Machine Learning, Quantum Mechanics, and Chemical Compound Space

We review recent studies dealing with the generation of machine learning models of molecular and solid properties. The models are trained and validated using standard quantum chemistry results obtained for organic molecules and materials selected from chemical space at random

High-speed imaging in fluids

High-speed imaging is in popular demand for a broad range of experiments in fluids. It allows for a detailed visualization of the event under study by acquiring a series of image frames captured at high temporal and spatial resolution. This review covers high-speed imaging basics, by defining criteria for high-speed imaging experiments in fluids and to give rule-of-thumbs for a series of cases. It also considers stroboscopic imaging, triggering and illumination, and scaling issues. It provides guidelines for testing and calibration. Ultra high-speed imaging at frame rates exceeding 1 million frames per second is reviewed, and the combination of conventional experiments in fluids techniques with high-speed imaging techniques are discussed. The review is concluded with a high-speed imaging chart, which summarizes criteria for temporal scale and spatial scale and which facilitates the selection of a high-speed imaging system for the applicatio

Nonequilibrium thermodynamics of interacting tunneling transport: variational grand potential, density-functional formulation, and nature of steady-state forces

The standard formulation of tunneling transport rests on an open-boundary modeling. There, conserving approximations to nonequilibrium Green function or quantum-statistical mechanics provide consistent but computational costly approaches; alternatively, use of density-dependent ballistic-transport calculations [e.g., Phys. Rev. B 52, 5335 (1995)], here denoted `DBT', provide computationally efficient (approximate) atomistic characterizations of the electron behavior but has until now lacked a formal justification. This paper presents an exact, variational nonequilibrium thermodynamic theory for fully interacting tunneling and provides a rigorous foundation for frozen-nuclei DBT calculations as a lowest order approximation to an exact nonequilibrium thermodynamics density functional evaluation. The theory starts from the complete electron nonequilibrium quantum statistical mechanics and I identify the operator for the nonequilibrium Gibbs free energy. I demonstrate a minimal property of a functional for the nonequilibrium thermodynamic grand potential which thus uniquely identifies the solution as the exact nonequilibrium density matrix. I also show that a uniqueness-of-density proof from a closely related study [Phys. Rev. B 78, 165109 (2008)] makes it possible to provide a single-particle formulation based on universal electron-density functionals. I illustrate a formal evaluation of the thermodynamics grand potential value which is closely related to the variation in scattering phase shifts and hence to Friedel density oscillations. This paper also discusses the difference between the here-presented exact thermodynamics forces and the often-used electrostatic forces. Finally the paper documents an inherent adiabatic nature of the thermodynamics forces and observes that these are suited for a nonequilibrium implementation of the Born-Oppenheimer approximation.Comment: 37 pages, 3 Figure

Predictions and measurements of isothermal flowfields in axisymmetric combustor geometries

Numerical predictions, flow visualization experiments and time-mean velocity measurements were obtained for six basic nonreacting flowfields (with inlet swirl vane angles of 0 (swirler removed), 45 and 70 degrees and sidewall expansion angles of 90 and 45 degrees) in an idealized axisymmetric combustor geometry. A flowfield prediction computer program was developed which solves appropriate finite difference equations including a conventional two equation k-epsilon eddy viscosity turbulence model. The wall functions employed were derived from previous swirling flow measurements, and the stairstep approximation was employed to represent the sloping wall at the inlet to the test chamber. Recirculation region boundaries have been sketched from the entire flow visualization photograph collection. Tufts, smoke, and neutrally buoyant helium filled soap bubbles were employed as flow tracers. A five hole pitot probe was utilized to measure the axial, radial, and swirl time mean velocity components

Probabilistic Image Models and their Massively Parallel Architectures : A Seamless Simulation- and VLSI Design-Framework Approach

Algorithmic robustness in real-world scenarios and real-time processing capabilities are the two essential and at the same time contradictory requirements modern image-processing systems have to fulfill to go significantly beyond state-of-the-art systems. Without suitable image processing and analysis systems at hand, which comply with the before mentioned contradictory requirements, solutions and devices for the application scenarios of the next generation will not become reality. This issue would eventually lead to a serious restraint of innovation for various branches of industry. This thesis presents a coherent approach to the above mentioned problem. The thesis at first describes a massively parallel architecture template and secondly a seamless simulation- and semiconductor-technology-independent design framework for a class of probabilistic image models, which are formulated on a regular Markovian processing grid. The architecture template is composed of different building blocks, which are rigorously derived from Markov Random Field theory with respect to the constraints of \it massively parallel processing \rm and \it technology independence\rm. This systematic derivation procedure leads to many benefits: it decouples the architecture characteristics from constraints of one specific semiconductor technology; it guarantees that the derived massively parallel architecture is in conformity with theory; and it finally guarantees that the derived architecture will be suitable for VLSI implementations. The simulation-framework addresses the unique hardware-relevant simulation needs of MRF based processing architectures. Furthermore the framework ensures a qualified representation for simulation of the image models and their massively parallel architectures by means of their specific simulation modules. This allows for systematic studies with respect to the combination of numerical, architectural, timing and massively parallel processing constraints to disclose novel insights into MRF models and their hardware architectures. The design-framework rests upon a graph theoretical approach, which offers unique capabilities to fulfill the VLSI demands of massively parallel MRF architectures: the semiconductor technology independence guarantees a technology uncommitted architecture for several design steps without restricting the design space too early; the design entry by means of behavioral descriptions allows for a functional representation without determining the architecture at the outset; and the topology-synthesis simplifies and separates the data- and control-path synthesis. Detailed results discussed in the particular chapters together with several additional results collected in the appendix will further substantiate the claims made in this thesis

Process capability modelling: a review report of feature representation methodologies

Approximately 150 technical papers on the features methodology have been carefully studied and some selected papers have been commented upon. The abstracts of the comments are documented and attached to this report. The methodologies reviewed are mainly divided into two approaches, ie. feature recognition and design by features. Papers which deal with some specific topics such as feature taxonomies, dimensions and tolerances, feature concepts, etc. are also included in the document