Aircraft aerodynamic prediction method for V/STOL transition including flow separation

A numerical procedure was developed for the aerodynamic force and moment analysis of V/STOL aircraft operating in the transition regime between hover and conventional forward flight. The trajectories, cross sectional area variations, and mass entrainment rates of the jets are calculated by the Adler-Baron Jet-in-Crossflow Program. The inviscid effects of the interaction between the jets and airframe on the aerodynamic properties are determined by use of the MCAIR 3-D Subsonic properties are determined by use of the MCAIR 3-D Subsonic Potential Flow Program, a surface panel method. In addition, the MCAIR 3-D Geometry influence Coefficient Program is used to calculate a matrix of partial derivatives that represent the rate of change of the inviscid aerodynamic properties with respect to arbitrary changes in the effective wing shape

A study of beryllium and beryllium-lithium complexes in single crystal silicon

When beryllium is thermally diffused into silicon, it gives rise to acceptor levels 191 MeV and 145 meV above the valence band. Quenching and annealing studies indicate that the 145-MeV level is due to a more complex beryllium configuration than the 191-MeV level. When lithium is thermally diffused into a beryllium-doped silicon sample, it produces two acceptor levels at 106 MeV and 81 MeV. Quenching and annealing studies indicate that these levels are due to lithium forming a complex with the defects responsible for the 191-MeV and 145-MeV beryllium levels, respectively. Electrical measurements imply that the lithium impurity ions are physically close to the beryllium impurity atoms. The ground state of the 106-MeV beryllium level is split into two levels, presumably by internal strains. Tentative models are proposed

Size and habit evolution of PETN crystals - a lattice Monte Carlo study

Starting from an accurate inter-atomic potential we develop a simple scheme of generating an ''on-lattice'' molecular potential of short range, which is then incorporated into a lattice Monte Carlo code for simulating size and shape evolution of nanocrystallites. As a specific example, we test such a procedure on the morphological evolution of a molecular crystal of interest to us, e.g., Pentaerythritol Tetranitrate, or PETN, and obtain realistic facetted structures in excellent agreement with experimental morphologies. We investigate several interesting effects including, the evolution of the initial shape of a ''seed'' to an equilibrium configuration, and the variation of growth morphology as a function of the rate of particle addition relative to diffusion

Monte Carlo with Absorbing Markov Chains: Fast Local Algorithms for Slow Dynamics

A class of Monte Carlo algorithms which incorporate absorbing Markov chains is presented. In a particular limit, the lowest-order of these algorithms reduces to the $n$-fold way algorithm. These algorithms are applied to study the escape from the metastable state in the two-dimensional square-lattice nearest-neighbor Ising ferromagnet in an unfavorable applied field, and the agreement with theoretical predictions is very good. It is demonstrated that the higher-order algorithms can be many orders of magnitude faster than either the traditional Monte Carlo or $n$-fold way algorithms.Comment: ReVTeX, Request 3 figures from [email protected]

Towards Molecular Simulations that are Transparent, Reproducible, Usable By Others, and Extensible (TRUE)

Systems composed of soft matter (e.g., liquids, polymers, foams, gels, colloids, and most biological materials) are ubiquitous in science and engineering, but molecular simulations of such systems pose particular computational challenges, requiring time and/or ensemble-averaged data to be collected over long simulation trajectories for property evaluation. Performing a molecular simulation of a soft matter system involves multiple steps, which have traditionally been performed by researchers in a "bespoke" fashion, resulting in many published soft matter simulations not being reproducible based on the information provided in the publications. To address the issue of reproducibility and to provide tools for computational screening, we have been developing the open-source Molecular Simulation and Design Framework (MoSDeF) software suite. In this paper, we propose a set of principles to create Transparent, Reproducible, Usable by others, and Extensible (TRUE) molecular simulations. MoSDeF facilitates the publication and dissemination of TRUE simulations by automating many of the critical steps in molecular simulation, thus enhancing their reproducibility. We provide several examples of TRUE molecular simulations: All of the steps involved in creating, running and extracting properties from the simulations are distributed on open-source platforms (within MoSDeF and on GitHub), thus meeting the definition of TRUE simulations

Numerical analysis of nanograin collision by classical molecular dynamics

Interstellar dust grains [1] comprise only 1% of the mass in the molecular clouds of galaxies and yet catalyze the formation of many gas phase molecules, in particular H2 [2], which allows for the cooling and collapse of these clouds and the formation of stars and planets. High-energy radiation and particles from hot stars, supernovae, or active black holes can alter the physical properties of dust grains and thereby affect their role in these processes. There is no experimental study on grain-grain collisions, for grain smaller than tens of microns, except for clusters with less than 100 atoms. Studies at the mm/cm scale can be roughly understood by continuum models, but these models might break down at the nanometer scale. There are many atomistic molecular dynamics (MD) simulations on the destruction of 3D droplets due to large temperature input [3], 2D solids [4, 5], or collision of disks [6], but there are very few simulations on grain-grain collisions, never going beyond tens of atoms [7, 8]. Here we demonstrate how MD simulations of grain-grain collisions for grain with more than 100 atoms can be used to understand what happens for nanometer-sized grains, colliding at relatively low velocities

Phase Separation of Crystal Surfaces: A Lattice Gas Approach

We consider both equilibrium and kinetic aspects of the phase separation (``thermal faceting") of thermodynamically unstable crystal surfaces into a hill--valley structure. The model we study is an Ising lattice gas for a simple cubic crystal with nearest--neighbor attractive interactions and weak next--nearest--neighbor repulsive interactions. It is likely applicable to alkali halides with the sodium chloride structure. Emphasis is placed on the fact that the equilibrium crystal shape can be interpreted as a phase diagram and that the details of its structure tell us into which surface orientations an unstable surface will decompose. We find that, depending on the temperature and growth conditions, a number of interesting behaviors are expected. For a crystal in equilibrium with its vapor, these include a low temperature regime with logarithmically--slow separation into three symmetrically--equivalent facets, and a higher temperature regime where separation proceeds as a power law in time into an entire one--parameter family of surface orientations. For a crystal slightly out of equilibrium with its vapor (slow crystal growth or etching), power--law growth should be the rule at late enough times. However, in the low temperature regime, the rate of separation rapidly decreases as the chemical potential difference between crystal and vapor phases goes to zero.Comment: 16 pages (RevTex 3.0); 12 postscript figures available on request ([email protected]). Submitted to Physical Review E. SFU-JDSDJB-94-0

Big-Data Science in Porous Materials: Materials Genomics and Machine Learning

By combining metal nodes with organic linkers we can potentially synthesize millions of possible metal organic frameworks (MOFs). At present, we have libraries of over ten thousand synthesized materials and millions of in-silico predicted materials. The fact that we have so many materials opens many exciting avenues to tailor make a material that is optimal for a given application. However, from an experimental and computational point of view we simply have too many materials to screen using brute-force techniques. In this review, we show that having so many materials allows us to use big-data methods as a powerful technique to study these materials and to discover complex correlations. The first part of the review gives an introduction to the principles of big-data science. We emphasize the importance of data collection, methods to augment small data sets, how to select appropriate training sets. An important part of this review are the different approaches that are used to represent these materials in feature space. The review also includes a general overview of the different ML techniques, but as most applications in porous materials use supervised ML our review is focused on the different approaches for supervised ML. In particular, we review the different method to optimize the ML process and how to quantify the performance of the different methods. In the second part, we review how the different approaches of ML have been applied to porous materials. In particular, we discuss applications in the field of gas storage and separation, the stability of these materials, their electronic properties, and their synthesis. The range of topics illustrates the large variety of topics that can be studied with big-data science. Given the increasing interest of the scientific community in ML, we expect this list to rapidly expand in the coming years.Comment: Editorial changes (typos fixed, minor adjustments to figures

Surface Aggregation of Urinary Proteins and Aspartic Acid-Rich Peptides on the Faces of Calcium Oxalate Monohydrate Investigated by In Situ Force Microscopy

The growth of calcium oxalate monohydrate in the presence of Tamm-Horsfall protein (THP), osteopontin, and the 27-residue synthetic peptides (DDDS)6DDD and (DDDG)6DDD (D = aspartic acid, S = serine, and G = glycine) was investigated via in situ atomic force microscopy. The results show that these four growth modulators create extensive deposits on the crystal faces. Depending on the modulator and crystal face, these deposits can occur as discrete aggregates, filamentary structures, or uniform coatings. These proteinaceous films can lead to either the inhibition of or an increase in the step speeds (with respect to the impurity-free system), depending on a range of factors that include peptide or protein concentration, supersaturation, and ionic strength. While THP and the linear peptides act, respectively, to exclusively increase and inhibit growth on the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left( {\bar{1}01} \right)$$\end{document} face, both exhibit dual functionality on the (010) face, inhibiting growth at low supersaturation or high modulator concentration and accelerating growth at high supersaturation or low modulator concentration. Based on analyses of growth morphologies and dependencies of step speeds on supersaturation and protein or peptide concentration, we propose a picture of growth modulation that accounts for the observations in terms of the strength of binding to the surfaces and steps and the interplay of electrostatic and solvent-induced forces at the crystal surface

Chronic depression: development and evaluation of the luebeck questionnaire for recording preoperational thinking (LQPT)

<p>Abstract</p> <p>Background</p> <p>A standardized instrument for recording the specific cognitive psychopathology of chronically depressed patients has not yet been developed. Up until now, preoperational thinking of chronically depressed patients has only been described in case studies, or through the external observations of therapists. The aim of this study was to develop and evaluate a standardized self-assessment instrument for measuring preoperational thinking that sufficiently conforms to the quality criteria for test theory.</p> <p>Methods</p> <p>The "Luebeck Questionnaire for Recording Preoperational Thinking (LQPT)" was developed and evaluated using a german sample consisting of 30 episodically depressed, 30 chronically depressed and 30 healthy volunteers. As an initial step the questionnaire was subjected to an item analysis and a final test form was compiled. In a second step, reliability and validity tests were performed.</p> <p>Results</p> <p>Overall, the results of this study showed that the LQPT is a useful, reliable and valid instrument. The reliability (split-half reliability 0.885; internal consistency 0.901) and the correlations with other instruments for measuring related constructs (control beliefs, interpersonal problems, stress management) proved to be satisfactory. Chronically depressed patients, episodically depressed patients and healthy volunteers could be distinguished from one another in a statistically significant manner (p < 0.001).</p> <p>Conclusion</p> <p>The questionnaire fulfilled the classical test quality criteria. With the LQPT there is an opportunity to test the theory underlying the CBASP model.</p