Dynamic simulation algorithm

Lamoureux G, Roux B (2003) Modeling induced polarization with classical Drude oscillators theory and molecular dynamics simulation algorithm. J Chem Phys 119(6) 3025-3039... 

When the CPU requests a data item from main memory, the memory subsystem will check to see if it can be found in cache. If the data is not in cache, a cache miss occurs. When this happens the data item will be searched for at lower levels of the memory system and when it is eventually found it is brought into the cache. Data are fetched from memory in units of a cache line. This kind of memory organization is motivated by the observation that data that is used often should be accessible as quickly as possible and when a data is accessed it is also very likely that data items located close to it in memory will also be accessed soon. So memory access patterns which are local in space and time will be quickly serviced. Molecular Dynamics simulation algorithms often have a quite a lot of potential for memory access patterns that are local both in time and space. How well this can be exploited is very much dependent on the data-structures that are used in implementations. Which, of all possible data-structures, are optimal for MD is currently an open question. 

The theory for various molecular dynamics simulation algorithms for the calculation of transport coefficients of liquid crystals is presented. We show in particular how the thermal conductivity and the viscosity are obtained. The viscosity of a nematic liquid crystal has seven independent components because of the lower symmetry. We present numerical results for various phases of the Gay-Berne fluid even though the theory is completely general and applicable to more realistic model systems. 

YUGl, K., NAKAYAMA, Y., TOMITA, M., A hybrid static/dynamic simulation algorithm Towards large-scale pathway simulation, in Proceedings of the 3" International Conference on Systems Biology (E. Aurell, J. Elf, J. Jeppsson, eds.). 2002, p. 235... 

Previous research in the dynamic simulation of robotic mechanisms includes the examination of both open-chain mechanisms [2,3,12,42] and closed-chain configurations [4, 16, 22, 31, 33, 39]. Although many of these earli results are useful and impextant, further improvements in the computational efficiency of dynamic simulation algorithms are necessary for real-time implementation. 

This book is organized into two parts. The first part addresses the efficient computation of manipulator inertia matrices, both joint space and operational space. Grrresponding algorithms may be found in Chapters 3 and 4, respectively. Ibe second part of this book presents efficient dynamic simulation algorithms for closed-chain robotic systems and is comprised of Chapters S and 6. 

In the sixth section, the complete dynamic simulation algorithm for a single closed chain is presented as a series of four computational steps. Each step is explained in detail, particularly the step which computes the unknown contact forces and moments. The integration of the joint rates and accelerations to obtain the next state positions and rates is also briefly discussed. The computational requirements of both versions of the simulation algorithm are tabulated and compared in the seventh section of this chapter. 

Dynamic Simulation Algorithm for a Single Closed Chain... 

The final stq> in any dynamic simulation algorithm is the numerical integration of the joint accel ations and rates to determine the next state joint rates and positions. Many different integration methods may be found in the literature to accomplish this task. FamUiar exaipples include the fourth-order Runge-Kutta... 

In this section, the computational requirements of the dynamic simulation algorithm for a single closed chain are summarized and discussed. The number of required scalar operations is tabulated for each step, with the exception of the integration step. The q)erations required for integration are usually not included in the overall computational complexity of a simulation algorithm. 

Tables S.l and 5.2 list the computational requirements for the new dynamic simulation algorithm, using the most efficient algorithms known for each calculation for different values of N. The computations are tabulated in toms of the matrix and vector quantities which are found in the first three stq>s of the algorithm. The requited scalar opoations (multiplications, additions) are given for an AT-link, serial manipulator with simple revolute and prismatic joints only. The efficient matrix transformations and oth simplifications described in Chapter 3 have been applied in each stq>, and the computations necessary to determine the individual link transformation matrices have also been included.

Dynamic Simulation Algorithm for Simple Closed-Chain Mechanisms... 

Like the dynamic simulation algorithm fw a single closed chain, the algorithm developed here for simple closed-chain mechanisms may also be presented as a series of steps. In this case, five computational steps are required, and they are as follows ... 

In this chapter, a general and efficient dynamic simulation algorithm for simple closed-chain mechanisms was derived. The algorithm is tq>plicable to both lype... 

An examination of the validity of nonequflibrium molecular-dynamics simulation algorithms for arbitrary steady-state flows. J. Chem, Phys., 123,... 

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