Algorithm implementation on the Navier-Stokes computer

The Navier-Stokes Computer is a multi-purpose parallel-processing supercomputer which is currently under development at Princeton University. It consists of multiple local memory parallel processors, called Nodes, which are interconnected in a hypercube network. Details of the procedures involved in implementing an algorithm on the Navier-Stokes computer are presented. The particular finite difference algorithm considered in this analysis was developed for simulation of laminar-turbulent transition in wall bounded shear flows. Projected timing results for implementing this algorithm indicate that operation rates in excess of 42 GFLOPS are feasible on a 128 Node machine

Numerical simulation of channel flow transition, resolution requirements and structure of the hairpin vortex

Three-dimensional, nonlinear numerical simulations are presented for the K-type and H-type transitions for channel flow. There are two objectives. The first is to establish firmly the resolution requirements for the various stages in the transition process. Comparisons between calculations on various grids suggest a set of guidelines for maintaining a physically meaningful calculation. The second objective is to map out the structure of the hairpin vortices which arise in K-type and H-type transitions in channel flow, to the latest stage currently feasible. Flow field details are presented for both a subcritical Reynolds number of 1500 and a supercritical Reynolds number of 8000. The diagnostics include illustrations of the vertical shear, streamwise and spanwise vorticity, helicity, vortex stretching, and vortex diffusion fields

Shock-fitted Euler solutions to shock-vortex interactions

The interaction of a shock wave with a hot spot, a single vortex and a vortex street is studied within the framework of the two dimensional compressible Euler equations. The numerical results obtained by the pseudospectral method and the finite difference MacCormack method are compared. In both the methods the shock wave is fitted as a boundary of the computational domain

Quantum Manifestation of Elastic Constants in Nanostructures

Generally, there are two distinct effects in modifying the properties of low-dimensional nanostructures: surface effect (SS) due to increased surface-volume ratio and quantum size effect (QSE) due to quantum confinement in reduced dimension. The SS has been widely shown to affect the elastic constants and mechanical properties of nanostructures. Here, using Pb nanofilm and graphene nanoribbon as model systems, we demonstrate the QSE on the elastic constants of nanostructures by first-principles calculations. We show that generally QSE is dominant in affecting the elastic constants of metallic nanostructures while SS is more pronounced in semiconductor and insulator nanostructures. Our findings have broad implications in quantum aspects of nanomechanics

Low Temperature Magnetic Properties of the Double Exchange Model

We study the {\it ferromagnetic} (FM) Kondo lattice model in the strong coupling limit (double exchange (DE) model). The DE mechanism proposed by Zener to explain ferromagnetism has unexpected properties when there is more than one itinerant electron. We find that, in general, the many-body ground state of the DE model is {\it not} globally FM ordered (except for special filled-shell cases). Also, the low energy excitations of this model are distinct from spin wave excitations in usual Heisenberg ferromagnets, which will result in unusual dynamic magnetic properties.Comment: 5 pages, RevTeX, 5 Postscript figures include

Analysis of sensitivity and optimization for mistuned bladed disk forced response using high-fidelity models

An effective method is developed for efficient calculations of the sensitivity of the maximum forced response levels for mistuned bladed disks with respect to blade frequency mistuning. The expressions for 1st and 2nd order sensitivity coefficients are derived in an analytical form which provides high accuracy and computational efficiency. Then, the optimization methods are used for searching the best and worst mistuning patterns of bladed disks. Two major types of the mistuning optimization problems are considered: (i) a continuous optimization problem when the blade mistuning can take any values from a prescribed range and (ii) a combinatorial optimization problem, when the set of mistuned blades is given and the optimization can be achieved by blade re-arrangement in a disk. For the first type of the optimization problem a set of sensitivity-based optimization algorithms is applied and for the second type a variant of a genetic algorithm is developed. The analysis of mistuning sensitivity coefficients and results of optimization searching are shown on an example of a realistic turbine bladed disk

Persistent Current in the Ferromagnetic Kondo Lattice Model

In this paper, we study the zero temperature persistent current in a ferromagnetic Kondo lattice model in the strong coupling limit. In this model, there are spontaneous spin textures at some values of the external magnetic flux. These spin textures contribute a geometric flux, which can induce an additional spontaneous persistent current. Since this spin texture changes with the external magnetic flux, we find that there is an anomalous persistent current in some region of magnetic flux: near Phi/Phi_0=0 for an even number of electrons and Phi/Phi_0=1/2 for an odd number of electrons.Comment: 6 RevTeX pages, 10 figures include

On the soliton width in the incommensurate phase of spin-Peierls systems

We study using bosonization techniques the effects of frustration due to competing interactions and of the interchain elastic couplings on the soliton width and soliton structure in spin-Peierls systems. We compare the predictions of this study with numerical results obtained by exact diagonalization of finite chains. We conclude that frustration produces in general a reduction of the soliton width while the interchain elastic coupling increases it. We discuss these results in connection with recent measurements of the soliton width in the incommensurate phase of CuGeO_3.Comment: 4 pages, latex, 2 figures embedded in the tex

Resistance-gene-directed discovery of a natural-product herbicide with a new mode of action.

Bioactive natural products have evolved to inhibit specific cellular targets and have served as lead molecules for health and agricultural applications for the past century1-3. The post-genomics era has brought a renaissance in the discovery of natural products using synthetic-biology tools4-6. However, compared to traditional bioactivity-guided approaches, genome mining of natural products with specific and potent biological activities remains challenging4. Here we present the discovery and validation of a potent herbicide that targets a critical metabolic enzyme that is required for plant survival. Our approach is based on the co-clustering of a self-resistance gene in the natural-product biosynthesis gene cluster7-9, which provides insight into the potential biological activity of the encoded compound. We targeted dihydroxy-acid dehydratase in the branched-chain amino acid biosynthetic pathway in plants; the last step in this pathway is often targeted for herbicide development10. We show that the fungal sesquiterpenoid aspterric acid, which was discovered using the method described above, is a sub-micromolar inhibitor of dihydroxy-acid dehydratase that is effective as a herbicide in spray applications. The self-resistance gene astD was validated to be insensitive to aspterric acid and was deployed as a transgene in the establishment of plants that are resistant to aspterric acid. This herbicide-resistance gene combination complements the urgent ongoing efforts to overcome weed resistance11. Our discovery demonstrates the potential of using a resistance-gene-directed approach in the discovery of bioactive natural products