Emulation of multivariate simulators using thin-plate splines with application to atmospheric dispersion

It is often desirable to build a statistical emulator of a complex computer simulator in order to perform analysis which would otherwise be computationally infeasible. We propose methodology to model multivariate output from a computer simulator taking into account output structure in the responses. The utility of this approach is demonstrated by applying it to a chemical and biological hazard prediction model. Predicting the hazard area which results from an accidental or deliberate chemical or biological release is imperative in civil and military planning and also in emergency response. The hazard area resulting from such a release is highly structured in space and we therefore propose the use of a thin-plate spline to capture the spatial structure and fit a Gaussian process emulator to the coefficients of the resultant basis functions. We compare and contrast four different techniques for emulating multivariate output: dimension-reduction using (i) a fully Bayesian approach with a principal component basis, (ii) a fully Bayesian approach with a thin-plate spline basis, assuming that the basis coefficients are independent, and (iii) a “plug-in” Bayesian approach with a thin-plate spline basis and a separable covariance structure; and (iv) a functional data modeling approach using a tensor-product (separable) Gaussian process. We develop methodology for the two thin-plate spline emulators and demonstrate that these emulators significantly outperform the principal component emulator. Further, the separable thin-plate spline emulator, which accounts for the dependence between basis coefficients, provides substantially more realistic quantification of uncertainty, and is also computationally more tractable, allowing fast emulation. For high resolution output data, it also offers substantial predictive and computational ad- vantages over the tensor-product Gaussian process emulator

Mission oriented study of advanced nuclear system parameters, phase 6. Volume 1 - Summary technical report Final report

Summarized study tasks, analyses, and results of advanced nuclear propulsion parameters for Mars and Venus mission

Influence of temper condition on the nonlinear stress-strain behavior of boron-aluminum

The influence of temper condition on the tensile and compressive stress-strain behavior for six boron-aluminum laminates was investigated. In addition to monotonic tension and compression tests, tension-tension, compression-compression, and tension--compression tests were conducted to study the effects of cyclic loading. Tensile strength results are a function of the laminate configuration; unidirectional laminates were affected considerably more than other laminates with some strength values increasing and others decreasing

Stripe phases in the two-dimensional Falicov-Kimball model

The observation of charge stripe order in the doped nickelate and cuprate materials has motivated much theoretical effort to understand the underlying mechanism of the stripe phase. Numerical studies of the Hubbard model show two possibilities: (i) stripe order arises from a tendency toward phase separation and its competition with the long-range Coulomb interaction or (ii) stripe order inherently arises as a compromise between itinerancy and magnetic interactions. Here we determine the restricted phase diagrams of the two-dimensional Falicov-Kimball model and see that it displays rich behavior illustrating both possibilities in different regions of the phase diagram.Comment: (5 pages, 3 figures

Thermodynamic limit of the density matrix renormalization for the spin-1 Heisenberg chain

The density matrix renormalization group (``DMRG'') discovered by White has shown to be a powerful method to understand the properties of many one dimensional quantum systems. In the case where renormalization eventually converges to a fixed point we show that quantum states in the thermodynamic limit with periodic boundary conditions can be simply represented by a special type of product ground state with a natural description of Bloch states of elementary excitations that are spin-1 solitons. We then observe that these states can be rederived through a simple variational ansatz making no reference to a renormalization construction. The method is tested on the spin-1 Heisenberg model.Comment: 13 pages uuencoded compressed postscript including figure

To Duckweeds (\u3cem\u3eLandoltia punctata\u3c/em\u3e), Nanoparticulate Copper Oxide is More Inhibitory than the Soluble Copper in the Bulk Solution

CuO nanoparticles (CuO-NP) were synthesized in a hydrogen diffusion flame. Particle size and morphology were characterized using scanning mobility particle sizing, Brunauer–Emmett–Teller analysis, dynamic light scattering, and transmission electron microscopy. The solubility of CuO-NP varied with both pH and presence of other ions. CuO-NP and comparable doses of soluble Cu were applied to duckweeds, Landoltia punctata. Growth was inhibited 50% by either 0.6 mg L−1 soluble copper or by 1.0 mg L−1 CuO-NP that released only 0.16 mg L−1 soluble Cu into growth medium. A significant decrease of chlorophyll was observed in plants stressed by 1.0 mg L−1 CuO-NP, but not in the comparable 0.2 mg L−1 soluble Cu treatment. The Cu content of fronds exposed to CuO-NP is four times higher than in fronds exposed to an equivalent dose of soluble copper, and this is enough to explain the inhibitory effects on growth and chlorophyll content