Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

This chapter introduces the finite element method (FEM) as a tool for solution of classical electromagnetic problems. Although we discuss the main points in the application of the finite element method to electromagnetic design, including formulation and implementation, those who seek deeper understanding of the finite element method should consult some of the works listed in the bibliography section.

Introduction to the Finite Element Method

Fast Fourier Transform

Computational Fluid Dynamics: Principles and Applications, Third Edition presents students, engineers, and scientists with all they need to gain a solid understanding of the numerical methods and principles underlying modern computation techniques in fluid dynamics By providing complete coverage of the essential knowledge required in order to write codes or understand commercial codes, the book gives the reader an overview of fundamentals and solution strategies in the early chapters before moving on to cover the details of different solution techniques

	This updated edition includes new worked programming examples, expanded coverage and recent literature regarding incompressible flows, the Discontinuous Galerkin Method, the Lattice Boltzmann Method, higher-order spatial schemes, implicit Runge-Kutta methods and parallelization

	An accompanying companion website contains the sources of 1-D and 2-D Euler and Navier-Stokes flow solvers (structured and unstructured) and grid generators, along with tools for Von Neumann stability analysis of 1-D model equations and examples of various parallelization techniques



	
		Will provide you with the knowledge required to develop and understand modern flow simulation codes
	
		Features new worked programming examples and expanded coverage of incompressible flows, implicit Runge-Kutta methods and code parallelization, among other topics
	
		Includes accompanying companion website that contains the sources of 1-D and 2-D flow solvers as well as grid generators and examples of parallelization techniques

Computational Fluid Dynamics: Principles and Applications Ed. 3

Most numerical integration techniques consist of approximating the integrand by a polynomial in a region or regions and then integrating the polynomial exactly. Often a complicated integrand can be factored into a non-negative ''weight'' function and another function better approximated by a polynomial, thus $\int_{a}^{b} g(t)dt = \int_{a}^{b} \omega (t)f(t)dt \approx \sum_{i=1}^{N} w_i f(t_i)$. Hopefully, the quadrature rule ${\{w_j, t_j\}}_{j=1}^{N}$ corresponding to the weight function $\omega$(t) is available in tabulated form, but more likely it is not. We present here two algorithms for generating the Gaussian quadrature rule defined by the weight function when: a) the three term recurrence relation is known for the orthogonal polynomials generated by $\omega$(t), and b) the moments of the weight function are known or can be calculated.

Calculation of Gauss quadrature rules.

A framework is described and demonstrated for CFD analysis of helicopter rotors in hover and forward flight. Starting from the Navier–Stokes equations, the paper describes the periodic rotor blade motions required to trim the rotor in forward flight (blade flapping, blade lead-lag and blade pitching) as well as the required mesh deformation. Throughout, the rotor blades are assumed to be rigid and the rotor to be fully articulated with separate hinges for each blade. The employed method allows for rotors with different numbers of blades and with various rotor hub layouts to be analysed. This method is then combined with a novel grid deformation strategy which preserves the quality of multi-block structured, body-fitted grids around the blades. The coupling of the CFD method with a rotor trimming approach is also described and implemented. The complete framework is validated for hovering and forward flying rotors and comparisons are made against available experimental data. Finally, suggestions for further development are put forward. For all cases, results were in good agreement with experiments and rapid convergence has been obtained. Comparisons between the present grid deformation method and transfinite interpolation were made highlighting the advantages of the current approach. Copyright © 2006 John Wiley & Sons, Ltd.

A framework for CFD analysis of helicopter rotors in hover and forward flight

Elements of computational fluid dynamics on block structured grids using implicit solvers

Interval model updating with irreducible uncertainty using the Kriging predictor

Numerical simulation of three-dimensional dynamic stall has been undertaken using computational fluid dynamics. The full Navier–Stokes equations, coupled with a two-equation turbulence model, where appropriate, have been solved on multiblock strucured grids in a time-accurate fashion. Results have neen obtained for wings of square planform and of NACA 0012 section. Efforts have been devoted to the accurate modeling of the flow near the wing tips, which, for this case, were sharp without tip caps. The obtained results revealed the time evolution of the dynamic stall vortex, which, for this case, takes the shape of a capital omega+spanning the wing. The obtained results compare well against experimental data both for the surface pressure distribution on the wing and the flow topology. Of significant importance is the interaction between the three-dimensional dynamic stall vortex and the tip vortex. The present results indicate that once the two vortices are formed both appear to originate from the same region, which is located near the leading edge of the tip. During the ramping of the wing, the two vortices grow significantly in size. The dynamic stall vortex dettaches from the wing in the inboard region but remains close to the wing’s leading edge near the tip. The overall configuration of the developed vortical system takes a form. To our knowledge, this is the first detailed numerical study of three-dimensional dynamic stall appearing in the literature.

Investigation of Three-Dimensional Dynamic Stall Using Computational Fluid Dynamics

This paper focuses on the evaluation of the dynamic stability derivative formulation. The derivatives are calculated using the Euler and Reynolds-averaged Navier–Stokes equations, and a time-domain solver was used for the computation of aerodynamic loads for forced periodic motions. To validate the predictions, two test cases are used. For the standard dynamic model geometry, a database of dynamic simulations illustrates the effects of the systematic variation of motion and fluid parameters involved. A satisfactory agreement was observed with available experimental data, and the dependency of dynamic derivatives on a number of parameters, such as Mach number, mean angle of attack, frequency, and amplitude, was assessed. For the transonic cruiser wind-tunnel geometry, static and unsteady aerodynamic characteristics were validated against experimental measurements. The ability of models based on the dynamic derivatives to predict large-amplitude motion forces and moments was assessed. It was demonstrated that the dynamic derivative model does not represent all of the important effects due to aerodynamics.

Ken Badcock

Papers

A framework for CFD analysis of helicopter rotors in hover and forward flight

Elements of computational fluid dynamics on block structured grids using implicit solvers

Interval model updating with irreducible uncertainty using the Kriging predictor

Investigation of Three-Dimensional Dynamic Stall Using Computational Fluid Dynamics

Evaluation of Dynamic Derivatives Using Computational Fluid Dynamics