develop a set of more generalised rules for behaviour across events. A unique cluster of 20 large (3 x 106 - 94 x 106 m3) rock avalanche deposits along the Vaigat Strait, West Greenland, offers a unique opportunity to model a large sample of adjacent events sourced from a stretch of coastal mountains of relatively uniform geology and structure. Our simulations of these events were performed using VolcFlow, a geophysical mass flow code developed to simulate volcanic debris avalanches. Rheological calibration of the model was performed using a well-constrained event at Paatuut (AD 2000). The best-fit simulation assumes a constant retarding stress with a collisional stress coefficient (T0 = 250 kPa, ξ = 0.01), and simulates run-out to within ±0.3% of that observed. Despite being widely used to simulate rock avalanche propagation, other models, that assume either a Coulomb frictional or a Voellmy rheology, failed to reproduce the observed event characteristics and deposit distribution at Paatuut. We applied this calibration to 19 other events, simulating rock avalanche motion across 3D terrain of varying levels of complexity. Our findings illustrate the utility and sensitivity of modelling a single rock avalanche satisfactorily as a function of rheology, alongside the validity of applying the same parameters elsewhere, even within similar boundary conditions. VolcFlow can plausibly account for the observed morphology of a series of deposits emplaced by events of different types, although its performance is sensitive to a range of topographic and geometric factors. These exercises show encouraging results in the model's ability to simulate a series of events using a single set of parameters obtained by back-analysis of the Paatuut event alone. The results also hold important implications for our process understanding of rock avalanches in confined fjord settings, where correctly modelling material flux at the point of entry into the water is critical in tsunami generation.

Discretely Integrated Condition Event (DICE) Simulation for Pharmacoeconomics.

PubMed

Caro, J Jaime

2016-07-01

Several decision-analytic modeling techniques are in use for pharmacoeconomic analyses. Discretely integrated condition event (DICE) simulation is proposed as a unifying approach that has been deliberately designed to meet the modeling requirements in a straightforward transparent way, without forcing assumptions (e.g., only one transition per cycle) or unnecessary complexity. At the core of DICE are conditions that represent aspects that persist over time. They have levels that can change and many may coexist. Events reflect instantaneous occurrences that may modify some conditions or the timing of other events. The conditions are discretely integrated with events by updating their levels at those times. Profiles of determinant values allow for differences among patients in the predictors of the disease course. Any number of valuations (e.g., utility, cost, willingness-to-pay) of conditions and events can be applied concurrently in a single run. A DICE model is conveniently specified in a series of tables that follow a consistent format and the simulation can be implemented fully in MS Excel, facilitating review and validation. DICE incorporates both state-transition (Markov) models and non-resource-constrained discrete event simulation in a single formulation; it can be executed as a cohort or a microsimulation; and deterministically or stochastically.

Simulation and study of small numbers of random events

NASA Technical Reports Server (NTRS)

Shelton, R. D.

1986-01-01

Random events were simulated by computer and subjected to various statistical methods to extract important parameters. Various forms of curve fitting were explored, such as least squares, least distance from a line, maximum likelihood. Problems considered were dead time, exponential decay, and spectrum extraction from cosmic ray data using binned data and data from individual events. Computer programs, mostly of an iterative nature, were developed to do these simulations and extractions and are partially listed as appendices. The mathematical basis for the compuer programs is given.

Cell short circuit, preshort signature

NASA Technical Reports Server (NTRS)

Lurie, C.

1980-01-01

Short-circuit events observed in ground test simulations of DSCS-3 battery in-orbit operations are analyzed. Voltage signatures appearing in the data preceding the short-circuit event are evaluated. The ground test simulation is briefly described along with performance during reconditioning discharges. Results suggest that a characteristic signature develops prior to a shorting event.

SimEngine v. 1.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Le, Hai D.

2017-03-02

SimEngine provides the core functionalities and components that are key to the development of discrete event simulation tools. These include events, activities, event queues, random number generators, and basic result tracking classes. SimEngine was designed for high performance, integrates seamlessly into any Microsoft .Net development environment, and provides a flexible API for simulation developers.

Episodic simulation of future events is impaired in mild Alzheimer's disease

PubMed Central

Addis, Donna Rose; Sacchetti, Daniel C.; Ally, Brandon A.; Budson, Andrew E.; Schacter, Daniel L.

2009-01-01

Recent neuroimaging studies have demonstrated that both remembering the past and simulating the future activate a core neural network including the medial temporal lobes. Regions of this network, in particular the medial temporal lobes, are prime sites for amyloid deposition and are structurally and functionally compromised in Alzheimer's disease (AD). While we know some functions of this core network, specifically episodic autobiographical memory, are impaired in AD, no study has examined whether future episodic simulation is similarly impaired. We tested the ability of sixteen AD patients and sixteen age-matched controls to generate past and future autobiographical events using an adapted version of the Autobiographical Interview. Participants also generated five remote autobiographical memories from across the lifespan. Event transcriptions were segmented into distinct details, classified as either internal (episodic) or external (non-episodic). AD patients exhibited deficits in both remembering past events and simulating future events, generating fewer internal and external episodic details than healthy older controls. The internal and external detail scores were strongly correlated across past and future events, providing further evidence of the close linkages between the mental representations of past and future. PMID:19497331

Optimization of Operations Resources via Discrete Event Simulation Modeling

NASA Technical Reports Server (NTRS)

Joshi, B.; Morris, D.; White, N.; Unal, R.

1996-01-01

The resource levels required for operation and support of reusable launch vehicles are typically defined through discrete event simulation modeling. Minimizing these resources constitutes an optimization problem involving discrete variables and simulation. Conventional approaches to solve such optimization problems involving integer valued decision variables are the pattern search and statistical methods. However, in a simulation environment that is characterized by search spaces of unknown topology and stochastic measures, these optimization approaches often prove inadequate. In this paper, we have explored the applicability of genetic algorithms to the simulation domain. Genetic algorithms provide a robust search strategy that does not require continuity and differentiability of the problem domain. The genetic algorithm successfully minimized the operation and support activities for a space vehicle, through a discrete event simulation model. The practical issues associated with simulation optimization, such as stochastic variables and constraints, were also taken into consideration.

Simulating recurrent event data with hazard functions defined on a total time scale.

PubMed

Jahn-Eimermacher, Antje; Ingel, Katharina; Ozga, Ann-Kathrin; Preussler, Stella; Binder, Harald

2015-03-08

In medical studies with recurrent event data a total time scale perspective is often needed to adequately reflect disease mechanisms. This means that the hazard process is defined on the time since some starting point, e.g. the beginning of some disease, in contrast to a gap time scale where the hazard process restarts after each event. While techniques such as the Andersen-Gill model have been developed for analyzing data from a total time perspective, techniques for the simulation of such data, e.g. for sample size planning, have not been investigated so far. We have derived a simulation algorithm covering the Andersen-Gill model that can be used for sample size planning in clinical trials as well as the investigation of modeling techniques. Specifically, we allow for fixed and/or random covariates and an arbitrary hazard function defined on a total time scale. Furthermore we take into account that individuals may be temporarily insusceptible to a recurrent incidence of the event. The methods are based on conditional distributions of the inter-event times conditional on the total time of the preceeding event or study start. Closed form solutions are provided for common distributions. The derived methods have been implemented in a readily accessible R script. The proposed techniques are illustrated by planning the sample size for a clinical trial with complex recurrent event data. The required sample size is shown to be affected not only by censoring and intra-patient correlation, but also by the presence of risk-free intervals. This demonstrates the need for a simulation algorithm that particularly allows for complex study designs where no analytical sample size formulas might exist. The derived simulation algorithm is seen to be useful for the simulation of recurrent event data that follow an Andersen-Gill model. Next to the use of a total time scale, it allows for intra-patient correlation and risk-free intervals as are often observed in clinical trial data. Its application therefore allows the simulation of data that closely resemble real settings and thus can improve the use of simulation studies for designing and analysing studies.

Numerical simulations of an advection fog event over Shanghai Pudong International Airport with the WRF model

NASA Astrophysics Data System (ADS)

Lin, Caiyan; Zhang, Zhongfeng; Pu, Zhaoxia; Wang, Fengyun

2017-10-01

A series of numerical simulations is conducted to understand the formation, evolution, and dissipation of an advection fog event over Shanghai Pudong International Airport (ZSPD) with the Weather Research and Forecasting (WRF) model. Using the current operational settings at the Meteorological Center of East China Air Traffic Management Bureau, the WRF model successfully predicts the fog event at ZSPD. Additional numerical experiments are performed to examine the physical processes associated with the fog event. The results indicate that prediction of this particular fog event is sensitive to microphysical schemes for the time of fog dissipation but not for the time of fog onset. The simulated timing of the arrival and dissipation of the fog, as well as the cloud distribution, is substantially sensitive to the planetary boundary layer and radiation (both longwave and shortwave) processes. Moreover, varying forecast lead times also produces different simulation results for the fog event regarding its onset and duration, suggesting a trade-off between more accurate initial conditions and a proper forecast lead time that allows model physical processes to spin up adequately during the fog simulation. The overall outcomes from this study imply that the complexity of physical processes and their interactions within the WRF model during fog evolution and dissipation is a key area of future research.

A geostatistical extreme-value framework for fast simulation of natural hazard events

PubMed Central

Stephenson, David B.

2016-01-01

We develop a statistical framework for simulating natural hazard events that combines extreme value theory and geostatistics. Robust generalized additive model forms represent generalized Pareto marginal distribution parameters while a Student’s t-process captures spatial dependence and gives a continuous-space framework for natural hazard event simulations. Efficiency of the simulation method allows many years of data (typically over 10 000) to be obtained at relatively little computational cost. This makes the model viable for forming the hazard module of a catastrophe model. We illustrate the framework by simulating maximum wind gusts for European windstorms, which are found to have realistic marginal and spatial properties, and validate well against wind gust measurements. PMID:27279768

Alternative formulations of the Laplace transform boundary element (LTBE) numerical method for the solution of diffusion-type equations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moridis, G.

1992-03-01

The Laplace Transform Boundary Element (LTBE) method is a recently introduced numerical method, and has been used for the solution of diffusion-type PDEs. It completely eliminates the time dependency of the problem and the need for time discretization, yielding solutions numerical in space and semi-analytical in time. In LTBE solutions are obtained in the Laplace spare, and are then inverted numerically to yield the solution in time. The Stehfest and the DeHoog formulations of LTBE, based on two different inversion algorithms, are investigated. Both formulations produce comparable, extremely accurate solutions.

Space-Time Discrete KPZ Equation

NASA Astrophysics Data System (ADS)

Cannizzaro, G.; Matetski, K.

2018-03-01

We study a general family of space-time discretizations of the KPZ equation and show that they converge to its solution. The approach we follow makes use of basic elements of the theory of regularity structures (Hairer in Invent Math 198(2):269-504, 2014) as well as its discrete counterpart (Hairer and Matetski in Discretizations of rough stochastic PDEs, 2015. arXiv:1511.06937). Since the discretization is in both space and time and we allow non-standard discretization for the product, the methods mentioned above have to be suitably modified in order to accommodate the structure of the models under study.

Nonlocal integrable PDEs from hierarchies of symmetry laws: The example of Pohlmeyer-Lund-Regge equation and its reflectionless potential solutions

NASA Astrophysics Data System (ADS)

Demontis, F.; Ortenzi, G.; van der Mee, C.

2018-04-01

By following the ideas presented by Fukumoto and Miyajima in Fukumoto and Miyajima (1996) we derive a generalized method for constructing integrable nonlocal equations starting from any bi-Hamiltonian hierarchy supplied with a recursion operator. This construction provides the right framework for the application of the full machinery of the inverse scattering transform. We pay attention to the Pohlmeyer-Lund-Regge equation coming from the nonlinear Schrödinger hierarchy and construct the formula for the reflectionless potential solutions which are generalizations of multi-solitons. Some explicit examples are discussed.

Alternative to the Palatini method: A new variational principle

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goenner, Hubert

2010-06-15

A variational principle is suggested within Riemannian geometry, in which an auxiliary metric and the Levi Civita connection are varied independently. The auxiliary metric plays the role of a Lagrange multiplier and introduces nonminimal coupling of matter to the curvature scalar. The field equations are 2nd order PDEs and easier to handle than those following from the so-called Palatini method. Moreover, in contrast to the latter method, no gradients of the matter variables appear. In cosmological modeling, the physics resulting from the alternative variational principle will differ from the modeling using the standard Palatini method.

On a modified form of navier-stokes equations for three-dimensional flows.

PubMed

Venetis, J

2015-01-01

A rephrased form of Navier-Stokes equations is performed for incompressible, three-dimensional, unsteady flows according to Eulerian formalism for the fluid motion. In particular, we propose a geometrical method for the elimination of the nonlinear terms of these fundamental equations, which are expressed in true vector form, and finally arrive at an equivalent system of three semilinear first order PDEs, which hold for a three-dimensional rectangular Cartesian coordinate system. Next, we present the related variational formulation of these modified equations as well as a general type of weak solutions which mainly concern Sobolev spaces.

On a Modified Form of Navier-Stokes Equations for Three-Dimensional Flows

PubMed Central

Venetis, J.

2015-01-01

A rephrased form of Navier-Stokes equations is performed for incompressible, three-dimensional, unsteady flows according to Eulerian formalism for the fluid motion. In particular, we propose a geometrical method for the elimination of the nonlinear terms of these fundamental equations, which are expressed in true vector form, and finally arrive at an equivalent system of three semilinear first order PDEs, which hold for a three-dimensional rectangular Cartesian coordinate system. Next, we present the related variational formulation of these modified equations as well as a general type of weak solutions which mainly concern Sobolev spaces. PMID:25918743

An efficient technique for higher order fractional differential equation.

PubMed

Ali, Ayyaz; Iqbal, Muhammad Asad; Ul-Hassan, Qazi Mahmood; Ahmad, Jamshad; Mohyud-Din, Syed Tauseef

2016-01-01

In this study, we establish exact solutions of fractional Kawahara equation by using the idea of [Formula: see text]-expansion method. The results of different studies show that the method is very effective and can be used as an alternative for finding exact solutions of nonlinear evolution equations (NLEEs) in mathematical physics. The solitary wave solutions are expressed by the hyperbolic, trigonometric, exponential and rational functions. Graphical representations along with the numerical data reinforce the efficacy of the used procedure. The specified idea is very effective, expedient for fractional PDEs, and could be extended to other physical problems.

Noniterative three-dimensional grid generation using parabolic partial differential equations

NASA Technical Reports Server (NTRS)

Edwards, T. A.

1985-01-01

A new algorithm for generating three-dimensional grids has been developed and implemented which numerically solves a parabolic partial differential equation (PDE). The solution procedure marches outward in two coordinate directions, and requires inversion of a scalar tridiagonal system in the third. Source terms have been introduced to control the spacing and angle of grid lines near the grid boundaries, and to control the outer boundary point distribution. The method has been found to generate grids about 100 times faster than comparable grids generated via solution of elliptic PDEs, and produces smooth grids for finite-difference flow calculations.

The Kadomtsev{endash}Petviashvili equation as a source of integrable model equations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maccari, A.

1996-12-01

A new integrable and nonlinear partial differential equation (PDE) in 2+1 dimensions is obtained, by an asymptotically exact reduction method based on Fourier expansion and spatiotemporal rescaling, from the Kadomtsev{endash}Petviashvili equation. The integrability property is explicitly demonstrated, by exhibiting the corresponding Lax pair, that is obtained by applying the reduction technique to the Lax pair of the Kadomtsev{endash}Petviashvili equation. This model equation is likely to be of applicative relevance, because it may be considered a consistent approximation of a large class of nonlinear evolution PDEs. {copyright} {ital 1996 American Institute of Physics.}

A New Class of Highly Accurate Differentiation Schemes Based on the Prolate Spheroidal Wave Functions

DTIC Science & Technology

2011-04-07

predictor - corrector scheme. Such an approach for the solution of time-dependent PDEs, which is some- times referred to as the “method of lines,” is studied...particular, λj = i j |λj |. We define the self -adjoint operator Qc : L 2([−1, 1]) → L2([−1, 1]) by the formula Qc(φ) = 1 π ∫ 1 −1 sin( c (x− t)) x− t φ...Gaussian quadratures for bandlimited functions is to use the Newton-type nonlinear optimization algorithm of [14]. Specifically, for bandlimit c and

Twirling and Whirling: Viscous Dynamics of Rotating Elastica

NASA Astrophysics Data System (ADS)

Powers, Thomas R.; Wolgemuth, Charles W.; Goldstein, Raymond E.

1999-11-01

Motivated by diverse phenomena in cellular biophysics, including bacterial flagellar motion and DNA transcription and replication, we study the overdamped nonlinear dynamics of a rotationally forced filament with twist and bend elasticity. The competition between twist diffusion and writhing instabilities is described by a novel pair of coupled PDEs for twist and bend evolution. Analytical and numerical methods elucidate the twist-bend coupling and reveal two dynamical regimes separated by a Hopf bifurcation: (i) diffusion-dominated axial rotation, or twirling, and (ii) steady-state crankshafting motion, or whirling. The consequences of these phenomena for self-propulsion are investigated, and experimental tests proposed.

Computation of partially invariant solutions for the Einstein Walker manifolds' identifying equations

NASA Astrophysics Data System (ADS)

Nadjafikhah, Mehdi; Jafari, Mehdi

2013-12-01

In this paper, partially invariant solutions (PISs) method is applied in order to obtain new four-dimensional Einstein Walker manifolds. This method is based on subgroup classification for the symmetry group of partial differential equations (PDEs) and can be regarded as the generalization of the similarity reduction method. For this purpose, those cases of PISs which have the defect structure δ=1 and are resulted from two-dimensional subalgebras are considered in the present paper. Also it is shown that the obtained PISs are distinct from the invariant solutions that obtained by similarity reduction method.

Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liao, Qifeng, E-mail: liaoqf@shanghaitech.edu.cn; Lin, Guang, E-mail: guanglin@purdue.edu

2016-07-15

In this paper we present a reduced basis ANOVA approach for partial deferential equations (PDEs) with random inputs. The ANOVA method combined with stochastic collocation methods provides model reduction in high-dimensional parameter space through decomposing high-dimensional inputs into unions of low-dimensional inputs. In this work, to further reduce the computational cost, we investigate spatial low-rank structures in the ANOVA-collocation method, and develop efficient spatial model reduction techniques using hierarchically generated reduced bases. We present a general mathematical framework of the methodology, validate its accuracy and demonstrate its efficiency with numerical experiments.

Dynamic transition between fixed- and mobile-bed: mathematical and numerical aspects

NASA Astrophysics Data System (ADS)

Zugliani, Daniel; Pasqualini, Matteo; Rosatti, Giorgio

2017-04-01

Free-surface flows with high sediment transport (as debris flow or hyper-concentrated flow) are composed by a mixture of fluid and solid phase, usually water and sediment. When these flows propagate over loose beds, particles constituting the mixture of water and sediments strongly interact with the ones forming the bed, leading to erosion or deposition. However, there are lots of other situations when the mixture flows over rigid bedrocks or over artificially paved transects, so there is no mass exchange between bed and mixture. The two situations are usually referred to as, respectively, mobile- and fixed-bed conditions. From a mathematical point of view, the systems of Partial Differential Equations (PDEs) that describe these flows derive from mass and momentum balance of both phases, but, the two resulting PDEs systems are different. The main difference concerns the concentration: in the mobile-bed condition, the concentration is linked to the local flow conditions by means of a suitable rheological relation, while in the fixed-bed case, the concentration is an unknown of the problem. It is quite common that a free surface flow with high sediment transport, in its path, encounters both conditions. In the recent work of Rosatti & Zugliani 2015, the mathematical and numerical description of the transition between fixed- and mobile-bed was successfully resolved, for the case of low sediment transport phenomena, by the introduction of a suitable erodibility variable and satisfactory results were obtained. The main disadvantage of the approach is related to the erodibility variable, that changes in space, based on bed characteristics, but remains constant in time. However, the nature of the bed can change dynamically as result of deposition over fixed bed or high erosion over mobile bed. With this work, we extend the applicability of the mentioned approach to the more complex PDEs describing the hyper-concentrated flow. Moreover, we introduce a strategy that allows a dynamic time variation of the erodibility variable. The issue of the dynamic transition between fixed- and mobile-bed condition is tackled, from a numerical point of view, using a particular predictor corrector technique that compare the transported concentration related with the fixed bed and the equilibrium concentration, deriving from a closure relation, associated to the mobile bed condition. Through a comparison between exact solution, built using the generalized Rankine - Hugoniot condition, and the numeric results, we highlight capabilities and limits of this enhanced technique. Bibliography: G. Rosatti and D. Zugliani, 2015. "Modelling the transition between fixed and mobile bed conditions in two-phase free-surface flows: The Composite Riemann Problem and its numerical solution". Journal of Computational Physics, 285:226-250

Interval sampling methods and measurement error: a computer simulation.

PubMed

Wirth, Oliver; Slaven, James; Taylor, Matthew A

2014-01-01

A simulation study was conducted to provide a more thorough account of measurement error associated with interval sampling methods. A computer program simulated the application of momentary time sampling, partial-interval recording, and whole-interval recording methods on target events randomly distributed across an observation period. The simulation yielded measures of error for multiple combinations of observation period, interval duration, event duration, and cumulative event duration. The simulations were conducted up to 100 times to yield measures of error variability. Although the present simulation confirmed some previously reported characteristics of interval sampling methods, it also revealed many new findings that pertain to each method's inherent strengths and weaknesses. The analysis and resulting error tables can help guide the selection of the most appropriate sampling method for observation-based behavioral assessments. © Society for the Experimental Analysis of Behavior.

A role for affect in the link between episodic simulation and prosociality.

PubMed

Gaesser, Brendan; DiBiase, Haley D; Kensinger, Elizabeth A

2017-09-01

Prospection and prosociality are hallmarks of our species. Little is known, however, about how our ability to imagine or simulate specific future events contributes to our capacity for prosociality. Here, we investigated this relationship, revealing how the affective response that arises from a simulated prosocial event motivates a willingness to help a person in need. Across two experiments, people reported being more willing to help in specific situations after simulating future helping events that elicited positive (versus negative or neutral) affect. Positive affect increased engagement of theory of mind for the person in need, which in turn informed prosocial responses. Moreover, the subjective experience of scene imagery and theory of mind systematically couple together depending on the affective valence of future simulations, providing new insight into how affective valence guides a prosocial function of episodic simulation.

An Overview of Importance Splitting for Rare Event Simulation

ERIC Educational Resources Information Center

Morio, Jerome; Pastel, Rudy; Le Gland, Francois

2010-01-01

Monte Carlo simulations are a classical tool to analyse physical systems. When unlikely events are to be simulated, the importance sampling technique is often used instead of Monte Carlo. Importance sampling has some drawbacks when the problem dimensionality is high or when the optimal importance sampling density is complex to obtain. In this…

Design and Evaluation of Simulations for the Development of Complex Decision-Making Skills.

ERIC Educational Resources Information Center

Hartley, Roger; Varley, Glen

2002-01-01

Command and Control Training Using Simulation (CACTUS) is a computer digital mapping system used by police to manage large-scale public events. Audio and video records of adaptive training scenarios using CACTUS show how the simulation develops decision-making skills for strategic and tactical event management. (SK)

A Spiking Neural Simulator Integrating Event-Driven and Time-Driven Computation Schemes Using Parallel CPU-GPU Co-Processing: A Case Study.

PubMed

Naveros, Francisco; Luque, Niceto R; Garrido, Jesús A; Carrillo, Richard R; Anguita, Mancia; Ros, Eduardo

2015-07-01

Time-driven simulation methods in traditional CPU architectures perform well and precisely when simulating small-scale spiking neural networks. Nevertheless, they still have drawbacks when simulating large-scale systems. Conversely, event-driven simulation methods in CPUs and time-driven simulation methods in graphic processing units (GPUs) can outperform CPU time-driven methods under certain conditions. With this performance improvement in mind, we have developed an event-and-time-driven spiking neural network simulator suitable for a hybrid CPU-GPU platform. Our neural simulator is able to efficiently simulate bio-inspired spiking neural networks consisting of different neural models, which can be distributed heterogeneously in both small layers and large layers or subsystems. For the sake of efficiency, the low-activity parts of the neural network can be simulated in CPU using event-driven methods while the high-activity subsystems can be simulated in either CPU (a few neurons) or GPU (thousands or millions of neurons) using time-driven methods. In this brief, we have undertaken a comparative study of these different simulation methods. For benchmarking the different simulation methods and platforms, we have used a cerebellar-inspired neural-network model consisting of a very dense granular layer and a Purkinje layer with a smaller number of cells (according to biological ratios). Thus, this cerebellar-like network includes a dense diverging neural layer (increasing the dimensionality of its internal representation and sparse coding) and a converging neural layer (integration) similar to many other biologically inspired and also artificial neural networks.

Exploring the content and quality of episodic future simulations in semantic dementia.

PubMed

Irish, Muireann; Addis, Donna Rose; Hodges, John R; Piguet, Olivier

2012-12-01

Semantic dementia (SD) is a progressive neurodegenerative disorder characterised by the amodal loss of semantic knowledge in the context of relatively preserved recent episodic memory. Recent studies have demonstrated that despite relatively intact episodic memory the capacity for future simulation in SD is profoundly impaired, resulting in an asymmetric profile where past retrieval is significantly better than future simulation (referred to as a past>future effect). Here, we sought to identify the origins of this asymmetric profile by conducting a fine-grained analysis of the contextual details provided during past retrieval and future simulation in SD. Participants with SD (n=14), Alzheimer's disease (n=11), and healthy controls (n=14) had previously completed an experimental past-future interview in which they generated three past events from the previous year, and three future events in the next year, and provided subjective qualitative ratings of vividness, emotional valence, emotional intensity, task difficulty, and personal significance for each event described. Our results confirmed the striking impairment for future simulation in SD, despite a relative preservation of past episodic retrieval. Examination of the contextual details provided for past memories and future simulations revealed significant impairments irrespective of contextual detail type for future simulations in SD, and demonstrated that the future thinking deficit in this cohort was driven by a marked decline in the provision of internal (episodic) event details. In contrast with this past>future effect for internal event details, SD patients displayed a future>past effect for external (non-episodic) event details. Analyses of the qualitative ratings provided for past and future events indicated that SD patients' phenomenological experience did not differ between temporal conditions. Our findings underscore the fact that successful extraction of episodic elements from the past is not sufficient for the generation of novel future simulations in SD. The notable disconnect between objective task performance and patients' subjective experience during future simulation likely reflects the tendency of SD patients to recast entire past events into the future condition. Accordingly, the familiarity of the recapitulated details results in similar ratings of vividness and emotionality across temporal conditions, despite marked differences in the richness of contextual details as the patient moves from the past to the future. Copyright © 2012 Elsevier Ltd. All rights reserved.

Flood simulation and verification with IoT sensors

NASA Astrophysics Data System (ADS)

Chang, Che-Hao; Hsu, Chih-Tsung; Wu, Shiang-Jen; Huang, Sue-Wei

2017-04-01

2D flood dynamic simulation is a vivid tool to demonstrate the possible expose area that sustain impact of high rise of water level. Along with progress in high resolution digital terrain model, the simulation results are quite convinced yet not proved to be close to what is really happened. Due to the dynamic and uncertain essence, the expose area usually could not be well defined during a flood event. Recent development in IoT sensors bring a low power and long distance communication which help us to collect real time flood depths. With these time series of flood depths at different locations, we are capable of verifying the simulation results corresponding to the flood event. 16 flood gauges with IoT specification as well as two flood events in Annan district, Tainan city, Taiwan are examined in this study. During the event in 11, June, 2016, 12 flood gauges works well and 8 of them provide observation match to simulation.

High order spectral difference lattice Boltzmann method for incompressible hydrodynamics

NASA Astrophysics Data System (ADS)

Li, Weidong

2017-09-01

This work presents a lattice Boltzmann equation (LBE) based high order spectral difference method for incompressible flows. In the present method, the spectral difference (SD) method is adopted to discretize the convection and collision term of the LBE to obtain high order (≥3) accuracy. Because the SD scheme represents the solution as cell local polynomials and the solution polynomials have good tensor-product property, the present spectral difference lattice Boltzmann method (SD-LBM) can be implemented on arbitrary unstructured quadrilateral meshes for effective and efficient treatment of complex geometries. Thanks to only first oder PDEs involved in the LBE, no special techniques, such as hybridizable discontinuous Galerkin method (HDG), local discontinuous Galerkin method (LDG) and so on, are needed to discrete diffusion term, and thus, it simplifies the algorithm and implementation of the high order spectral difference method for simulating viscous flows. The proposed SD-LBM is validated with four incompressible flow benchmarks in two-dimensions: (a) the Poiseuille flow driven by a constant body force; (b) the lid-driven cavity flow without singularity at the two top corners-Burggraf flow; and (c) the unsteady Taylor-Green vortex flow; (d) the Blasius boundary-layer flow past a flat plate. Computational results are compared with analytical solutions of these cases and convergence studies of these cases are also given. The designed accuracy of the proposed SD-LBM is clearly verified.

Solute Dynamics and Imaging in the Tear Film on an Eye-shaped Domain

NASA Astrophysics Data System (ADS)

Braun, R. J.; Li, Longfei; Henshaw, William; Driscoll, Tobin; King-Smith, P. E.

2015-11-01

The concentration of ions in the tear film (osmolarity) is a key variable in understanding dry eye symptoms and disease, yet its global distribution is not available; direct measurements are restricted to a region near the temporal canthus. It has been suggested that imaging methods that use solutes such as fluorescein can be used as a proxy for estimating the osmolarity. The concentration of fluorescein is not measured directly either but the intensity as a function of concentration and thickness of the film is well established. We derived a mathematical model that couples multiple solutes and fluid dynamics within the tear film on a 2D eye-shaped domain. The model includes the physical effects of evaporation, surface tension, viscosity, ocular surface wettability, osmolarity, osmosis, fluorescence and tear fluid supply and drainage. We solved the governing system of coupled nonlinear PDEs using the Overture computational framework developed at LLNL, together with a hybrid time stepping scheme (using variable step BDF and RKC). Results of our numerical simulations provide new insight about the osmolarity distribution and its connection with images obtained in vivo over the whole ocular surface and in local regions of tear thinning due to evaporation and other effects. This work was supported in part by NSF grants 1022706 and 1412085, and NIH grant 1R01EY021794.

Semi-implicit integration factor methods on sparse grids for high-dimensional systems

NASA Astrophysics Data System (ADS)

Wang, Dongyong; Chen, Weitao; Nie, Qing

2015-07-01

Numerical methods for partial differential equations in high-dimensional spaces are often limited by the curse of dimensionality. Though the sparse grid technique, based on a one-dimensional hierarchical basis through tensor products, is popular for handling challenges such as those associated with spatial discretization, the stability conditions on time step size due to temporal discretization, such as those associated with high-order derivatives in space and stiff reactions, remain. Here, we incorporate the sparse grids with the implicit integration factor method (IIF) that is advantageous in terms of stability conditions for systems containing stiff reactions and diffusions. We combine IIF, in which the reaction is treated implicitly and the diffusion is treated explicitly and exactly, with various sparse grid techniques based on the finite element and finite difference methods and a multi-level combination approach. The overall method is found to be efficient in terms of both storage and computational time for solving a wide range of PDEs in high dimensions. In particular, the IIF with the sparse grid combination technique is flexible and effective in solving systems that may include cross-derivatives and non-constant diffusion coefficients. Extensive numerical simulations in both linear and nonlinear systems in high dimensions, along with applications of diffusive logistic equations and Fokker-Planck equations, demonstrate the accuracy, efficiency, and robustness of the new methods, indicating potential broad applications of the sparse grid-based integration factor method.

Monte-Carlo Event Generators for Jet Modification in d(p)-A and A-A Collisions

NASA Astrophysics Data System (ADS)

Kordell, Michael C., III

This work outlines methods to use jet simulations to study both initial and final state nuclear effects in heavy-ion collisions. To study the initial state of heavy-ion collisions, the production of jets and high momentum hadrons from jets, produced in deuteron (d)-Au collisions at the relativistic heavy-ion collider (RHIC) and proton (p)- Pb collisions at the large hadron collider (LHC) are studied as a function of centrality, a measure of the impact parameter of the collision. A modified version of the event generator PYTHIA, widely used to simulate p-p collisions, is used in conjunction with a nuclear Monte-Carlo event generator which simulates the locations of the nucleons within a large nucleus. It is demonstrated how events with a hard jet may be simulated, in such a way that the parton distribution function of the projectile is frozen during its interaction with the extended nucleus. Using this approach, it is demonstrated that the puzzling enhancement seen in peripheral events at RHIC and the LHC, as well as the suppression seen in central events at the LHC are mainly due to mis-binning of central and semi-central events, containing a jet, as peripheral events. This occurs due to the suppression of soft particle production away from the jet, caused by the depletion of energy available in a nucleon of the deuteron (in d-Au at RHIC) or in the proton (in p-Pb at LHC), after the production of a hard jet. In conclusion, partonic correlations built out of simple energy conservation are responsible for such an effect, though these are sampled at the hard scale of jet production and, as such, represent smaller states. To study final state nuclear effects, the modification of hard jets in the Quark Gluon Plasma (QGP) is simulated using the MATTER event generator. Based on the higher twist formalism of energy loss, the MATTER event generator simulates the evolution of highly virtual partons through a medium. These partons sampled from an underlying PYTHIA kernel undergo splitting through a combination of vacuum and medium induced emission. The momentum exchange with the medium is simulated via the jet transport coefficient q̂, which is assumed to scale with the entropy density at a given location in the medium. The entropy density is obtained from a relativistic viscous fluid dynamics simulation (VISH2+1D) in 2+1 space time dimensions. Results for jet and hadron observables are presented using an independent fragmentation model.

Discrete event simulation tool for analysis of qualitative models of continuous processing systems

NASA Technical Reports Server (NTRS)

Malin, Jane T. (Inventor); Basham, Bryan D. (Inventor); Harris, Richard A. (Inventor)

1990-01-01

An artificial intelligence design and qualitative modeling tool is disclosed for creating computer models and simulating continuous activities, functions, and/or behavior using developed discrete event techniques. Conveniently, the tool is organized in four modules: library design module, model construction module, simulation module, and experimentation and analysis. The library design module supports the building of library knowledge including component classes and elements pertinent to a particular domain of continuous activities, functions, and behavior being modeled. The continuous behavior is defined discretely with respect to invocation statements, effect statements, and time delays. The functionality of the components is defined in terms of variable cluster instances, independent processes, and modes, further defined in terms of mode transition processes and mode dependent processes. Model construction utilizes the hierarchy of libraries and connects them with appropriate relations. The simulation executes a specialized initialization routine and executes events in a manner that includes selective inherency of characteristics through a time and event schema until the event queue in the simulator is emptied. The experimentation and analysis module supports analysis through the generation of appropriate log files and graphics developments and includes the ability of log file comparisons.

Discrete event simulation: the preferred technique for health economic evaluations?

PubMed

Caro, Jaime J; Möller, Jörgen; Getsios, Denis

2010-12-01

To argue that discrete event simulation should be preferred to cohort Markov models for economic evaluations in health care. The basis for the modeling techniques is reviewed. For many health-care decisions, existing data are insufficient to fully inform them, necessitating the use of modeling to estimate the consequences that are relevant to decision-makers. These models must reflect what is known about the problem at a level of detail sufficient to inform the questions. Oversimplification will result in estimates that are not only inaccurate, but potentially misleading. Markov cohort models, though currently popular, have so many limitations and inherent assumptions that they are inadequate to inform most health-care decisions. An event-based individual simulation offers an alternative much better suited to the problem. A properly designed discrete event simulation provides more accurate, relevant estimates without being computationally prohibitive. It does require more data and may be a challenge to convey transparently, but these are necessary trade-offs to provide meaningful and valid results. In our opinion, discrete event simulation should be the preferred technique for health economic evaluations today. © 2010, International Society for Pharmacoeconomics and Outcomes Research (ISPOR).

Running Parallel Discrete Event Simulators on Sierra

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barnes, P. D.; Jefferson, D. R.

2015-12-03

In this proposal we consider porting the ROSS/Charm++ simulator and the discrete event models that run under its control so that they run on the Sierra architecture and make efficient use of the Volta GPUs.

An investigation into pilot and system response to critical in-flight events, volume 2

NASA Technical Reports Server (NTRS)

Rockwell, T. H.; Giffin, W. C.

1981-01-01

Critical in-flight event is studied using mission simulation and written tests of pilot responses. Materials and procedures used in knowledge tests, written tests, and mission simulations are included

3D Simulation of External Flooding Events for the RISMC Pathway

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prescott, Steven; Mandelli, Diego; Sampath, Ramprasad

2015-09-01

Incorporating 3D simulations as part of the Risk-Informed Safety Margins Characterization (RISMIC) Toolkit allows analysts to obtain a more complete picture of complex system behavior for events including external plant hazards. External events such as flooding have become more important recently – however these can be analyzed with existing and validated simulated physics toolkits. In this report, we describe these approaches specific to flooding-based analysis using an approach called Smoothed Particle Hydrodynamics. The theory, validation, and example applications of the 3D flooding simulation are described. Integrating these 3D simulation methods into computational risk analysis provides a spatial/visual aspect to themore » design, improves the realism of results, and can prove visual understanding to validate the analysis of flooding.« less

Pseudo-global warming controls on the intensity and morphology of extreme convective storm events

NASA Astrophysics Data System (ADS)

Trapp, R. J.

2015-12-01

This research seeks to answer the basic question of how current-day extreme convective storm events might be represented under future anthropogenic climate change. We adapt the "pseudo-global warming" (PGW) methodology employed by Lackmann (2013, 2015) and others, who have investigated flooding and tropical cyclone events under climate change. Here, we exploit coupled atmosphere-ocean GCM data contributed to the CMIP5 archive, and take the mean 3D atmospheric state simulated during May 1990-1999 and subtract it from that simulated during May 2090-2099. Such 3D changes in temperature, humidity, geopotential height, and winds are added to synoptic/meso-scale analyses (NAM-ANL) of specific events, and this modified atmospheric state is then used for initial and boundary conditions for real-data WRF model simulations of the events at high resolution. Comparison of an ensemble of these simulations with control (CTRL) simulations facilitates assessment of PGW effects. In contrast to the robust development of supercellular convection in our CTRL simulations, the combined effects of increased CIN and decreased forcing under PGW led to a failure of convection initiation in many of our ensemble members. Those members that had sufficient matching between the CIN and forcing tended to generate stronger convective updrafts than in the CTRL simulations, because of the relatively higher CAPE under PGW. And, the members with enhanced updrafts also tended to have enhanced vertical rotation. In fact, such mesocyclonic rotation and attendant supercellular morphology were even found in simulations that were driven with PGW-reduced environmental wind shear.

Simulation of earthquake ground motions in the eastern United States using deterministic physics‐based and site‐based stochastic approaches

USGS Publications Warehouse

Rezaeian, Sanaz; Hartzell, Stephen; Sun, Xiaodan; Mendoza, Carlos

2017-01-01

Earthquake ground‐motion recordings are scarce in the central and eastern United States (CEUS) for large‐magnitude events and at close distances. We use two different simulation approaches, a deterministic physics‐based method and a site‐based stochastic method, to simulate ground motions over a wide range of magnitudes. Drawing on previous results for the modeling of recordings from the 2011 Mw 5.8 Mineral, Virginia, earthquake and using the 2001 Mw 7.6 Bhuj, India, earthquake as a tectonic analog for a large magnitude CEUS event, we are able to calibrate the two simulation methods over this magnitude range. Both models show a good fit to the Mineral and Bhuj observations from 0.1 to 10 Hz. Model parameters are then adjusted to obtain simulations for Mw 6.5, 7.0, and 7.6 events in the CEUS. Our simulations are compared with the 2014 U.S. Geological Survey weighted combination of existing ground‐motion prediction equations in the CEUS. The physics‐based simulations show comparable response spectral amplitudes and a fairly similar attenuation with distance. The site‐based stochastic simulations suggest a slightly faster attenuation of the response spectral amplitudes with distance for larger magnitude events and, as a result, slightly lower amplitudes at distances greater than 200 km. Both models are plausible alternatives and, given the few available data points in the CEUS, can be used to represent the epistemic uncertainty in modeling of postulated CEUS large‐magnitude events.

Performance of residents and anesthesiologists in a simulation-based skill assessment.

PubMed

Murray, David J; Boulet, John R; Avidan, Michael; Kras, Joseph F; Henrichs, Bernadette; Woodhouse, Julie; Evers, Alex S

2007-11-01

Anesthesiologists and anesthesia residents are expected to acquire and maintain skills to manage a wide range of acute intraoperative anesthetic events. The purpose of this study was to determine whether an inventory of simulated intraoperative scenarios provided a reliable and valid measure of anesthesia residents' and anesthesiologists' skill. Twelve simulated acute intraoperative scenarios were designed to assess the performance of 64 residents and 35 anesthesiologists. The participants were divided into four groups based on their training and experience. There were 31 new CA-1, 12 advanced CA-1, and 22 CA-2/CA-3 residents as well as a group of 35 experienced anesthesiologists who participated in the assessment. Each participant managed a set of simulated events. The advanced CA-1 residents, CA-2/CA-3 residents, and 35 anesthesiologists managed 8 of 12 intraoperative simulation exercises. The 31 CA-1 residents each managed 3 intraoperative scenarios. The new CA-1 residents received lower scores on the simulated intraoperative events than the other groups of participants. The advanced CA-1 residents, CA-2/CA-3 residents, and anesthesiologists performed similarly on the overall assessment. There was a wide range of scores obtained by individuals in each group. A number of the exercises were difficult for the majority of participants to recognize and treat, but most events effectively discriminated among participants who achieved higher and lower overall scores. This simulation-based assessment provided a valid method to distinguish the skills of more experienced anesthesia residents and anesthesiologists from residents in early training. The overall score provided a reliable measure of a participant's ability to recognize and manage simulated acute intraoperative events. Additional studies are needed to determine whether these simulation-based assessments are valid measures of clinical performance.

Using Discrete Event Simulation for Programming Model Exploration at Extreme-Scale: Macroscale Components for the Structural Simulation Toolkit (SST).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilke, Jeremiah J; Kenny, Joseph P.

2015-02-01

Discrete event simulation provides a powerful mechanism for designing and testing new extreme- scale programming models for high-performance computing. Rather than debug, run, and wait for results on an actual system, design can first iterate through a simulator. This is particularly useful when test beds cannot be used, i.e. to explore hardware or scales that do not yet exist or are inaccessible. Here we detail the macroscale components of the structural simulation toolkit (SST). Instead of depending on trace replay or state machines, the simulator is architected to execute real code on real software stacks. Our particular user-space threading frameworkmore » allows massive scales to be simulated even on small clusters. The link between the discrete event core and the threading framework allows interesting performance metrics like call graphs to be collected from a simulated run. Performance analysis via simulation can thus become an important phase in extreme-scale programming model and runtime system design via the SST macroscale components.« less

SQERTSS: Dynamic rank based throttling of transition probabilities in kinetic Monte Carlo simulations

DOE PAGES

Danielson, Thomas; Sutton, Jonathan E.; Hin, Céline; ...

2017-06-09

Lattice based Kinetic Monte Carlo (KMC) simulations offer a powerful simulation technique for investigating large reaction networks while retaining spatial configuration information, unlike ordinary differential equations. However, large chemical reaction networks can contain reaction processes with rates spanning multiple orders of magnitude. This can lead to the problem of “KMC stiffness” (similar to stiffness in differential equations), where the computational expense has the potential to be overwhelmed by very short time-steps during KMC simulations, with the simulation spending an inordinate amount of KMC steps / cpu-time simulating fast frivolous processes (FFPs) without progressing the system (reaction network). In order tomore » achieve simulation times that are experimentally relevant or desired for predictions, a dynamic throttling algorithm involving separation of the processes into speed-ranks based on event frequencies has been designed and implemented with the intent of decreasing the probability of FFP events, and increasing the probability of slow process events -- allowing rate limiting events to become more likely to be observed in KMC simulations. This Staggered Quasi-Equilibrium Rank-based Throttling for Steady-state (SQERTSS) algorithm designed for use in achieving and simulating steady-state conditions in KMC simulations. Lastly, as shown in this work, the SQERTSS algorithm also works for transient conditions: the correct configuration space and final state will still be achieved if the required assumptions are not violated, with the caveat that the sizes of the time-steps may be distorted during the transient period.« less

SQERTSS: Dynamic rank based throttling of transition probabilities in kinetic Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Danielson, Thomas; Sutton, Jonathan E.; Hin, Céline; Savara, Aditya

2017-10-01

Lattice based Kinetic Monte Carlo (KMC) simulations offer a powerful simulation technique for investigating large reaction networks while retaining spatial configuration information, unlike ordinary differential equations. However, large chemical reaction networks can contain reaction processes with rates spanning multiple orders of magnitude. This can lead to the problem of "KMC stiffness" (similar to stiffness in differential equations), where the computational expense has the potential to be overwhelmed by very short time-steps during KMC simulations, with the simulation spending an inordinate amount of KMC steps/CPU time simulating fast frivolous processes (FFPs) without progressing the system (reaction network). In order to achieve simulation times that are experimentally relevant or desired for predictions, a dynamic throttling algorithm involving separation of the processes into speed-ranks based on event frequencies has been designed and implemented with the intent of decreasing the probability of FFP events, and increasing the probability of slow process events-allowing rate limiting events to become more likely to be observed in KMC simulations. This Staggered Quasi-Equilibrium Rank-based Throttling for Steady-state (SQERTSS) algorithm is designed for use in achieving and simulating steady-state conditions in KMC simulations. As shown in this work, the SQERTSS algorithm also works for transient conditions: the correct configuration space and final state will still be achieved if the required assumptions are not violated, with the caveat that the sizes of the time-steps may be distorted during the transient period.

Shared cognitive processes underlying past and future thinking: the impact of imagery and concurrent task demands on event specificity.

PubMed

Anderson, Rachel J; Dewhurst, Stephen A; Nash, Robert A

2012-03-01

Recent literature has argued that whereas remembering the past and imagining the future make use of shared cognitive substrates, simulating future events places heavier demands on executive resources. These propositions were explored in 3 experiments comparing the impact of imagery and concurrent task demands on speed and accuracy of past event retrieval and future event simulation. Results provide support for the suggestion that both past and future episodes can be constructed through 2 mechanisms: a noneffortful "direct" pathway and a controlled, effortful "generative" pathway. However, limited evidence emerged for the suggestion that simulating of future, compared with retrieving past, episodes places heavier demands on executive resources; only under certain conditions did it emerge as a more error prone and lengthier process. The findings are discussed in terms of how retrieval and simulation make use of the same cognitive substrates in subtly different ways. 2012 APA, all rights reserved

Heinrich events simulated across the glacial

NASA Astrophysics Data System (ADS)

Ziemen, F. A.; Mikolajewicz, U.

2015-12-01

Heinrich events are among the most prominent climate change events recorded in proxies across the northern hemisphere. They are the archetype of ice sheet — climate interactions on millennial time scales. Nevertheless, the exact mechanisms that cause Heinrich events are still under discussion, and their climatic consequences are far from being fully understood. We contribute to answering the open questions by studying Heinrich events in a coupled ice sheet model (ISM) atmosphere-ocean-vegetation general circulation model (AOVGCM) framework, where this variability occurs as part of the model generated internal variability. The setup consists of a northern hemisphere setup of the modified Parallel Ice Sheet Model (mPISM) coupled to the global AOVGCM ECHAM5/MPIOM/LPJ. The simulations were performed fully coupled and with transient orbital and greenhouse gas forcing. They span from several millennia before the last glacial maximum into the deglaciation. We analyze simulations where the ISM is coupled asynchronously to the AOVGCM and simulations where the ISM and the ocean model are coupled synchronously and the atmosphere model is coupled asynchronously to them. The modeled Heinrich events show a marked influence of the ice discharge on the Atlantic circulation and heat transport.

DVS-SOFTWARE: An Effective Tool for Applying Highly Parallelized Hardware To Computational Geophysics

NASA Astrophysics Data System (ADS)

Herrera, I.; Herrera, G. S.

2015-12-01

Most geophysical systems are macroscopic physical systems. The behavior prediction of such systems is carried out by means of computational models whose basic models are partial differential equations (PDEs) [1]. Due to the enormous size of the discretized version of such PDEs it is necessary to apply highly parallelized super-computers. For them, at present, the most efficient software is based on non-overlapping domain decomposition methods (DDM). However, a limiting feature of the present state-of-the-art techniques is due to the kind of discretizations used in them. Recently, I. Herrera and co-workers using 'non-overlapping discretizations' have produced the DVS-Software which overcomes this limitation [2]. The DVS-software can be applied to a great variety of geophysical problems and achieves very high parallel efficiencies (90%, or so [3]). It is therefore very suitable for effectively applying the most advanced parallel supercomputers available at present. In a parallel talk, in this AGU Fall Meeting, Graciela Herrera Z. will present how this software is being applied to advance MOD-FLOW. Key Words: Parallel Software for Geophysics, High Performance Computing, HPC, Parallel Computing, Domain Decomposition Methods (DDM)REFERENCES [1]. Herrera Ismael and George F. Pinder, Mathematical Modelling in Science and Engineering: An axiomatic approach", John Wiley, 243p., 2012. [2]. Herrera, I., de la Cruz L.M. and Rosas-Medina A. "Non Overlapping Discretization Methods for Partial, Differential Equations". NUMER METH PART D E, 30: 1427-1454, 2014, DOI 10.1002/num 21852. (Open source) [3]. Herrera, I., & Contreras Iván "An Innovative Tool for Effectively Applying Highly Parallelized Software To Problems of Elasticity". Geofísica Internacional, 2015 (In press)

AKAP3 Selectively Binds PDE4A Isoforms in Bovine Spermatozoa1

PubMed Central

Bajpai, Malini; Fiedler, Sarah E.; Huang, Zaohua; Vijayaraghavan, Srinivasan; Olson, Gary E.; Livera, Gabriel; Conti, Marco; Carr, Daniel W.

2006-01-01

Cyclic AMP plays an important role in regulating sperm motility and acrosome reaction through activation of cAMP-dependent protein kinase A (PKA). Phosphodiesterases (PDEs) modulate the levels of cyclic nucleotides by catalyzing their degradation. Although PDE inhibitors specific to PDE1 and PDE4 are known to alter sperm motility and capacitation in humans, little is known about the role or subcellular distribution of PDEs in spermatozoa. The localization of PKA is regulated by A-kinase anchoring proteins (AKAPs), which may also control the intracellular distribution of PDE. The present study was undertaken to investigate the role and localization of PDE4 during sperm capacitation. Addition of Rolipram or RS25344, PDE4-specific inhibitors significantly increased the progressive motility of bovine spermatozoa. Immunolocalization techniques detected both PDE4A and AKAP3 (formerly known as AKAP110) in the principal piece of bovine spermatozoa. The PDE4A5 isoform was detected primarily in the Triton X-100-soluble fraction of caudal epididymal spermatozoa. However, in ejaculated spermatozoa it was seen primarily in the SDS-soluble fraction, indicating a shift in PDE4A5 localization into insoluble organelles during sperm capacitation. AKAP3 was detected only in the SDS-soluble fraction of both caudal and ejaculated sperm. Immunoprecipitation experiments using COS cells cotransfected with AKAP3 and either Pde4a5 or Pde4d provide evidence that PDE4A5 but not PDE4D interacts with AKAP3. Pulldown assays using sperm cell lysates confirm this interaction in vitro. These data suggest that AKAP3 binds both PKA and PDE4A and functions as a scaffolding protein in spermatozoa to regulate local cAMP concentrations and modulate sperm functions. PMID:16177223

On the optimal systems of subalgebras for the equations of hydrodynamic stability analysis of smooth shear flows and their group-invariant solutions

NASA Astrophysics Data System (ADS)

Hau, Jan-Niklas; Oberlack, Martin; Chagelishvili, George

2017-04-01

We present a unifying solution framework for the linearized compressible equations for two-dimensional linearly sheared unbounded flows using the Lie symmetry analysis. The full set of symmetries that are admitted by the underlying system of equations is employed to systematically derive the one- and two-dimensional optimal systems of subalgebras, whose connected group reductions lead to three distinct invariant ansatz functions for the governing sets of partial differential equations (PDEs). The purpose of this analysis is threefold and explicitly we show that (i) there are three invariant solutions that stem from the optimal system. These include a general ansatz function with two free parameters, as well as the ansatz functions of the Kelvin mode and the modal approach. Specifically, the first approach unifies these well-known ansatz functions. By considering two limiting cases of the free parameters and related algebraic transformations, the general ansatz function is reduced to either of them. This fact also proves the existence of a link between the Kelvin mode and modal ansatz functions, as these appear to be the limiting cases of the general one. (ii) The Lie algebra associated with the Lie group admitted by the PDEs governing the compressible dynamics is a subalgebra associated with the group admitted by the equations governing the incompressible dynamics, which allows an additional (scaling) symmetry. Hence, any consequences drawn from the compressible case equally hold for the incompressible counterpart. (iii) In any of the systems of ordinary differential equations, derived by the three ansatz functions in the compressible case, the linearized potential vorticity is a conserved quantity that allows us to analyze vortex and wave mode perturbations separately.

Parallel Allostery by cAMP and PDE Coordinates Activation and Termination Phases in cAMP Signaling.

PubMed

Krishnamurthy, Srinath; Tulsian, Nikhil Kumar; Chandramohan, Arun; Anand, Ganesh S

2015-09-15

The second messenger molecule cAMP regulates the activation phase of the cAMP signaling pathway through high-affinity interactions with the cytosolic cAMP receptor, the protein kinase A regulatory subunit (PKAR). Phosphodiesterases (PDEs) are enzymes responsible for catalyzing hydrolysis of cAMP to 5' AMP. It was recently shown that PDEs interact with PKAR to initiate the termination phase of the cAMP signaling pathway. While the steps in the activation phase are well understood, steps in the termination pathway are unknown. Specifically, the binding and allosteric networks that regulate the dynamic interplay between PKAR, PDE, and cAMP are unclear. In this study, PKAR and PDE from Dictyostelium discoideum (RD and RegA, respectively) were used as a model system to monitor complex formation in the presence and absence of cAMP. Amide hydrogen/deuterium exchange mass spectrometry was used to monitor slow conformational transitions in RD, using disordered regions as conformational probes. Our results reveal that RD regulates its interactions with cAMP and RegA at distinct loci by undergoing slow conformational transitions between two metastable states. In the presence of cAMP, RD and RegA form a stable ternary complex, while in the absence of cAMP they maintain transient interactions. RegA and cAMP each bind at orthogonal sites on RD with resultant contrasting effects on its dynamics through parallel allosteric relays at multiple important loci. RD thus serves as an integrative node in cAMP termination by coordinating multiple allosteric relays and governing the output signal response. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Cardiac Hypertrophy Is Inhibited by a Local Pool of cAMP Regulated by Phosphodiesterase 2.

PubMed

Zoccarato, Anna; Surdo, Nicoletta C; Aronsen, Jan M; Fields, Laura A; Mancuso, Luisa; Dodoni, Giuliano; Stangherlin, Alessandra; Livie, Craig; Jiang, He; Sin, Yuan Yan; Gesellchen, Frank; Terrin, Anna; Baillie, George S; Nicklin, Stuart A; Graham, Delyth; Szabo-Fresnais, Nicolas; Krall, Judith; Vandeput, Fabrice; Movsesian, Matthew; Furlan, Leonardo; Corsetti, Veronica; Hamilton, Graham; Lefkimmiatis, Konstantinos; Sjaastad, Ivar; Zaccolo, Manuela

2015-09-25

Chronic elevation of 3'-5'-cyclic adenosine monophosphate (cAMP) levels has been associated with cardiac remodeling and cardiac hypertrophy. However, enhancement of particular aspects of cAMP/protein kinase A signaling seems to be beneficial for the failing heart. cAMP is a pleiotropic second messenger with the ability to generate multiple functional outcomes in response to different extracellular stimuli with strict fidelity, a feature that relies on the spatial segregation of the cAMP pathway components in signaling microdomains. How individual cAMP microdomains affect cardiac pathophysiology remains largely to be established. The cAMP-degrading enzymes phosphodiesterases (PDEs) play a key role in shaping local changes in cAMP. Here we investigated the effect of specific inhibition of selected PDEs on cardiac myocyte hypertrophic growth. Using pharmacological and genetic manipulation of PDE activity, we found that the rise in cAMP resulting from inhibition of PDE3 and PDE4 induces hypertrophy, whereas increasing cAMP levels via PDE2 inhibition is antihypertrophic. By real-time imaging of cAMP levels in intact myocytes and selective displacement of protein kinase A isoforms, we demonstrate that the antihypertrophic effect of PDE2 inhibition involves the generation of a local pool of cAMP and activation of a protein kinase A type II subset, leading to phosphorylation of the nuclear factor of activated T cells. Different cAMP pools have opposing effects on cardiac myocyte cell size. PDE2 emerges as a novel key regulator of cardiac hypertrophy in vitro and in vivo, and its inhibition may have therapeutic applications. © 2015 American Heart Association, Inc.

Identification of the gamma subunit-interacting residues on photoreceptor cGMP phosphodiesterase, PDE6alpha '.

PubMed

Granovsky, A E; Artemyev, N O

2000-12-29

Photoreceptor cGMP phosphodiesterase (PDE6) is the effector enzyme in the G protein-mediated visual transduction cascade. In the dark, the activity of PDE6 is shut off by the inhibitory gamma subunit (Pgamma). Chimeric proteins between cone PDE6alpha' and cGMP-binding and cGMP-specific PDE (PDE5) have been constructed and expressed in Sf9 cells to study the mechanism of inhibition of PDE6 catalytic activity by Pgamma. Substitution of the segment PDE5-(773-820) by the corresponding PDE6alpha'-(737-784) sequence in the wild-type PDE5 or in a PDE5/PDE6alpha' chimera containing the catalytic domain of PDE5 results in chimeric enzymes capable of inhibitory interaction with Pgamma. The catalytic properties of the chimeric PDEs remained similar to those of PDE5. Ala-scanning mutational analysis of the Pgamma-binding region, PDE6alpha'-(750-760), revealed PDE6alpha' residues essential for the interaction. The M758A mutation markedly impaired and the Q752A mutation moderately impaired the inhibition of chimeric PDE by Pgamma. The analysis of the catalytic properties of mutant PDEs and a model of the PDE6 catalytic domain suggest that residues Met(758) and Gln(752) directly bind Pgamma. A model of the PDE6 catalytic site shows that PDE6alpha'-(750-760) forms a loop at the entrance to the cGMP-binding pocket. Binding of Pgamma to Met(758) would effectively block access of cGMP to the catalytic cavity, providing a structural basis for the mechanism of PDE6 inhibition.

Role of Phosphodiesterases on the Function of Aryl Hydrocarbon Receptor-Interacting Protein (AIP) in the Pituitary Gland and on the Evaluation of AIP Gene Variants.

PubMed

Hernández-Ramírez, Laura C; Trivellin, Giampaolo; Stratakis, Constantine A

2017-04-01

Familial isolated pituitary adenoma (FIPA) is caused in about 20% of cases by loss-of-function germline mutations in the AIP gene. Patients harboring AIP mutations usually present with somatotropinomas resulting either in gigantism or young-onset acromegaly. AIP encodes for a co-chaperone protein endowed with tumor suppressor properties in somatotroph cells. Among other mechanisms proposed to explain this function, a regulatory effect over the 3',5'-cyclic adenosine monophosphate (cAMP) signaling pathway seems to play a prominent role. In this setting, the well-known interaction between AIP and 2 different isoforms of phosphodiesterases (PDEs), PDE2A3 and PDE4A5, is of particular interest. While the interaction with over-expressed AIP does not seem to affect PDE2A3 function, the reported effect on PDE4A5 is, in contrast, reduced enzymatic activity. In this review, we explore the possible implications of these molecular interactions for the function of somatotroph cells. In particular, we discuss how both PDEs and AIP could act as negative regulators of the cAMP pathway in the pituitary, probably both by shared and independent mechanisms. Moreover, we describe how the evaluation of the AIP-PDE4A5 interaction has proven to be a useful tool for testing AIP mutations, complementing other in silico, in vitro, and in vivo analyses. Improved assessment of the pathogenicity of AIP mutations is indeed paramount to provide adequate guidance for genetic counseling and clinical screening in AIP mutation carriers, which can lead to prospective diagnosis of pituitary adenomas. © Georg Thieme Verlag KG Stuttgart · New York.

Sildenafil, a selective phosphodiesterase type 5 inhibitor, enhances memory reconsolidation of an inhibitory avoidance task in mice.

PubMed

Boccia, M M; Blake, M G; Krawczyk, M C; Baratti, C M

2011-07-07

Intracellular levels of the second messengers cAMP and cGMP are maintained through a balance between production, carried out by adenyl cyclase (AC) and guanylyl cyclase (GC), and degradation, carried out by phosphodiesterases (PDEs). Recently, PDEs have gained increased attention as potential new targets for cognition enhancement, with particular reference to phosphodiesterase type 5 (PDE5A). It is accepted that once consolidation is completed memory becomes permanent, but it has also been suggested that reactivation (memory retrieval) of the original memory makes it sensitive to the same treatments that affect memory consolidation when given after training. This new period of sensitivity coined the term reconsolidation. Sildenafil (1, 3, and 10mg/kg, ip), a cGMP-PDE5 inhibitor, facilitated retention performance of a one-trial step-through inhibitory avoidance task, when administered to CF-1 male mice immediately after retrieval. The effects of sildenafil (1mg/kg, ip) were time-dependent, long-lasting and inversely correlated with memory age. The administration of sildenafil (1mg/kg, ip) 30 min prior to the 2nd retention test did not affect retention of mice given post-retrieval injections of either vehicle or sildenafil (1mg/kg, ip). Finally, an enhancement of retention was also observed in CF-1 female mice receiving sildenafil (1mg/kg, ip) immediately, but not 180 min after retrieval. In the present paper we reported for the first time that systemic administration of sildenafil after memory reactivation enhances retention performance of the original learning. Our results indirectly point out cGMP, a component of the NO/cGMP/PKG pathway, as a necessary factor for memory reconsolidation. Copyright © 2011 Elsevier B.V. All rights reserved.

Numerical methods for solving moment equations in kinetic theory of neuronal network dynamics

NASA Astrophysics Data System (ADS)

Rangan, Aaditya V.; Cai, David; Tao, Louis

2007-02-01

Recently developed kinetic theory and related closures for neuronal network dynamics have been demonstrated to be a powerful theoretical framework for investigating coarse-grained dynamical properties of neuronal networks. The moment equations arising from the kinetic theory are a system of (1 + 1)-dimensional nonlinear partial differential equations (PDE) on a bounded domain with nonlinear boundary conditions. The PDEs themselves are self-consistently specified by parameters which are functions of the boundary values of the solution. The moment equations can be stiff in space and time. Numerical methods are presented here for efficiently and accurately solving these moment equations. The essential ingredients in our numerical methods include: (i) the system is discretized in time with an implicit Euler method within a spectral deferred correction framework, therefore, the PDEs of the kinetic theory are reduced to a sequence, in time, of boundary value problems (BVPs) with nonlinear boundary conditions; (ii) a set of auxiliary parameters is introduced to recast the original BVP with nonlinear boundary conditions as BVPs with linear boundary conditions - with additional algebraic constraints on the auxiliary parameters; (iii) a careful combination of two Newton's iterates for the nonlinear BVP with linear boundary condition, interlaced with a Newton's iterate for solving the associated algebraic constraints is constructed to achieve quadratic convergence for obtaining the solutions with self-consistent parameters. It is shown that a simple fixed-point iteration can only achieve a linear convergence for the self-consistent parameters. The practicability and efficiency of our numerical methods for solving the moment equations of the kinetic theory are illustrated with numerical examples. It is further demonstrated that the moment equations derived from the kinetic theory of neuronal network dynamics can very well capture the coarse-grained dynamical properties of integrate-and-fire neuronal networks.

El Nino - La Nina events simulated with Cane and Zebiak`s model and observed with satellite or in situ data. Part I: Model data comparison

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perigaud C.; Dewitte, B.

The Zebiak and Cane model is used in its {open_quotes}uncoupled mode,{close_quotes} meaning that the oceanic model component is driven by the Florida State University (FSU) wind stress anomalies over 1980-93 to simulate sea surface temperature anomalies, and these are used in the atmospheric model component to generate wind anomalies. Simulations are compared with data derived from FSU winds, International Satellite Cloud Climatology Project cloud convection, Advanced Very High Resolution Radiometer SST, Geosat sea level, 20{degrees}C isotherm depth derived from an expendable bathythermograph, and current velocities estimated from drifters or current-meter moorings. Forced by the simulated SST, the atmospheric model ismore » fairly successful in reproducing the observed westerlies during El Nino events. The model fails to simulate the easterlies during La Nina 1988. The simulated forcing of the atmosphere is in very poor agreement with the heating derived from cloud convection data. Similarly, the model is fairly successful in reproducing the warm anomalies during El Nino events. However, it fails to simulate the observed cold anomalies. Simulated variations of thermocline depth agree reasonably well with observations. The model simulates zonal current anomalies that are reversing at a dominant 9-month frequency. Projecting altimetric observations on Kelvin and Rossby waves provides an estimate of zonal current anomalies, which is consistent with the ones derived from drifters or from current meter moorings. Unlike the simulated ones, the observed zonal current anomalies reverse from eastward during El Nino events to westward during La Nina events. The simulated 9-month oscillations correspond to a resonant mode of the basin. They can be suppressed by cancelling the wave reflection at the boundaries, or they can be attenuated by increasing the friction in the ocean model. 58 refs., 14 figs., 6 tabs.« less

Reduced Order Modeling for Prediction and Control of Large-Scale Systems.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kalashnikova, Irina; Arunajatesan, Srinivasan; Barone, Matthew Franklin

2014-05-01

This report describes work performed from June 2012 through May 2014 as a part of a Sandia Early Career Laboratory Directed Research and Development (LDRD) project led by the first author. The objective of the project is to investigate methods for building stable and efficient proper orthogonal decomposition (POD)/Galerkin reduced order models (ROMs): models derived from a sequence of high-fidelity simulations but having a much lower computational cost. Since they are, by construction, small and fast, ROMs can enable real-time simulations of complex systems for onthe- spot analysis, control and decision-making in the presence of uncertainty. Of particular interest tomore » Sandia is the use of ROMs for the quantification of the compressible captive-carry environment, simulated for the design and qualification of nuclear weapons systems. It is an unfortunate reality that many ROM techniques are computationally intractable or lack an a priori stability guarantee for compressible flows. For this reason, this LDRD project focuses on the development of techniques for building provably stable projection-based ROMs. Model reduction approaches based on continuous as well as discrete projection are considered. In the first part of this report, an approach for building energy-stable Galerkin ROMs for linear hyperbolic or incompletely parabolic systems of partial differential equations (PDEs) using continuous projection is developed. The key idea is to apply a transformation induced by the Lyapunov function for the system, and to build the ROM in the transformed variables. It is shown that, for many PDE systems including the linearized compressible Euler and linearized compressible Navier-Stokes equations, the desired transformation is induced by a special inner product, termed the “symmetry inner product”. Attention is then turned to nonlinear conservation laws. A new transformation and corresponding energy-based inner product for the full nonlinear compressible Navier-Stokes equations is derived, and it is demonstrated that if a Galerkin ROM is constructed in this inner product, the ROM system energy will be bounded in a way that is consistent with the behavior of the exact solution to these PDEs, i.e., the ROM will be energy-stable. The viability of the linear as well as nonlinear continuous projection model reduction approaches developed as a part of this project is evaluated on several test cases, including the cavity configuration of interest in the targeted application area. In the second part of this report, some POD/Galerkin approaches for building stable ROMs using discrete projection are explored. It is shown that, for generic linear time-invariant (LTI) systems, a discrete counterpart of the continuous symmetry inner product is a weighted L2 inner product obtained by solving a Lyapunov equation. This inner product was first proposed by Rowley et al., and is termed herein the “Lyapunov inner product“. Comparisons between the symmetry inner product and the Lyapunov inner product are made, and the performance of ROMs constructed using these inner products is evaluated on several benchmark test cases. Also in the second part of this report, a new ROM stabilization approach, termed “ROM stabilization via optimization-based eigenvalue reassignment“, is developed for generic LTI systems. At the heart of this method is a constrained nonlinear least-squares optimization problem that is formulated and solved numerically to ensure accuracy of the stabilized ROM. Numerical studies reveal that the optimization problem is computationally inexpensive to solve, and that the new stabilization approach delivers ROMs that are stable as well as accurate. Summaries of “lessons learned“ and perspectives for future work motivated by this LDRD project are provided at the end of each of the two main chapters.« less

Simulation of EAST vertical displacement events by tokamak simulation code

NASA Astrophysics Data System (ADS)

Qiu, Qinglai; Xiao, Bingjia; Guo, Yong; Liu, Lei; Xing, Zhe; Humphreys, D. A.

2016-10-01

Vertical instability is a potentially serious hazard for elongated plasma. In this paper, the tokamak simulation code (TSC) is used to simulate vertical displacement events (VDE) on the experimental advanced superconducting tokamak (EAST). Key parameters from simulations, including plasma current, plasma shape and position, flux contours and magnetic measurements match experimental data well. The growth rates simulated by TSC are in good agreement with TokSys results. In addition to modeling the free drift, an EAST fast vertical control model enables TSC to simulate the course of VDE recovery. The trajectories of the plasma current center and control currents on internal coils (IC) fit experimental data well.

DISCRETE EVENT SIMULATION OF OPTICAL SWITCH MATRIX PERFORMANCE IN COMPUTER NETWORKS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Imam, Neena; Poole, Stephen W

2013-01-01

In this paper, we present application of a Discrete Event Simulator (DES) for performance modeling of optical switching devices in computer networks. Network simulators are valuable tools in situations where one cannot investigate the system directly. This situation may arise if the system under study does not exist yet or the cost of studying the system directly is prohibitive. Most available network simulators are based on the paradigm of discrete-event-based simulation. As computer networks become increasingly larger and more complex, sophisticated DES tool chains have become available for both commercial and academic research. Some well-known simulators are NS2, NS3, OPNET,more » and OMNEST. For this research, we have applied OMNEST for the purpose of simulating multi-wavelength performance of optical switch matrices in computer interconnection networks. Our results suggest that the application of DES to computer interconnection networks provides valuable insight in device performance and aids in topology and system optimization.« less

Just-in-time connectivity for large spiking networks.

PubMed

Lytton, William W; Omurtag, Ahmet; Neymotin, Samuel A; Hines, Michael L

2008-11-01

The scale of large neuronal network simulations is memory limited due to the need to store connectivity information: connectivity storage grows as the square of neuron number up to anatomically relevant limits. Using the NEURON simulator as a discrete-event simulator (no integration), we explored the consequences of avoiding the space costs of connectivity through regenerating connectivity parameters when needed: just in time after a presynaptic cell fires. We explored various strategies for automated generation of one or more of the basic static connectivity parameters: delays, postsynaptic cell identities, and weights, as well as run-time connectivity state: the event queue. Comparison of the JitCon implementation to NEURON's standard NetCon connectivity method showed substantial space savings, with associated run-time penalty. Although JitCon saved space by eliminating connectivity parameters, larger simulations were still memory limited due to growth of the synaptic event queue. We therefore designed a JitEvent algorithm that added items to the queue only when required: instead of alerting multiple postsynaptic cells, a spiking presynaptic cell posted a callback event at the shortest synaptic delay time. At the time of the callback, this same presynaptic cell directly notified the first postsynaptic cell and generated another self-callback for the next delay time. The JitEvent implementation yielded substantial additional time and space savings. We conclude that just-in-time strategies are necessary for very large network simulations but that a variety of alternative strategies should be considered whose optimality will depend on the characteristics of the simulation to be run.

Just in time connectivity for large spiking networks

PubMed Central

Lytton, William W.; Omurtag, Ahmet; Neymotin, Samuel A; Hines, Michael L

2008-01-01

The scale of large neuronal network simulations is memory-limited due to the need to store connectivity information: connectivity storage grows as the square of neuron number up to anatomically-relevant limits. Using the NEURON simulator as a discrete-event simulator (no integration), we explored the consequences of avoiding the space costs of connectivity through regenerating connectivity parameters when needed – just-in-time after a presynaptic cell fires. We explored various strategies for automated generation of one or more of the basic static connectivity parameters: delays, postsynaptic cell identities and weights, as well as run-time connectivity state: the event queue. Comparison of the JitCon implementation to NEURON’s standard NetCon connectivity method showed substantial space savings, with associated run-time penalty. Although JitCon saved space by eliminating connectivity parameters, larger simulations were still memory-limited due to growth of the synaptic event queue. We therefore designed a JitEvent algorithm that only added items to the queue when required: instead of alerting multiple postsynaptic cells, a spiking presynaptic cell posted a callback event at the shortest synaptic delay time. At the time of the callback, this same presynaptic cell directly notified the first postsynaptic cell and generated another self-callback for the next delay time. The JitEvent implementation yielded substantial additional time and space savings. We conclude that just-in-time strategies are necessary for very large network simulations but that a variety of alternative strategies should be considered whose optimality will depend on the characteristics of the simulation to be run. PMID:18533821

A General and Efficient Method for Incorporating Precise Spike Times in Globally Time-Driven Simulations

PubMed Central

Hanuschkin, Alexander; Kunkel, Susanne; Helias, Moritz; Morrison, Abigail; Diesmann, Markus

2010-01-01

Traditionally, event-driven simulations have been limited to the very restricted class of neuronal models for which the timing of future spikes can be expressed in closed form. Recently, the class of models that is amenable to event-driven simulation has been extended by the development of techniques to accurately calculate firing times for some integrate-and-fire neuron models that do not enable the prediction of future spikes in closed form. The motivation of this development is the general perception that time-driven simulations are imprecise. Here, we demonstrate that a globally time-driven scheme can calculate firing times that cannot be discriminated from those calculated by an event-driven implementation of the same model; moreover, the time-driven scheme incurs lower computational costs. The key insight is that time-driven methods are based on identifying a threshold crossing in the recent past, which can be implemented by a much simpler algorithm than the techniques for predicting future threshold crossings that are necessary for event-driven approaches. As run time is dominated by the cost of the operations performed at each incoming spike, which includes spike prediction in the case of event-driven simulation and retrospective detection in the case of time-driven simulation, the simple time-driven algorithm outperforms the event-driven approaches. Additionally, our method is generally applicable to all commonly used integrate-and-fire neuronal models; we show that a non-linear model employing a standard adaptive solver can reproduce a reference spike train with a high degree of precision. PMID:21031031

The ATLAS Simulation Infrastructure

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2010-09-25

The simulation software for the ATLAS Experiment at the Large Hadron Collider is being used for large-scale production of events on the LHC Computing Grid. This simulation requires many components, from the generators that simulate particle collisions, through packages simulating the response of the various detectors and triggers. All of these components come together under the ATLAS simulation infrastructure. In this paper, that infrastructure is discussed, including that supporting the detector description, interfacing the event generation, and combining the GEANT4 simulation of the response of the individual detectors. Also described are the tools allowing the software validation, performance testing, andmore » the validation of the simulated output against known physics processes.« less

Parallel Stochastic discrete event simulation of calcium dynamics in neuron.

PubMed

Ishlam Patoary, Mohammad Nazrul; Tropper, Carl; McDougal, Robert A; Zhongwei, Lin; Lytton, William W

2017-09-26

The intra-cellular calcium signaling pathways of a neuron depends on both biochemical reactions and diffusions. Some quasi-isolated compartments (e.g. spines) are so small and calcium concentrations are so low that one extra molecule diffusing in by chance can make a nontrivial difference in its concentration (percentage-wise). These rare events can affect dynamics discretely in such way that they cannot be evaluated by a deterministic simulation. Stochastic models of such a system provide a more detailed understanding of these systems than existing deterministic models because they capture their behavior at a molecular level. Our research focuses on the development of a high performance parallel discrete event simulation environment, Neuron Time Warp (NTW), which is intended for use in the parallel simulation of stochastic reaction-diffusion systems such as intra-calcium signaling. NTW is integrated with NEURON, a simulator which is widely used within the neuroscience community. We simulate two models, a calcium buffer and a calcium wave model. The calcium buffer model is employed in order to verify the correctness and performance of NTW by comparing it to a serial deterministic simulation in NEURON. We also derived a discrete event calcium wave model from a deterministic model using the stochastic IP3R structure.

Modelling approaches: the case of schizophrenia.

PubMed

Heeg, Bart M S; Damen, Joep; Buskens, Erik; Caleo, Sue; de Charro, Frank; van Hout, Ben A

2008-01-01

Schizophrenia is a chronic disease characterized by periods of relative stability interrupted by acute episodes (or relapses). The course of the disease may vary considerably between patients. Patient histories show considerable inter- and even intra-individual variability. We provide a critical assessment of the advantages and disadvantages of three modelling techniques that have been used in schizophrenia: decision trees, (cohort and micro-simulation) Markov models and discrete event simulation models. These modelling techniques are compared in terms of building time, data requirements, medico-scientific experience, simulation time, clinical representation, and their ability to deal with patient heterogeneity, the timing of events, prior events, patient interaction, interaction between co-variates and variability (first-order uncertainty). We note that, depending on the research question, the optimal modelling approach should be selected based on the expected differences between the comparators, the number of co-variates, the number of patient subgroups, the interactions between co-variates, and simulation time. Finally, it is argued that in case micro-simulation is required for the cost-effectiveness analysis of schizophrenia treatments, a discrete event simulation model is best suited to accurately capture all of the relevant interdependencies in this chronic, highly heterogeneous disease with limited long-term follow-up data.

An Aircraft Encounter with Turbulence in the Vicinity of a Thunderstorm

NASA Technical Reports Server (NTRS)

Hamilton, David W.; Proctor, Fred H.

2003-01-01

Large eddy simulations of three convective turbulence events are investigated and compared with observational data. Two events were characterized with severe turbulence and the other with moderate turbulence. Two of the events occurred during NASA s turbulence flight experiments during the spring of 2002, and the third was an event identified by the Flight Operational Quality Assurance (FOQA) Program. Each event was associated with developing or ongoing convection and was characterized by regions of low to moderate radar reflectivity. Model comparisons with observations are favorable. The data sets from these simulations can be used to test turbulence detection sensors.

Simulated Performance of the Orbiting Wide-angle Light Collectors (OWL) Experiment

NASA Technical Reports Server (NTRS)

Krizmanic, J. F.; Whitaker, Ann F. (Technical Monitor)

2001-01-01

The Orbiting Wide-angle Light collectors (OWL) experiment is in NASA's mid-term strategic plan and will stereoscopically image, from equatorial orbit, the air fluorescence signal generated by airshowers induced by the ultrahigh energy (E greater than few x 10(exp 19) eV) component of the cosmic radiation. The use of a space-based platform enables an extremely large event acceptance aperture and thus will allow a high statistics measurement of these rare events. Detailed Monte Carlo simulations are required to quantify the physics potential of the mission as well as optimize the instrumental parameters. This paper reports on the results of the GSFC Monte Carlo simulation for two different, OWL instrument baseline designs. These results indicate that, assuming a continuation of the cosmic ray spectrum (theta approximately E(exp -2.75), OWL could have an event rate of 4000 events/year with E greater than or equal to 10(exp 20) eV. Preliminary results, based upon these Monte Carlo simulations, indicate that events can be accurately reconstructed in the detector focal plane arrays for the OWL instrument baseline designs under consideration.

Modeling a Million-Node Slim Fly Network Using Parallel Discrete-Event Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wolfe, Noah; Carothers, Christopher; Mubarak, Misbah

As supercomputers close in on exascale performance, the increased number of processors and processing power translates to an increased demand on the underlying network interconnect. The Slim Fly network topology, a new lowdiameter and low-latency interconnection network, is gaining interest as one possible solution for next-generation supercomputing interconnect systems. In this paper, we present a high-fidelity Slim Fly it-level model leveraging the Rensselaer Optimistic Simulation System (ROSS) and Co-Design of Exascale Storage (CODES) frameworks. We validate our Slim Fly model with the Kathareios et al. Slim Fly model results provided at moderately sized network scales. We further scale the modelmore » size up to n unprecedented 1 million compute nodes; and through visualization of network simulation metrics such as link bandwidth, packet latency, and port occupancy, we get an insight into the network behavior at the million-node scale. We also show linear strong scaling of the Slim Fly model on an Intel cluster achieving a peak event rate of 36 million events per second using 128 MPI tasks to process 7 billion events. Detailed analysis of the underlying discrete-event simulation performance shows that a million-node Slim Fly model simulation can execute in 198 seconds on the Intel cluster.« less

Assessment of the Weather Research and Forecasting (WRF) model for simulation of extreme rainfall events in the upper Ganga Basin

NASA Astrophysics Data System (ADS)

Chawla, Ila; Osuri, Krishna K.; Mujumdar, Pradeep P.; Niyogi, Dev

2018-02-01

Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Most of the global rainfall products are available at a coarse resolution, rendering them less desirable for extreme rainfall analysis. Therefore, regional mesoscale models such as the advanced research version of the Weather Research and Forecasting (WRF) model are often used to provide rainfall estimates at fine grid spacing. Modelling heavy rainfall events is an enduring challenge, as such events depend on multi-scale interactions, and the model configurations such as grid spacing, physical parameterization and initialization. With this background, the WRF model is implemented in this study to investigate the impact of different processes on extreme rainfall simulation, by considering a representative event that occurred during 15-18 June 2013 over the Ganga Basin in India, which is located at the foothills of the Himalayas. This event is simulated with ensembles involving four different microphysics (MP), two cumulus (CU) parameterizations, two planetary boundary layers (PBLs) and two land surface physics options, as well as different resolutions (grid spacing) within the WRF model. The simulated rainfall is evaluated against the observations from 18 rain gauges and the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42RT version 7 data. From the analysis, it should be noted that the choice of MP scheme influences the spatial pattern of rainfall, while the choice of PBL and CU parameterizations influences the magnitude of rainfall in the model simulations. Further, the WRF run with Goddard MP, Mellor-Yamada-Janjic PBL and Betts-Miller-Janjic CU scheme is found to perform best in simulating this heavy rain event. The selected configuration is evaluated for several heavy to extremely heavy rainfall events that occurred across different months of the monsoon season in the region. The model performance improved through incorporation of detailed land surface processes involving prognostic soil moisture evolution in Noah scheme compared to the simple Slab model. To analyse the effect of model grid spacing, two sets of downscaling ratios - (i) 1 : 3, global to regional (G2R) scale and (ii) 1 : 9, global to convection-permitting scale (G2C) - are employed. Results indicate that a higher downscaling ratio (G2C) causes higher variability and consequently large errors in the simulations. Therefore, G2R is adopted as a suitable choice for simulating heavy rainfall event in the present case study. Further, the WRF-simulated rainfall is found to exhibit less bias when compared with the NCEP FiNaL (FNL) reanalysis data.

Diagnosing added value of convection-permitting regional models using precipitation event identification and tracking

NASA Astrophysics Data System (ADS)

Chang, W.; Wang, J.; Marohnic, J.; Kotamarthi, V. R.; Moyer, E. J.

2017-12-01

We use a novel rainstorm identification and tracking algorithm (Chang et al 2016) to evaluate the effects of using resolved convection on improving how faithfully high-resolution regional simulations capture precipitation characteristics. The identification and tracking algorithm allocates all precipitation to individual rainstorms, including low-intensity events with complicated features, and allows us to decompose changes or biases in total mean precipitation into their causes: event size, intensity, number, and duration. It allows lower threshold for tracking so captures nearly all rainfall and improves tracking, so that events that are clearly meteorologically related are tracked across lifespans up to days. We evaluate a series of dynamically downscaled simulations of the summertime United States at 12 and 4 km under different model configurations, and find that resolved convection offers the largest gains in reducing biases in precipitation characteristics, especially in event size. Simulations with parametrized convection produce event sizes 80-220% too large in extent; with resolved convection the bias is reduced to 30%. The identification and tracking algorithm also allows us to demonstrate that the diurnal cycle in rainfall stems not from temporal variation in the production of new events but from diurnal fluctuations in rainfall from existing events. We show further hat model errors in the diurnal cycle biases are best represented as additive offsets that differ by time of day, and again that convection-permitting simulations are most efficient in reducing these additive biases.

Simulator for Microlens Planet Surveys

NASA Astrophysics Data System (ADS)

Ipatov, Sergei I.; Horne, Keith; Alsubai, Khalid A.; Bramich, Daniel M.; Dominik, Martin; Hundertmark, Markus P. G.; Liebig, Christine; Snodgrass, Colin D. B.; Street, Rachel A.; Tsapras, Yiannis

2014-04-01

We summarize the status of a computer simulator for microlens planet surveys. The simulator generates synthetic light curves of microlensing events observed with specified networks of telescopes over specified periods of time. Particular attention is paid to models for sky brightness and seeing, calibrated by fitting to data from the OGLE survey and RoboNet observations in 2011. Time intervals during which events are observable are identified by accounting for positions of the Sun and the Moon, and other restrictions on telescope pointing. Simulated observations are then generated for an algorithm that adjusts target priorities in real time with the aim of maximizing planet detection zone area summed over all the available events. The exoplanet detection capability of observations was compared for several telescopes.

Monte Carlo generator ELRADGEN 2.0 for simulation of radiative events in elastic ep-scattering of polarized particles

NASA Astrophysics Data System (ADS)

Akushevich, I.; Filoti, O. F.; Ilyichev, A.; Shumeiko, N.

2012-07-01

The structure and algorithms of the Monte Carlo generator ELRADGEN 2.0 designed to simulate radiative events in polarized ep-scattering are presented. The full set of analytical expressions for the QED radiative corrections is presented and discussed in detail. Algorithmic improvements implemented to provide faster simulation of hard real photon events are described. Numerical tests show high quality of generation of photonic variables and radiatively corrected cross section. The comparison of the elastic radiative tail simulated within the kinematical conditions of the BLAST experiment at MIT BATES shows a good agreement with experimental data. Catalogue identifier: AELO_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AELO_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC license, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 1299 No. of bytes in distributed program, including test data, etc.: 11 348 Distribution format: tar.gz Programming language: FORTRAN 77 Computer: All Operating system: Any RAM: 1 MB Classification: 11.2, 11.4 Nature of problem: Simulation of radiative events in polarized ep-scattering. Solution method: Monte Carlo simulation according to the distributions of the real photon kinematic variables that are calculated by the covariant method of QED radiative correction estimation. The approach provides rather fast and accurate generation. Running time: The simulation of 108 radiative events for itest:=1 takes up to 52 seconds on Pentium(R) Dual-Core 2.00 GHz processor.

An accelerated algorithm for discrete stochastic simulation of reaction-diffusion systems using gradient-based diffusion and tau-leaping.

PubMed

Koh, Wonryull; Blackwell, Kim T

2011-04-21

Stochastic simulation of reaction-diffusion systems enables the investigation of stochastic events arising from the small numbers and heterogeneous distribution of molecular species in biological cells. Stochastic variations in intracellular microdomains and in diffusional gradients play a significant part in the spatiotemporal activity and behavior of cells. Although an exact stochastic simulation that simulates every individual reaction and diffusion event gives a most accurate trajectory of the system's state over time, it can be too slow for many practical applications. We present an accelerated algorithm for discrete stochastic simulation of reaction-diffusion systems designed to improve the speed of simulation by reducing the number of time-steps required to complete a simulation run. This method is unique in that it employs two strategies that have not been incorporated in existing spatial stochastic simulation algorithms. First, diffusive transfers between neighboring subvolumes are based on concentration gradients. This treatment necessitates sampling of only the net or observed diffusion events from higher to lower concentration gradients rather than sampling all diffusion events regardless of local concentration gradients. Second, we extend the non-negative Poisson tau-leaping method that was originally developed for speeding up nonspatial or homogeneous stochastic simulation algorithms. This method calculates each leap time in a unified step for both reaction and diffusion processes while satisfying the leap condition that the propensities do not change appreciably during the leap and ensuring that leaping does not cause molecular populations to become negative. Numerical results are presented that illustrate the improvement in simulation speed achieved by incorporating these two new strategies.

On the Role of Ionospheric Ions in Sawtooth Events

NASA Astrophysics Data System (ADS)

Lund, E. J.; Nowrouzi, N.; Kistler, L. M.; Cai, X.; Frey, H. U.

2018-01-01

Simulations have suggested that feedback of heavy ions originating in the ionosphere is an important mechanism for driving sawtooth injections. However, this feedback may only be necessary for events driven by coronal mass ejections (CMEs), whereas in events driven by streaming interaction regions (SIRs), solar wind variability may suffice to drive these injections. Here we present case studies of two sawtooth events for which in situ data are available in both the magnetotail (Cluster) and the nightside auroral region (FAST), as well as global auroral images (IMAGE). One event, on 1 October 2001, was driven by a CME; the other, on 24 October 2002, was driven by an SIR. The available data do not support the hypothesis that heavy ion feedback is necessary to drive either event. This result is consistent with simulations of the SIR-driven event but disagrees with simulation results for a different CME-driven event. We also find that in an overwhelming majority of the sawtooth injections for which Cluster tail data are available, the O+ observed in the tail comes from the cusp rather than the nightside auroral region, which further casts doubt on the hypothesis that ionospheric heavy ion feedback is the cause of sawtooth injections.

Analysis of Quasi-Elastic e-n and e-p Scattering from Deuterium

NASA Astrophysics Data System (ADS)

Balsamo, Alexander; Gilfoyle, Gerard; CLAS12 Collaboration

2017-09-01

One of Jefferson Lab's goals is to unravel the quark-gluon structure of nuclei. We will use the ratio, R, of electron-neutron to electron-proton scattering on deuterium to probe the magnetic form factor of the neutron. We have developed an end-to-end analysis from simulation to extraction of R in quasi-elastic kinematics for an approved experiment with the CLAS12 detector. We focus on neutrons detected in the CLAS12 calorimeters and protons measured with the CLAS12 forward detector. Events were generated with the Quasi-Elastic Event Generator (QUEEG) and passed through the Monte Carlo code gemc to simulate the CLAS12 response. These simulated events were reconstructed using the latest CLAS12 Common Tools. We first match the solid angle for e-n and e-p events. The electron information is used to predict the path of both a neutron and proton through CLAS12. If both particles interact in CLAS12 the e-n and e-p events have the same solid angle. We select QE events by searching for nuclei near the predicted position. An angular cut between the predicted 3-momentum of the nucleon and the measured value, θpq, separates QE and inelastic events. We will show the simulated R as a function of the four-momentum transfer Q2. Work supported by the University of Richmond and the US Department of Energy.

Simulating Mission Command for Planning and Analysis

DTIC Science & Technology

2015-06-01

mission plan. 14. SUBJECT TERMS Mission Planning, CPM , PERT, Simulation, DES, Simkit, Triangle Distribution, Critical Path 15. NUMBER OF...Battalion Task Force CO Company CPM Critical Path Method DES Discrete Event Simulation FA BAT Field Artillery Battalion FEL Future Event List FIST...management tools that can be utilized to find the critical path in military projects. These are the Critical Path Method ( CPM ) and the Program Evaluation and

Cross-Paradigm Simulation Modeling: Challenges and Successes

DTIC Science & Technology

2011-12-01

is also highlighted. 2.1 Discrete-Event Simulation Discrete-event simulation ( DES ) is a modeling method for stochastic, dynamic models where...which almost anything can be coded; models can be incredibly detailed. Most commercial DES software has a graphical interface which allows the user to...results. Although the above definition is the commonly accepted definition of DES , there are two different worldviews that dominate DES modeling today: a

Rigorous Model Reduction for a Damped-Forced Nonlinear Beam Model: An Infinite-Dimensional Analysis

NASA Astrophysics Data System (ADS)

Kogelbauer, Florian; Haller, George

2018-06-01

We use invariant manifold results on Banach spaces to conclude the existence of spectral submanifolds (SSMs) in a class of nonlinear, externally forced beam oscillations. SSMs are the smoothest nonlinear extensions of spectral subspaces of the linearized beam equation. Reduction in the governing PDE to SSMs provides an explicit low-dimensional model which captures the correct asymptotics of the full, infinite-dimensional dynamics. Our approach is general enough to admit extensions to other types of continuum vibrations. The model-reduction procedure we employ also gives guidelines for a mathematically self-consistent modeling of damping in PDEs describing structural vibrations.

On framing potential features of SWCNTs and MWCNTs in mixed convective flow

NASA Astrophysics Data System (ADS)

Hayat, T.; Ullah, Siraj; Khan, M. Ijaz; Alsaedi, A.

2018-03-01

Our target in this research article is to elaborate the characteristics of Darcy-Forchheimer relation in carbon-water nanoliquid flow induced by impermeable stretched cylinder. Energy expression is modeled through viscous dissipation and nonlinear thermal radiation. Application of appropriate transformations yields nonlinear ODEs through nonlinear PDEs. Shooting technique is adopted for the computations of nonlinear ODEs. Importance of influential variables for velocity and thermal fields is elaborated graphically. Moreover rate of heat transfer and drag force are calculated and demonstrated through Tables. Our analysis reports that velocity is higher for ratio of rate constant and buoyancy factor when compared with porosity and volume fraction.

Rheology of the Cu-H2O nanofluid in porous channel with heat transfer: Multiple solutions

NASA Astrophysics Data System (ADS)

Raza, J.; Rohni, A. M.; Omar, Z.; Awais, M.

2017-02-01

Dynamics of nanofluid comprising a base fluid (water) with copper (Cu) nanoparticles have been considered in channel with porous walls under magnetic field influence. The channel walls are considered to be permeable in order to analyze the wall mass transfer phenomenon. Relevant mathematical modelling has been performed and the derived PDEs are converted into coupled nonlinear ODEs by using suitable transformations. Computations have been made numerically by employing the shooting technique. It is noted that multiple solutions occur for the variation of suction Reynolds number, solid volume fraction and magnetic parameters which are interpreted in detail.

Numerical Modeling of Pulse Detonation Rocket Engine Gasdynamics and Performance

NASA Technical Reports Server (NTRS)

Morris, C. I.

2003-01-01

Pulse detonation engines (PDB) have generated considerable research interest in recent years as a chemical propulsion system potentially offering improved performance and reduced complexity compared to conventional gas turbines and rocket engines. The detonative mode of combustion employed by these devices offers a theoretical thermodynamic advantage over the constant-pressure deflagrative combustion mode used in conventional engines. However, the unsteady blowdown process intrinsic to all pulse detonation devices has made realistic estimates of the actual propulsive performance of PDES problematic. The recent review article by Kailasanath highlights some of the progress that has been made in comparing the available experimental measurements with analytical and numerical models.

Conservation laws and conserved quantities for (1+1)D linearized Boussinesq equations

NASA Astrophysics Data System (ADS)

Carvalho, Cindy; Harley, Charis

2017-05-01

Conservation laws and physical conserved quantities for the (1+1)D linearized Boussinesq equations at a constant water depth are presented. These equations describe incompressible, inviscid, irrotational fluid flow in the form of a non steady solitary wave. A systematic multiplier approach is used to obtain the conservation laws of the system of third order partial differential equations (PDEs) in dimensional form. Physical conserved quantities are derived by integrating the conservation laws in the direction of wave propagation and imposing decaying boundary conditions in the horizontal direction. One of these is a newly discovered conserved quantity which relates to an energy flux density.

Effective Methods for Solving Band SLEs after Parabolic Nonlinear PDEs

NASA Astrophysics Data System (ADS)

Veneva, Milena; Ayriyan, Alexander

2018-04-01

A class of models of heat transfer processes in a multilayer domain is considered. The governing equation is a nonlinear heat-transfer equation with different temperature-dependent densities and thermal coefficients in each layer. Homogeneous Neumann boundary conditions and ideal contact ones are applied. A finite difference scheme on a special uneven mesh with a second-order approximation in the case of a piecewise constant spatial step is built. This discretization leads to a pentadiagonal system of linear equations (SLEs) with a matrix which is neither diagonally dominant, nor positive definite. Two different methods for solving such a SLE are developed - diagonal dominantization and symbolic algorithms.

A free boundary problem for steady small plaques in the artery and their stability

NASA Astrophysics Data System (ADS)

Friedman, Avner; Hao, Wenrui; Hu, Bei

2015-08-01

Atherosclerosis is a leading cause of death in the United States and worldwide; it originates from a plaque which builds up in the artery. In this paper, we consider a simplified model of plaque growth involving LDL and HDL cholesterols, macrophages and foam cells, which satisfy a coupled system of PDEs with a free boundary, the interface between the plaque and the blood flow. We prove that there exist small radially symmetric stationary plaques and establish a sharp condition that ensures their stability. We also determine necessary and sufficient conditions under which a small initial plaque will shrink and disappear, or persist for all times.

Simulating large-scale pedestrian movement using CA and event driven model: Methodology and case study

NASA Astrophysics Data System (ADS)

Li, Jun; Fu, Siyao; He, Haibo; Jia, Hongfei; Li, Yanzhong; Guo, Yi

2015-11-01

Large-scale regional evacuation is an important part of national security emergency response plan. Large commercial shopping area, as the typical service system, its emergency evacuation is one of the hot research topics. A systematic methodology based on Cellular Automata with the Dynamic Floor Field and event driven model has been proposed, and the methodology has been examined within context of a case study involving the evacuation within a commercial shopping mall. Pedestrians walking is based on Cellular Automata and event driven model. In this paper, the event driven model is adopted to simulate the pedestrian movement patterns, the simulation process is divided into normal situation and emergency evacuation. The model is composed of four layers: environment layer, customer layer, clerk layer and trajectory layer. For the simulation of movement route of pedestrians, the model takes into account purchase intention of customers and density of pedestrians. Based on evacuation model of Cellular Automata with Dynamic Floor Field and event driven model, we can reflect behavior characteristics of customers and clerks at the situations of normal and emergency evacuation. The distribution of individual evacuation time as a function of initial positions and the dynamics of the evacuation process is studied. Our results indicate that the evacuation model using the combination of Cellular Automata with Dynamic Floor Field and event driven scheduling can be used to simulate the evacuation of pedestrian flows in indoor areas with complicated surroundings and to investigate the layout of shopping mall.

Statistical variances of diffusional properties from ab initio molecular dynamics simulations

NASA Astrophysics Data System (ADS)

He, Xingfeng; Zhu, Yizhou; Epstein, Alexander; Mo, Yifei

2018-12-01

Ab initio molecular dynamics (AIMD) simulation is widely employed in studying diffusion mechanisms and in quantifying diffusional properties of materials. However, AIMD simulations are often limited to a few hundred atoms and a short, sub-nanosecond physical timescale, which leads to models that include only a limited number of diffusion events. As a result, the diffusional properties obtained from AIMD simulations are often plagued by poor statistics. In this paper, we re-examine the process to estimate diffusivity and ionic conductivity from the AIMD simulations and establish the procedure to minimize the fitting errors. In addition, we propose methods for quantifying the statistical variance of the diffusivity and ionic conductivity from the number of diffusion events observed during the AIMD simulation. Since an adequate number of diffusion events must be sampled, AIMD simulations should be sufficiently long and can only be performed on materials with reasonably fast diffusion. We chart the ranges of materials and physical conditions that can be accessible by AIMD simulations in studying diffusional properties. Our work provides the foundation for quantifying the statistical confidence levels of diffusion results from AIMD simulations and for correctly employing this powerful technique.

SIMULATING SUB-DECADAL CHANNEL MORPHOLOGIC CHANGE IN EPHEMERAL STREAM NETWORKS

EPA Science Inventory

A distributed watershed model was modified to simulate cumulative channel morphologic
change from multiple runoff events in ephemeral stream networks. The model incorporates the general design of the event-based Kinematic Runoff and" Erosion Model (KINEROS), which describes t...

Event-driven simulations of nonlinear integrate-and-fire neurons.

PubMed

Tonnelier, Arnaud; Belmabrouk, Hana; Martinez, Dominique

2007-12-01

Event-driven strategies have been used to simulate spiking neural networks exactly. Previous work is limited to linear integrate-and-fire neurons. In this note, we extend event-driven schemes to a class of nonlinear integrate-and-fire models. Results are presented for the quadratic integrate-and-fire model with instantaneous or exponential synaptic currents. Extensions to conductance-based currents and exponential integrate-and-fire neurons are discussed.

A cascading failure analysis tool for post processing TRANSCARE simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

This is a MATLAB-based tool to post process simulation results in the EPRI software TRANSCARE, for massive cascading failure analysis following severe disturbances. There are a few key modules available in this tool, including: 1. automatically creating a contingency list to run TRANSCARE simulations, including substation outages above a certain kV threshold, N-k (1, 2 or 3) generator outages and branche outages; 2. read in and analyze a CKO file of PCG definition, an initiating event list, and a CDN file; 3. post process all the simulation results saved in a CDN file and perform critical event corridor analysis; 4.more » provide a summary of TRANSCARE simulations; 5. Identify the most frequently occurring event corridors in the system; and 6. Rank the contingencies using a user defined security index to quantify consequences in terms of total load loss, total number of cascades, etc.« less

Scavenging and recombination kinetics in a radiation spur: The successive ordered scavenging events

NASA Astrophysics Data System (ADS)

Al-Samra, Eyad H.; Green, Nicholas J. B.

2018-03-01

This study describes stochastic models to investigate the successive ordered scavenging events in a spur of four radicals, a model system based on a radiation spur. Three simulation models have been developed to obtain the probabilities of the ordered scavenging events: (i) a Monte Carlo random flight (RF) model, (ii) hybrid simulations in which the reaction rate coefficient is used to generate scavenging times for the radicals and (iii) the independent reaction times (IRT) method. The results of these simulations are found to be in agreement with one another. In addition, a detailed master equation treatment is also presented, and used to extract simulated rate coefficients of the ordered scavenging reactions from the RF simulations. These rate coefficients are transient, the rate coefficients obtained for subsequent reactions are effectively equal, and in reasonable agreement with the simple correction for competition effects that has recently been proposed.

Comparison Of Quantitative Precipitation Estimates Derived From Rain Gauge And Radar Derived Algorithms For Operational Flash Flood Support.

NASA Astrophysics Data System (ADS)

Streubel, D. P.; Kodama, K.

2014-12-01

To provide continuous flash flood situational awareness and to better differentiate severity of ongoing individual precipitation events, the National Weather Service Research Distributed Hydrologic Model (RDHM) is being implemented over Hawaii and Alaska. In the implementation process of RDHM, three gridded precipitation analyses are used as forcing. The first analysis is a radar only precipitation estimate derived from WSR-88D digital hybrid reflectivity, a Z-R relationship and aggregated into an hourly ¼ HRAP grid. The second analysis is derived from a rain gauge network and interpolated into an hourly ¼ HRAP grid using PRISM climatology. The third analysis is derived from a rain gauge network where rain gauges are assigned static pre-determined weights to derive a uniform mean areal precipitation that is applied over a catchment on a ¼ HRAP grid. To assess the effect of different QPE analyses on the accuracy of RDHM simulations and to potentially identify a preferred analysis for operational use, each QPE was used to force RDHM to simulate stream flow for 20 USGS peak flow events. An evaluation of the RDHM simulations was focused on peak flow magnitude, peak flow timing, and event volume accuracy to be most relevant for operational use. Results showed RDHM simulations based on the observed rain gauge amounts were more accurate in simulating peak flow magnitude and event volume relative to the radar derived analysis. However this result was not consistent for all 20 events nor was it consistent for a few of the rainfall events where an annual peak flow was recorded at more than one USGS gage. Implications of this indicate that a more robust QPE forcing with the inclusion of uncertainty derived from the three analyses may provide a better input for simulating extreme peak flow events.

Modeling Temporal Processes in Early Spacecraft Design: Application of Discrete-Event Simulations for Darpa's F6 Program

NASA Technical Reports Server (NTRS)

Dubos, Gregory F.; Cornford, Steven

2012-01-01

While the ability to model the state of a space system over time is essential during spacecraft operations, the use of time-based simulations remains rare in preliminary design. The absence of the time dimension in most traditional early design tools can however become a hurdle when designing complex systems whose development and operations can be disrupted by various events, such as delays or failures. As the value delivered by a space system is highly affected by such events, exploring the trade space for designs that yield the maximum value calls for the explicit modeling of time.This paper discusses the use of discrete-event models to simulate spacecraft development schedule as well as operational scenarios and on-orbit resources in the presence of uncertainty. It illustrates how such simulations can be utilized to support trade studies, through the example of a tool developed for DARPA's F6 program to assist the design of "fractionated spacecraft".

Parallel Discrete Molecular Dynamics Simulation With Speculation and In-Order Commitment*†

PubMed Central

Khan, Md. Ashfaquzzaman; Herbordt, Martin C.

2011-01-01

Discrete molecular dynamics simulation (DMD) uses simplified and discretized models enabling simulations to advance by event rather than by timestep. DMD is an instance of discrete event simulation and so is difficult to scale: even in this multi-core era, all reported DMD codes are serial. In this paper we discuss the inherent difficulties of scaling DMD and present our method of parallelizing DMD through event-based decomposition. Our method is microarchitecture inspired: speculative processing of events exposes parallelism, while in-order commitment ensures correctness. We analyze the potential of this parallelization method for shared-memory multiprocessors. Achieving scalability required extensive experimentation with scheduling and synchronization methods to mitigate serialization. The speed-up achieved for a variety of system sizes and complexities is nearly 6× on an 8-core and over 9× on a 12-core processor. We present and verify analytical models that account for the achieved performance as a function of available concurrency and architectural limitations. PMID:21822327

Parallel Discrete Molecular Dynamics Simulation With Speculation and In-Order Commitment.

PubMed

Khan, Md Ashfaquzzaman; Herbordt, Martin C

2011-07-20

Discrete molecular dynamics simulation (DMD) uses simplified and discretized models enabling simulations to advance by event rather than by timestep. DMD is an instance of discrete event simulation and so is difficult to scale: even in this multi-core era, all reported DMD codes are serial. In this paper we discuss the inherent difficulties of scaling DMD and present our method of parallelizing DMD through event-based decomposition. Our method is microarchitecture inspired: speculative processing of events exposes parallelism, while in-order commitment ensures correctness. We analyze the potential of this parallelization method for shared-memory multiprocessors. Achieving scalability required extensive experimentation with scheduling and synchronization methods to mitigate serialization. The speed-up achieved for a variety of system sizes and complexities is nearly 6× on an 8-core and over 9× on a 12-core processor. We present and verify analytical models that account for the achieved performance as a function of available concurrency and architectural limitations.

Estimating rare events in biochemical systems using conditional sampling.

PubMed

Sundar, V S

2017-01-28

The paper focuses on development of variance reduction strategies to estimate rare events in biochemical systems. Obtaining this probability using brute force Monte Carlo simulations in conjunction with the stochastic simulation algorithm (Gillespie's method) is computationally prohibitive. To circumvent this, important sampling tools such as the weighted stochastic simulation algorithm and the doubly weighted stochastic simulation algorithm have been proposed. However, these strategies require an additional step of determining the important region to sample from, which is not straightforward for most of the problems. In this paper, we apply the subset simulation method, developed as a variance reduction tool in the context of structural engineering, to the problem of rare event estimation in biochemical systems. The main idea is that the rare event probability is expressed as a product of more frequent conditional probabilities. These conditional probabilities are estimated with high accuracy using Monte Carlo simulations, specifically the Markov chain Monte Carlo method with the modified Metropolis-Hastings algorithm. Generating sample realizations of the state vector using the stochastic simulation algorithm is viewed as mapping the discrete-state continuous-time random process to the standard normal random variable vector. This viewpoint opens up the possibility of applying more sophisticated and efficient sampling schemes developed elsewhere to problems in stochastic chemical kinetics. The results obtained using the subset simulation method are compared with existing variance reduction strategies for a few benchmark problems, and a satisfactory improvement in computational time is demonstrated.

Widespread, Very Heavy Precipitation Events in Contemporary and Scenario Summer Climates from NARCCAP Simulations

NASA Astrophysics Data System (ADS)

Kawazoe, S.; Gutowski, W. J., Jr.

2015-12-01

We analyze the ability of regional climate models (RCMs) to simulate very heavy daily precipitation and supporting processes for both contemporary and future-scenario simulations during summer (JJA). RCM output comes from North American Regional Climate Change Assessment Program (NARCCAP) simulations, which are all run at a spatial resolution of 50 km. Analysis focuses on the upper Mississippi basin for summer, between 1982-1998 for the contemporary climate, and 2052-2068 during the scenario climate. We also compare simulated precipitation and supporting processes with those obtained from observed precipitation and reanalysis atmospheric states. Precipitation observations are from the University of Washington (UW) and the Climate Prediction Center (CPC) gridded dataset. Utilizing two observational datasets helps determine if any uncertainties arise from differences in precipitation gridding schemes. Reanalysis fields come from the North American Regional Reanalysis. The NARCCAP models generally reproduce well the precipitation-vs.-intensity spectrum seen in observations, while producing overly strong precipitation at high intensity thresholds. In the future-scenario climate, there is a decrease in frequency for light to moderate precipitation intensities, while an increase in frequency is seen for the higher intensity events. Further analysis focuses on precipitation events exceeding the 99.5 percentile that occur simultaneously at several points in the region, yielding so-called "widespread events". For widespread events, we analyze local and large scale environmental parameters, such as 2-m temperature and specific humidity, 500-hPa geopotential heights, Convective Available Potential Energy (CAPE), vertically integrated moisture flux convergence, among others, to compare atmospheric states and processes leading to such events in the models and observations. The results suggest that an analysis of atmospheric states supporting very heavy precipitation events is a more fruitful path for understanding and detecting changes than simply looking at precipitation itself.

Fast Simulation of Electromagnetic Showers in the ATLAS Calorimeter: Frozen Showers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barberio, E.; /Melbourne U.; Boudreau, J.

2011-11-29

One of the most time consuming process simulating pp interactions in the ATLAS detector at LHC is the simulation of electromagnetic showers in the calorimeter. In order to speed up the event simulation several parametrisation methods are available in ATLAS. In this paper we present a short description of a frozen shower technique, together with some recent benchmarks and comparison with full simulation. An expected high rate of proton-proton collisions in ATLAS detector at LHC requires large samples of simulated events (Monte Carlo) to study various physics processes. A detailed simulation of particle reactions ('full simulation') in the ATLAS detectormore » is based on GEANT4 and is very accurate. However, due to complexity of the detector, high particle multiplicity and GEANT4 itself, the average CPU time spend to simulate typical QCD event in pp collision is 20 or more minutes for modern computers. During detector simulation the largest time is spend in the calorimeters (up to 70%) most of which is required for electromagnetic particles in the electromagnetic (EM) part of the calorimeters. This is the motivation for fast simulation approaches which reduce the simulation time without affecting the accuracy. Several of fast simulation methods available within the ATLAS simulation framework (standard Athena based simulation program) are discussed here with the focus on the novel frozen shower library (FS) technique. The results obtained with FS are presented here as well.« less

An Event-Based Approach to Design a Teamwork Training Scenario and Assessment Tool in Surgery.

PubMed

Nguyen, Ngan; Watson, William D; Dominguez, Edward

2016-01-01

Simulation is a technique recommended for teaching and measuring teamwork, but few published methodologies are available on how best to design simulation for teamwork training in surgery and health care in general. The purpose of this article is to describe a general methodology, called event-based approach to training (EBAT), to guide the design of simulation for teamwork training and discuss its application to surgery. The EBAT methodology draws on the science of training by systematically introducing training exercise events that are linked to training requirements (i.e., competencies being trained and learning objectives) and performance assessment. The EBAT process involves: Of the 4 teamwork competencies endorsed by the Agency for Healthcare Research Quality and Department of Defense, "communication" was chosen to be the focus of our training efforts. A total of 5 learning objectives were defined based on 5 validated teamwork and communication techniques. Diagnostic laparoscopy was chosen as the clinical context to frame the training scenario, and 29 KSAs were defined based on review of published literature on patient safety and input from subject matter experts. Critical events included those that correspond to a specific phase in the normal flow of a surgical procedure as well as clinical events that may occur when performing the operation. Similar to the targeted KSAs, targeted responses to the critical events were developed based on existing literature and gathering input from content experts. Finally, a 29-item EBAT-derived checklist was created to assess communication performance. Like any instructional tool, simulation is only effective if it is designed and implemented appropriately. It is recognized that the effectiveness of simulation depends on whether (1) it is built upon a theoretical framework, (2) it uses preplanned structured exercises or events to allow learners the opportunity to exhibit the targeted KSAs, (3) it assesses performance, and (4) it provides formative and constructive feedback to bridge the gap between the learners' KSAs and the targeted KSAs. The EBAT methodology guides the design of simulation that incorporates these 4 features and, thus, enhances training effectiveness with simulation. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

A Two-Step Method to Select Major Surge-Producing Extratropical Cyclones from a 10,000-Year Stochastic Catalog

NASA Astrophysics Data System (ADS)

Keshtpoor, M.; Carnacina, I.; Yablonsky, R. M.

2016-12-01

Extratropical cyclones (ETCs) are the primary driver of storm surge events along the UK and northwest mainland Europe coastlines. In an effort to evaluate the storm surge risk in coastal communities in this region, a stochastic catalog is developed by perturbing the historical storm seeds of European ETCs to account for 10,000 years of possible ETCs. Numerical simulation of the storm surge generated by the full 10,000-year stochastic catalog, however, is computationally expensive and may take several months to complete with available computational resources. A new statistical regression model is developed to select the major surge-generating events from the stochastic ETC catalog. This regression model is based on the maximum storm surge, obtained via numerical simulations using a calibrated version of the Delft3D-FM hydrodynamic model with a relatively coarse mesh, of 1750 historical ETC events that occurred over the past 38 years in Europe. These numerically-simulated surge values were regressed to the local sea level pressure and the U and V components of the wind field at the location of 196 tide gauge stations near the UK and northwest mainland Europe coastal areas. The regression model suggests that storm surge values in the area of interest are highly correlated to the U- and V-component of wind speed, as well as the sea level pressure. Based on these correlations, the regression model was then used to select surge-generating storms from the 10,000-year stochastic catalog. Results suggest that roughly 105,000 events out of 480,000 stochastic storms are surge-generating events and need to be considered for numerical simulation using a hydrodynamic model. The selected stochastic storms were then simulated in Delft3D-FM, and the final refinement of the storm population was performed based on return period analysis of the 1750 historical event simulations at each of the 196 tide gauges in preparation for Delft3D-FM fine mesh simulations.

Simulation of Top Quark Pair Production as a Background for Higgs Events at the Compact Muon Solenoid

NASA Astrophysics Data System (ADS)

Justus, Christopher

2005-04-01

In this study, we simulated top-antitop (tt-bar) quark events at the Compact Muon Solenoid (CMS), an experiment presently being constructed at the Large Hadron Collider in Geneva, Switzerland. The tt-bar process is an important background for Higgs events. We used a chain of software to simulate and reconstruct processes that will occur inside the detector. CMKIN was used to generate and store Monte Carlo Events. OSCAR, a GEANT4 based CMS detector simulator, was used to simulate the CMS detector and how particles would interact with the detector. Next, we used ORCA to simulate the response of the readout electronics at CMS. Last, we used the Jet/MET Root maker to create root files of jets and missing energy. We are now using this software analysis chain to complete a systematic study of initial state radiation at hadron colliders. This study is essential because tt-bar is the main background for the Higgs boson and these processes are extremely sensitive to initial state radiation. Results of our initial state radiation study will be presented. We started this study at the new LHC Physics Center (LPC) located at Fermi National Accelerator Laboratory, and we are now completing the study at the University of Rochester.

Evolution of Flow channels and Dipolarization Using THEMIS Observations and Global MHD Simulations

NASA Astrophysics Data System (ADS)

El-Alaoui, M.; McPherron, R. L.; Nishimura, Y.

2017-12-01

We have extensively analyzed a substorm on March 14, 2008 for which we have observations from THEMIS spacecraft located beyond 9 RE near 2100 local time. The available data include an extensive network of all sky cameras and ground magnetometers that establish the times of various auroral and magnetic events. This arrangement provided an excellent data set with which to investigate meso-scale structures in the plasma sheet. We have used a global magnetohydrodynamic simulation to investigate the structure and dynamics of the magnetotail current sheet during this substorm. Both earthward and tailward flows were found in the observations as well as the simulations. The simulation shows that the flow channels follow tortuous paths that are often reflected or deflected before arriving at the inner magnetosphere. The simulation shows a sequence of fast flows and dipolarization events similar to what is seen in the data, though not at precisely the same times or locations. We will use our simulation results combined with the observations to investigate the global convection systems and current sheet structure during this event, showing how meso-scale structures fit into the context of the overall tail dynamics during this event. Our study includes determining the location, timing and strength of several current wedges and expansion onsets during an 8-hour interval.

Simulation of metals transport and toxicity at a mine-impacted watershed: California Gulch, Colorado.

PubMed

Velleux, Mark L; Julien, Pierre Y; Rojas-Sanchez, Rosalia; Clements, William H; England, John F

2006-11-15

The transport and toxicity of metals at the California Gulch, Colorado mine-impacted watershed were simulated with a spatially distributed watershed model. Using a database of observations for the period 1984-2004, hydrology, sediment transport, and metals transport were simulated for a June 2003 calibration event and a September 2003 validation event. Simulated flow volumes were within approximately 10% of observed conditions. Observed ranges of total suspended solids, cadmium, copper, and zinc concentrations were also successfully simulated. The model was then used to simulate the potential impacts of a 1-in-100-year rainfall event. Driven by large flows and corresponding soil and sediment erosion for the 1-in-100-year event, estimated solids and metals export from the watershed is 10,000 metric tons for solids, 215 kg for Cu, 520 kg for Cu, and 15,300 kg for Zn. As expressed by the cumulative criterion unit (CCU) index, metals concentrations far exceed toxic effects thresholds, suggesting a high probability of toxic effects downstream of the gulch. More detailed Zn source analyses suggest that much of the Zn exported from the gulch originates from slag piles adjacent to the lower gulch floodplain and an old mining site located near the head of the lower gulch.

Crash avoidance in response to challenging driving events: The roles of age, serialization, and driving simulator platform.

PubMed

Bélanger, Alexandre; Gagnon, Sylvain; Stinchcombe, Arne

2015-09-01

We examined the crash avoidance behaviors of older and middle-aged drivers in reaction to six simulated challenging road events using two different driving simulator platforms. Thirty-five healthy adults aged 21-36 years old (M=28.9±3.96) and 35 healthy adults aged 65-83 years old (M=72.1±4.34) were tested using a mid-level simulator, and 27 adults aged 21-38 years old (M=28.6±6.63) and 27 healthy adults aged 65-83 years old (M=72.7±5.39) were tested on a low-cost desktop simulator. Participants completed a set of six challenging events varying in terms of the maneuvers required, avoiding space given, directional avoidance cues, and time pressure. Results indicated that older drivers showed higher crash risk when events required multiple synchronized reactions. In situations that required simultaneous use of steering and braking, older adults tended to crash significantly more frequently. As for middle-aged drivers, their crashes were attributable to faster driving speed. The same age-related driving patterns were observed across simulator platforms. Our findings support the hypothesis that older adults tend to react serially while engaging in cognitively challenging road maneuvers. Copyright © 2015 Elsevier Ltd. All rights reserved.

Computer simulation of the metastatic progression.

PubMed

Wedemann, Gero; Bethge, Anja; Haustein, Volker; Schumacher, Udo

2014-01-01

A novel computer model based on a discrete event simulation procedure describes quantitatively the processes underlying the metastatic cascade. Analytical functions describe the size of the primary tumor and the metastases, while a rate function models the intravasation events of the primary tumor and metastases. Events describe the behavior of the malignant cells until the formation of new metastases. The results of the computer simulations are in quantitative agreement with clinical data determined from a patient with hepatocellular carcinoma in the liver. The model provides a more detailed view on the process than a conventional mathematical model. In particular, the implications of interventions on metastasis formation can be calculated.

Priority Queues for Computer Simulations

NASA Technical Reports Server (NTRS)

Steinman, Jeffrey S. (Inventor)

1998-01-01

The present invention is embodied in new priority queue data structures for event list management of computer simulations, and includes a new priority queue data structure and an improved event horizon applied to priority queue data structures. ne new priority queue data structure is a Qheap and is made out of linked lists for robust, fast, reliable, and stable event list management and uses a temporary unsorted list to store all items until one of the items is needed. Then the list is sorted, next, the highest priority item is removed, and then the rest of the list is inserted in the Qheap. Also, an event horizon is applied to binary tree and splay tree priority queue data structures to form the improved event horizon for event management.

Do strategic processes contribute to the specificity of future simulation in depression?

PubMed

Addis, Donna Rose; Hach, Sylvia; Tippett, Lynette J

2016-06-01

The tendency to generate overgeneral past or future events is characteristic of individuals with a history of depression. Although much research has investigated the contribution of rumination and avoidance to the reduced specificity of past events, comparatively little research has examined (1) whether the specificity of future events is differentially reduced in depression and (2) the role of executive functions in this phenomenon. Our study aimed to redress this imbalance. Participants with either current or past experience of depressive symptoms ('depressive group'; N = 24) and matched controls ('control group'; N = 24) completed tests of avoidance, rumination, and executive functions. A modified Autobiographical Memory Test was administered to assess the specificity of past and future events. The depressive group were more ruminative and avoidant than controls, but did not exhibit deficits in executive function. Although overall the depressive group generated significantly fewer specific events than controls, this reduction was driven by a significant group difference in future event specificity. Strategic retrieval processes were correlated with both past and future specificity, and predictive of the future specificity, whereas avoidance and rumination were not. Our findings demonstrate that future simulation appears to be particularly vulnerable to disruption in individuals with current or past experience of depressive symptoms, consistent with the notion that future simulation is more cognitively demanding than autobiographical memory retrieval. Moreover, our findings suggest that even subtle changes in executive functions such as strategic processes may impact the ability to imagine specific future events. Future simulation may be particularly vulnerable to executive dysfunction in individuals with current/previous depressive symptoms, with evidence of a differential reduction in the specificity of future events. Strategic retrieval abilities were associated with the degree of future event specificity whereas levels of rumination and avoidance were not. Given that the ability to generate specific simulations of the future is associated with enhanced psychological wellbeing, problem solving and coping behaviours, understanding how to increase the specificity of future simulations in depression is an important direction for future research and clinical practice. Interventions focusing on improving the ability to engage strategic processes may be a fruitful avenue for increasing the ability to imagine specific future events in depression. The autobiographical event tasks have somewhat limited ecological validity as they do not account for the many social and environmental cues present in everyday life; the development of more clinically-relevant tasks may be of benefit to this area of study. © 2016 The British Psychological Society.

ADHydro: A Large-scale High Resolution Multi-Physics Distributed Water Resources Model for Water Resource Simulations in a Parallel Computing Environment

NASA Astrophysics Data System (ADS)

lai, W.; Steinke, R. C.; Ogden, F. L.

2013-12-01

Physics-based watershed models are useful tools for hydrologic studies, water resources management and economic analyses in the contexts of climate, land-use, and water-use changes. This poster presents development of a physics-based, high-resolution, distributed water resources model suitable for simulating large watersheds in a massively parallel computing environment. Developing this model is one of the objectives of the NSF EPSCoR RII Track II CI-WATER project, which is joint between Wyoming and Utah. The model, which we call ADHydro, is aimed at simulating important processes in the Rocky Mountain west, includes: rainfall and infiltration, snowfall and snowmelt in complex terrain, vegetation and evapotranspiration, soil heat flux and freezing, overland flow, channel flow, groundwater flow and water management. The ADHydro model uses the explicit finite volume method to solve PDEs for 2D overland flow, 2D saturated groundwater flow coupled to 1D channel flow. The model has a quasi-3D formulation that couples 2D overland flow and 2D saturated groundwater flow using the 1D Talbot-Ogden finite water-content infiltration and redistribution model. This eliminates difficulties in solving the highly nonlinear 3D Richards equation, while the finite volume Talbot-Ogden infiltration solution is computationally efficient, guaranteed to conserve mass, and allows simulation of the effect of near-surface groundwater tables on runoff generation. The process-level components of the model are being individually tested and validated. The model as a whole will be tested on the Green River basin in Wyoming and ultimately applied to the entire Upper Colorado River basin. ADHydro development has necessitated development of tools for large-scale watershed modeling, including open-source workflow steps to extract hydromorphological information from GIS data, integrate hydrometeorological and water management forcing input, and post-processing and visualization of large output data sets. The ADHydro model will be coupled with relevant components of the NOAH-MP land surface scheme and the WRF mesoscale meteorological model. Model objectives include well documented Application Programming Interfaces (APIs) to facilitate modifications and additions by others. We will release the model as open-source in 2014 and begin establishing a users' community.

Detection and characterization of debris avalanche and pyroclastic flow dynamics from the simulation of the seismic signal they generate: application to Montserrat, Lesser Antilles

NASA Astrophysics Data System (ADS)

Zhao, J.; Mangeney, A.; Moretti, L.; Stutzmann, E.; Calder, E. S.; Smith, P. J.; Capdeville, Y.; Le Friant, A.; Cole, P.; Luckett, R.; Robertson, R.

2011-12-01

Gravitational instabilities such as debris avalanches or pyroclastic flows represent one of the major natural hazards for populations who live in mountainous or volcanic areas. Detection and understanding of the dynamics of these events is crucial for risk assessment. Furthermore, during an eruption, a series of explosions and gravitational flows can occur, making it difficult to retrieve the characteristics of the individual gravitational events such as their volume, velocity, etc. In this context, the seismic signal generated by these events provides a unique tool to extract information on the history of the eruptive process and to validate gravitational flow models. We analyze here a series of events including explosions, debris avalanche and pyroclastic flows occurring in Montserrat in December 1997. This seismic signal is composed of six main pulses. The characteristics of the seismic signals generated by pyroclastic flows (amplitude, emergent onset, frequency spectrum, etc.) are described and linked to the volume of the individual events estimated from past field surveys. As a first step, we simulate the waveform of each event by assuming that the generation process reduces to a simple force applied at the surface of the topography. Going further, we perform detailed numerical simulation of the Boxing Day debris avalanche and of the following pyroclastic flow using a landslide model able to take into account the 3D topography. The stress field generated by the gravitational flows on the topography is then applied as surface boundary condition in a wave propagation model, making it possible to simulate the seismic signal generated by the avalanche and pyroclastic flow. Comparison between the simulated signal and the seismic signal recorded at the Puerto Rico seismic station located 450 km away from the source, show that this method allows us to reproduce the low frequency seismic signal and to constrain the volume and frictional behavior of the individual events. As a result, simulation of seismic signals generated by gravitational flows provides insight into the history of eruptive sequences and into the characteristics of the individual events.