Differential Geometry and Lie Groups for Physicists

NASA Astrophysics Data System (ADS)

Fecko, Marián.

2011-03-01

Introduction; 1. The concept of a manifold; 2. Vector and tensor fields; 3. Mappings of tensors induced by mappings of manifolds; 4. Lie derivative; 5. Exterior algebra; 6. Differential calculus of forms; 7. Integral calculus of forms; 8. Particular cases and applications of Stoke's Theorem; 9. Poincaré Lemma and cohomologies; 10. Lie Groups - basic facts; 11. Differential geometry of Lie Groups; 12. Representations of Lie Groups and Lie Algebras; 13. Actions of Lie Groups and Lie Algebras on manifolds; 14. Hamiltonian mechanics and symplectic manifolds; 15. Parallel transport and linear connection on M; 16. Field theory and the language of forms; 17. Differential geometry on TM and T*M; 18. Hamiltonian and Lagrangian equations; 19. Linear connection and the frame bundle; 20. Connection on a principal G-bundle; 21. Gauge theories and connections; 22. Spinor fields and Dirac operator; Appendices; Bibliography; Index.

Arbitrary-Order Conservative and Consistent Remapping and a Theory of Linear Maps: Part II

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ullrich, Paul A.; Devendran, Dharshi; Johansen, Hans

2016-04-01

The focus on this series of articles is on the generation of accurate, conservative, consistent, and (optionally) monotone linear offline maps. This paper is the second in the series. It extends on the first part by describing four examples of 2D linear maps that can be constructed in accordance with the theory of the earlier work. The focus is again on spherical geometry, although these techniques can be readily extended to arbitrary manifolds. The four maps include conservative, consistent, and (optionally) monotone linear maps (i) between two finite-volume meshes, (ii) from finite-volume to finite-element meshes using a projection-type approach, (iii)more » from finite-volume to finite-element meshes using volumetric integration, and (iv) between two finite-element meshes. Arbitrary order of accuracy is supported for each of the described nonmonotone maps.« less

Towards generalized mirror symmetry for twisted connected sum G 2 manifolds

NASA Astrophysics Data System (ADS)

Braun, Andreas P.; Del Zotto, Michele

2018-03-01

We revisit our construction of mirror symmetries for compactifications of Type II superstrings on twisted connected sum G 2 manifolds. For a given G 2 manifold, we discuss evidence for the existence of mirror symmetries of two kinds: one is an autoequivalence for a given Type II superstring on a mirror pair of G 2 manifolds, the other is a duality between Type II strings with different chiralities for another pair of mirror manifolds. We clarify the role of the B-field in the construction, and check that the corresponding massless spectra are respected by the generalized mirror maps. We discuss hints towards a homological version based on BPS spectroscopy. We provide several novel examples of smooth, as well as singular, mirror G 2 backgrounds via pairs of dual projecting tops. We test our conjectures against a Joyce orbifold example, where we reproduce, using our geometrical methods, the known mirror maps that arise from the SCFT worldsheet perspective. Along the way, we discuss non-Abelian gauge symmetries, and argue for the generation of the Affleck-Harvey-Witten superpotential in the pure SYM case.

Invariants, Attractors and Bifurcation in Two Dimensional Maps with Polynomial Interaction

NASA Astrophysics Data System (ADS)

Hacinliyan, Avadis Simon; Aybar, Orhan Ozgur; Aybar, Ilknur Kusbeyzi

This work will present an extended discrete-time analysis on maps and their generalizations including iteration in order to better understand the resulting enrichment of the bifurcation properties. The standard concepts of stability analysis and bifurcation theory for maps will be used. Both iterated maps and flows are used as models for chaotic behavior. It is well known that when flows are converted to maps by discretization, the equilibrium points remain the same but a richer bifurcation scheme is observed. For example, the logistic map has a very simple behavior as a differential equation but as a map fold and period doubling bifurcations are observed. A way to gain information about the global structure of the state space of a dynamical system is investigating invariant manifolds of saddle equilibrium points. Studying the intersections of the stable and unstable manifolds are essential for understanding the structure of a dynamical system. It has been known that the Lotka-Volterra map and systems that can be reduced to it or its generalizations in special cases involving local and polynomial interactions admit invariant manifolds. Bifurcation analysis of this map and its higher iterates can be done to understand the global structure of the system and the artifacts of the discretization by comparing with the corresponding results from the differential equation on which they are based.

Equation-free and variable free modeling for complex/multiscale systems. Coarse-grained computation in science and engineering using fine-grained models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kevrekidis, Ioannis G.

The work explored the linking of modern developing machine learning techniques (manifold learning and in particular diffusion maps) with traditional PDE modeling/discretization/scientific computation techniques via the equation-free methodology developed by the PI. The result (in addition to several PhD degrees, two of them by CSGF Fellows) was a sequence of strong developments - in part on the algorithmic side, linking data mining with scientific computing, and in part on applications, ranging from PDE discretizations to molecular dynamics and complex network dynamics.

Maps on statistical manifolds exactly reduced from the Perron-Frobenius equations for solvable chaotic maps

NASA Astrophysics Data System (ADS)

Goto, Shin-itiro; Umeno, Ken

2018-03-01

Maps on a parameter space for expressing distribution functions are exactly derived from the Perron-Frobenius equations for a generalized Boole transform family. Here the generalized Boole transform family is a one-parameter family of maps, where it is defined on a subset of the real line and its probability distribution function is the Cauchy distribution with some parameters. With this reduction, some relations between the statistical picture and the orbital one are shown. From the viewpoint of information geometry, the parameter space can be identified with a statistical manifold, and then it is shown that the derived maps can be characterized. Also, with an induced symplectic structure from a statistical structure, symplectic and information geometric aspects of the derived maps are discussed.

Trace identities and their semiclassical implications

NASA Astrophysics Data System (ADS)

Smilansky, Uzy

2000-03-01

The compatibility of the semiclassical quantization of area-preserving maps with some exact identities which follow from the unitarity of the quantum evolution operator is discussed. The quantum identities involve relations between traces of powers of the evolution operator. For classically integrable maps, the semiclassical approximation is shown to be compatible with the trace identities. This is done by the identification of stationary phase manifolds which give the main contributions to the result. The compatibility of the semiclassical quantization with the trace identities demonstrates the crucial importance of non-diagonal contributions. The same technique is not applicable for chaotic maps, and the compatibility of the semiclassical theory in this case remains unsettled. However, the trace identities are applied to maps which appear naturally in the theory of quantum graphs, revealing some features of the periodic orbit theory for these paradigms of quantum chaos.

Manifold absolute pressure estimation using neural network with hybrid training algorithm

PubMed Central

Selamat, Hazlina; Alimin, Ahmad Jais; Haniff, Mohamad Fadzli

2017-01-01

In a modern small gasoline engine fuel injection system, the load of the engine is estimated based on the measurement of the manifold absolute pressure (MAP) sensor, which took place in the intake manifold. This paper present a more economical approach on estimating the MAP by using only the measurements of the throttle position and engine speed, resulting in lower implementation cost. The estimation was done via two-stage multilayer feed-forward neural network by combining Levenberg-Marquardt (LM) algorithm, Bayesian Regularization (BR) algorithm and Particle Swarm Optimization (PSO) algorithm. Based on the results found in 20 runs, the second variant of the hybrid algorithm yields a better network performance than the first variant of hybrid algorithm, LM, LM with BR and PSO by estimating the MAP closely to the simulated MAP values. By using a valid experimental training data, the estimator network that trained with the second variant of the hybrid algorithm showed the best performance among other algorithms when used in an actual retrofit fuel injection system (RFIS). The performance of the estimator was also validated in steady-state and transient condition by showing a closer MAP estimation to the actual value. PMID:29190779

Intrinsic map dynamics exploration for uncharted effective free-energy landscapes

PubMed Central

Covino, Roberto; Coifman, Ronald R.; Gear, C. William; Georgiou, Anastasia S.; Kevrekidis, Ioannis G.

2017-01-01

We describe and implement a computer-assisted approach for accelerating the exploration of uncharted effective free-energy surfaces (FESs). More generally, the aim is the extraction of coarse-grained, macroscopic information from stochastic or atomistic simulations, such as molecular dynamics (MD). The approach functionally links the MD simulator with nonlinear manifold learning techniques. The added value comes from biasing the simulator toward unexplored phase-space regions by exploiting the smoothness of the gradually revealed intrinsic low-dimensional geometry of the FES. PMID:28634293

Preliminary Work for Identifying and Tracking Combustion Reaction Pathways by Coherent Microwave Mapping of Photoelectrons

DTIC Science & Technology

2016-06-24

wall Radar technique has been built and preliminary results of pyrolysis of iso-butane have been obtained. Qualitative measurements of ethylene in...The (2+1) REMPI ionizations of ethylene (C2H4, 11B3u(π,3p) Rydberg manifold) was selectively induced at 310─325nm. The ethylene was detectable at...quantitative measurements of ethylene as one of the pyrolysis products by using coherent microwave Rayleigh scattering (Radar) from Resonant Enhanced Multi

Hierarchical brain mapping via a generalized Dirichlet solution for mapping brain manifolds

NASA Astrophysics Data System (ADS)

Joshi, Sarang C.; Miller, Michael I.; Christensen, Gary E.; Banerjee, Ayan; Coogan, Tom; Grenander, Ulf

1995-08-01

In this paper we present a coarse-to-fine approach for the transformation of digital anatomical textbooks from the ideal to the individual that unifies the work on landmark deformations and volume based transformation. The Hierarchical approach is linked to the Biological problem itself, coming out of the various kinds of information which is provided by the anatomists. This information is in the form of points, lines, surfaces and sub-volumes corresponding to 0, 1, 2, and 3 dimensional sub-manifolds respectively. The algorithm is driven by these sub- manifolds. We follow the approach that the highest dimensional transformation is a result from the solution of a sequence of lower dimensional problems driven by successive refinements or partitions of the images into various Biologically meaningful sub-structures.

Comparison of Spatiotemporal Mapping Techniques for Enormous Etl and Exploitation Patterns

NASA Astrophysics Data System (ADS)

Deiotte, R.; La Valley, R.

2017-10-01

The need to extract, transform, and exploit enormous volumes of spatiotemporal data has exploded with the rise of social media, advanced military sensors, wearables, automotive tracking, etc. However, current methods of spatiotemporal encoding and exploitation simultaneously limit the use of that information and increase computing complexity. Current spatiotemporal encoding methods from Niemeyer and Usher rely on a Z-order space filling curve, a relative of Peano's 1890 space filling curve, for spatial hashing and interleaving temporal hashes to generate a spatiotemporal encoding. However, there exist other space-filling curves, and that provide different manifold coverings that could promote better hashing techniques for spatial data and have the potential to map spatiotemporal data without interleaving. The concatenation of Niemeyer's and Usher's techniques provide a highly efficient space-time index. However, other methods have advantages and disadvantages regarding computational cost, efficiency, and utility. This paper explores the several methods using a range of sizes of data sets from 1K to 10M observations and provides a comparison of the methods.

Applying manifold learning techniques to the CAESAR database

NASA Astrophysics Data System (ADS)

Mendoza-Schrock, Olga; Patrick, James; Arnold, Gregory; Ferrara, Matthew

2010-04-01

Understanding and organizing data is the first step toward exploiting sensor phenomenology for dismount tracking. What image features are good for distinguishing people and what measurements, or combination of measurements, can be used to classify the dataset by demographics including gender, age, and race? A particular technique, Diffusion Maps, has demonstrated the potential to extract features that intuitively make sense [1]. We want to develop an understanding of this tool by validating existing results on the Civilian American and European Surface Anthropometry Resource (CAESAR) database. This database, provided by the Air Force Research Laboratory (AFRL) Human Effectiveness Directorate and SAE International, is a rich dataset which includes 40 traditional, anthropometric measurements of 4400 human subjects. If we could specifically measure the defining features for classification, from this database, then the future question will then be to determine a subset of these features that can be measured from imagery. This paper briefly describes the Diffusion Map technique, shows potential for dimension reduction of the CAESAR database, and describes interesting problems to be further explored.

Fluid manifold design for a solar energy storage tank

NASA Technical Reports Server (NTRS)

Humphries, W. R.; Hewitt, H. C.; Griggs, E. I.

1975-01-01

A design technique for a fluid manifold for use in a solar energy storage tank is given. This analytical treatment generalizes the fluid equations pertinent to manifold design, giving manifold pressures, velocities, and orifice pressure differentials in terms of appropriate fluid and manifold geometry parameters. Experimental results used to corroborate analytical predictions are presented. These data indicate that variations in discharge coefficients due to variations in orifices can cause deviations between analytical predictions and actual performance values.

Research on the transfers to Halo orbits from the view of invariant manifolds

NASA Astrophysics Data System (ADS)

Xu, Ming; Tan, Tian; Xu, ShiJie

2012-04-01

This paper discusses the evolutions of invariant manifolds of Halo orbits by low-thrust and lunar gravity. The possibility of applying all these manifolds in designing low-thrust transfer, and the presence of single-impulse trajectories under lunar gravity are also explained. The relationship between invariant manifolds and the altitude of the perigee is investigated using a Poincaré map. Six types of single-impulse transfer trajectories are then attained from the geometry of the invariant manifolds. The evolutions of controlled manifolds are surveyed by the gradient law of Jacobi energy, and the following conclusions are drawn. First, the low thrust (acceleration or deceleration) near the libration point is very inefficient that the spacecraft free-flies along the invariant manifolds. The purpose is to increase its velocity and avoid stagnation near the libration point. Second, all controlled manifolds are captured because they lie inside the boundary of Earth's gravity trap in the configuration space. The evolutions of invariant manifolds under lunar gravity are indicated from the relationship between the lunar phasic angle and the altitude of the perigee. Third and last, most of the manifolds have preserved their topologies in the circular restricted three-body problem. However, the altitudes of the perigee of few manifolds are quite non-continuous, which can be used to generate single- impulse flyby trajectories.

Double Neimark Sacker bifurcation and torus bifurcation of a class of vibratory systems with symmetrical rigid stops

NASA Astrophysics Data System (ADS)

Luo, G. W.; Chu, Y. D.; Zhang, Y. L.; Zhang, J. G.

2006-11-01

A multidegree-of-freedom system having symmetrically placed rigid stops and subjected to periodic excitation is considered. The system consists of linear components, but the maximum displacement of one of the masses is limited to a threshold value by the symmetrical rigid stops. Repeated impacts usually occur in the vibratory system due to the rigid amplitude constraints. Such models play an important role in the studies of mechanical systems with clearances or gaps. Double Neimark-Sacker bifurcation of the system is analyzed by using the center manifold and normal form method of maps. The period-one double-impact symmetrical motion and homologous disturbed map of the system are derived analytically. A center manifold theorem technique is applied to reduce the Poincaré map to a four-dimensional one, and the normal form map associated with double Neimark-Sacker bifurcation is obtained. The bifurcation sets for the normal-form map are illustrated in detail. Local behavior of the vibratory systems with symmetrical rigid stops, near the points of double Neimark-Sacker bifurcations, is reported by the presentation of results for a three-degree-of-freedom vibratory system with symmetrical stops. The existence and stability of period-one double-impact symmetrical motion are analyzed explicitly. Also, local bifurcations at the points of change in stability are analyzed, thus giving some information on dynamical behavior near the points of double Neimark-Sacker bifurcations. Near the value of double Neimark-Sacker bifurcation there exist period-one double-impact symmetrical motion and quasi-periodic impact motions. The quasi-periodic impact motions are represented by the closed circle and "tire-like" attractor in projected Poincaré sections. With change of system parameters, the quasi-periodic impact motions usually lead to chaos via "tire-like" torus doubling.

Mirror symmetry in emergent gravity

NASA Astrophysics Data System (ADS)

Yang, Hyun Seok

2017-09-01

Given a six-dimensional symplectic manifold (M , B), a nondegenerate, co-closed four-form C introduces a dual symplectic structure B ˜ = * C independent of B via the Hodge duality *. We show that the doubling of symplectic structures due to the Hodge duality results in two independent classes of noncommutative U (1) gauge fields by considering the Seiberg-Witten map for each symplectic structure. As a result, emergent gravity suggests a beautiful picture that the variety of six-dimensional manifolds emergent from noncommutative U (1) gauge fields is doubled. In particular, the doubling for the variety of emergent Calabi-Yau manifolds allows us to arrange a pair of Calabi-Yau manifolds such that they are mirror to each other. Therefore, we argue that the mirror symmetry of Calabi-Yau manifolds is the Hodge theory for the deformation of symplectic and dual symplectic structures.

Continuous Optimization on Constraint Manifolds

NASA Technical Reports Server (NTRS)

Dean, Edwin B.

1988-01-01

This paper demonstrates continuous optimization on the differentiable manifold formed by continuous constraint functions. The first order tensor geodesic differential equation is solved on the manifold in both numerical and closed analytic form for simple nonlinear programs. Advantages and disadvantages with respect to conventional optimization techniques are discussed.

Projective mappings and dimensions of vector spaces of three types of Killing-Yano tensors on pseudo Riemannian manifolds of constant curvature

NASA Astrophysics Data System (ADS)

Mikeš, Josef; Stepanov, Sergey; Hinterleitner, Irena

2012-07-01

In our paper we have determined the dimension of the space of conformal Killing-Yano tensors and the dimensions of its two subspaces of closed conformal Killing-Yano and Killing-Yano tensors on pseudo Riemannian manifolds of constant curvature. This result is a generalization of well known results on sharp upper bounds of the dimensions of the vector spaces of conformal Killing-Yano, Killing-Yano and concircular vector fields on pseudo Riemannian manifolds of constant curvature.

Exploring the CAESAR database using dimensionality reduction techniques

NASA Astrophysics Data System (ADS)

Mendoza-Schrock, Olga; Raymer, Michael L.

2012-06-01

The Civilian American and European Surface Anthropometry Resource (CAESAR) database containing over 40 anthropometric measurements on over 4000 humans has been extensively explored for pattern recognition and classification purposes using the raw, original data [1-4]. However, some of the anthropometric variables would be impossible to collect in an uncontrolled environment. Here, we explore the use of dimensionality reduction methods in concert with a variety of classification algorithms for gender classification using only those variables that are readily observable in an uncontrolled environment. Several dimensionality reduction techniques are employed to learn the underlining structure of the data. These techniques include linear projections such as the classical Principal Components Analysis (PCA) and non-linear (manifold learning) techniques, such as Diffusion Maps and the Isomap technique. This paper briefly describes all three techniques, and compares three different classifiers, Naïve Bayes, Adaboost, and Support Vector Machines (SVM), for gender classification in conjunction with each of these three dimensionality reduction approaches.

Unsupervised image matching based on manifold alignment.

PubMed

Pei, Yuru; Huang, Fengchun; Shi, Fuhao; Zha, Hongbin

2012-08-01

This paper challenges the issue of automatic matching between two image sets with similar intrinsic structures and different appearances, especially when there is no prior correspondence. An unsupervised manifold alignment framework is proposed to establish correspondence between data sets by a mapping function in the mutual embedding space. We introduce a local similarity metric based on parameterized distance curves to represent the connection of one point with the rest of the manifold. A small set of valid feature pairs can be found without manual interactions by matching the distance curve of one manifold with the curve cluster of the other manifold. To avoid potential confusions in image matching, we propose an extended affine transformation to solve the nonrigid alignment in the embedding space. The comparatively tight alignments and the structure preservation can be obtained simultaneously. The point pairs with the minimum distance after alignment are viewed as the matchings. We apply manifold alignment to image set matching problems. The correspondence between image sets of different poses, illuminations, and identities can be established effectively by our approach.

Nonlinear model identification and spectral submanifolds for multi-degree-of-freedom mechanical vibrations

NASA Astrophysics Data System (ADS)

Szalai, Robert; Ehrhardt, David; Haller, George

2017-06-01

In a nonlinear oscillatory system, spectral submanifolds (SSMs) are the smoothest invariant manifolds tangent to linear modal subspaces of an equilibrium. Amplitude-frequency plots of the dynamics on SSMs provide the classic backbone curves sought in experimental nonlinear model identification. We develop here, a methodology to compute analytically both the shape of SSMs and their corresponding backbone curves from a data-assimilating model fitted to experimental vibration signals. This model identification utilizes Taken's delay-embedding theorem, as well as a least square fit to the Taylor expansion of the sampling map associated with that embedding. The SSMs are then constructed for the sampling map using the parametrization method for invariant manifolds, which assumes that the manifold is an embedding of, rather than a graph over, a spectral subspace. Using examples of both synthetic and real experimental data, we demonstrate that this approach reproduces backbone curves with high accuracy.

The Effective Dynamics of the Volume Preserving Mean Curvature Flow

NASA Astrophysics Data System (ADS)

Chenn, Ilias; Fournodavlos, G.; Sigal, I. M.

2018-04-01

We consider the dynamics of small closed submanifolds (`bubbles') under the volume preserving mean curvature flow. We construct a map from (n+1 )-dimensional Euclidean space into a given (n+1 )-dimensional Riemannian manifold which characterizes the existence, stability and dynamics of constant mean curvature submanifolds. This is done in terms of a reduced area function on the Euclidean space, which is given constructively and can be computed perturbatively. This allows us to derive adiabatic and effective dynamics of the bubbles. The results can be mapped by rescaling to the dynamics of fixed size bubbles in almost Euclidean Riemannian manifolds.

Fiber-connected, indefinite Morse 2-functions on connected n-manifolds

PubMed Central

Gay, David T.; Kirby, Robion C.

2011-01-01

We discuss generic smooth maps from smooth manifolds to smooth surfaces, which we call “Morse 2-functions,” and homotopies between such maps. The two central issues are to keep the fibers connected, in which case the Morse 2-function is “fiber-connected,” and to avoid local extrema over one-dimensional submanifolds of the range, in which case the Morse 2-function is “indefinite.” This is foundational work for the long-range goal of defining smooth invariants from Morse 2-functions using tools analogous to classical Morse homology and Cerf theory. PMID:21518894

Natural differential operations on manifolds: an algebraic approach

NASA Astrophysics Data System (ADS)

Katsylo, P. I.; Timashev, D. A.

2008-10-01

Natural algebraic differential operations on geometric quantities on smooth manifolds are considered. A method for the investigation and classification of such operations is described, the method of IT-reduction. With it the investigation of natural operations reduces to the analysis of rational maps between k-jet spaces, which are equivariant with respect to certain algebraic groups. On the basis of the method of IT-reduction a finite generation theorem is proved: for tensor bundles \\mathscr{V},\\mathscr{W}\\to M all the natural differential operations D\\colon\\Gamma(\\mathscr{V})\\to\\Gamma(\\mathscr{W}) of degree at most d can be algebraically constructed from some finite set of such operations. Conceptual proofs of known results on the classification of natural linear operations on arbitrary and symplectic manifolds are presented. A non-existence theorem is proved for natural deformation quantizations on Poisson manifolds and symplectic manifolds.Bibliography: 21 titles.

Salient object detection: manifold-based similarity adaptation approach

NASA Astrophysics Data System (ADS)

Zhou, Jingbo; Ren, Yongfeng; Yan, Yunyang; Gao, Shangbing

2014-11-01

A saliency detection algorithm based on manifold-based similarity adaptation is proposed. The proposed algorithm is divided into three steps. First, we segment an input image into superpixels, which are represented as the nodes in a graph. Second, a new similarity measurement is used in the proposed algorithm. The weight matrix of the graph, which indicates the similarities between the nodes, uses a similarity-based method. It also captures the manifold structure of the image patches, in which the graph edges are determined in a data adaptive manner in terms of both similarity and manifold structure. Then, we use local reconstruction method as a diffusion method to obtain the saliency maps. The objective function in the proposed method is based on local reconstruction, with which estimated weights capture the manifold structure. Experiments on four bench-mark databases demonstrate the accuracy and robustness of the proposed method.

Reconstruction of phase maps from the configuration of phase singularities in two-dimensional manifolds.

PubMed

Herlin, Antoine; Jacquemet, Vincent

2012-05-01

Phase singularity analysis provides a quantitative description of spiral wave patterns observed in chemical or biological excitable media. The configuration of phase singularities (locations and directions of rotation) is easily derived from phase maps in two-dimensional manifolds. The question arises whether one can construct a phase map with a given configuration of phase singularities. The existence of such a phase map is guaranteed provided that the phase singularity configuration satisfies a certain constraint associated with the topology of the supporting medium. This paper presents a constructive mathematical approach to numerically solve this problem in the plane and on the sphere as well as in more general geometries relevant to atrial anatomy including holes and a septal wall. This tool can notably be used to create initial conditions with a controllable spiral wave configuration for cardiac propagation models and thus help in the design of computer experiments in atrial electrophysiology.

Hippocampus Segmentation Based on Local Linear Mapping

PubMed Central

Pang, Shumao; Jiang, Jun; Lu, Zhentai; Li, Xueli; Yang, Wei; Huang, Meiyan; Zhang, Yu; Feng, Yanqiu; Huang, Wenhua; Feng, Qianjin

2017-01-01

We propose local linear mapping (LLM), a novel fusion framework for distance field (DF) to perform automatic hippocampus segmentation. A k-means cluster method is propose for constructing magnetic resonance (MR) and DF dictionaries. In LLM, we assume that the MR and DF samples are located on two nonlinear manifolds and the mapping from the MR manifold to the DF manifold is differentiable and locally linear. We combine the MR dictionary using local linear representation to present the test sample, and combine the DF dictionary using the corresponding coefficients derived from local linear representation procedure to predict the DF of the test sample. We then merge the overlapped predicted DF patch to obtain the DF value of each point in the test image via a confidence-based weighted average method. This approach enabled us to estimate the label of the test image according to the predicted DF. The proposed method was evaluated on brain images of 35 subjects obtained from SATA dataset. Results indicate the effectiveness of the proposed method, which yields mean Dice similarity coefficients of 0.8697, 0.8770 and 0.8734 for the left, right and bi-lateral hippocampus, respectively. PMID:28368016

Hippocampus Segmentation Based on Local Linear Mapping.

PubMed

Pang, Shumao; Jiang, Jun; Lu, Zhentai; Li, Xueli; Yang, Wei; Huang, Meiyan; Zhang, Yu; Feng, Yanqiu; Huang, Wenhua; Feng, Qianjin

2017-04-03

We propose local linear mapping (LLM), a novel fusion framework for distance field (DF) to perform automatic hippocampus segmentation. A k-means cluster method is propose for constructing magnetic resonance (MR) and DF dictionaries. In LLM, we assume that the MR and DF samples are located on two nonlinear manifolds and the mapping from the MR manifold to the DF manifold is differentiable and locally linear. We combine the MR dictionary using local linear representation to present the test sample, and combine the DF dictionary using the corresponding coefficients derived from local linear representation procedure to predict the DF of the test sample. We then merge the overlapped predicted DF patch to obtain the DF value of each point in the test image via a confidence-based weighted average method. This approach enabled us to estimate the label of the test image according to the predicted DF. The proposed method was evaluated on brain images of 35 subjects obtained from SATA dataset. Results indicate the effectiveness of the proposed method, which yields mean Dice similarity coefficients of 0.8697, 0.8770 and 0.8734 for the left, right and bi-lateral hippocampus, respectively.

Hippocampus Segmentation Based on Local Linear Mapping

NASA Astrophysics Data System (ADS)

Pang, Shumao; Jiang, Jun; Lu, Zhentai; Li, Xueli; Yang, Wei; Huang, Meiyan; Zhang, Yu; Feng, Yanqiu; Huang, Wenhua; Feng, Qianjin

2017-04-01

We propose local linear mapping (LLM), a novel fusion framework for distance field (DF) to perform automatic hippocampus segmentation. A k-means cluster method is propose for constructing magnetic resonance (MR) and DF dictionaries. In LLM, we assume that the MR and DF samples are located on two nonlinear manifolds and the mapping from the MR manifold to the DF manifold is differentiable and locally linear. We combine the MR dictionary using local linear representation to present the test sample, and combine the DF dictionary using the corresponding coefficients derived from local linear representation procedure to predict the DF of the test sample. We then merge the overlapped predicted DF patch to obtain the DF value of each point in the test image via a confidence-based weighted average method. This approach enabled us to estimate the label of the test image according to the predicted DF. The proposed method was evaluated on brain images of 35 subjects obtained from SATA dataset. Results indicate the effectiveness of the proposed method, which yields mean Dice similarity coefficients of 0.8697, 0.8770 and 0.8734 for the left, right and bi-lateral hippocampus, respectively.

Battery Vent Mechanism And Method

DOEpatents

Ching, Larry K. W.

2000-02-15

Disclosed herein is a venting mechanism for a battery. The venting mechanism includes a battery vent structure which is located on the battery cover and may be integrally formed therewith. The venting mechanism includes an opening extending through the battery cover such that the opening communicates with a plurality of battery cells located within the battery case. The venting mechanism also includes a vent manifold which attaches to the battery vent structure. The vent manifold includes a first opening which communicates with the battery vent structure opening and second and third openings which allow the vent manifold to be connected to two separate conduits. In this manner, a plurality of batteries may be interconnected for venting purposes, thus eliminating the need to provide separate vent lines for each battery. The vent manifold may be attached to the battery vent structure by a spin-welding technique. To facilitate this technique, the vent manifold may be provided with a flange portion which fits into a corresponding groove portion on the battery vent structure. The vent manifold includes an internal chamber which is large enough to completely house a conventional battery flame arrester and overpressure safety valve. In this manner, the vent manifold, when installed, lessens the likelihood of tampering with the flame arrester and safety valve.

Battery venting system and method

DOEpatents

Casale, T.J.; Ching, L.K.W.; Baer, J.T.; Swan, D.H.

1999-01-05

Disclosed herein is a venting mechanism for a battery. The venting mechanism includes a battery vent structure which is located on the battery cover and may be integrally formed therewith. The venting mechanism includes an opening extending through the battery cover such that the opening communicates with a plurality of battery cells located within the battery case. The venting mechanism also includes a vent manifold which attaches to the battery vent structure. The vent manifold includes a first opening which communicates with the battery vent structure opening and second and third openings which allow the vent manifold to be connected to two separate conduits. In this manner, a plurality of batteries may be interconnected for venting purposes, thus eliminating the need to provide separate vent lines for each battery. The vent manifold may be attached to the battery vent structure by a spin-welding technique. To facilitate this technique, the vent manifold may be provided with a flange portion which fits into a corresponding groove portion on the battery vent structure. The vent manifold includes an internal chamber which is large enough to completely house a conventional battery flame arrester and overpressure safety valve. In this manner, the vent manifold, when installed, lessens the likelihood of tampering with the flame arrester and safety valve. 8 figs.

Battery venting system and method

DOEpatents

Casale, Thomas J.; Ching, Larry K. W.; Baer, Jose T.; Swan, David H.

1999-01-05

Disclosed herein is a venting mechanism for a battery. The venting mechanism includes a battery vent structure which is located on the battery cover and may be integrally formed therewith. The venting mechanism includes an opening extending through the battery cover such that the opening communicates with a plurality of battery cells located within the battery case. The venting mechanism also includes a vent manifold which attaches to the battery vent structure. The vent manifold includes a first opening which communicates with the battery vent structure opening and second and third openings which allow the vent manifold to be connected to two separate conduits. In this manner, a plurality of batteries may be interconnected for venting purposes, thus eliminating the need to provide separate vent lines for each battery. The vent manifold may be attached to the battery vent structure by a spin-welding technique. To facilitate this technique, the vent manifold may be provided with a flange portion which fits into a corresponding groove portion on the battery vent structure. The vent manifold includes an internal chamber which is large enough to completely house a conventional battery flame arrester and overpressure safety valve. In this manner, the vent manifold, when installed, lessens the likelihood of tampering with the flame arrester and safety valve.

Symplectic homoclinic tangles of the ideal separatrix of the DIII-D from type I ELMs

NASA Astrophysics Data System (ADS)

Punjabi, Alkesh; Ali, Halima

2012-10-01

The ideal separatrix of the divertor tokamaks is a degenerate manifold where both the stable and unstable manifolds coincide. Non-axisymmetric magnetic perturbations remove the degeneracy; and split the separatrix manifold. This creates an extremely complex topological structure, called homoclinic tangles. The unstable manifold intersects the stable manifold and creates alternating inner and outer lobes at successive homoclinic points. The Hamiltonian system must preserve the symplectic topological invariance, and this controls the size and radial extent of the lobes. Very recently, lobes near the X-point have been experimentally observed in MAST [A. Kirk et al, PRL 108, 255003 (2012)]. We have used the DIII-D map [A. Punjabi, NF 49, 115020 (2009)] to calculate symplectic homoclinic tangles of the ideal separatrix of the DIII-D from the type I ELMs represented by the peeling-ballooning modes (m,n)=(30,10)+(40,10). The DIII-D map is symplectic, accurate, and is in natural canonical coordinates which are invertible to physical coordinates [A. Punjabi and H. Ali, POP 15, 122502 (2008)]. To our knowledge, we are the first to symplectically calculate these tangles in physical space. Homoclinic tangles of separatrix can cause radial displacement of mobile passing electrons and create sheared radial electric fields and currents, resulting in radial flows, drifts, differential spinning, and reduction in turbulence, and other effects. This work is supported by the grants DE-FG02-01ER54624 and DE-FG02-04ER54793.

Broad Search for Unstable Resonant Orbits in the Planar Circular Restricted Three-Body Problem

NASA Technical Reports Server (NTRS)

Anderson, Rodney L.; Campagnola, Stefano; Lantoine, Gregory

2013-01-01

Unstable resonant orbits in the circular restricted three-body problem have increasingly been used for trajectory design using optimization and invariant manifold techniques.In this study, several methods for computing these unstable resonant orbits are explored including flyby maps, continuation from two-body models, and grid searches. Families of orbits are computed focusing on the Jupiter-Europa system, and their characteristics are explored. Different parameters such as period and stability are examined for each set of resonantor bits, and the continuation of several specific orbits is explored in more detail.

Application of remote sensing, GIS and MCA techniques for delineating groundwater prospect zones in Kashipur block, Purulia district, West Bengal

NASA Astrophysics Data System (ADS)

Nag, S. K.; Kundu, Anindita

2018-03-01

Demand of groundwater resources has increased manifold with population expansion as well as with the advent of modern civilization. Assessment, planning and management of groundwater resource are becoming crucial and extremely urgent in recent time. The study area belongs to Kashipur block, Purulia district, West Bengal. The area is characterized with dry climate and hard rock terrain. The objective of this study is to delineate groundwater potential zone for the assessment of groundwater availability using remote sensing, GIS and MCA techniques. Different thematic layers such as hydrogeomorphology, slope and lineament density maps have been transformed to raster data in TNT mips pro2012. To assign weights and ranks to different input factor maps, multi-influencing factor (MIF) technique has been used. The weights assigned to each factor have been computed statistically. Weighted index overlay modeling technique was used to develop a groundwater potential zone map with three weighted and scored parameters. Finally, the study area has been categorized into four distinct groundwater potential zones—excellent 1.5% (6.45 sq. km), good 53% (227.9 sq. km), moderate 45% (193.5 sq. km.) and poor 0.5% (2.15 sq. km). The outcome of the present study will help local authorities, researchers, decision makers and planners in formulating proper planning and management of groundwater resources in different hydrogeological situations.

Relativistic collisions as Yang-Baxter maps

NASA Astrophysics Data System (ADS)

Kouloukas, Theodoros E.

2017-10-01

We prove that one-dimensional elastic relativistic collisions satisfy the set-theoretical Yang-Baxter equation. The corresponding collision maps are symplectic and admit a Lax representation. Furthermore, they can be considered as reductions of a higher dimensional integrable Yang-Baxter map on an invariant manifold. In this framework, we study the integrability of transfer maps that represent particular periodic sequences of collisions.

Chern-Simons theory and S-duality

NASA Astrophysics Data System (ADS)

Dimofte, Tudor; Gukov, Sergei

2013-05-01

We study S-dualities in analytically continued SL(2) Chern-Simons theory on a 3-manifold M. By realizing Chern-Simons theory via a compactification of a 6d five-brane theory on M, various objects and symmetries in Chern-Simons theory become related to objects and operations in dual 2d, 3d, and 4d theories. For example, the space of flat SL(2 , {C} ) connections on M is identified with the space of supersymmetric vacua in a dual 3d gauge theory. The hidden symmetry [InlineMediaObject not available: see fulltext.] of SL(2) Chern-Simons theory can be identified as the S-duality transformation of {N}=4 super-Yang-Mills theory (obtained by compactifying the five-brane theory on a torus); whereas the mapping class group action in Chern-Simons theory on a three-manifold M with boundary C is realized as S-duality in 4d {N}=2 super-Yang-Mills theory associated with the Riemann surface C. We illustrate these symmetries by considering simple examples of 3-manifolds that include knot complements and punctured torus bundles, on the one hand, and mapping cylinders associated with mapping class group transformations, on the other. A generalization of mapping class group actions further allows us to study the transformations between several distinguished coordinate systems on the phase space of Chern-Simons theory, the SL(2) Hitchin moduli space.

Kernel Manifold Alignment for Domain Adaptation.

PubMed

Tuia, Devis; Camps-Valls, Gustau

2016-01-01

The wealth of sensory data coming from different modalities has opened numerous opportunities for data analysis. The data are of increasing volume, complexity and dimensionality, thus calling for new methodological innovations towards multimodal data processing. However, multimodal architectures must rely on models able to adapt to changes in the data distribution. Differences in the density functions can be due to changes in acquisition conditions (pose, illumination), sensors characteristics (number of channels, resolution) or different views (e.g. street level vs. aerial views of a same building). We call these different acquisition modes domains, and refer to the adaptation problem as domain adaptation. In this paper, instead of adapting the trained models themselves, we alternatively focus on finding mappings of the data sources into a common, semantically meaningful, representation domain. This field of manifold alignment extends traditional techniques in statistics such as canonical correlation analysis (CCA) to deal with nonlinear adaptation and possibly non-corresponding data pairs between the domains. We introduce a kernel method for manifold alignment (KEMA) that can match an arbitrary number of data sources without needing corresponding pairs, just few labeled examples in all domains. KEMA has interesting properties: 1) it generalizes other manifold alignment methods, 2) it can align manifolds of very different complexities, performing a discriminative alignment preserving each manifold inner structure, 3) it can define a domain-specific metric to cope with multimodal specificities, 4) it can align data spaces of different dimensionality, 5) it is robust to strong nonlinear feature deformations, and 6) it is closed-form invertible, which allows transfer across-domains and data synthesis. To authors' knowledge this is the first method addressing all these important issues at once. We also present a reduced-rank version of KEMA for computational efficiency, and discuss the generalization performance of KEMA under Rademacher principles of stability. Aligning multimodal data with KEMA reports outstanding benefits when used as a data pre-conditioner step in the standard data analysis processing chain. KEMA exhibits very good performance over competing methods in synthetic controlled examples, visual object recognition and recognition of facial expressions tasks. KEMA is especially well-suited to deal with high-dimensional problems, such as images and videos, and under complicated distortions, twists and warpings of the data manifolds. A fully functional toolbox is available at https://github.com/dtuia/KEMA.git.

Reconstructing 3D Face Model with Associated Expression Deformation from a Single Face Image via Constructing a Low-Dimensional Expression Deformation Manifold.

PubMed

Wang, Shu-Fan; Lai, Shang-Hong

2011-10-01

Facial expression modeling is central to facial expression recognition and expression synthesis for facial animation. In this work, we propose a manifold-based 3D face reconstruction approach to estimating the 3D face model and the associated expression deformation from a single face image. With the proposed robust weighted feature map (RWF), we can obtain the dense correspondences between 3D face models and build a nonlinear 3D expression manifold from a large set of 3D facial expression models. Then a Gaussian mixture model in this manifold is learned to represent the distribution of expression deformation. By combining the merits of morphable neutral face model and the low-dimensional expression manifold, a novel algorithm is developed to reconstruct the 3D face geometry as well as the facial deformation from a single face image in an energy minimization framework. Experimental results on simulated and real images are shown to validate the effectiveness and accuracy of the proposed algorithm.

High-Dimensional Intrinsic Interpolation Using Gaussian Process Regression and Diffusion Maps

DOE PAGES

Thimmisetty, Charanraj A.; Ghanem, Roger G.; White, Joshua A.; ...

2017-10-10

This article considers the challenging task of estimating geologic properties of interest using a suite of proxy measurements. The current work recast this task as a manifold learning problem. In this process, this article introduces a novel regression procedure for intrinsic variables constrained onto a manifold embedded in an ambient space. The procedure is meant to sharpen high-dimensional interpolation by inferring non-linear correlations from the data being interpolated. The proposed approach augments manifold learning procedures with a Gaussian process regression. It first identifies, using diffusion maps, a low-dimensional manifold embedded in an ambient high-dimensional space associated with the data. Itmore » relies on the diffusion distance associated with this construction to define a distance function with which the data model is equipped. This distance metric function is then used to compute the correlation structure of a Gaussian process that describes the statistical dependence of quantities of interest in the high-dimensional ambient space. The proposed method is applicable to arbitrarily high-dimensional data sets. Here, it is applied to subsurface characterization using a suite of well log measurements. The predictions obtained in original, principal component, and diffusion space are compared using both qualitative and quantitative metrics. Considerable improvement in the prediction of the geological structural properties is observed with the proposed method.« less

High-Dimensional Intrinsic Interpolation Using Gaussian Process Regression and Diffusion Maps

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thimmisetty, Charanraj A.; Ghanem, Roger G.; White, Joshua A.

This article considers the challenging task of estimating geologic properties of interest using a suite of proxy measurements. The current work recast this task as a manifold learning problem. In this process, this article introduces a novel regression procedure for intrinsic variables constrained onto a manifold embedded in an ambient space. The procedure is meant to sharpen high-dimensional interpolation by inferring non-linear correlations from the data being interpolated. The proposed approach augments manifold learning procedures with a Gaussian process regression. It first identifies, using diffusion maps, a low-dimensional manifold embedded in an ambient high-dimensional space associated with the data. Itmore » relies on the diffusion distance associated with this construction to define a distance function with which the data model is equipped. This distance metric function is then used to compute the correlation structure of a Gaussian process that describes the statistical dependence of quantities of interest in the high-dimensional ambient space. The proposed method is applicable to arbitrarily high-dimensional data sets. Here, it is applied to subsurface characterization using a suite of well log measurements. The predictions obtained in original, principal component, and diffusion space are compared using both qualitative and quantitative metrics. Considerable improvement in the prediction of the geological structural properties is observed with the proposed method.« less

Interactive Design and Visualization of Branched Covering Spaces.

PubMed

Roy, Lawrence; Kumar, Prashant; Golbabaei, Sanaz; Zhang, Yue; Zhang, Eugene

2018-01-01

Branched covering spaces are a mathematical concept which originates from complex analysis and topology and has applications in tensor field topology and geometry remeshing. Given a manifold surface and an -way rotational symmetry field, a branched covering space is a manifold surface that has an -to-1 map to the original surface except at the ramification points, which correspond to the singularities in the rotational symmetry field. Understanding the notion and mathematical properties of branched covering spaces is important to researchers in tensor field visualization and geometry processing, and their application areas. In this paper, we provide a framework to interactively design and visualize the branched covering space (BCS) of an input mesh surface and a rotational symmetry field defined on it. In our framework, the user can visualize not only the BCSs but also their construction process. In addition, our system allows the user to design the geometric realization of the BCS using mesh deformation techniques as well as connecting tubes. This enables the user to verify important facts about BCSs such as that they are manifold surfaces around singularities, as well as the Riemann-Hurwitz formula which relates the Euler characteristic of the BCS to that of the original mesh. Our system is evaluated by student researchers in scientific visualization and geometry processing as well as faculty members in mathematics at our university who teach topology. We include their evaluations and feedback in the paper.

Topological analysis of group fragmentation in multiagent systems

NASA Astrophysics Data System (ADS)

DeLellis, Pietro; Porfiri, Maurizio; Bollt, Erik M.

2013-02-01

In social animals, the presence of conflicts of interest or multiple leaders can promote the emergence of two or more subgroups. Such subgroups are easily recognizable by human observers, yet a quantitative and objective measure of group fragmentation is currently lacking. In this paper, we explore the feasibility of detecting group fragmentation by embedding the raw data from the individuals' motions on a low-dimensional manifold and analyzing the topological features of this manifold. To perform the embedding, we employ the isomap algorithm, which is a data-driven machine learning tool extensively used in computer vision. We implement this procedure on a data set generated by a modified à la Vicsek model, where agents are partitioned into two or more subsets and an independent leader is assigned to each subset. The dimensionality of the embedding manifold is shown to be a measure of the number of emerging subgroups in the selected observation window and a cluster analysis is proposed to aid the interpretation of these findings. To explore the feasibility of using this approach to characterize group fragmentation in real time and thus reduce the computational cost in data processing and storage, we propose an interpolation method based on an inverse mapping from the embedding space to the original space. The effectiveness of the interpolation technique is illustrated on a test-bed example with potential impact on the regulation of collective behavior of animal groups using robotic stimuli.

Inverse Problems for Semilinear Wave Equations on Lorentzian Manifolds

NASA Astrophysics Data System (ADS)

Lassas, Matti; Uhlmann, Gunther; Wang, Yiran

2018-06-01

We consider inverse problems in space-time ( M, g), a 4-dimensional Lorentzian manifold. For semilinear wave equations {\\square_g u + H(x, u) = f}, where {\\square_g} denotes the usual Laplace-Beltrami operator, we prove that the source-to-solution map {L: f → u|_V}, where V is a neighborhood of a time-like geodesic {μ}, determines the topological, differentiable structure and the conformal class of the metric of the space-time in the maximal set, where waves can propagate from {μ} and return back. Moreover, on a given space-time ( M, g), the source-to-solution map determines some coefficients of the Taylor expansion of H in u.

Analysis of Preferred Directions in Phase Space for Tidal Measurements at Europa

NASA Astrophysics Data System (ADS)

Boone, D.; Scheeres, D. J.

2012-12-01

The NASA Jupiter Europa Orbiter mission requires a circular, near-polar orbit to measure Europa's Love numbers, geophysical coefficients which give insight into whether a liquid ocean exists. This type of orbit about planetary satellites is known to be unstable. The effects of Jupiter's tidal gravity are seen in changes in Europa's gravity field and surface deformation, which are sensed through doppler tracking over time and altimetry measurements respectively. These two measurement types separately determine the h and k Love numbers, a combination of which bounds how thick the ice shell of Europa is and whether liquid water is present. This work shows how the properties of an unstable periodic orbit about Europa generate preferred measurement directions in position and velocity phase space for the orbit determination process. We generate an error covariance over seven days for the orbiter state and science parameters using a periodic orbit and then disperse the orbit initial conditions in a Monte Carlo simulation according to this covariance. The dispersed orbits are shown to have a bias toward longer lifetimes and we discuss this as an effect of the stable and unstable manifolds of the periodic orbit. Using an epoch formulation of a square-root information filter, measurements aligned with the unstable manifold mapped back in time add more information to the orbit determination process than measurements aligned with the stable manifold. This corresponds to a contraction in the uncertainty of the estimate of the desired parameters, including the Love numbers. We demonstrate this mapping mathematically using a representation of the State Transition Matrix involving its eigenvectors and eigenvalues. Then using the properties of left and right eigenvectors, we show how measurements in the orbit determination process are mapped in time leading to a concentration of information at epoch. We present examples of measurements taken on different time schedules to show the effect of preferred phase space directions in the estimation process. Manifold coordinate decomposition is applied to the orbit initial conditions as well as measurement partials in the filter to show the alignment of each with the stable and unstable manifolds of the periodic orbit. The connection between orbit lifetime and regions of increased information density in phase space is made using the properties of these manifolds. Low altitude, near-polar periodic orbits with these characteristics are discussed along with the estimation results for the Love numbers, orbiter state, and orbit lifetime. Different measurement schedules and the resulting estimation performance are presented along with an analysis of information content for single measurements with respect to manifold alignment. These results allow more sensitive estimation of the tidal Love numbers and may allow measurements to be taken less frequently or compensate for corrupted data arcs. Other measurement types will be mapped in the same way using the State Transition matrix and have increased information density at epoch if aligned with the unstable manifold. In the same way, these results are applicable to planetary satellite orbiters about Enceladus or Dione since they share the governing equations of motion and properties of unstable periodic orbits.

On the Use of CAD-Native Predicates and Geometry in Surface Meshing

NASA Technical Reports Server (NTRS)

Aftosmis, M. J.

1999-01-01

Several paradigms for accessing CAD geometry during surface meshing for CFD are discussed. File translation, inconsistent geometry engines and non-native point construction are all identified as sources of non-robustness. The paper argues in favor of accessing CAD parts and assemblies in their native format, without translation, and for the use of CAD-native predicates and constructors in surface mesh generation. The discussion also emphasizes the importance of examining the computational requirements for exact evaluation of triangulation predicates during surface meshing. The native approach is demonstrated through an algorithm for the generation of closed manifold surface triangulations from CAD geometry. CAD parts and assemblies are used in their native format, and a part's native geometry engine is accessed through a modeler-independent application programming interface (API). In seeking a robust and fully automated procedure, the algorithm is based on a new physical space manifold triangulation technique specially developed to avoid robustness issues associated with poorly conditioned mappings. In addition, this approach avoids the usual ambiguities associated with floating-point predicate evaluation on constructed coordinate geometry in a mapped space. The technique is incremental, so that each new site improves the triangulation by some well defined quality measure. The algorithm terminates after achieving a prespecified measure of mesh quality and produces a triangulation such that no angle is less than a given angle bound, a or greater than pi - 2alpha. This result also sets bounds on the maximum vertex degree, triangle aspect-ratio and maximum stretching rate for the triangulation. In addition to the output triangulations for a variety of CAD parts, the discussion presents related theoretical results which assert the existence of such an angle bound, and demonstrate that maximum bounds of between 25 deg and 30 deg may be achieved in practice.

Automatic Generation of CFD-Ready Surface Triangulations from CAD Geometry

NASA Technical Reports Server (NTRS)

Aftosmis, M. J.; Delanaye, M.; Haimes, R.; Nixon, David (Technical Monitor)

1998-01-01

This paper presents an approach for the generation of closed manifold surface triangulations from CAD geometry. CAD parts and assemblies are used in their native format, without translation, and a part's native geometry engine is accessed through a modeler-independent application programming interface (API). In seeking a robust and fully automated procedure, the algorithm is based on a new physical space manifold triangulation technique which was developed to avoid robustness issues associated with poorly conditioned mappings. In addition, this approach avoids the usual ambiguities associated with floating-point predicate evaluation on constructed coordinate geometry in a mapped space, The technique is incremental, so that each new site improves the triangulation by some well defined quality measure. Sites are inserted using a variety of priority queues to ensure that new insertions will address the worst triangles first, As a result of this strategy, the algorithm will return its 'best' mesh for a given (prespecified) number of sites. Alternatively, the algorithm may be allowed to terminate naturally after achieving a prespecified measure of mesh quality. The resulting triangulations are 'CFD-ready' in that: (1) Edges match the underlying part model to within a specified tolerance. (2) Triangles on disjoint surfaces in close proximity have matching length-scales. (3) The algorithm produces a triangulation such that no angle is less than a given angle bound, alpha, or greater than Pi - 2alpha This result also sets bounds on the maximum vertex degree, triangle aspect-ratio and maximum stretching rate for the triangulation. In addition to tile output triangulations for a variety of CAD parts, tile discussion presents related theoretical results which assert the existence of such all angle bound, and demonstrate that maximum bounds of between 25 deg and 30 deg may be achieved in practice.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sehgal, Ray M.; Maroudas, Dimitrios, E-mail: maroudas@ecs.umass.edu, E-mail: ford@ecs.umass.edu; Ford, David M., E-mail: maroudas@ecs.umass.edu, E-mail: ford@ecs.umass.edu

We have developed a coarse-grained description of the phase behavior of the isolated 38-atom Lennard-Jones cluster (LJ{sub 38}). The model captures both the solid-solid polymorphic transitions at low temperatures and the complex cluster breakup and melting transitions at higher temperatures. For this coarse model development, we employ the manifold learning technique of diffusion mapping. The outcome of the diffusion mapping analysis over a broad temperature range indicates that two order parameters are sufficient to describe the cluster's phase behavior; we have chosen two such appropriate order parameters that are metrics of condensation and overall crystallinity. In this well-justified coarse-variable space,more » we calculate the cluster's free energy landscape (FEL) as a function of temperature, employing Monte Carlo umbrella sampling. These FELs are used to quantify the phase behavior and onsets of phase transitions of the LJ{sub 38} cluster.« less

Optimization of Insertion Cost for Transfer Trajectories to Libration Point Orbits

NASA Technical Reports Server (NTRS)

Howell, K. C.; Wilson, R. S.; Lo, M. W.

1999-01-01

The objective of this work is the development of efficient techniques to optimize the cost associated with transfer trajectories to libration point orbits in the Sun-Earth-Moon four body problem, that may include lunar gravity assists. Initially, dynamical systems theory is used to determine invariant manifolds associated with the desired libration point orbit. These manifolds are employed to produce an initial approximation to the transfer trajectory. Specific trajectory requirements such as, transfer injection constraints, inclusion of phasing loops, and targeting of a specified state on the manifold are then incorporated into the design of the transfer trajectory. A two level differential corrections process is used to produce a fully continuous trajectory that satisfies the design constraints, and includes appropriate lunar and solar gravitational models. Based on this methodology, and using the manifold structure from dynamical systems theory, a technique is presented to optimize the cost associated with insertion onto a specified libration point orbit.

Manifold Embedding and Semantic Segmentation for Intraoperative Guidance With Hyperspectral Brain Imaging.

PubMed

Ravi, Daniele; Fabelo, Himar; Callic, Gustavo Marrero; Yang, Guang-Zhong

2017-09-01

Recent advances in hyperspectral imaging have made it a promising solution for intra-operative tissue characterization, with the advantages of being non-contact, non-ionizing, and non-invasive. Working with hyperspectral images in vivo, however, is not straightforward as the high dimensionality of the data makes real-time processing challenging. In this paper, a novel dimensionality reduction scheme and a new processing pipeline are introduced to obtain a detailed tumor classification map for intra-operative margin definition during brain surgery. However, existing approaches to dimensionality reduction based on manifold embedding can be time consuming and may not guarantee a consistent result, thus hindering final tissue classification. The proposed framework aims to overcome these problems through a process divided into two steps: dimensionality reduction based on an extension of the T-distributed stochastic neighbor approach is first performed and then a semantic segmentation technique is applied to the embedded results by using a Semantic Texton Forest for tissue classification. Detailed in vivo validation of the proposed method has been performed to demonstrate the potential clinical value of the system.

Infinitesimal moduli of G2 holonomy manifolds with instanton bundles

NASA Astrophysics Data System (ADS)

de la Ossa, Xenia; Larfors, Magdalena; Svanes, Eirik E.

2016-11-01

We describe the infinitesimal moduli space of pairs ( Y, V) where Y is a manifold with G 2 holonomy, and V is a vector bundle on Y with an instanton connection. These structures arise in connection to the moduli space of heterotic string compactifications on compact and non-compact seven dimensional spaces, e.g. domain walls. Employing the canonical G 2 cohomology developed by Reyes-Carrión and Fernández and Ugarte, we show that the moduli space decomposes into the sum of the bundle moduli {H}_{{overset{ěe }{d}}_A}^1(Y,End(V)) plus the moduli of the G 2 structure preserving the instanton condition. The latter piece is contained in {H}_{overset{ěe }{d}θ}^1(Y,TY) , and is given by the kernel of a map overset{ěe }{F} which generalises the concept of the Atiyah map for holomorphic bundles on complex manifolds to the case at hand. In fact, the map overset{ěe }{F} is given in terms of the curvature of the bundle and maps {H}_{overset{ěe }{d}θ}^1(Y,TY) into {H}_{{overset{ěe }{d}}_A}^2(Y,End(V)) , and moreover can be used to define a cohomology on an extension bundle of TY by End( V). We comment further on the resemblance with the holomorphic Atiyah algebroid and connect the story to physics, in particular to heterotic compactifications on ( Y, V) when α' = 0.

The response analysis of fractional-order stochastic system via generalized cell mapping method.

PubMed

Wang, Liang; Xue, Lili; Sun, Chunyan; Yue, Xiaole; Xu, Wei

2018-01-01

This paper is concerned with the response of a fractional-order stochastic system. The short memory principle is introduced to ensure that the response of the system is a Markov process. The generalized cell mapping method is applied to display the global dynamics of the noise-free system, such as attractors, basins of attraction, basin boundary, saddle, and invariant manifolds. The stochastic generalized cell mapping method is employed to obtain the evolutionary process of probability density functions of the response. The fractional-order ϕ 6 oscillator and the fractional-order smooth and discontinuous oscillator are taken as examples to give the implementations of our strategies. Studies have shown that the evolutionary direction of the probability density function of the fractional-order stochastic system is consistent with the unstable manifold. The effectiveness of the method is confirmed using Monte Carlo results.

On the Inverse Mapping of the Formal Symplectic Groupoid of a Deformation Quantization

NASA Astrophysics Data System (ADS)

Karabegov, Alexander V.

2004-10-01

To each natural star product on a Poisson manifold $M$ we associate an antisymplectic involutive automorphism of the formal neighborhood of the zero section of the cotangent bundle of $M$. If $M$ is symplectic, this mapping is shown to be the inverse mapping of the formal symplectic groupoid of the star product. The construction of the inverse mapping involves modular automorphisms of the star product.

Bäcklund transformations for harmonic maps in two independent variables

NASA Astrophysics Data System (ADS)

Başkal, S.; Eriş, A.

1994-06-01

Bäcklund transformations for harmonic maps are described as the action of the structure group on harmonic one-forms or as gauge transformations of the soliton connection constructed via embedding the configuration manifold into a flat space. As an illustration, Bäcklund transformations for maps from M 2 to the Poincaré upper half-plane and for maps determining stationary vacuum gravitational fields with axial symmetry are obtained.

A THEOREM OF BOURGIN-YANG TYPE FOR \\mathbb{Z}_p^n-ACTION

NASA Astrophysics Data System (ADS)

Volovikov, A. Yu

1993-02-01

A theorem of Bourgin-Yang type is proved for maps of spaces with \\mathbb{Z}_p^n-action into manifolds. The results are applied to the problem of Knaster for maps of spheres into the line and the plane.Bibliography: 44 titles.

A comparative study of two prediction models for brain tumor progression

NASA Astrophysics Data System (ADS)

Zhou, Deqi; Tran, Loc; Wang, Jihong; Li, Jiang

2015-03-01

MR diffusion tensor imaging (DTI) technique together with traditional T1 or T2 weighted MRI scans supplies rich information sources for brain cancer diagnoses. These images form large-scale, high-dimensional data sets. Due to the fact that significant correlations exist among these images, we assume low-dimensional geometry data structures (manifolds) are embedded in the high-dimensional space. Those manifolds might be hidden from radiologists because it is challenging for human experts to interpret high-dimensional data. Identification of the manifold is a critical step for successfully analyzing multimodal MR images. We have developed various manifold learning algorithms (Tran et al. 2011; Tran et al. 2013) for medical image analysis. This paper presents a comparative study of an incremental manifold learning scheme (Tran. et al. 2013) versus the deep learning model (Hinton et al. 2006) in the application of brain tumor progression prediction. The incremental manifold learning is a variant of manifold learning algorithm to handle large-scale datasets in which a representative subset of original data is sampled first to construct a manifold skeleton and remaining data points are then inserted into the skeleton by following their local geometry. The incremental manifold learning algorithm aims at mitigating the computational burden associated with traditional manifold learning methods for large-scale datasets. Deep learning is a recently developed multilayer perceptron model that has achieved start-of-the-art performances in many applications. A recent technique named "Dropout" can further boost the deep model by preventing weight coadaptation to avoid over-fitting (Hinton et al. 2012). We applied the two models on multiple MRI scans from four brain tumor patients to predict tumor progression and compared the performances of the two models in terms of average prediction accuracy, sensitivity, specificity and precision. The quantitative performance metrics were calculated as average over the four patients. Experimental results show that both the manifold learning and deep neural network models produced better results compared to using raw data and principle component analysis (PCA), and the deep learning model is a better method than manifold learning on this data set. The averaged sensitivity and specificity by deep learning are comparable with these by the manifold learning approach while its precision is considerably higher. This means that the predicted abnormal points by deep learning are more likely to correspond to the actual progression region.

Man-Made Object Extraction from Remote Sensing Imagery by Graph-Based Manifold Ranking

NASA Astrophysics Data System (ADS)

He, Y.; Wang, X.; Hu, X. Y.; Liu, S. H.

2018-04-01

The automatic extraction of man-made objects from remote sensing imagery is useful in many applications. This paper proposes an algorithm for extracting man-made objects automatically by integrating a graph model with the manifold ranking algorithm. Initially, we estimate a priori value of the man-made objects with the use of symmetric and contrast features. The graph model is established to represent the spatial relationships among pre-segmented superpixels, which are used as the graph nodes. Multiple characteristics, namely colour, texture and main direction, are used to compute the weights of the adjacent nodes. Manifold ranking effectively explores the relationships among all the nodes in the feature space as well as initial query assignment; thus, it is applied to generate a ranking map, which indicates the scores of the man-made objects. The man-made objects are then segmented on the basis of the ranking map. Two typical segmentation algorithms are compared with the proposed algorithm. Experimental results show that the proposed algorithm can extract man-made objects with high recognition rate and low omission rate.

Distributed coupling and multi-frequency microwave accelerators

DOEpatents

Tantawi, Sami G.; Li, Zenghai; Borchard, Philipp

2016-07-05

A microwave circuit for a linear accelerator has multiple metallic cell sections, a pair of distribution waveguide manifolds, and a sequence of feed arms connecting the manifolds to the cell sections. The distribution waveguide manifolds are connected to the cell sections so that alternating pairs of cell sections are connected to opposite distribution waveguide manifolds. The distribution waveguide manifolds have concave modifications of their walls opposite the feed arms, and the feed arms have portions of two distinct widths. In some embodiments, the distribution waveguide manifolds are connected to the cell sections by two different types of junctions adapted to allow two frequency operation. The microwave circuit may be manufactured by making two quasi-identical parts, and joining the two parts to form the microwave circuit, thereby allowing for many manufacturing techniques including electron beam welding, and thereby allowing the use of un-annealled copper alloys, and hence greater tolerance to high gradient operation.

Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

NASA Astrophysics Data System (ADS)

Nedialkova, Lilia V.; Amat, Miguel A.; Kevrekidis, Ioannis G.; Hummer, Gerhard

2014-09-01

Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlap with clusters obtained previously by using the backbone dihedral angles as input, with small—but nontrivial—differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space.

Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nedialkova, Lilia V.; Amat, Miguel A.; Kevrekidis, Ioannis G., E-mail: yannis@princeton.edu, E-mail: gerhard.hummer@biophys.mpg.de

Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlapmore » with clusters obtained previously by using the backbone dihedral angles as input, with small—but nontrivial—differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space.« less

Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

PubMed Central

Nedialkova, Lilia V.; Amat, Miguel A.; Kevrekidis, Ioannis G.; Hummer, Gerhard

2014-01-01

Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlap with clusters obtained previously by using the backbone dihedral angles as input, with small—but nontrivial—differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space. PMID:25240340

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Sang Beom; Dsilva, Carmeline J.; Debenedetti, Pablo G., E-mail: pdebene@princeton.edu

Understanding the mechanisms by which proteins fold from disordered amino-acid chains to spatially ordered structures remains an area of active inquiry. Molecular simulations can provide atomistic details of the folding dynamics which complement experimental findings. Conventional order parameters, such as root-mean-square deviation and radius of gyration, provide structural information but fail to capture the underlying dynamics of the protein folding process. It is therefore advantageous to adopt a method that can systematically analyze simulation data to extract relevant structural as well as dynamical information. The nonlinear dimensionality reduction technique known as diffusion maps automatically embeds the high-dimensional folding trajectories inmore » a lower-dimensional space from which one can more easily visualize folding pathways, assuming the data lie approximately on a lower-dimensional manifold. The eigenvectors that parametrize the low-dimensional space, furthermore, are determined systematically, rather than chosen heuristically, as is done with phenomenological order parameters. We demonstrate that diffusion maps can effectively characterize the folding process of a Trp-cage miniprotein. By embedding molecular dynamics simulation trajectories of Trp-cage folding in diffusion maps space, we identify two folding pathways and intermediate structures that are consistent with the previous studies, demonstrating that this technique can be employed as an effective way of analyzing and constructing protein folding pathways from molecular simulations.« less

5D Super Yang-Mills on Y p, q Sasaki-Einstein Manifolds

NASA Astrophysics Data System (ADS)

Qiu, Jian; Zabzine, Maxim

2015-01-01

On any simply connected Sasaki-Einstein five dimensional manifold one can construct a super Yang-Mills theory which preserves at least two supersymmetries. We study the special case of toric Sasaki-Einstein manifolds known as Y p, q manifolds. We use the localisation technique to compute the full perturbative part of the partition function. The full equivariant result is expressed in terms of a certain special function which appears to be a curious generalisation of the triple sine function. As an application of our general result we study the large N behaviour for the case of single hypermultiplet in adjoint representation and we derive the N 3-behaviour in this case.

Generalized Legendre transformations and symmetries of the WDVV equations

NASA Astrophysics Data System (ADS)

Strachan, Ian A. B.; Stedman, Richard

2017-03-01

The Witten-Dijkgraaf-Verlinde-Verlinde (or WDVV) equations, as one would expect from an integrable system, has many symmetries, both continuous and discrete. One class—the so-called Legendre transformations—were introduced by Dubrovin. They are a discrete set of symmetries between the stronger concept of a Frobenius manifold, and are generated by certain flat vector fields. In this paper this construction is generalized to the case where the vector field (called here the Legendre field) is non-flat but satisfies a certain set of defining equations. One application of this more general theory is to generate the induced symmetry between almost-dual Frobenius manifolds whose underlying Frobenius manifolds are related by a Legendre transformation. This also provides a map between rational and trigonometric solutions of the WDVV equations.

Marginal semi-supervised sub-manifold projections with informative constraints for dimensionality reduction and recognition.

PubMed

Zhang, Zhao; Zhao, Mingbo; Chow, Tommy W S

2012-12-01

In this work, sub-manifold projections based semi-supervised dimensionality reduction (DR) problem learning from partial constrained data is discussed. Two semi-supervised DR algorithms termed Marginal Semi-Supervised Sub-Manifold Projections (MS³MP) and orthogonal MS³MP (OMS³MP) are proposed. MS³MP in the singular case is also discussed. We also present the weighted least squares view of MS³MP. Based on specifying the types of neighborhoods with pairwise constraints (PC) and the defined manifold scatters, our methods can preserve the local properties of all points and discriminant structures embedded in the localized PC. The sub-manifolds of different classes can also be separated. In PC guided methods, exploring and selecting the informative constraints is challenging and random constraint subsets significantly affect the performance of algorithms. This paper also introduces an effective technique to select the informative constraints for DR with consistent constraints. The analytic form of the projection axes can be obtained by eigen-decomposition. The connections between this work and other related work are also elaborated. The validity of the proposed constraint selection approach and DR algorithms are evaluated by benchmark problems. Extensive simulations show that our algorithms can deliver promising results over some widely used state-of-the-art semi-supervised DR techniques. Copyright © 2012 Elsevier Ltd. All rights reserved.

Landau-Ginzburg to Calabi-Yau dictionary for D-branes

NASA Astrophysics Data System (ADS)

Aspinwall, Paul S.

2007-08-01

Based on the work by Orlov (e-print arXiv:math.AG/0503632), we give a precise recipe for mapping between B-type D-branes in a Landau-Ginzburg orbifold model (or Gepner model) and the corresponding large radius Calabi-Yau manifold. The D-branes in Landau-Ginzburg theories correspond to matrix factorizations and the D-branes on the Calabi-Yau manifolds are objects in the derived category. We give several examples including branes on quotient singularities associated with weighted projective spaces. We are able to confirm several conjectures and statements in the literature.

Monitoring the performance of a storm water separating manifold with distributed temperature sensing.

PubMed

Langeveld, J G; de Haan, C; Klootwijk, M; Schilperoort, R P S

2012-01-01

Storm water separating manifolds in house connections have been introduced as a cost effective solution to disconnect impervious areas from combined sewers. Such manifolds have been applied by the municipality of Breda, the Netherlands. In order to investigate the performance of the manifolds, a monitoring technique (distributed temperature sensing or DTS) using fiber optic cables has been applied in the sewer system of Breda. This paper describes the application of DTS as a research tool in sewer systems. DTS proves to be a powerful tool to monitor the performance of (parts of) a sewer system in time and space. The research project showed that DTS is capable of monitoring the performance of house connections and identifying locations of inflow of both sewage and storm runoff. The research results show that the performance of storm water separating manifolds varies over time, thus making them unreliable.

The classical dynamic symmetry for the U(1) -Kepler problems

NASA Astrophysics Data System (ADS)

Bouarroudj, Sofiane; Meng, Guowu

2018-01-01

For the Jordan algebra of hermitian matrices of order n ≥ 2, we let X be its submanifold consisting of rank-one semi-positive definite elements. The composition of the cotangent bundle map πX: T∗ X → X with the canonical map X → CP n - 1 (i.e., the map that sends a given hermitian matrix to its column space), pulls back the Kähler form of the Fubini-Study metric on CP n - 1 to a real closed differential two-form ωK on T∗ X. Let ωX be the canonical symplectic form on T∗ X and μ a real number. A standard fact says that ωμ ≔ωX + 2 μωK turns T∗ X into a symplectic manifold, hence a Poisson manifold with Poisson bracket {,}μ. In this article we exhibit a Poisson realization of the simple real Lie algebra su(n , n) on the Poisson manifold (T∗ X ,{,}μ) , i.e., a Lie algebra homomorphism from su(n , n) to (C∞(T∗ X , R) ,{,}μ). Consequently one obtains the Laplace-Runge-Lenz vector for the classical U(1) -Kepler problem of level n and magnetic charge μ. Since the McIntosh-Cisneros-Zwanziger-Kepler problems (MICZ-Kepler Problems) are the U(1) -Kepler problems of level 2, the work presented here is a direct generalization of the work by A. Barut and G. Bornzin (1971) on the classical dynamic symmetry for the MICZ-Kepler problems.

A novel manifold-manifold distance index applied to looseness state assessment of viscoelastic sandwich structures

NASA Astrophysics Data System (ADS)

Sun, Chuang; Zhang, Zhousuo; Guo, Ting; Luo, Xue; Qu, Jinxiu; Zhang, Chenxuan; Cheng, Wei; Li, Bing

2014-06-01

Viscoelastic sandwich structures (VSS) are widely used in mechanical equipment; their state assessment is necessary to detect structural states and to keep equipment running with high reliability. This paper proposes a novel manifold-manifold distance-based assessment (M2DBA) method for assessing the looseness state in VSSs. In the M2DBA method, a manifold-manifold distance is viewed as a health index. To design the index, response signals from the structure are firstly acquired by condition monitoring technology and a Hankel matrix is constructed by using the response signals to describe state patterns of the VSS. Thereafter, a subspace analysis method, that is, principal component analysis (PCA), is performed to extract the condition subspace hidden in the Hankel matrix. From the subspace, pattern changes in dynamic structural properties are characterized. Further, a Grassmann manifold (GM) is formed by organizing a set of subspaces. The manifold is mapped to a reproducing kernel Hilbert space (RKHS), where support vector data description (SVDD) is used to model the manifold as a hypersphere. Finally, a health index is defined as the cosine of the angle between the hypersphere centers corresponding to the structural baseline state and the looseness state. The defined health index contains similarity information existing in the two structural states, so structural looseness states can be effectively identified. Moreover, the health index is derived by analysis of the global properties of subspace sets, which is different from traditional subspace analysis methods. The effectiveness of the health index for state assessment is validated by test data collected from a VSS subjected to different degrees of looseness. The results show that the health index is a very effective metric for detecting the occurrence and extension of structural looseness. Comparison results indicate that the defined index outperforms some existing state-of-the-art ones.

Clogging of Manifolds with Evaporatively Frozen Propellants. Part 2; Analysis

NASA Technical Reports Server (NTRS)

Simmon, J. A.; Gift, R. D.; Spurlock, J. M.

1966-01-01

The mechanisms of evaporative freezing of leaking propellant and the creation of flow stoppages within injector manifolds is discussed. A quantitative analysis of the conditions, including the existence of minimum and maximum leak rates, for the accumulation of evaporatively frozen propellant is presented. Clogging of the injector manifolds of the Apollo SPS and the Gemini OAMS engines by the freezing of leaking propellant is predicted and the seriousness of the consequences are discussed. Based on the analysis a realistic evaluation of selected techniques to eliminate flow stoppages by frozen propellant is made.

Locating an atmospheric contamination source using slow manifolds

NASA Astrophysics Data System (ADS)

Tang, Wenbo; Haller, George; Baik, Jong-Jin; Ryu, Young-Hee

2009-04-01

Finite-size particle motion in fluids obeys the Maxey-Riley equations, which become singular in the limit of infinitesimally small particle size. Because of this singularity, finding the source of a dispersed set of small particles is a numerically ill-posed problem that leads to exponential blowup. Here we use recent results on the existence of a slow manifold in the Maxey-Riley equations to overcome this difficulty in source inversion. Specifically, we locate the source of particles by projecting their dispersed positions on a time-varying slow manifold, and by advecting them on the manifold in backward time. We use this technique to locate the source of a hypothetical anthrax release in an unsteady three-dimensional atmospheric wind field in an urban street canyon.

Mapping of the Available Chemical Space versus the Chemical Universe of Lead-Like Compounds.

PubMed

Lin, Arkadii; Horvath, Dragos; Afonina, Valentina; Marcou, Gilles; Reymond, Jean-Louis; Varnek, Alexandre

2018-03-20

This is, to our knowledge, the most comprehensive analysis to date based on generative topographic mapping (GTM) of fragment-like chemical space (40 million molecules with no more than 17 heavy atoms, both from the theoretically enumerated GDB-17 and real-world PubChem/ChEMBL databases). The challenge was to prove that a robust map of fragment-like chemical space can actually be built, in spite of a limited (≪10 5 ) maximal number of compounds ("frame set") usable for fitting the GTM manifold. An evolutionary map building strategy has been updated with a "coverage check" step, which discards manifolds failing to accommodate compounds outside the frame set. The evolved map has a good propensity to separate actives from inactives for more than 20 external structure-activity sets. It was proven to properly accommodate the entire collection of 40 m compounds. Next, it served as a library comparison tool to highlight biases of real-world molecules (PubChem and ChEMBL) versus the universe of all possible species represented by FDB-17, a fragment-like subset of GDB-17 containing 10 million molecules. Specific patterns, proper to some libraries and absent from others (diversity holes), were highlighted. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Algebraic models of local period maps and Yukawa algebras

NASA Astrophysics Data System (ADS)

Bandiera, Ruggero; Manetti, Marco

2018-02-01

We describe some L_{∞} model for the local period map of a compact Kähler manifold. Applications include the study of deformations with associated variation of Hodge structure constrained by certain closed strata of the Grassmannian of the de Rham cohomology. As a by-product, we obtain an interpretation in the framework of deformation theory of the Yukawa coupling.

Dynamics on Networks of Manifolds

NASA Astrophysics Data System (ADS)

DeVille, Lee; Lerman, Eugene

2015-03-01

We propose a precise definition of a continuous time dynamical system made up of interacting open subsystems. The interconnections of subsystems are coded by directed graphs. We prove that the appropriate maps of graphs called graph fibrations give rise to maps of dynamical systems. Consequently surjective graph fibrations give rise to invariant subsystems and injective graph fibrations give rise to projections of dynamical systems.

Cohomological rigidity of manifolds defined by 3-dimensional polytopes

NASA Astrophysics Data System (ADS)

Buchstaber, V. M.; Erokhovets, N. Yu.; Masuda, M.; Panov, T. E.; Park, S.

2017-04-01

A family of closed manifolds is said to be cohomologically rigid if a cohomology ring isomorphism implies a diffeomorphism for any two manifolds in the family. Cohomological rigidity is established here for large families of 3-dimensional and 6-dimensional manifolds defined by 3-dimensional polytopes. The class \\mathscr{P} of 3-dimensional combinatorial simple polytopes P different from tetrahedra and without facets forming 3- and 4-belts is studied. This class includes mathematical fullerenes, that is, simple 3- polytopes with only 5-gonal and 6-gonal facets. By a theorem of Pogorelov, any polytope in \\mathscr{P} admits in Lobachevsky 3-space a right-angled realisation which is unique up to isometry. Our families of smooth manifolds are associated with polytopes in the class \\mathscr{P}. The first family consists of 3-dimensional small covers of polytopes in \\mathscr{P}, or equivalently, hyperbolic 3-manifolds of Löbell type. The second family consists of 6-dimensional quasitoric manifolds over polytopes in \\mathscr{P}. Our main result is that both families are cohomologically rigid, that is, two manifolds M and M' from either family are diffeomorphic if and only if their cohomology rings are isomorphic. It is also proved that if M and M' are diffeomorphic, then their corresponding polytopes P and P' are combinatorially equivalent. These results are intertwined with classical subjects in geometry and topology such as the combinatorics of 3-polytopes, the Four Colour Theorem, aspherical manifolds, a diffeomorphism classification of 6-manifolds, and invariance of Pontryagin classes. The proofs use techniques of toric topology. Bibliography: 69 titles.

Exact nonlinear model reduction for a von Kármán beam: Slow-fast decomposition and spectral submanifolds

NASA Astrophysics Data System (ADS)

Jain, Shobhit; Tiso, Paolo; Haller, George

2018-06-01

We apply two recently formulated mathematical techniques, Slow-Fast Decomposition (SFD) and Spectral Submanifold (SSM) reduction, to a von Kármán beam with geometric nonlinearities and viscoelastic damping. SFD identifies a global slow manifold in the full system which attracts solutions at rates faster than typical rates within the manifold. An SSM, the smoothest nonlinear continuation of a linear modal subspace, is then used to further reduce the beam equations within the slow manifold. This two-stage, mathematically exact procedure results in a drastic reduction of the finite-element beam model to a one-degree-of freedom nonlinear oscillator. We also introduce the technique of spectral quotient analysis, which gives the number of modes relevant for reduction as output rather than input to the reduction process.

Self-organizing adaptive map: autonomous learning of curves and surfaces from point samples.

PubMed

Piastra, Marco

2013-05-01

Competitive Hebbian Learning (CHL) (Martinetz, 1993) is a simple and elegant method for estimating the topology of a manifold from point samples. The method has been adopted in a number of self-organizing networks described in the literature and has given rise to related studies in the fields of geometry and computational topology. Recent results from these fields have shown that a faithful reconstruction can be obtained using the CHL method only for curves and surfaces. Within these limitations, these findings constitute a basis for defining a CHL-based, growing self-organizing network that produces a faithful reconstruction of an input manifold. The SOAM (Self-Organizing Adaptive Map) algorithm adapts its local structure autonomously in such a way that it can match the features of the manifold being learned. The adaptation process is driven by the defects arising when the network structure is inadequate, which cause a growth in the density of units. Regions of the network undergo a phase transition and change their behavior whenever a simple, local condition of topological regularity is met. The phase transition is eventually completed across the entire structure and the adaptation process terminates. In specific conditions, the structure thus obtained is homeomorphic to the input manifold. During the adaptation process, the network also has the capability to focus on the acquisition of input point samples in critical regions, with a substantial increase in efficiency. The behavior of the network has been assessed experimentally with typical data sets for surface reconstruction, including suboptimal conditions, e.g. with undersampling and noise. Copyright © 2012 Elsevier Ltd. All rights reserved.

Low-energy transfers to cislunar periodic orbits visiting triangular libration points

NASA Astrophysics Data System (ADS)

Lei, Hanlun; Xu, Bo

2018-01-01

This paper investigates the cislunar periodic orbits that pass through triangular libration points of the Earth-Moon system and studies the techniques on design low-energy transfer trajectories. In order to compute periodic orbits, families of impulsive transfers between triangular libration points are taken to generate the initial guesses of periodic orbits, and multiple shooting techniques are applied to solving the problem. Then, varieties of periodic orbits in cislunar space are obtained, and stability analysis shows that the majority of them are unstable. Among these periodic orbits, an unstable periodic orbit in near 3:2 resonance with the Moon is taken as the nominal orbit of an assumed mission. As the stable manifolds of the target orbit could approach the Moon, low-energy transfer trajectories can be designed by combining lunar gravity assist with the invariant manifold structure of the target orbit. In practice, both the natural and perturbed invariant manifolds are considered to obtain the low-energy transfers, which are further refined to the Sun-perturbed Earth-Moon system. Results indicate that (a) compared to the case of natural invariant manifolds, the optimal transfers using perturbed invariant manifolds could reduce flight time at least 50 days, (b) compared to the cheapest direct transfer, the optimal low-energy transfer obtained by combining lunar gravity assist and invariant manifolds could save on-board fuel consumption more than 200 m/s, and (c) by taking advantage of the gravitational perturbation of the Sun, the low-energy transfers could save more fuel consumption than the corresponding ones obtained in the Earth-Moon system.

A framework for optimal kernel-based manifold embedding of medical image data.

PubMed

Zimmer, Veronika A; Lekadir, Karim; Hoogendoorn, Corné; Frangi, Alejandro F; Piella, Gemma

2015-04-01

Kernel-based dimensionality reduction is a widely used technique in medical image analysis. To fully unravel the underlying nonlinear manifold the selection of an adequate kernel function and of its free parameters is critical. In practice, however, the kernel function is generally chosen as Gaussian or polynomial and such standard kernels might not always be optimal for a given image dataset or application. In this paper, we present a study on the effect of the kernel functions in nonlinear manifold embedding of medical image data. To this end, we first carry out a literature review on existing advanced kernels developed in the statistics, machine learning, and signal processing communities. In addition, we implement kernel-based formulations of well-known nonlinear dimensional reduction techniques such as Isomap and Locally Linear Embedding, thus obtaining a unified framework for manifold embedding using kernels. Subsequently, we present a method to automatically choose a kernel function and its associated parameters from a pool of kernel candidates, with the aim to generate the most optimal manifold embeddings. Furthermore, we show how the calculated selection measures can be extended to take into account the spatial relationships in images, or used to combine several kernels to further improve the embedding results. Experiments are then carried out on various synthetic and phantom datasets for numerical assessment of the methods. Furthermore, the workflow is applied to real data that include brain manifolds and multispectral images to demonstrate the importance of the kernel selection in the analysis of high-dimensional medical images. Copyright © 2014 Elsevier Ltd. All rights reserved.

Improving CNN Performance Accuracies With Min-Max Objective.

PubMed

Shi, Weiwei; Gong, Yihong; Tao, Xiaoyu; Wang, Jinjun; Zheng, Nanning

2017-06-09

We propose a novel method for improving performance accuracies of convolutional neural network (CNN) without the need to increase the network complexity. We accomplish the goal by applying the proposed Min-Max objective to a layer below the output layer of a CNN model in the course of training. The Min-Max objective explicitly ensures that the feature maps learned by a CNN model have the minimum within-manifold distance for each object manifold and the maximum between-manifold distances among different object manifolds. The Min-Max objective is general and able to be applied to different CNNs with insignificant increases in computation cost. Moreover, an incremental minibatch training procedure is also proposed in conjunction with the Min-Max objective to enable the handling of large-scale training data. Comprehensive experimental evaluations on several benchmark data sets with both the image classification and face verification tasks reveal that employing the proposed Min-Max objective in the training process can remarkably improve performance accuracies of a CNN model in comparison with the same model trained without using this objective.

Ice Shape Characterization Using Self-Organizing Maps

NASA Technical Reports Server (NTRS)

McClain, Stephen T.; Tino, Peter; Kreeger, Richard E.

2011-01-01

A method for characterizing ice shapes using a self-organizing map (SOM) technique is presented. Self-organizing maps are neural-network techniques for representing noisy, multi-dimensional data aligned along a lower-dimensional and possibly nonlinear manifold. For a large set of noisy data, each element of a finite set of codebook vectors is iteratively moved in the direction of the data closest to the winner codebook vector. Through successive iterations, the codebook vectors begin to align with the trends of the higher-dimensional data. In information processing, the intent of SOM methods is to transmit the codebook vectors, which contains far fewer elements and requires much less memory or bandwidth, than the original noisy data set. When applied to airfoil ice accretion shapes, the properties of the codebook vectors and the statistical nature of the SOM methods allows for a quantitative comparison of experimentally measured mean or average ice shapes to ice shapes predicted using computer codes such as LEWICE. The nature of the codebook vectors also enables grid generation and surface roughness descriptions for use with the discrete-element roughness approach. In the present study, SOM characterizations are applied to a rime ice shape, a glaze ice shape at an angle of attack, a bi-modal glaze ice shape, and a multi-horn glaze ice shape. Improvements and future explorations will be discussed.

Tall sections from non-minimal transformations

DOE PAGES

Morrison, David R.; Park, Daniel S.

2016-10-10

In previous study, we have shown that elliptic fibrations with two sections, or Mordell-Weil rank one, can always be mapped birationally to a Weierstrass model of a certain form, namely, the Jacobian of a P 112 model. Most constructions of elliptically fibered Calabi-Yau manifolds with two sections have been carried out assuming that the image of this birational map was a “minimal” Weierstrass model. In this paper, we show that for some elliptically fibered Calabi-Yau manifolds with Mordell-Weil rank-one, the Jacobian of the P 112 model is not minimal. Said another way, starting from a Calabi-Yau Weierstrass model, the totalmore » space must be blown up (thereby destroying the “Calabi-Yau” property) in order to embed the model into P 112. In particular, we show that the elliptic fibrations studied recently by Klevers and Taylor fall into this class of models.« less

Nonsmooth modal analysis of a N-degree-of-freedom system undergoing a purely elastic impact law

NASA Astrophysics Data System (ADS)

Legrand, Mathias; Junca, Stéphane; Heng, Sokly

2017-04-01

The dynamics of a N-degree-of-freedom autonomous oscillator undergoing an energy-preserving impact law on one of its masses is investigated in the light of nonlinear modal analysis. The impacted rigid foundation provides a natural Poincaré section of the investigated system from which is formulated a smooth First Return Map well-defined away from the grazing trajectory. In order to focus on the impact-induced nonlinearity, the oscillator is assumed linear. Continuous one-parameter families of T-periodic orbits featuring one impact per period and lying on two-dimensional invariant manifolds in the state-space are shown to exist. The geometry of these piecewise-smooth manifolds is such that a linear "flat" portion (on which contact is not activated) is continuously attached to a purely nonlinear portion (on which contact is activated once per period) exhibiting a velocity discontinuity through a grazing orbit. These features explain the newly introduced terminology "Nonsmooth modal analysis". The stability of the periodic orbits lying on the invariant manifolds is also explored by calculating the eigenvalues of the linearized First Return Map. Internal resonances and multiple impacts per period are not addressed in this work. However, the pre-stressed case is succinctly described and extensions to multiple oscillators as well as self-contact are discussed.

The Design-To-Cost Manifold

NASA Technical Reports Server (NTRS)

Dean, Edwin B.

1990-01-01

Design-to-cost is a popular technique for controlling costs. Although qualitative techniques exist for implementing design to cost, quantitative methods are sparse. In the launch vehicle and spacecraft engineering process, the question whether to minimize mass is usually an issue. The lack of quantification in this issue leads to arguments on both sides. This paper presents a mathematical technique which both quantifies the design-to-cost process and the mass/complexity issue. Parametric cost analysis generates and applies mathematical formulas called cost estimating relationships. In their most common forms, they are continuous and differentiable. This property permits the application of the mathematics of differentiable manifolds. Although the terminology sounds formidable, the application of the techniques requires only a knowledge of linear algebra and ordinary differential equations, common subjects in undergraduate scientific and engineering curricula. When the cost c is expressed as a differentiable function of n system metrics, setting the cost c to be a constant generates an n-1 dimensional subspace of the space of system metrics such that any set of metric values in that space satisfies the constant design-to-cost criterion. This space is a differentiable manifold upon which all mathematical properties of a differentiable manifold may be applied. One important property is that an easily implemented system of ordinary differential equations exists which permits optimization of any function of the system metrics, mass for example, over the design-to-cost manifold. A dual set of equations defines the directions of maximum and minimum cost change. A simplified approximation of the PRICE H(TM) production-production cost is used to generate this set of differential equations over [mass, complexity] space. The equations are solved in closed form to obtain the one dimensional design-to-cost trade and design-for-cost spaces. Preliminary results indicate that cost is relatively insensitive to changes in mass and that the reduction of complexity, both in the manufacturing process and of the spacecraft, is dominant in reducing cost.

Information hiding and retrieval in Rydberg wave packets using half-cycle pulses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murray, J. M.; Pisharody, S. N.; Wen, H.

We demonstrate an information hiding and retrieval scheme with the relative phases between states in a Rydberg wave packet acting as the bits of a data register. We use a terahertz half-cycle pulse (HCP) to transfer phase-encoded information from an optically accessible angular momentum manifold to another manifold which is not directly accessed by our laser pulses, effectively hiding the information from our optical interferometric measurement techniques. A subsequent HCP acting on these wave packets reintroduces the information back into the optically accessible data register manifold which can then be read out.

Robust Head-Pose Estimation Based on Partially-Latent Mixture of Linear Regressions.

PubMed

Drouard, Vincent; Horaud, Radu; Deleforge, Antoine; Ba, Sileye; Evangelidis, Georgios

2017-03-01

Head-pose estimation has many applications, such as social event analysis, human-robot and human-computer interaction, driving assistance, and so forth. Head-pose estimation is challenging, because it must cope with changing illumination conditions, variabilities in face orientation and in appearance, partial occlusions of facial landmarks, as well as bounding-box-to-face alignment errors. We propose to use a mixture of linear regressions with partially-latent output. This regression method learns to map high-dimensional feature vectors (extracted from bounding boxes of faces) onto the joint space of head-pose angles and bounding-box shifts, such that they are robustly predicted in the presence of unobservable phenomena. We describe in detail the mapping method that combines the merits of unsupervised manifold learning techniques and of mixtures of regressions. We validate our method with three publicly available data sets and we thoroughly benchmark four variants of the proposed algorithm with several state-of-the-art head-pose estimation methods.

The Stack of Yang-Mills Fields on Lorentzian Manifolds

NASA Astrophysics Data System (ADS)

Benini, Marco; Schenkel, Alexander; Schreiber, Urs

2018-03-01

We provide an abstract definition and an explicit construction of the stack of non-Abelian Yang-Mills fields on globally hyperbolic Lorentzian manifolds. We also formulate a stacky version of the Yang-Mills Cauchy problem and show that its well-posedness is equivalent to a whole family of parametrized PDE problems. Our work is based on the homotopy theoretical approach to stacks proposed in Hollander (Isr. J. Math. 163:93-124, 2008), which we shall extend by further constructions that are relevant for our purposes. In particular, we will clarify the concretification of mapping stacks to classifying stacks such as BG con.

Detecting Anisotropic Inclusions Through EIT

NASA Astrophysics Data System (ADS)

Cristina, Jan; Päivärinta, Lassi

2017-12-01

We study the evolution equation {partialtu=-Λtu} where {Λt} is the Dirichlet-Neumann operator of a decreasing family of Riemannian manifolds with boundary {Σt}. We derive a lower bound for the solution of such an equation, and apply it to a quantitative density estimate for the restriction of harmonic functions on M}=Σ_{0 to the boundaries of {partialΣt}. Consequently we are able to derive a lower bound for the difference of the Dirichlet-Neumann maps in terms of the difference of a background metrics g and an inclusion metric {g+χ_{Σ}(h-g)} on a manifold M.

Nonexistence of stable F-stationary maps of a functional related to pullback metrics.

PubMed

Li, Jing; Liu, Fang; Zhao, Peibiao

2017-01-01

Let [Formula: see text] be a compact convex hypersurface in [Formula: see text]. In this paper, we prove that if the principal curvatures [Formula: see text] of [Formula: see text] satisfy [Formula: see text] and [Formula: see text], then there exists no nonconstant stable F -stationary map between M and a compact Riemannian manifold when (6) or (7) holds.

75 FR 71371 - Airworthiness Directives; Thielert Aircraft Engines GmbH Models TAE 125-01, TAE 125-02-99, and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-23

... permeability is not always recognized as fault by the FADEC. The MAP value measured by the sensor may be lower... channel B manifold air pressure (MAP) sensor hose permeability is not always recognized as fault by the... between the national Government and the States, or on the distribution of power and responsibilities among...

Active learning for semi-supervised clustering based on locally linear propagation reconstruction.

PubMed

Chang, Chin-Chun; Lin, Po-Yi

2015-03-01

The success of semi-supervised clustering relies on the effectiveness of side information. To get effective side information, a new active learner learning pairwise constraints known as must-link and cannot-link constraints is proposed in this paper. Three novel techniques are developed for learning effective pairwise constraints. The first technique is used to identify samples less important to cluster structures. This technique makes use of a kernel version of locally linear embedding for manifold learning. Samples neither important to locally linear propagation reconstructions of other samples nor on flat patches in the learned manifold are regarded as unimportant samples. The second is a novel criterion for query selection. This criterion considers not only the importance of a sample to expanding the space coverage of the learned samples but also the expected number of queries needed to learn the sample. To facilitate semi-supervised clustering, the third technique yields inferred must-links for passing information about flat patches in the learned manifold to semi-supervised clustering algorithms. Experimental results have shown that the learned pairwise constraints can capture the underlying cluster structures and proven the feasibility of the proposed approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

Local matrix learning in clustering and applications for manifold visualization.

PubMed

Arnonkijpanich, Banchar; Hasenfuss, Alexander; Hammer, Barbara

2010-05-01

Electronic data sets are increasing rapidly with respect to both, size of the data sets and data resolution, i.e. dimensionality, such that adequate data inspection and data visualization have become central issues of data mining. In this article, we present an extension of classical clustering schemes by local matrix adaptation, which allows a better representation of data by means of clusters with an arbitrary spherical shape. Unlike previous proposals, the method is derived from a global cost function. The focus of this article is to demonstrate the applicability of this matrix clustering scheme to low-dimensional data embedding for data inspection. The proposed method is based on matrix learning for neural gas and manifold charting. This provides an explicit mapping of a given high-dimensional data space to low dimensionality. We demonstrate the usefulness of this method for data inspection and manifold visualization. 2009 Elsevier Ltd. All rights reserved.

Characterization and control of self-motions in redundant manipulators

NASA Technical Reports Server (NTRS)

Burdick, J.; Seraji, Homayoun

1989-01-01

The presence of redundant degrees of freedom in a manipulator structure leads to a physical phenomenon known as a self-motion, which is a continuous motion of the manipulator joints that leaves the end-effector motionless. In the first part of the paper, a global manifold mapping reformulation of manipulator kinematics is reviewed, and the inverse kinematic solution for redundant manipulators is developed in terms of self-motion manifolds. Global characterizations of the self-motion manifolds in terms of their number, geometry, homotopy class, and null space are reviewed using examples. Much previous work in redundant manipulator control has been concerned with the redundancy resolution problem, in which methods are developed to determine, or resolve, the motion of the joints in order to achieve end-effector trajectory control while optimizing additional objective functions. Redundancy resolution problems can be equivalently posed as the control of self-motions. Alternatives for redundancy resolution are briefly discussed.

Multi-subject Manifold Alignment of Functional Network Structures via Joint Diagonalization.

PubMed

Nenning, Karl-Heinz; Kollndorfer, Kathrin; Schöpf, Veronika; Prayer, Daniela; Langs, Georg

2015-01-01

Functional magnetic resonance imaging group studies rely on the ability to establish correspondence across individuals. This enables location specific comparison of functional brain characteristics. Registration is often based on morphology and does not take variability of functional localization into account. This can lead to a loss of specificity, or confounds when studying diseases. In this paper we propose multi-subject functional registration by manifold alignment via coupled joint diagonalization. The functional network structure of each subject is encoded in a diffusion map, where functional relationships are decoupled from spatial position. Two-step manifold alignment estimates initial correspondences between functionally equivalent regions. Then, coupled joint diagonalization establishes common eigenbases across all individuals, and refines the functional correspondences. We evaluate our approach on fMRI data acquired during a language paradigm. Experiments demonstrate the benefits in matching accuracy achieved by coupled joint diagonalization compared to previously proposed functional alignment approaches, or alignment based on structural correspondences.

Geometric U-folds in four dimensions

NASA Astrophysics Data System (ADS)

Lazaroiu, C. I.; Shahbazi, C. S.

2018-01-01

We describe a general construction of geometric U-folds compatible with a non-trivial extension of the global formulation of four-dimensional extended supergravity on a differentiable spin manifold. The topology of geometric U-folds depends on certain flat fiber bundles which encode how supergravity fields are globally glued together. We show that smooth non-trivial U-folds of this type can exist only in theories where both the scalar and space-time manifolds have non-trivial fundamental group and in addition the scalar map of the solution is homotopically non-trivial. Consistency with string theory requires smooth geometric U-folds to be glued using subgroups of the effective discrete U-duality group, implying that the fundamental group of the scalar manifold of such solutions must be a subgroup of the latter. We construct simple examples of geometric U-folds in a generalization of the axion-dilaton model of \

Feasibility and Testing of Additive Manufactured Components

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dehoff, Ryan R.; Hummelt, Ed; Solovyeva, Lyudmila

2016-09-01

This project focused on demonstrating the ability to fabricate two parts with different geometry: an arc flash interrupter and a hydraulic manifold. Eaton Corporation provided ORNL solid models, information related to tolerances and sensitive parameters of the parts and provided testing and evaluation. ORNL successfully manufactured both components, provided cost models of the manufacturing (materials, labor, time and post processing) and delivered test components for Eaton evaluation. The arc flash suppressor was fabricated using the Renishaw laser powder bed technology in CoCrMo while the manifold was produced from Ti-6Al-4V using the Arcam electron beam melting technology. These manufacturing techniques weremore » selected based on the design and geometrical tolerances required. A full-scale manifold was produced on the Arcam A2 system (nearly 12 inches tall). A portion of the manifold was also produced in the Arcam Q10 system. Although a full scale manifold could not be produced in the system, a full scale manifold is expected to have similar material properties, geometric accuracy, and surface finish as could be fabricated on an Arcam Q20 system that is capable of producing four full scale manifolds in a production environment. In addition to the manifold, mechanical test specimens, geometric tolerance artifacts, and microstructure samples were produced alongside the manifold. The development and demonstration of these two key components helped Eaton understand the impact additive manufacturing can have on many of their existing products. By working within the MDF and leveraging ORNL’s manufacturing and characterization capabilities, the work will ensure the rapid insertion and commercialization of this technology.« less

Quasi-hamiltonian quotients as disjoint unions of symplectic manifolds

NASA Astrophysics Data System (ADS)

Schaffhauser, Florent

2007-08-01

The main result of this paper is Theorem 2.12 which says that the quotient μ-1({1})/U associated to a quasi-hamiltonian space (M, ω, μ: M → U) has a symplectic structure even when 1 is not a regular value of the momentum map μ. Namely, it is a disjoint union of symplectic manifolds of possibly different dimensions, which generalizes the result of Alekseev, Malkin and Meinrenken in [AMM98]. We illustrate this theorem with the example of representation spaces of surface groups. As an intermediary step, we give a new class of examples of quasi-hamiltonian spaces: the isotropy submanifold MK whose points are the points of M with isotropy group K ⊂ U. The notion of quasi-hamiltonian space was introduced by Alekseev, Malkin and Meinrenken in their paper [AMM98]. The main motivation for it was the existence, under some regularity assumptions, of a symplectic structure on the associated quasi-hamiltonian quotient. Throughout their paper, the analogy with usual hamiltonian spaces is often used as a guiding principle, replacing Lie-algebra-valued momentum maps with Lie-group-valued momentum maps. In the hamiltonian setting, when the usual regularity assumptions on the group action or the momentum map are dropped, Lerman and Sjamaar showed in [LS91] that the quotient associated to a hamiltonian space carries a stratified symplectic structure. In particular, this quotient space is a disjoint union of symplectic manifolds. In this paper, we prove an analogous result for quasi-hamiltonian quotients. More precisely, we show that for any quasi-hamiltonian space (M, ω, μ: M → U), the associated quotient M//U := μ-1({1})/U is a disjoint union of symplectic manifolds (Theorem 2.12): [ mu^{-1}(\\{1\\})/U = bigsqcup_{jin J} (mu^{-1}(\\{1\\})\\cap M_{K_j})/L_{K_j} . ] Here Kj denotes a closed subgroup of U and MKj denotes the isotropy submanifold of type Kj: MKj = {x ∈ M | Ux = Kj}. Finally, LKj is the quotient group LKj = { N}(Kj)/K_j, where { N}(Kj) is the normalizer of Kj in U. As an intermediary step in our study, we show that MKj is a quasi-hamiltonian space when endowed with the (free) action of LKj.

Locally optimal transfer trajectories between libration point orbits using invariant manifolds

NASA Astrophysics Data System (ADS)

Davis, Kathryn E.

2009-12-01

Techniques from dynamical systems theory and primer vector theory have been applied to the construction of locally optimal transfer trajectories between libration point orbits. When two libration point orbits have different energies, it has been found that the unstable manifold of the first orbit can be connected to the stable manifold of the second orbit with a bridging trajectory. A bounding sphere centered on the secondary, with a radius less than the radius of the sphere of influence of the secondary, was used to study the stable and unstable manifold trajectories. It was numerically demonstrated that within the bounding sphere, the two-body parameters of the unstable and stable manifold trajectories could be analyzed to locate low transfer costs. It was shown that as the two-body parameters of an unstable manifold trajectory more closely matched the two-body parameters of a stable manifold trajectory, the total DeltaV necessary to complete the transfer decreased. Primer vector theory was successfully applied to a transfer to determine the optimal maneuvers required to create the bridging trajectory that connected the unstable manifold of the first orbit to the stable manifold of the second orbit. Transfer trajectories were constructed between halo orbits in the Sun-Earth and Earth-Moon three-body systems. Multiple solutions were found between the same initial and final orbits, where certain solutions retraced interior portions of the trajectory. All of the trajectories created satisfied the conditions for optimality. The costs of transfers constructed using invariant manifolds were compared to the costs of transfers constructed without the use of invariant manifolds, when data was available. In all cases, the total cost of the transfers were significantly lower when invariant manifolds were used in the transfer construction. In many cases, the transfers that employed invariant manifolds were three to four times more efficient, in terms of fuel expenditure, than the transfer that did not. The decrease in transfer cost was accompanied by an increase in transfer time of flight. Transfers constructed in the Earth-Moon system were shown to be particularly viable for lunar navigation and communication constellations, as excellent coverage of the lunar surface can be achieved during the transfer.

Planarity constrained multi-view depth map reconstruction for urban scenes

NASA Astrophysics Data System (ADS)

Hou, Yaolin; Peng, Jianwei; Hu, Zhihua; Tao, Pengjie; Shan, Jie

2018-05-01

Multi-view depth map reconstruction is regarded as a suitable approach for 3D generation of large-scale scenes due to its flexibility and scalability. However, there are challenges when this technique is applied to urban scenes where apparent man-made regular shapes may present. To address this need, this paper proposes a planarity constrained multi-view depth (PMVD) map reconstruction method. Starting with image segmentation and feature matching for each input image, the main procedure is iterative optimization under the constraints of planar geometry and smoothness. A set of candidate local planes are first generated by an extended PatchMatch method. The image matching costs are then computed and aggregated by an adaptive-manifold filter (AMF), whereby the smoothness constraint is applied to adjacent pixels through belief propagation. Finally, multiple criteria are used to eliminate image matching outliers. (Vertical) aerial images, oblique (aerial) images and ground images are used for qualitative and quantitative evaluations. The experiments demonstrated that the PMVD outperforms the popular multi-view depth map reconstruction with an accuracy two times better for the aerial datasets and achieves an outcome comparable to the state-of-the-art for ground images. As expected, PMVD is able to preserve the planarity for piecewise flat structures in urban scenes and restore the edges in depth discontinuous areas.

The construction of combinatorial manifolds with prescribed sets of links of vertices

NASA Astrophysics Data System (ADS)

Gaifullin, A. A.

2008-10-01

To every oriented closed combinatorial manifold we assign the set (with repetitions) of isomorphism classes of links of its vertices. The resulting transformation \\mathcal{L} is the main object of study in this paper. We pose an inversion problem for \\mathcal{L} and show that this problem is closely related to Steenrod's problem on the realization of cycles and to the Rokhlin-Schwartz-Thom construction of combinatorial Pontryagin classes. We obtain a necessary condition for a set of isomorphism classes of combinatorial spheres to belong to the image of \\mathcal{L}. (Sets satisfying this condition are said to be balanced.) We give an explicit construction showing that every balanced set of isomorphism classes of combinatorial spheres falls into the image of \\mathcal{L} after passing to a multiple set and adding several pairs of the form (Z,-Z), where -Z is the sphere Z with the orientation reversed. Given any singular simplicial cycle \\xi of a space X, this construction enables us to find explicitly a combinatorial manifold M and a map \\varphi\\colon M\\to X such that \\varphi_* \\lbrack M \\rbrack =r[\\xi] for some positive integer r. The construction is based on resolving singularities of \\xi. We give applications of the main construction to cobordisms of manifolds with singularities and cobordisms of simple cells. In particular, we prove that every rational additive invariant of cobordisms of manifolds with singularities admits a local formula. Another application is the construction of explicit (though inefficient) local combinatorial formulae for polynomials in the rational Pontryagin classes of combinatorial manifolds.

The dynamics of phase locking and points of resonance in a forced magnetic oscillator

NASA Astrophysics Data System (ADS)

Bryant, Paul; Jeffries, Carson

1987-03-01

We report data on an experimental system: a forced symmetric oscillator containing a saturable inductor with magnetic hysteresis. It displays a Hopf bifurcation to quasiperiodicity, entrainment horns, and chaos. We study in detail the bifurcations and hysteresis occurring near points of resonance (particularly “ strong resonance”) and show how the observed behavior can be understood using Arnold's theory. Much of the behavior relating to the entrainment horns is explored: period doubling and symmetry breaking bifurcations; homoclinic bifurcations; and crises and other bifurcations taking place at the horn boundaries. Important features of the behavior related to symmetry properties of the oscillator are studied and explained through the concept of a half-cycle map. The system is shown to exhibit a Hopf bifurcation from a phase-locked state to periodic “islands”, similar to those found in Hamiltonian systems. An initialization technique is used to observe the manifolds of saddle orbits and other hidden structure. An unusual differential equation model is developed which is irreversible and generates a noninvertible Poincaré map of the plane. Noninvertibility of this planar map has important effects on the behavior observed. The Poincaré map may also be approximated through experimental measurements, resulting in a planar map with parameter dependence. This model gives good correspondence with the system in a region of the parameter space.

Transport properties in nontwist area-preserving maps

DOE PAGES

Szezech Jr., J. D.; Caldas, I. L.; Lopes, S. R.; ...

2009-10-23

Nontwist systems, common in the dynamical descriptions of fluids and plasmas, possess a shearless curve with a concomitant transport barrier that eliminates or reduces chaotic transport, even after its breakdown. In order to investigate the transport properties of nontwist systems, we analyze the barrier escape time and barrier transmissivity for the standard nontwist map, a paradigm of such systems. We interpret the sensitive dependence of these quantities upon map parameters by investigating chaotic orbit stickiness and the associated role played by the dominant crossing of stable and unstable manifolds.

Automated standardization technique for an inductively-coupled plasma emission spectrometer

USGS Publications Warehouse

Garbarino, John R.; Taylor, Howard E.

1982-01-01

The manifold assembly subsystem described permits real-time computer-controlled standardization and quality control of a commercial inductively-coupled plasma atomic emission spectrometer. The manifold assembly consists of a branch-structured glass manifold, a series of microcomputer-controlled solenoid valves, and a reservoir for each standard. Automated standardization involves selective actuation of each solenoid valve that permits a specific mixed standard solution to be pumped to the nebulizer of the spectrometer. Quality control is based on the evaluation of results obtained for a mixed standard containing 17 analytes, that is measured periodically with unknown samples. An inaccurate standard evaluation triggers restandardization of the instrument according to a predetermined protocol. Interaction of the computer-controlled manifold assembly hardware with the spectrometer system is outlined. Evaluation of the automated standardization system with respect to reliability, simplicity, flexibility, and efficiency is compared to the manual procedure. ?? 1982.

The Center for Computational Biology: resources, achievements, and challenges

PubMed Central

Dinov, Ivo D; Thompson, Paul M; Woods, Roger P; Van Horn, John D; Shattuck, David W; Parker, D Stott

2011-01-01

The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains. PMID:22081221

The Center for Computational Biology: resources, achievements, and challenges.

PubMed

Toga, Arthur W; Dinov, Ivo D; Thompson, Paul M; Woods, Roger P; Van Horn, John D; Shattuck, David W; Parker, D Stott

2012-01-01

The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains.

Multilayer Joint Gait-Pose Manifolds for Human Gait Motion Modeling.

PubMed

Ding, Meng; Fan, Guolian

2015-11-01

We present new multilayer joint gait-pose manifolds (multilayer JGPMs) for complex human gait motion modeling, where three latent variables are defined jointly in a low-dimensional manifold to represent a variety of body configurations. Specifically, the pose variable (along the pose manifold) denotes a specific stage in a walking cycle; the gait variable (along the gait manifold) represents different walking styles; and the linear scale variable characterizes the maximum stride in a walking cycle. We discuss two kinds of topological priors for coupling the pose and gait manifolds, i.e., cylindrical and toroidal, to examine their effectiveness and suitability for motion modeling. We resort to a topologically-constrained Gaussian process (GP) latent variable model to learn the multilayer JGPMs where two new techniques are introduced to facilitate model learning under limited training data. First is training data diversification that creates a set of simulated motion data with different strides. Second is the topology-aware local learning to speed up model learning by taking advantage of the local topological structure. The experimental results on the Carnegie Mellon University motion capture data demonstrate the advantages of our proposed multilayer models over several existing GP-based motion models in terms of the overall performance of human gait motion modeling.

Cascades of alternating pitchfork and flip bifurcations in H-bridge inverters

NASA Astrophysics Data System (ADS)

Avrutin, Viktor; Zhusubaliyev, Zhanybai T.; Mosekilde, Erik

2017-04-01

Power electronic DC/AC converters (inverters) play an important role in modern power engineering. These systems are also of considerable theoretical interest because their dynamics is influenced by the presence of two vastly different forcing frequencies. As a consequence, inverter systems may be modeled in terms of piecewise smooth maps with an extremely high number of switching manifolds. We have recently shown that models of this type can demonstrate a complicated bifurcation structure associated with the occurrence of border collisions. Considering the example of a PWM H-bridge single-phase inverter, the present paper discusses a number of unusual phenomena that can occur in piecewise smooth maps with a very large number of switching manifolds. We show in particular how smooth (pitchfork and flip) bifurcations may form a macroscopic pattern that stretches across the overall bifurcation structure. We explain the observed bifurcation phenomena, show under which conditions they occur, and describe them quantitatively by means of an analytic approximation.

Localization in abelian Chern-Simons theory

NASA Astrophysics Data System (ADS)

McLellan, B. D. K.

2013-02-01

Chern-Simons theory on a closed contact three-manifold is studied when the Lie group for gauge transformations is compact, connected, and abelian. The abelian Chern-Simons partition function is derived using the Faddeev-Popov gauge fixing method. The partition function is then formally computed using the technique of non-abelian localization. This study leads to a natural identification of the abelian Reidemeister-Ray-Singer torsion as a specific multiple of the natural unit symplectic volume form on the moduli space of flat abelian connections for the class of Sasakian three-manifolds. The torsion part of the abelian Chern-Simons partition function is computed explicitly in terms of Seifert data for a given Sasakian three-manifold.

Resonance-Based Time-Frequency Manifold for Feature Extraction of Ship-Radiated Noise.

PubMed

Yan, Jiaquan; Sun, Haixin; Chen, Hailan; Junejo, Naveed Ur Rehman; Cheng, En

2018-03-22

In this paper, a novel time-frequency signature using resonance-based sparse signal decomposition (RSSD), phase space reconstruction (PSR), time-frequency distribution (TFD) and manifold learning is proposed for feature extraction of ship-radiated noise, which is called resonance-based time-frequency manifold (RTFM). This is suitable for analyzing signals with oscillatory, non-stationary and non-linear characteristics in a situation of serious noise pollution. Unlike the traditional methods which are sensitive to noise and just consider one side of oscillatory, non-stationary and non-linear characteristics, the proposed RTFM can provide the intact feature signature of all these characteristics in the form of a time-frequency signature by the following steps: first, RSSD is employed on the raw signal to extract the high-oscillatory component and abandon the low-oscillatory component. Second, PSR is performed on the high-oscillatory component to map the one-dimensional signal to the high-dimensional phase space. Third, TFD is employed to reveal non-stationary information in the phase space. Finally, manifold learning is applied to the TFDs to fetch the intrinsic non-linear manifold. A proportional addition of the top two RTFMs is adopted to produce the improved RTFM signature. All of the case studies are validated on real audio recordings of ship-radiated noise. Case studies of ship-radiated noise on different datasets and various degrees of noise pollution manifest the effectiveness and robustness of the proposed method.

Resonance-Based Time-Frequency Manifold for Feature Extraction of Ship-Radiated Noise

PubMed Central

Yan, Jiaquan; Sun, Haixin; Chen, Hailan; Junejo, Naveed Ur Rehman; Cheng, En

2018-01-01

In this paper, a novel time-frequency signature using resonance-based sparse signal decomposition (RSSD), phase space reconstruction (PSR), time-frequency distribution (TFD) and manifold learning is proposed for feature extraction of ship-radiated noise, which is called resonance-based time-frequency manifold (RTFM). This is suitable for analyzing signals with oscillatory, non-stationary and non-linear characteristics in a situation of serious noise pollution. Unlike the traditional methods which are sensitive to noise and just consider one side of oscillatory, non-stationary and non-linear characteristics, the proposed RTFM can provide the intact feature signature of all these characteristics in the form of a time-frequency signature by the following steps: first, RSSD is employed on the raw signal to extract the high-oscillatory component and abandon the low-oscillatory component. Second, PSR is performed on the high-oscillatory component to map the one-dimensional signal to the high-dimensional phase space. Third, TFD is employed to reveal non-stationary information in the phase space. Finally, manifold learning is applied to the TFDs to fetch the intrinsic non-linear manifold. A proportional addition of the top two RTFMs is adopted to produce the improved RTFM signature. All of the case studies are validated on real audio recordings of ship-radiated noise. Case studies of ship-radiated noise on different datasets and various degrees of noise pollution manifest the effectiveness and robustness of the proposed method. PMID:29565288

Study of intake manifold for Universiti Malaysia Perlis automotive racing team formula student race car

NASA Astrophysics Data System (ADS)

Norizan, A.; Rahman, M. T. A.; Amin, N. A. M.; Basha, M. H.; Ismail, M. H. N.; Hamid, A. F. A.

2017-10-01

This paper describes the design differences between the intake manifold and restrictor used in racing cars that participate in the Formula Student (FSAE) competition. To fulfil the criteria of rules and regulation of the race, each race car must have a restriction device that has a maximum diameter of 20 mm installed between the throttle body and intake manifold. To overcome these problems, a restrictor has been designed and analysed using the steady state analysis, to reduce the loss of pressure in the restrictor. Design of the restrictor has a fixed parameter of the maximum diameter of 20mm. There are some differences that have been taken to make the comparison between the design of the restrictor, the diameter of the inlet and outlet, the curvature of the surface, convergence and divergence angle and length of the restrictor. Intake manifold was designed based on the design of the chassis, which shall not exceed the envelope defined by the FSAE competition. A good intake manifold design will affect the performance of the engine. Each design have made an analysis designed to ensure that each cylinder engine gets its air evenly. To verify the design, steady state analysis was made for a total mass flow rate and the velocity of air leaving a runner in each engine. Data such as the engine MAP reading was recorded by using Haltech ECU Management Software as reference purposes.

Energy minimization on manifolds for docking flexible molecules

PubMed Central

Mirzaei, Hanieh; Zarbafian, Shahrooz; Villar, Elizabeth; Mottarella, Scott; Beglov, Dmitri; Vajda, Sandor; Paschalidis, Ioannis Ch.; Vakili, Pirooz; Kozakov, Dima

2015-01-01

In this paper we extend a recently introduced rigid body minimization algorithm, defined on manifolds, to the problem of minimizing the energy of interacting flexible molecules. The goal is to integrate moving the ligand in six dimensional rotational/translational space with internal rotations around rotatable bonds within the two molecules. We show that adding rotational degrees of freedom to the rigid moves of the ligand results in an overall optimization search space that is a manifold to which our manifold optimization approach can be extended. The effectiveness of the method is shown for three different docking problems of increasing complexity. First we minimize the energy of fragment-size ligands with a single rotatable bond as part of a protein mapping method developed for the identification of binding hot spots. Second, we consider energy minimization for docking a flexible ligand to a rigid protein receptor, an approach frequently used in existing methods. In the third problem we account for flexibility in both the ligand and the receptor. Results show that minimization using the manifold optimization algorithm is substantially more efficient than minimization using a traditional all-atom optimization algorithm while producing solutions of comparable quality. In addition to the specific problems considered, the method is general enough to be used in a large class of applications such as docking multidomain proteins with flexible hinges. The code is available under open source license (at http://cluspro.bu.edu/Code/Code_Rigtree.tar), and with minimal effort can be incorporated into any molecular modeling package. PMID:26478722

A manifold learning approach to target detection in high-resolution hyperspectral imagery

NASA Astrophysics Data System (ADS)

Ziemann, Amanda K.

Imagery collected from airborne platforms and satellites provide an important medium for remotely analyzing the content in a scene. In particular, the ability to detect a specific material within a scene is of high importance to both civilian and defense applications. This may include identifying "targets" such as vehicles, buildings, or boats. Sensors that process hyperspectral images provide the high-dimensional spectral information necessary to perform such analyses. However, for a d-dimensional hyperspectral image, it is typical for the data to inherently occupy an m-dimensional space, with m << d. In the remote sensing community, this has led to a recent increase in the use of manifold learning, which aims to characterize the embedded lower-dimensional, non-linear manifold upon which the hyperspectral data inherently lie. Classic hyperspectral data models include statistical, linear subspace, and linear mixture models, but these can place restrictive assumptions on the distribution of the data; this is particularly true when implementing traditional target detection approaches, and the limitations of these models are well-documented. With manifold learning based approaches, the only assumption is that the data reside on an underlying manifold that can be discretely modeled by a graph. The research presented here focuses on the use of graph theory and manifold learning in hyperspectral imagery. Early work explored various graph-building techniques with application to the background model of the Topological Anomaly Detection (TAD) algorithm, which is a graph theory based approach to anomaly detection. This led towards a focus on target detection, and in the development of a specific graph-based model of the data and subsequent dimensionality reduction using manifold learning. An adaptive graph is built on the data, and then used to implement an adaptive version of locally linear embedding (LLE). We artificially induce a target manifold and incorporate it into the adaptive LLE transformation; the artificial target manifold helps to guide the separation of the target data from the background data in the new, lower-dimensional manifold coordinates. Then, target detection is performed in the manifold space.

Fine topology and locally Minkowskian manifolds

NASA Astrophysics Data System (ADS)

Agrawal, Gunjan; Sinha, Soami Pyari

2018-05-01

Fine topology is one of the several well-known topologies of physical and mathematical relevance. In the present paper, it is obtained that the nonempty open sets of different dimensional Minkowski spaces with the fine topology are not homeomorphic. This leads to the introduction of a new class of manifolds. It turns out that the technique developed here is also applicable to some other topologies, namely, the s-topology, space topology, f-topology, and A-topology.

A map for heavy inertial particles in fluid flows

NASA Astrophysics Data System (ADS)

Vilela, Rafael D.; de Oliveira, Vitor M.

2017-06-01

We introduce a map which reproduces qualitatively many fundamental properties of the dynamics of heavy particles in fluid flows. These include a uniform rate of decrease of volume in phase space, a slow-manifold effective dynamics when the single parameter s (analogous of the Stokes number) approaches zero, the possibility of fold caustics in the "velocity field", and a minimum, as a function of s, of the Lyapunov (Kaplan-Yorke) dimension of the attractor where particles accumulate.

Function approximation using combined unsupervised and supervised learning.

PubMed

Andras, Peter

2014-03-01

Function approximation is one of the core tasks that are solved using neural networks in the context of many engineering problems. However, good approximation results need good sampling of the data space, which usually requires exponentially increasing volume of data as the dimensionality of the data increases. At the same time, often the high-dimensional data is arranged around a much lower dimensional manifold. Here we propose the breaking of the function approximation task for high-dimensional data into two steps: (1) the mapping of the high-dimensional data onto a lower dimensional space corresponding to the manifold on which the data resides and (2) the approximation of the function using the mapped lower dimensional data. We use over-complete self-organizing maps (SOMs) for the mapping through unsupervised learning, and single hidden layer neural networks for the function approximation through supervised learning. We also extend the two-step procedure by considering support vector machines and Bayesian SOMs for the determination of the best parameters for the nonlinear neurons in the hidden layer of the neural networks used for the function approximation. We compare the approximation performance of the proposed neural networks using a set of functions and show that indeed the neural networks using combined unsupervised and supervised learning outperform in most cases the neural networks that learn the function approximation using the original high-dimensional data.

Colliding impulsive gravitational waves

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nutku, Y.; Halil, M.

1977-11-28

We formulate the problem of colliding plane gravitational waves with two polarizations as the harmonic mappings of Riemannian manifolds and construct an exact solution of the vacuum Einstein field equations describing the interaction of colliding impulsive gravitational waves which in the limit of collinear polarization reduces to the solution of Khan and Penrose.

An accurate computational method for an order parameter with a Markov state model constructed using a manifold-learning technique

NASA Astrophysics Data System (ADS)

Ito, Reika; Yoshidome, Takashi

2018-01-01

Markov state models (MSMs) are a powerful approach for analyzing the long-time behaviors of protein motion using molecular dynamics simulation data. However, their quantitative performance with respect to the physical quantities is poor. We believe that this poor performance is caused by the failure to appropriately classify protein conformations into states when constructing MSMs. Herein, we show that the quantitative performance of an order parameter is improved when a manifold-learning technique is employed for the classification in the MSM. The MSM construction using the K-center method, which has been previously used for classification, has a poor quantitative performance.

GPU accelerated manifold correction method for spinning compact binaries

NASA Astrophysics Data System (ADS)

Ran, Chong-xi; Liu, Song; Zhong, Shuang-ying

2018-04-01

The graphics processing unit (GPU) acceleration of the manifold correction algorithm based on the compute unified device architecture (CUDA) technology is designed to simulate the dynamic evolution of the Post-Newtonian (PN) Hamiltonian formulation of spinning compact binaries. The feasibility and the efficiency of parallel computation on GPU have been confirmed by various numerical experiments. The numerical comparisons show that the accuracy on GPU execution of manifold corrections method has a good agreement with the execution of codes on merely central processing unit (CPU-based) method. The acceleration ability when the codes are implemented on GPU can increase enormously through the use of shared memory and register optimization techniques without additional hardware costs, implying that the speedup is nearly 13 times as compared with the codes executed on CPU for phase space scan (including 314 × 314 orbits). In addition, GPU-accelerated manifold correction method is used to numerically study how dynamics are affected by the spin-induced quadrupole-monopole interaction for black hole binary system.

Microchannel cooling of face down bonded chips

DOEpatents

Bernhardt, Anthony F.

1993-01-01

Microchannel cooling is applied to flip-chip bonded integrated circuits, in a manner which maintains the advantages of flip-chip bonds, while overcoming the difficulties encountered in cooling the chips. The technique is suited to either multichip integrated circuit boards in a plane, or to stacks of circuit boards in a three dimensional interconnect structure. Integrated circuit chips are mounted on a circuit board using flip-chip or control collapse bonds. A microchannel structure is essentially permanently coupled with the back of the chip. A coolant delivery manifold delivers coolant to the microchannel structure, and a seal consisting of a compressible elastomer is provided between the coolant delivery manifold and the microchannel structure. The integrated circuit chip and microchannel structure are connected together to form a replaceable integrated circuit module which can be easily decoupled from the coolant delivery manifold and the circuit board. The coolant supply manifolds may be disposed between the circuit boards in a stack and coupled to supplies of coolant through a side of the stack.

Microchannel cooling of face down bonded chips

DOEpatents

Bernhardt, A.F.

1993-06-08

Microchannel cooling is applied to flip-chip bonded integrated circuits, in a manner which maintains the advantages of flip-chip bonds, while overcoming the difficulties encountered in cooling the chips. The technique is suited to either multi chip integrated circuit boards in a plane, or to stacks of circuit boards in a three dimensional interconnect structure. Integrated circuit chips are mounted on a circuit board using flip-chip or control collapse bonds. A microchannel structure is essentially permanently coupled with the back of the chip. A coolant delivery manifold delivers coolant to the microchannel structure, and a seal consisting of a compressible elastomer is provided between the coolant delivery manifold and the microchannel structure. The integrated circuit chip and microchannel structure are connected together to form a replaceable integrated circuit module which can be easily decoupled from the coolant delivery manifold and the circuit board. The coolant supply manifolds may be disposed between the circuit boards in a stack and coupled to supplies of coolant through a side of the stack.

Postoperative 3D spine reconstruction by navigating partitioning manifolds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kadoury, Samuel, E-mail: samuel.kadoury@polymtl.ca; Labelle, Hubert, E-mail: hubert.labelle@recherche-ste-justine.qc.ca; Parent, Stefan, E-mail: stefan.parent@umontreal.ca

Purpose: The postoperative evaluation of scoliosis patients undergoing corrective treatment is an important task to assess the strategy of the spinal surgery. Using accurate 3D geometric models of the patient’s spine is essential to measure longitudinal changes in the patient’s anatomy. On the other hand, reconstructing the spine in 3D from postoperative radiographs is a challenging problem due to the presence of instrumentation (metallic rods and screws) occluding vertebrae on the spine. Methods: This paper describes the reconstruction problem by searching for the optimal model within a manifold space of articulated spines learned from a training dataset of pathological casesmore » who underwent surgery. The manifold structure is implemented based on a multilevel manifold ensemble to structure the data, incorporating connections between nodes within a single manifold, in addition to connections between different multilevel manifolds, representing subregions with similar characteristics. Results: The reconstruction pipeline was evaluated on x-ray datasets from both preoperative patients and patients with spinal surgery. By comparing the method to ground-truth models, a 3D reconstruction accuracy of 2.24 ± 0.90 mm was obtained from 30 postoperative scoliotic patients, while handling patients with highly deformed spines. Conclusions: This paper illustrates how this manifold model can accurately identify similar spine models by navigating in the low-dimensional space, as well as computing nonlinear charts within local neighborhoods of the embedded space during the testing phase. This technique allows postoperative follow-ups of spinal surgery using personalized 3D spine models and assess surgical strategies for spinal deformities.« less

Saddle Slow Manifolds and Canard Orbits in [Formula: see text] and Application to the Full Hodgkin-Huxley Model.

PubMed

Hasan, Cris R; Krauskopf, Bernd; Osinga, Hinke M

2018-04-19

Many physiological phenomena have the property that some variables evolve much faster than others. For example, neuron models typically involve observable differences in time scales. The Hodgkin-Huxley model is well known for explaining the ionic mechanism that generates the action potential in the squid giant axon. Rubin and Wechselberger (Biol. Cybern. 97:5-32, 2007) nondimensionalized this model and obtained a singularly perturbed system with two fast, two slow variables, and an explicit time-scale ratio ε. The dynamics of this system are complex and feature periodic orbits with a series of action potentials separated by small-amplitude oscillations (SAOs); also referred to as mixed-mode oscillations (MMOs). The slow dynamics of this system are organized by two-dimensional locally invariant manifolds called slow manifolds which can be either attracting or of saddle type.In this paper, we introduce a general approach for computing two-dimensional saddle slow manifolds and their stable and unstable fast manifolds. We also develop a technique for detecting and continuing associated canard orbits, which arise from the interaction between attracting and saddle slow manifolds, and provide a mechanism for the organization of SAOs in [Formula: see text]. We first test our approach with an extended four-dimensional normal form of a folded node. Our results demonstrate that our computations give reliable approximations of slow manifolds and canard orbits of this model. Our computational approach is then utilized to investigate the role of saddle slow manifolds and associated canard orbits of the full Hodgkin-Huxley model in organizing MMOs and determining the firing rates of action potentials. For ε sufficiently large, canard orbits are arranged in pairs of twin canard orbits with the same number of SAOs. We illustrate how twin canard orbits partition the attracting slow manifold into a number of ribbons that play the role of sectors of rotations. The upshot is that we are able to unravel the geometry of slow manifolds and associated canard orbits without the need to reduce the model.

Continuous statistical modelling for rapid detection of adulteration of extra virgin olive oil using mid infrared and Raman spectroscopic data.

PubMed

Georgouli, Konstantia; Martinez Del Rincon, Jesus; Koidis, Anastasios

2017-02-15

The main objective of this work was to develop a novel dimensionality reduction technique as a part of an integrated pattern recognition solution capable of identifying adulterants such as hazelnut oil in extra virgin olive oil at low percentages based on spectroscopic chemical fingerprints. A novel Continuous Locality Preserving Projections (CLPP) technique is proposed which allows the modelling of the continuous nature of the produced in-house admixtures as data series instead of discrete points. The maintenance of the continuous structure of the data manifold enables the better visualisation of this examined classification problem and facilitates the more accurate utilisation of the manifold for detecting the adulterants. The performance of the proposed technique is validated with two different spectroscopic techniques (Raman and Fourier transform infrared, FT-IR). In all cases studied, CLPP accompanied by k-Nearest Neighbors (kNN) algorithm was found to outperform any other state-of-the-art pattern recognition techniques. Copyright © 2016 Elsevier Ltd. All rights reserved.

Surrogate based wind farm layout optimization using manifold mapping

NASA Astrophysics Data System (ADS)

Kaja Kamaludeen, Shaafi M.; van Zuijle, Alexander; Bijl, Hester

2016-09-01

High computational cost associated with the high fidelity wake models such as RANS or LES serves as a primary bottleneck to perform a direct high fidelity wind farm layout optimization (WFLO) using accurate CFD based wake models. Therefore, a surrogate based multi-fidelity WFLO methodology (SWFLO) is proposed. The surrogate model is built using an SBO method referred as manifold mapping (MM). As a verification, optimization of spacing between two staggered wind turbines was performed using the proposed surrogate based methodology and the performance was compared with that of direct optimization using high fidelity model. Significant reduction in computational cost was achieved using MM: a maximum computational cost reduction of 65%, while arriving at the same optima as that of direct high fidelity optimization. The similarity between the response of models, the number of mapping points and its position, highly influences the computational efficiency of the proposed method. As a proof of concept, realistic WFLO of a small 7-turbine wind farm is performed using the proposed surrogate based methodology. Two variants of Jensen wake model with different decay coefficients were used as the fine and coarse model. The proposed SWFLO method arrived at the same optima as that of the fine model with very less number of fine model simulations.

Sparse alignment for robust tensor learning.

PubMed

Lai, Zhihui; Wong, Wai Keung; Xu, Yong; Zhao, Cairong; Sun, Mingming

2014-10-01

Multilinear/tensor extensions of manifold learning based algorithms have been widely used in computer vision and pattern recognition. This paper first provides a systematic analysis of the multilinear extensions for the most popular methods by using alignment techniques, thereby obtaining a general tensor alignment framework. From this framework, it is easy to show that the manifold learning based tensor learning methods are intrinsically different from the alignment techniques. Based on the alignment framework, a robust tensor learning method called sparse tensor alignment (STA) is then proposed for unsupervised tensor feature extraction. Different from the existing tensor learning methods, L1- and L2-norms are introduced to enhance the robustness in the alignment step of the STA. The advantage of the proposed technique is that the difficulty in selecting the size of the local neighborhood can be avoided in the manifold learning based tensor feature extraction algorithms. Although STA is an unsupervised learning method, the sparsity encodes the discriminative information in the alignment step and provides the robustness of STA. Extensive experiments on the well-known image databases as well as action and hand gesture databases by encoding object images as tensors demonstrate that the proposed STA algorithm gives the most competitive performance when compared with the tensor-based unsupervised learning methods.

Convex decomposition techniques applied to handlebodies

NASA Astrophysics Data System (ADS)

Ortiz, Marcos A.

Contact structures on 3-manifolds are 2-plane fields satisfying a set of conditions. The study of contact structures can be traced back for over two-hundred years, and has been of interest to mathematicians such as Hamilton, Jacobi, Cartan, and Darboux. In the late 1900's, the study of these structures gained momentum as the work of Eliashberg and Bennequin described subtleties in these structures that could be used to find new invariants. In particular, it was discovered that contact structures fell into two classes: tight and overtwisted. While overtwisted contact structures are relatively well understood, tight contact structures remain an area of active research. One area of active study, in particular, is the classification of tight contact structures on 3-manifolds. This began with Eliashberg, who showed that the standard contact structure in real three-dimensional space is unique, and it has been expanded on since. Some major advancements and new techniques were introduced by Kanda, Honda, Etnyre, Kazez, Matic, and others. Convex decomposition theory was one product of these explorations. This technique involves cutting a manifold along convex surfaces (i.e. surfaces arranged in a particular way in relation to the contact structure) and investigating a particular set on these cutting surfaces to say something about the original contact structure. In the cases where the cutting surfaces are fairly nice, in some sense, Honda established a correspondence between information on the cutting surfaces and the tight contact structures supported by the original manifold. In this thesis, convex surface theory is applied to the case of handlebodies with a restricted class of dividing sets. For some cases, classification is achieved, and for others, some interesting patterns arise and are investigated.

Vacuum instability in Kaluza–Klein manifolds

NASA Astrophysics Data System (ADS)

Fucci, Guglielmo

2018-05-01

The purpose of this work in to analyze particle creation in spaces with extra dimensions. We consider, in particular, a massive scalar field propagating in a Kaluza–Klein manifold subject to a constant electric field. We compute the rate of particle creation from vacuum by using techniques rooted in the spectral zeta function formalism. The results we obtain show explicitly how the presence of the extra-dimensions and their specific geometric characteristics, influence the rate at which pairs of particles and anti-particles are generated.

Fermionic edge states and new physics

NASA Astrophysics Data System (ADS)

Govindarajan, T. R.; Tibrewala, Rakesh

2015-08-01

We investigate the properties of the Dirac operator on manifolds with boundaries in the presence of the Atiyah-Patodi-Singer boundary condition. An exact counting of the number of edge states for boundaries with isometry of a sphere is given. We show that the problem with the above boundary condition can be mapped to one where the manifold is extended beyond the boundary and the boundary condition is replaced by a delta function potential of suitable strength. We also briefly highlight how the problem of the self-adjointness of the operators in the presence of moving boundaries can be simplified by suitable transformations which render the boundary fixed and modify the Hamiltonian and the boundary condition to reflect the effect of moving boundary.

On the approximation of Lyapunov exponents and a question suggested by Anatole Katok

NASA Astrophysics Data System (ADS)

Dai, Xiongping

2010-03-01

Let \\mathcal {F}\\colon X\\times\\mathbb{Z}_+\\rightarrow \\rm{GL}(n,\\mathbb{R}) be a Hölder-continuous linear cocycle whose driving semiflow f\\colon X\\times\\mathbb{Z}_+\\rightarrow X preserves a probability μ on a compact metric space X. Using the concept of two-sided quasi-Pesin orbits introduced in this paper, we show that the Lyapunov characteristic spectrum of μ can be approached arbitrarily by that of periodic points of f. So, if all periodic points of f have only positive Lyapunov exponents and such exponents are uniformly bounded away from zero, then μ also has only positive exponents. In our arguments, the exponential closing property of the driving semiflow is a basic condition, and it is easy to check that every C1-expanding map of a closed manifold obeys this closing property. Consequently, if f is a C1+Hölder local diffeomorphism of a closed manifold and if it is Hölder conjugated to some C1-expanding map, then f is itself expanding. This gives a positive answer to a question suggested by Anatole Katok.

Symmetries of the Space of Linear Symplectic Connections

NASA Astrophysics Data System (ADS)

Fox, Daniel J. F.

2017-01-01

There is constructed a family of Lie algebras that act in a Hamiltonian way on the symplectic affine space of linear symplectic connections on a symplectic manifold. The associated equivariant moment map is a formal sum of the Cahen-Gutt moment map, the Ricci tensor, and a translational term. The critical points of a functional constructed from it interpolate between the equations for preferred symplectic connections and the equations for critical symplectic connections. The commutative algebra of formal sums of symmetric tensors on a symplectic manifold carries a pair of compatible Poisson structures, one induced from the canonical Poisson bracket on the space of functions on the cotangent bundle polynomial in the fibers, and the other induced from the algebraic fiberwise Schouten bracket on the symmetric algebra of each fiber of the cotangent bundle. These structures are shown to be compatible, and the required Lie algebras are constructed as central extensions of their! linear combinations restricted to formal sums of symmetric tensors whose first order term is a multiple of the differential of its zeroth order term.

Fast spatially resolved exhaust gas recirculation (EGR) distribution measurements in an internal combustion engine using absorption spectroscopy.

PubMed

Yoo, Jihyung; Prikhodko, Vitaly; Parks, James E; Perfetto, Anthony; Geckler, Sam; Partridge, William P

2015-09-01

Exhaust gas recirculation (EGR) in internal combustion engines is an effective method of reducing NOx emissions while improving efficiency. However, insufficient mixing between fresh air and exhaust gas can lead to cycle-to-cycle and cylinder-to-cylinder non-uniform charge gas mixtures of a multi-cylinder engine, which can in turn reduce engine performance and efficiency. A sensor packaged into a compact probe was designed, built and applied to measure spatiotemporal EGR distributions in the intake manifold of an operating engine. The probe promotes the development of more efficient and higher-performance engines by resolving high-speed in situ CO2 concentration at various locations in the intake manifold. The study employed mid-infrared light sources tuned to an absorption band of CO2 near 4.3 μm, an industry standard species for determining EGR fraction. The calibrated probe was used to map spatial EGR distributions in an intake manifold with high accuracy and monitor cycle-resolved cylinder-specific EGR fluctuations at a rate of up to 1 kHz.

Quasiparticle Representation of Coherent Nonlinear Optical Signals of Multiexcitons

NASA Astrophysics Data System (ADS)

Fingerhut, Benjamin; Bennet, Kochise; Roslyak, Oleksiy; Mukamel, Shaul

2013-03-01

Elementary excitations of many-Fermion systems can be described within the quasiparticle approach which is widely used in the calculation of transport and optical properties of metals, semiconductors, molecular aggregates and strongly correlated quantum materials. The excitations are then viewed as independent harmonic oscillators where the many-body interactions between the oscillators are mapped into anharmonicities. We present a Green's function approach based on coboson algebra for calculating nonlinear optical signals and apply it onwards the study of two and three exciton states. The method only requires the diagonalization of the single exciton manifold and avoids equations of motion of multi-exciton manifolds. Using coboson algebra many body effects are recast in terms of tetradic exciton-exciton interactions: Coulomb scattering and Pauli exchange. The physical space of Fermions is recovered by singular-value decomposition of the over-complete coboson basis set. The approach is used to calculate third and fifth order quantum coherence optical signals that directly probe correlations in two- and three exciton states and their projections on the two and single exciton manifold.

Fast Spatially Resolved Exhaust Gas Recirculation (EGR) Distribution Measurements in an Internal Combustion Engine Using Absorption Spectroscopy

DOE PAGES

Yoo, Jihyung; Prikhodko, Vitaly; Parks, James E.; ...

2015-09-01

One effective method of reducing NO x emissions while improving efficiency is exhaust gas recirculation (EGR) in internal combustion engines. But, insufficient mixing between fresh air and exhaust gas can lead to cycle-to-cycle and cylinder-to-cylinder nonuniform charge gas mixtures of a multi-cylinder engine, which can in turn reduce engine performance and efficiency. Furthermore, a sensor packaged into a compact probe was designed, built and applied to measure spatiotemporal EGR distributions in the intake manifold of an operating engine. The probe promotes the development of more efficient and higher-performance engines by resolving high-speed in situ CO 2 concentration at various locationsmore » in the intake manifold. Our study employed mid-infrared light sources tuned to an absorption band of CO 2 near 4.3 μm, an industry standard species for determining EGR fraction. The calibrated probe was used to map spatial EGR distributions in an intake manifold with high accuracy and monitor cycle-resolved cylinder-specific EGR fluctuations at a rate of up to 1 kHz.« less

Isospectral drums and simple groups

NASA Astrophysics Data System (ADS)

Thas, Koen

Nearly every known pair of isospectral but nonisometric manifolds — with as most famous members isospectral bounded ℝ-planar domains which makes one “not hear the shape of a drum” [M. Kac, Can one hear the shape of a drum? Amer. Math. Monthly 73(4 part 2) (1966) 1-23] — arise from the (group theoretical) Gassmann-Sunada method. Moreover, all the known ℝ-planar examples (so counter examples to Kac’s question) are constructed through a famous specialization of this method, called transplantation. We first describe a number of very general classes of length equivalent manifolds, with as particular cases isospectral manifolds, in each of the constructions starting from a given example that arises itself from the Gassmann-Sunada method. The constructions include the examples arising from the transplantation technique (and thus in particular the known planar examples). To that end, we introduce four properties — called FF, MAX, PAIR and INV — inspired by natural physical properties (which rule out trivial constructions), that are satisfied for each of the known planar examples. Vice versa, we show that length equivalent manifolds with FF, MAX, PAIR and INV which arise from the Gassmann-Sunada method, must fall under one of our prior constructions, thus describing a precise classification of these objects. Due to the nature of our constructions and properties, a deep connection with finite simple groups occurs which seems, perhaps, rather surprising in the context of this paper. On the other hand, our properties define in some sense physically irreducible pairs of length equivalent manifolds — “atoms” of general pairs of length equivalent manifolds, in that such a general pair of manifolds is patched up out of irreducible pairs — and that is precisely what simple groups are for general groups.

Charting molecular free-energy landscapes with an atlas of collective variables

NASA Astrophysics Data System (ADS)

Hashemian, Behrooz; Millán, Daniel; Arroyo, Marino

2016-11-01

Collective variables (CVs) are a fundamental tool to understand molecular flexibility, to compute free energy landscapes, and to enhance sampling in molecular dynamics simulations. However, identifying suitable CVs is challenging, and is increasingly addressed with systematic data-driven manifold learning techniques. Here, we provide a flexible framework to model molecular systems in terms of a collection of locally valid and partially overlapping CVs: an atlas of CVs. The specific motivation for such a framework is to enhance the applicability and robustness of CVs based on manifold learning methods, which fail in the presence of periodicities in the underlying conformational manifold. More generally, using an atlas of CVs rather than a single chart may help us better describe different regions of conformational space. We develop the statistical mechanics foundation for our multi-chart description and propose an algorithmic implementation. The resulting atlas of data-based CVs are then used to enhance sampling and compute free energy surfaces in two model systems, alanine dipeptide and β-D-glucopyranose, whose conformational manifolds have toroidal and spherical topologies.

Modularity, quaternion-Kähler spaces, and mirror symmetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alexandrov, Sergei; Banerjee, Sibasish

2013-10-15

We provide an explicit twistorial construction of quaternion-Kähler manifolds obtained by deformation of c-map spaces and carrying an isometric action of the modular group SL(2,Z). The deformation is not assumed to preserve any continuous isometry and therefore this construction presents a general framework for describing NS5-brane instanton effects in string compactifications with N= 2 supersymmetry. In this context the modular invariant parametrization of twistor lines found in this work yields the complete non-perturbative mirror map between type IIA and type IIB physical fields.

Assessment of Ice Shape Roughness Using a Self-Orgainizing Map Approach

NASA Technical Reports Server (NTRS)

Mcclain, Stephen T.; Kreeger, Richard E.

2013-01-01

Self-organizing maps are neural-network techniques for representing noisy, multidimensional data aligned along a lower-dimensional and nonlinear manifold. For a large set of noisy data, each element of a finite set of codebook vectors is iteratively moved in the direction of the data closest to the winner codebook vector. Through successive iterations, the codebook vectors begin to align with the trends of the higher-dimensional data. Prior investigations of ice shapes have focused on using self-organizing maps to characterize mean ice forms. The Icing Research Branch has recently acquired a high resolution three dimensional scanner system capable of resolving ice shape surface roughness. A method is presented for the evaluation of surface roughness variations using high-resolution surface scans based on a self-organizing map representation of the mean ice shape. The new method is demonstrated for 1) an 18-in. NACA 23012 airfoil 2 AOA just after the initial ice coverage of the leading 5 of the suction surface of the airfoil, 2) a 21-in. NACA 0012 at 0AOA following coverage of the leading 10 of the airfoil surface, and 3) a cold-soaked 21-in.NACA 0012 airfoil without ice. The SOM method resulted in descriptions of the statistical coverage limits and a quantitative representation of early stages of ice roughness formation on the airfoils. Limitations of the SOM method are explored, and the uncertainty limits of the method are investigated using the non-iced NACA 0012 airfoil measurements.

The para-HK/QK correspondence

NASA Astrophysics Data System (ADS)

Dyckmanns, Malte; Vaughan, Owen

2017-06-01

We generalise the hyper-Kähler/quaternionic Kähler (HK/QK) correspondence to include para-geometries, and present a new concise proof that the target manifold of the HK/QK correspondence is quaternionic Kähler. As an application, we construct one-parameter deformations of the temporal and Euclidean supergravity c-map metrics and show that they are para-quaternionic Kähler.

Leader–follower fixed-time consensus of multi-agent systems with high-order integrator dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tian, Bailing; Zuo, Zongyu; Wang, Hong

The leader-follower fixed-time consensus of high-order multi-agent systems with external disturbances is investigated in this paper. A novel sliding manifold is designed to ensure that the tracking errors converge to zero in a fixed-time during the sliding motion. Then, a distributed control law is designed based on Lyapunov technique to drive the system states to the sliding manifold in finite-time independent of initial conditions. Finally, the efficiency of the proposed method is illustrated by numerical simulations.

On the Circulation Manifold for Two Adjacent Lifting Sections

NASA Technical Reports Server (NTRS)

Zannetti, Luca; Iollo, Angelo

1998-01-01

The circulation functional relative to two adjacent lifting sections is studied for two cases. In the first case we consider two adjacent circles. The circulation is computed as a function of the displacement of the secondary circle along the axis joining the two centers and of the angle of attack of the secondary circle, The gradient of such functional is computed by deriving a set of elliptic functions with respect both to their argument and to their Period. In the second case studied, we considered a wing-flap configuration. The circulation is computed by some implicit mappings, whose differentials with respect to the variation of the geometrical configuration in the physical space are found by divided differences. Configurations giving rise to local maxima and minima in the circulation manifold are presented.

Shape Classification Using Wasserstein Distance for Brain Morphometry Analysis.

PubMed

Su, Zhengyu; Zeng, Wei; Wang, Yalin; Lu, Zhong-Lin; Gu, Xianfeng

2015-01-01

Brain morphometry study plays a fundamental role in medical imaging analysis and diagnosis. This work proposes a novel framework for brain cortical surface classification using Wasserstein distance, based on uniformization theory and Riemannian optimal mass transport theory. By Poincare uniformization theorem, all shapes can be conformally deformed to one of the three canonical spaces: the unit sphere, the Euclidean plane or the hyperbolic plane. The uniformization map will distort the surface area elements. The area-distortion factor gives a probability measure on the canonical uniformization space. All the probability measures on a Riemannian manifold form the Wasserstein space. Given any 2 probability measures, there is a unique optimal mass transport map between them, the transportation cost defines the Wasserstein distance between them. Wasserstein distance gives a Riemannian metric for the Wasserstein space. It intrinsically measures the dissimilarities between shapes and thus has the potential for shape classification. To the best of our knowledge, this is the first. work to introduce the optimal mass transport map to general Riemannian manifolds. The method is based on geodesic power Voronoi diagram. Comparing to the conventional methods, our approach solely depends on Riemannian metrics and is invariant under rigid motions and scalings, thus it intrinsically measures shape distance. Experimental results on classifying brain cortical surfaces with different intelligence quotients demonstrated the efficiency and efficacy of our method.

Schmidt boundaries of foliated space-times

NASA Astrophysics Data System (ADS)

Barletta, Elisabetta; Dragomir, Sorin; Magliaro, Marco

2014-10-01

For every (p+q)-dimensional foliated Lorentzian manifold (M, g, F), where F is a codimension q space-like foliation, we build its Q-completion \\bar{M} and Q-boundary {{\\partial }Q}M. These are analogs, within transverse Lorentzian geometry of foliated manifolds, to the b-completion and b-boundary \\dot{M} (due to (Schmidt 1971 Gen. Relativ. Gravit. 1 269-80)). The bundle morphism {{h}\\bot }:O(M,F,g)\\to O(F,{{g}Q}) (mapping the o(p)+o(1,q-1)-component of the Levi-Civita connection 1-form of (M,g) into the unique torsion-free adapted connection on the bundle of Lorentzian transverse orthonormal frames) is shown to induce a surjective continuous map \\partial {{h}\\bot }:{{\\partial }adt}M\\to {{\\partial }Q}M of the adapted boundary ({{\\partial }adt}M\\subset \\dot{M}) of M onto its Q-boundary. Map \\partial {{h}\\bot } is used to characterize {{\\partial }Q}M as the set of end points {{lim }t\\to {{1-}}}γ (t), in the topology of \\bar{M}, of all Q-incomplete curves γ :[0,1)\\to M. As an application we determine a class {{(\\partial {{h}\\bot })}-1}(P)\\subset \\dot{M} of b-boundary points, where M={R}× (0,m)× {{S}2}, g is Schwartzschild's metric, and F is the codimension two foliation tangent to the Killing vector fields \\partial /\\partial t and \\partial /\\partial \\varphi .

Shape Classification Using Wasserstein Distance for Brain Morphometry Analysis

PubMed Central

Su, Zhengyu; Zeng, Wei; Wang, Yalin; Lu, Zhong-Lin; Gu, Xianfeng

2015-01-01

Brain morphometry study plays a fundamental role in medical imaging analysis and diagnosis. This work proposes a novel framework for brain cortical surface classification using Wasserstein distance, based on uniformization theory and Riemannian optimal mass transport theory. By Poincare uniformization theorem, all shapes can be conformally deformed to one of the three canonical spaces: the unit sphere, the Euclidean plane or the hyperbolic plane. The uniformization map will distort the surface area elements. The area-distortion factor gives a probability measure on the canonical uniformization space. All the probability measures on a Riemannian manifold form the Wasserstein space. Given any 2 probability measures, there is a unique optimal mass transport map between them, the transportation cost defines the Wasserstein distance between them. Wasserstein distance gives a Riemannian metric for the Wasserstein space. It intrinsically measures the dissimilarities between shapes and thus has the potential for shape classification. To the best of our knowledge, this is the first work to introduce the optimal mass transport map to general Riemannian manifolds. The method is based on geodesic power Voronoi diagram. Comparing to the conventional methods, our approach solely depends on Riemannian metrics and is invariant under rigid motions and scalings, thus it intrinsically measures shape distance. Experimental results on classifying brain cortical surfaces with different intelligence quotients demonstrated the efficiency and efficacy of our method. PMID:26221691

Momentum Maps and Stochastic Clebsch Action Principles

NASA Astrophysics Data System (ADS)

Cruzeiro, Ana Bela; Holm, Darryl D.; Ratiu, Tudor S.

2018-01-01

We derive stochastic differential equations whose solutions follow the flow of a stochastic nonlinear Lie algebra operation on a configuration manifold. For this purpose, we develop a stochastic Clebsch action principle, in which the noise couples to the phase space variables through a momentum map. This special coupling simplifies the structure of the resulting stochastic Hamilton equations for the momentum map. In particular, these stochastic Hamilton equations collectivize for Hamiltonians that depend only on the momentum map variable. The Stratonovich equations are derived from the Clebsch variational principle and then converted into Itô form. In comparing the Stratonovich and Itô forms of the stochastic dynamical equations governing the components of the momentum map, we find that the Itô contraction term turns out to be a double Poisson bracket. Finally, we present the stochastic Hamiltonian formulation of the collectivized momentum map dynamics and derive the corresponding Kolmogorov forward and backward equations.

Normal forms for Poisson maps and symplectic groupoids around Poisson transversals

NASA Astrophysics Data System (ADS)

Frejlich, Pedro; Mărcuț, Ioan

2018-03-01

Poisson transversals are submanifolds in a Poisson manifold which intersect all symplectic leaves transversally and symplectically. In this communication, we prove a normal form theorem for Poisson maps around Poisson transversals. A Poisson map pulls a Poisson transversal back to a Poisson transversal, and our first main result states that simultaneous normal forms exist around such transversals, for which the Poisson map becomes transversally linear, and intertwines the normal form data of the transversals. Our second result concerns symplectic integrations. We prove that a neighborhood of a Poisson transversal is integrable exactly when the Poisson transversal itself is integrable, and in that case we prove a normal form theorem for the symplectic groupoid around its restriction to the Poisson transversal, which puts all structure maps in normal form. We conclude by illustrating our results with examples arising from Lie algebras.

Normal forms for Poisson maps and symplectic groupoids around Poisson transversals.

PubMed

Frejlich, Pedro; Mărcuț, Ioan

2018-01-01

Poisson transversals are submanifolds in a Poisson manifold which intersect all symplectic leaves transversally and symplectically. In this communication, we prove a normal form theorem for Poisson maps around Poisson transversals. A Poisson map pulls a Poisson transversal back to a Poisson transversal, and our first main result states that simultaneous normal forms exist around such transversals, for which the Poisson map becomes transversally linear, and intertwines the normal form data of the transversals. Our second result concerns symplectic integrations. We prove that a neighborhood of a Poisson transversal is integrable exactly when the Poisson transversal itself is integrable, and in that case we prove a normal form theorem for the symplectic groupoid around its restriction to the Poisson transversal, which puts all structure maps in normal form. We conclude by illustrating our results with examples arising from Lie algebras.

Unsupervised nonlinear dimensionality reduction machine learning methods applied to multiparametric MRI in cerebral ischemia: preliminary results

NASA Astrophysics Data System (ADS)

Parekh, Vishwa S.; Jacobs, Jeremy R.; Jacobs, Michael A.

2014-03-01

The evaluation and treatment of acute cerebral ischemia requires a technique that can determine the total area of tissue at risk for infarction using diagnostic magnetic resonance imaging (MRI) sequences. Typical MRI data sets consist of T1- and T2-weighted imaging (T1WI, T2WI) along with advanced MRI parameters of diffusion-weighted imaging (DWI) and perfusion weighted imaging (PWI) methods. Each of these parameters has distinct radiological-pathological meaning. For example, DWI interrogates the movement of water in the tissue and PWI gives an estimate of the blood flow, both are critical measures during the evolution of stroke. In order to integrate these data and give an estimate of the tissue at risk or damaged; we have developed advanced machine learning methods based on unsupervised non-linear dimensionality reduction (NLDR) techniques. NLDR methods are a class of algorithms that uses mathematically defined manifolds for statistical sampling of multidimensional classes to generate a discrimination rule of guaranteed statistical accuracy and they can generate a two- or three-dimensional map, which represents the prominent structures of the data and provides an embedded image of meaningful low-dimensional structures hidden in their high-dimensional observations. In this manuscript, we develop NLDR methods on high dimensional MRI data sets of preclinical animals and clinical patients with stroke. On analyzing the performance of these methods, we observed that there was a high of similarity between multiparametric embedded images from NLDR methods and the ADC map and perfusion map. It was also observed that embedded scattergram of abnormal (infarcted or at risk) tissue can be visualized and provides a mechanism for automatic methods to delineate potential stroke volumes and early tissue at risk.

Wave maps from Gödel's universe

NASA Astrophysics Data System (ADS)

Barletta, Elisabetta; Dragomir, Sorin; Magliaro, Marco

2014-10-01

Using a result by Koch (1988 Trans. Am. Math. Soc. 307 827-41) we realize Gödel's universe G_{α }^{4}=({{{R}}^{4}},{{g}_{α}}) as the total space of a principal {R}-bundle over a strictly pseudo-convex CR manifold M3 and exploit the analogy between {{g}_{Yalpha;}} and Fefferman's metric {{F}_{θ}} (Fefferman 1976 Ann. Math. 103 395-416 104 393-4) to show that for any {R}-invariant wave map Φ of G_{α}^{4} into a Riemannian manifold N, the corresponding base map φ :{{M}^{3}}\\to N is subelliptic harmonic, with respect to a canonical choice of contact form θ on M3. We show that the subelliptic Jacobi operator J_{b}^{φ} of ϕ has a discrete Dirichlet spectrum on any bounded domain D\\subset {{M}^{3}} supporting the Poincaré inequality on \\mathop{W}\\limits^{\\circ }{}_{H}^{1,2}(D,{{φ}^{-1}}TN) and Kondrakov compactness, i.e. compactness of the embedding \\mathop{W}\\limits^{\\circ }{}_{H}^{1,2}(D,{{φ }^{-1}}TN)\\hookrightarrow {{L}^{2}}(D,{{φ}^{-1}}TN). We exhibit an explicit solution π :G_{α}^{4}\\to {{M}^{3}} to the wave map system on G_{α}^{4}, of index in{{d}^{Ω}}(π)\\geqslant 1 for any bounded domain Ω \\subset G_{α}^{4}. Mounoud's distance (Mounoud 2001 Differ. Geom. Appl. 15 47-57) d_{{{G}_{0}}, Ω }^{∞}({{g}_{α }}, {{F}_{θ}}) is bounded below by a constant depending only on the rotation frequency of Gödel's universe, thus giving a measure of the bias of {{g}_{α}} from being Fefferman like in the region Ω \\subset {{{R}}^{4}}.

Mapping unstable manifolds using drifters/floats in a Southern Ocean field campaign

NASA Astrophysics Data System (ADS)

Shuckburgh, Emily F.

2012-09-01

Ideas from dynamical systems theory have been used in an observational field campaign in the Southern Ocean to provide information on the mixing structure of the flow. Instantaneous snapshops of data from satellite altimetry provide information concerning surface currents at a scale of 100 km or so. We show that by using time-series of satellite altimetry we are able to deduce reliable information about the structure of the surface flow at scales as small as 10 km or so. This information was used in near-real time to provide an estimate of the location of stable and unstable manifolds in the vicinity of the Antarctic Circumpolar Current. As part of a large U.K./U.S. observational field campaign (DIMES: Diapycnal and Isopycnal Mixing Experiment in the Southern Ocean) a number of drifters and floats were then released (at the surface and at a depth of approximately 1 km) close to the estimated hyperbolic point at the intersection of the two manifolds, in several locations with apparently different dynamical characteristics. The subsequent trajectories of the drifters/floats has allowed the unstable manifolds to be tracked, and the relative separation of pairs of floats has allowed an estimation of Lyapunov exponents. The results of these deployments have given insight into the strengths and limitations of the satellite data which does not resolve small scales in the velocity field, and have elucidated the transport and mixing structure of the Southern Ocean at the surface and at depth.

Dynamics of an advertising competition model with sales promotion

NASA Astrophysics Data System (ADS)

Jiang, Hui; Feng, Zhaosheng; Jiang, Guirong

2017-01-01

In this paper, an advertising competition model with sales promotion is constructed and investigated. Conditions of the existence and stability of period-T solutions are obtained by means of the discrete map. Flip bifurcation is analyzed by using the center manifold theory and three sales promotion strategies are discussed. Example and numerical simulations are illustrated which agree well with our theoretical analysis.

Helmholtz, Riemann, and the Sirens: Sound, Color, and the "Problem of Space"

NASA Astrophysics Data System (ADS)

Pesic, Peter

2013-09-01

Emerging from music and the visual arts, questions about hearing and seeing deeply affected Hermann Helmholtz's and Bernhard Riemann's contributions to what became called the "problem of space [ Raumproblem]," which in turn influenced Albert Einstein's approach to general relativity. Helmholtz's physiological investigations measured the time dependence of nerve conduction and mapped the three-dimensional manifold of color sensation. His concurrent studies on hearing illuminated musical evidence through experiments with mechanical sirens that connect audible with visible phenomena, especially how the concept of frequency unifies motion, velocity, and pitch. Riemann's critique of Helmholtz's work on hearing led Helmholtz to respond and study Riemann's then-unpublished lecture on the foundations of geometry. During 1862-1870, Helmholtz applied his findings on the manifolds of hearing and seeing to the Raumproblem by supporting the quadratic distance relation Riemann had assumed as his fundamental hypothesis about geometrical space. Helmholtz also drew a "close analogy … in all essential relations between the musical scale and space." These intersecting studies of hearing and seeing thus led to reconsideration and generalization of the very concept of "space," which Einstein shaped into the general manifold of relativistic space-time.

3D surface parameterization using manifold learning for medial shape representation

NASA Astrophysics Data System (ADS)

Ward, Aaron D.; Hamarneh, Ghassan

2007-03-01

The choice of 3D shape representation for anatomical structures determines the effectiveness with which segmentation, visualization, deformation, and shape statistics are performed. Medial axis-based shape representations have attracted considerable attention due to their inherent ability to encode information about the natural geometry of parts of the anatomy. In this paper, we propose a novel approach, based on nonlinear manifold learning, to the parameterization of medial sheets and object surfaces based on the results of skeletonization. For each single-sheet figure in an anatomical structure, we skeletonize the figure, and classify its surface points according to whether they lie on the upper or lower surface, based on their relationship to the skeleton points. We then perform nonlinear dimensionality reduction on the skeleton, upper, and lower surface points, to find the intrinsic 2D coordinate system of each. We then center a planar mesh over each of the low-dimensional representations of the points, and map the meshes back to 3D using the mappings obtained by manifold learning. Correspondence between mesh vertices, established in their intrinsic 2D coordinate spaces, is used in order to compute the thickness vectors emanating from the medial sheet. We show results of our algorithm on real brain and musculoskeletal structures extracted from MRI, as well as an artificial multi-sheet example. The main advantages to this method are its relative simplicity and noniterative nature, and its ability to correctly compute nonintersecting thickness vectors for a medial sheet regardless of both the amount of coincident bending and thickness in the object, and of the incidence of local concavities and convexities in the object's surface.

Direct biomechanical modeling of trabecular bone using a nonlinear manifold-based volumetric representation

NASA Astrophysics Data System (ADS)

Jin, Dakai; Lu, Jia; Zhang, Xiaoliu; Chen, Cheng; Bai, ErWei; Saha, Punam K.

2017-03-01

Osteoporosis is associated with increased fracture risk. Recent advancement in the area of in vivo imaging allows segmentation of trabecular bone (TB) microstructures, which is a known key determinant of bone strength and fracture risk. An accurate biomechanical modelling of TB micro-architecture provides a comprehensive summary measure of bone strength and fracture risk. In this paper, a new direct TB biomechanical modelling method using nonlinear manifold-based volumetric reconstruction of trabecular network is presented. It is accomplished in two sequential modules. The first module reconstructs a nonlinear manifold-based volumetric representation of TB networks from three-dimensional digital images. Specifically, it starts with the fuzzy digital segmentation of a TB network, and computes its surface and curve skeletons. An individual trabecula is identified as a topological segment in the curve skeleton. Using geometric analysis, smoothing and optimization techniques, the algorithm generates smooth, curved, and continuous representations of individual trabeculae glued at their junctions. Also, the method generates a geometrically consistent TB volume at junctions. In the second module, a direct computational biomechanical stress-strain analysis is applied on the reconstructed TB volume to predict mechanical measures. The accuracy of the method was examined using micro-CT imaging of cadaveric distal tibia specimens (N = 12). A high linear correlation (r = 0.95) between TB volume computed using the new manifold-modelling algorithm and that directly derived from the voxel-based micro-CT images was observed. Young's modulus (YM) was computed using direct mechanical analysis on the TB manifold-model over a cubical volume of interest (VOI), and its correlation with the YM, computed using micro-CT based conventional finite-element analysis over the same VOI, was examined. A moderate linear correlation (r = 0.77) was observed between the two YM measures. This preliminary results show the accuracy of the new nonlinear manifold modelling algorithm for TB, and demonstrate the feasibility of a new direct mechanical strain-strain analysis on a nonlinear manifold model of a highly complex biological structure.

Estimation for bilinear stochastic systems

NASA Technical Reports Server (NTRS)

Willsky, A. S.; Marcus, S. I.

1974-01-01

Three techniques for the solution of bilinear estimation problems are presented. First, finite dimensional optimal nonlinear estimators are presented for certain bilinear systems evolving on solvable and nilpotent lie groups. Then the use of harmonic analysis for estimation problems evolving on spheres and other compact manifolds is investigated. Finally, an approximate estimation technique utilizing cumulants is discussed.

State-to-state collisional interelectronic and intraelectronic energy transfer involving CN A 2Π v=3 and X 2Σ+ v=7 rotational levels

NASA Astrophysics Data System (ADS)

Jihua, Guo; Ali, Ashraf; Dagdigian, Paul J.

1986-12-01

Collisional transfer within the CN A 2Π v=3 vibrational manifold and to the X 2Σ+ v=7 manifold has been studied with initial and final rotational state resolution by an optical-optical double resonance technique. Despite the large energy gap between these two manifolds, the interelectronic cross sections are significant for only a relatively small range of ΔJ, and there is no observable propensity for energy resonant, large ΔJ transitions. The even-odd alternation vs N, observed previously in vA=7 collisions [N. Furio, A. Ali, and P. J. Dagdigian, J. Chem. Phys. 85, 3860 (1986)] and indicative of the near homonuclear form of the CN-Ar interaction potentials, is even more pronounced here for vA=3. The relative rate of intraelectronic and interelectronic energy transfer for the vA=3 N=6 F1f initial level was found to be comparable to that for the corresponding vA=7 level, despite the smaller Franck-Condon factor and larger energy gap to the neighboring vX=vA-4 manifold for the former.

Excitable Neurons, Firing Threshold Manifolds and Canards

PubMed Central

2013-01-01

We investigate firing threshold manifolds in a mathematical model of an excitable neuron. The model analyzed investigates the phenomenon of post-inhibitory rebound spiking due to propofol anesthesia and is adapted from McCarthy et al. (SIAM J. Appl. Dyn. Syst. 11(4):1674–1697, [2012]). Propofol modulates the decay time-scale of an inhibitory GABAa synaptic current. Interestingly, this system gives rise to rebound spiking within a specific range of propofol doses. Using techniques from geometric singular perturbation theory, we identify geometric structures, known as canards of folded saddle-type, which form the firing threshold manifolds. We find that the position and orientation of the canard separatrix is propofol dependent. Thus, the speeds of relevant slow synaptic processes are encoded within this geometric structure. We show that this behavior cannot be understood using a static, inhibitory current step protocol, which can provide a single threshold for rebound spiking but cannot explain the observed cessation of spiking for higher propofol doses. We then compare the analyses of dynamic and static synaptic inhibition, showing how the firing threshold manifolds of each relate, and why a current step approach is unable to fully capture the behavior of this model. PMID:23945278

Spaces of differential forms and maps with controlled distortion

NASA Astrophysics Data System (ADS)

Vodop'yanov, Sergei K.

2010-09-01

We study necessary and sufficient conditions for an approximately differentiable map f\\colon M\\to M' between Riemannian manifolds to induce a bounded transfer operator of differential forms with respect to the norms of Lebesgue spaces. As a corollary, we see that every homeomorphism f\\colon M\\to M' of class \\operatorname{ACL}(M) whose transfer operator of differential forms with norm in L_p is an isomorphism must necessarily be either quasi-conformal or quasi-isometric. We give some applications of our results to the study of the functoriality of cohomology in Lebesgue spaces.

Periodicity and Chaos Amidst Twisting and Folding in Two-Dimensional Maps

NASA Astrophysics Data System (ADS)

Garst, Swier; Sterk, Alef E.

We study the dynamics of three planar, noninvertible maps which rotate and fold the plane. Two maps are inspired by real-world applications whereas the third map is constructed to serve as a toy model for the other two maps. The dynamics of the three maps are remarkably similar. A stable fixed point bifurcates through a Hopf-Neĭmark-Sacker which leads to a countably infinite set of resonance tongues in the parameter plane of the map. Within a resonance tongue a periodic point can bifurcate through a period-doubling cascade. At the end of the cascade we detect Hénon-like attractors which are conjectured to be the closure of the unstable manifold of a saddle periodic point. These attractors have a folded structure which can be explained by means of the concept of critical lines. We also detect snap-back repellers which can either coexist with Hénon-like attractors or which can be formed when the saddle-point of a Hénon-like attractor becomes a source.

Geospatial techniques for allocating vulnerability zoning of geohazards along the Karakorum Highway, Gilgit-Baltistan-Pakistan

NASA Astrophysics Data System (ADS)

Khan, K. M.; Rashid, S.; Yaseen, M.; Ikram, M.

2016-12-01

The Karakoram Highway (KKH) 'eighth wonder of the world', constructed and completed by the consent of Pakistan and China in 1979 as a Friendship Highway. It connect Gilgit-Baltistan, a strategically prominent region of Pakistan, with Xinjiang region in China. Due to manifold geology/geomorphology, soil formation, steep slopes, climate change well as unsustainable anthropogenic activities, still, KKH is remarkably vulnerable to natural hazards i.e. land subsistence, landslides, erosion, rock fall, floods, debris flows, cyclical torrential rainfall and snowfall, lake outburst etc. Most of the time these geohazard's damaging effects jeopardized the life in the region. To ascertain the nature and frequency of the disaster and vulnerability zoning, a rating and management (logistic) analysis were made to investigate the spatiotemporal sharing of the natural hazard. The substantial dynamics of the physiograpy, geology, geomorphology, soils and climate were carefully understand while slope, aspect, elevation, profile curvature and rock hardness was calculated by different techniques. To assess the nature and intensity geospatial analysis were conducted and magnitude of every factor was gauged by using logistic regression. Moreover, ever relative variable was integrated in the evaluation process. Logistic regression and geospatial techniques were used to map the geohazard vulnerability zoning (GVZ). The GVZ model findings were endorsed by the reviews of documented hazards in the current years and the precision was realized more than 88.1 %. The study has proved the model authentication by highlighting the comfortable indenture among the vulnerability mapping and past documented hazards. By using a receiver operating characteristic curve, the logistic regression model made satisfactory results. The outcomes will be useful in sustainable land use and infrastructure planning, mainly in high risk zones for reduceing economic damages and community betterment.

76 FR 17757 - Airworthiness Directives; Thielert Aircraft Engines GmbH Models TAE 125-01, TAE 125-02-99, and...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-31

...: Service experience has shown that a case of FADEC channel B manifold air pressure (MAP) sensor hose... combustion chamber and thus the available power of the engine. A change in FADEC software version 2.91 will..., previous software versions allow--under certain conditions and on DA 42 aircraft only--the initiation of a...

Topological data analysis of contagion maps for examining spreading processes on networks.

PubMed

Taylor, Dane; Klimm, Florian; Harrington, Heather A; Kramár, Miroslav; Mischaikow, Konstantin; Porter, Mason A; Mucha, Peter J

2015-07-21

Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth's surface; however, in modern contagions long-range edges-for example, due to airline transportation or communication media-allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct 'contagion maps' that use multiple contagions on a network to map the nodes as a point cloud. By analysing the topology, geometry and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modelling, forecast and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.

Topological data analysis of contagion maps for examining spreading processes on networks

NASA Astrophysics Data System (ADS)

Taylor, Dane; Klimm, Florian; Harrington, Heather A.; Kramár, Miroslav; Mischaikow, Konstantin; Porter, Mason A.; Mucha, Peter J.

2015-07-01

Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth's surface; however, in modern contagions long-range edges--for example, due to airline transportation or communication media--allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct `contagion maps' that use multiple contagions on a network to map the nodes as a point cloud. By analysing the topology, geometry and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modelling, forecast and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.

[Multi-Target Recognition of Internal and External Defects of Potato by Semi-Transmission Hyperspectral Imaging and Manifold Learning Algorithm].

PubMed

Huang, Tao; Li, Xiao-yu; Jin, Rui; Ku, Jing; Xu, Sen-miao; Xu, Meng-ling; Wu, Zhen-zhong; Kong, De-guo

2015-04-01

The present paper put forward a non-destructive detection method which combines semi-transmission hyperspectral imaging technology with manifold learning dimension reduction algorithm and least squares support vector machine (LSSVM) to recognize internal and external defects in potatoes simultaneously. Three hundred fifteen potatoes were bought in farmers market as research object, and semi-transmission hyperspectral image acquisition system was constructed to acquire the hyperspectral images of normal external defects (bud and green rind) and internal defect (hollow heart) potatoes. In order to conform to the actual production, defect part is randomly put right, side and back to the acquisition probe when the hyperspectral images of external defects potatoes are acquired. The average spectrums (390-1,040 nm) were extracted from the region of interests for spectral preprocessing. Then three kinds of manifold learning algorithm were respectively utilized to reduce the dimension of spectrum data, including supervised locally linear embedding (SLLE), locally linear embedding (LLE) and isometric mapping (ISOMAP), the low-dimensional data gotten by manifold learning algorithms is used as model input, Error Correcting Output Code (ECOC) and LSSVM were combined to develop the multi-target classification model. By comparing and analyzing results of the three models, we concluded that SLLE is the optimal manifold learning dimension reduction algorithm, and the SLLE-LSSVM model is determined to get the best recognition rate for recognizing internal and external defects potatoes. For test set data, the single recognition rate of normal, bud, green rind and hollow heart potato reached 96.83%, 86.96%, 86.96% and 95% respectively, and he hybrid recognition rate was 93.02%. The results indicate that combining the semi-transmission hyperspectral imaging technology with SLLE-LSSVM is a feasible qualitative analytical method which can simultaneously recognize the internal and external defects potatoes and also provide technical reference for rapid on-line non-destructive detecting of the internal and external defects potatoes.

Characterization of fiber-forming peptides and proteins by means of atomic force microscopy.

PubMed

Creasey, Rhiannon G; Gibson, Christopher T; Voelcker, Nicolas H

2012-05-01

The atomic force microscope (AFM) is widely used in biological sciences due to its ability to perform imaging experiments at high resolution in a physiological environment, without special sample preparation such as fixation or staining. AFM is unique, in that it allows single molecule information of mechanical properties and molecular recognition to be gathered. This review sets out to identify methodological applications of AFM for characterization of fiber-forming proteins and peptides. The basics of AFM operation are detailed, with in-depth information for any life scientist to get a grasp on AFM capabilities. It also briefly describes antibody recognition imaging and mapping of nanomechanical properties on biological samples. Subsequently, examples of AFM application to fiber-forming natural proteins, and fiber-forming synthetic peptides are given. Here, AFM is used primarily for structural characterization of fibers in combination with other techniques, such as circular dichroism and fluorescence spectroscopy. More recent developments in antibody recognition imaging to identify constituents of protein fibers formed in human disease are explored. This review, as a whole, seeks to encourage the life scientists dealing with protein aggregation phenomena to consider AFM as a part of their research toolkit, by highlighting the manifold capabilities of this technique.

Spectral Quasi-Equilibrium Manifold for Chemical Kinetics.

PubMed

Kooshkbaghi, Mahdi; Frouzakis, Christos E; Boulouchos, Konstantinos; Karlin, Iliya V

2016-05-26

The Spectral Quasi-Equilibrium Manifold (SQEM) method is a model reduction technique for chemical kinetics based on entropy maximization under constraints built by the slowest eigenvectors at equilibrium. The method is revisited here and discussed and validated through the Michaelis-Menten kinetic scheme, and the quality of the reduction is related to the temporal evolution and the gap between eigenvalues. SQEM is then applied to detailed reaction mechanisms for the homogeneous combustion of hydrogen, syngas, and methane mixtures with air in adiabatic constant pressure reactors. The system states computed using SQEM are compared with those obtained by direct integration of the detailed mechanism, and good agreement between the reduced and the detailed descriptions is demonstrated. The SQEM reduced model of hydrogen/air combustion is also compared with another similar technique, the Rate-Controlled Constrained-Equilibrium (RCCE). For the same number of representative variables, SQEM is found to provide a more accurate description.

Adaptive Shape Kernel-Based Mean Shift Tracker in Robot Vision System

PubMed Central

2016-01-01

This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. We perform nonlinear manifold learning technique to obtain the low-dimensional shape space which is trained by training data with the same view as the tracking video. The proposed kernel searches the shape in the low-dimensional shape space obtained by nonlinear manifold learning technique and constructs the adaptive kernel shape in the high-dimensional shape space. It can improve mean shift tracker performance to track object position and object contour and avoid the background clutter. In the experimental part, we take the walking human as example to validate that our method is accurate and robust to track human position and describe human contour. PMID:27379165

Homological Order in Three and Four dimensions: Wilson Algebra, Entanglement Entropy and Twist Defects

NASA Astrophysics Data System (ADS)

Roy, Abhishek; Chen, Xiao; Teo, Jeffrey

2013-03-01

We investigate homological orders in two, three and four dimensions by studying Zk toric code models on simplicial, cellular or in general differential complexes. The ground state degeneracy is obtained from Wilson loop and surface operators, and the homological intersection form. We compute these for a series of closed 3 and 4 dimensional manifolds and study the projective representations of mapping class groups (modular transformations). Braiding statistics between point and string excitations in (3+1)-dimensions or between dual string excitations in (4+1)-dimensions are topologically determined by the higher dimensional linking number, and can be understood by an effective topological field theory. An algorithm for calculating entanglemnent entropy of any bipartition of closed manifolds is presented, and its topological signature is completely characterized homologically. Extrinsic twist defects (or disclinations) are studied in 2,3 and 4 dimensions and are shown to carry exotic fusion and braiding properties. Simons Fellowship

Identical phase oscillators with global sinusoidal coupling evolve by Mobius group action.

PubMed

Marvel, Seth A; Mirollo, Renato E; Strogatz, Steven H

2009-12-01

Systems of N identical phase oscillators with global sinusoidal coupling are known to display low-dimensional dynamics. Although this phenomenon was first observed about 20 years ago, its underlying cause has remained a puzzle. Here we expose the structure working behind the scenes of these systems by proving that the governing equations are generated by the action of the Mobius group, a three-parameter subgroup of fractional linear transformations that map the unit disk to itself. When there are no auxiliary state variables, the group action partitions the N-dimensional state space into three-dimensional invariant manifolds (the group orbits). The N-3 constants of motion associated with this foliation are the N-3 functionally independent cross ratios of the oscillator phases. No further reduction is possible, in general; numerical experiments on models of Josephson junction arrays suggest that the invariant manifolds often contain three-dimensional regions of neutrally stable chaos.

Mapping the Complete Reaction Path of a Complex Photochemical Reaction.

PubMed

Smith, Adam D; Warne, Emily M; Bellshaw, Darren; Horke, Daniel A; Tudorovskya, Maria; Springate, Emma; Jones, Alfred J H; Cacho, Cephise; Chapman, Richard T; Kirrander, Adam; Minns, Russell S

2018-05-04

We probe the dynamics of dissociating CS_{2} molecules across the entire reaction pathway upon excitation. Photoelectron spectroscopy measurements using laboratory-generated femtosecond extreme ultraviolet pulses monitor the competing dissociation, internal conversion, and intersystem crossing dynamics. Dissociation occurs either in the initially excited singlet manifold or, via intersystem crossing, in the triplet manifold. Both product channels are monitored and show that, despite being more rapid, the singlet dissociation is the minor product and that triplet state products dominate the final yield. We explain this by a consideration of accurate potential energy curves for both the singlet and triplet states. We propose that rapid internal conversion stabilizes the singlet population dynamically, allowing for singlet-triplet relaxation via intersystem crossing and the efficient formation of spin-forbidden dissociation products on longer timescales. The study demonstrates the importance of measuring the full reaction pathway for defining accurate reaction mechanisms.

Mapping the Complete Reaction Path of a Complex Photochemical Reaction

NASA Astrophysics Data System (ADS)

Smith, Adam D.; Warne, Emily M.; Bellshaw, Darren; Horke, Daniel A.; Tudorovskya, Maria; Springate, Emma; Jones, Alfred J. H.; Cacho, Cephise; Chapman, Richard T.; Kirrander, Adam; Minns, Russell S.

2018-05-01

We probe the dynamics of dissociating CS2 molecules across the entire reaction pathway upon excitation. Photoelectron spectroscopy measurements using laboratory-generated femtosecond extreme ultraviolet pulses monitor the competing dissociation, internal conversion, and intersystem crossing dynamics. Dissociation occurs either in the initially excited singlet manifold or, via intersystem crossing, in the triplet manifold. Both product channels are monitored and show that, despite being more rapid, the singlet dissociation is the minor product and that triplet state products dominate the final yield. We explain this by a consideration of accurate potential energy curves for both the singlet and triplet states. We propose that rapid internal conversion stabilizes the singlet population dynamically, allowing for singlet-triplet relaxation via intersystem crossing and the efficient formation of spin-forbidden dissociation products on longer timescales. The study demonstrates the importance of measuring the full reaction pathway for defining accurate reaction mechanisms.

Statistical Exploration of Electronic Structure of Molecules from Quantum Monte-Carlo Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prabhat, Mr; Zubarev, Dmitry; Lester, Jr., William A.

In this report, we present results from analysis of Quantum Monte Carlo (QMC) simulation data with the goal of determining internal structure of a 3N-dimensional phase space of an N-electron molecule. We are interested in mining the simulation data for patterns that might be indicative of the bond rearrangement as molecules change electronic states. We examined simulation output that tracks the positions of two coupled electrons in the singlet and triplet states of an H2 molecule. The electrons trace out a trajectory, which was analyzed with a number of statistical techniques. This project was intended to address the following scientificmore » questions: (1) Do high-dimensional phase spaces characterizing electronic structure of molecules tend to cluster in any natural way? Do we see a change in clustering patterns as we explore different electronic states of the same molecule? (2) Since it is hard to understand the high-dimensional space of trajectories, can we project these trajectories to a lower dimensional subspace to gain a better understanding of patterns? (3) Do trajectories inherently lie in a lower-dimensional manifold? Can we recover that manifold? After extensive statistical analysis, we are now in a better position to respond to these questions. (1) We definitely see clustering patterns, and differences between the H2 and H2tri datasets. These are revealed by the pamk method in a fairly reliable manner and can potentially be used to distinguish bonded and non-bonded systems and get insight into the nature of bonding. (2) Projecting to a lower dimensional subspace ({approx}4-5) using PCA or Kernel PCA reveals interesting patterns in the distribution of scalar values, which can be related to the existing descriptors of electronic structure of molecules. Also, these results can be immediately used to develop robust tools for analysis of noisy data obtained during QMC simulations (3) All dimensionality reduction and estimation techniques that we tried seem to indicate that one needs 4 or 5 components to account for most of the variance in the data, hence this 5D dataset does not necessarily lie on a well-defined, low dimensional manifold. In terms of specific clustering techniques, K-means was generally useful in exploring the dataset. The partition around medoids (pam) technique produced the most definitive results for our data showing distinctive patterns for both a sample of the complete data and time-series. The gap statistic with tibshirani criteria did not provide any distinction across the 2 dataset. The gap statistic w/DandF criteria, Model based clustering and hierarchical modeling simply failed to run on our datasets. Thankfully, the vanilla PCA technique was successful in handling our entire dataset. PCA revealed some interesting patterns for the scalar value distribution. Kernel PCA techniques (vanilladot, RBF, Polynomial) and MDS failed to run on the entire dataset, or even a significant fraction of the dataset, and we resorted to creating an explicit feature map followed by conventional PCA. Clustering using K-means and PAM in the new basis set seems to produce promising results. Understanding the new basis set in the scientific context of the problem is challenging, and we are currently working to further examine and interpret the results.« less

Lectures on Kähler Geometry - Series: London Mathematical Society Student Texts (No. 69)

NASA Astrophysics Data System (ADS)

Moroianu, Andrei

2004-03-01

Kähler geometry is a beautiful and intriguing area of mathematics, of substantial research interest to both mathematicians and physicists. This self-contained graduate text provides a concise and accessible introduction to the topic. The book begins with a review of basic differential geometry, before moving on to a description of complex manifolds and holomorphic vector bundles. Kähler manifolds are discussed from the point of view of Riemannian geometry, and Hodge and Dolbeault theories are outlined, together with a simple proof of the famous Kähler identities. The final part of the text studies several aspects of compact Kähler manifolds: the Calabi conjecture, Weitzenböck techniques, Calabi Yau manifolds, and divisors. All sections of the book end with a series of exercises and students and researchers working in the fields of algebraic and differential geometry and theoretical physics will find that the book provides them with a sound understanding of this theory. The first graduate-level text on Kähler geometry, providing a concise introduction for both mathematicians and physicists with a basic knowledge of calculus in several variables and linear algebra Over 130 exercises and worked examples Self-contained and presents varying viewpoints including Riemannian, complex and algebraic

Fault Diagnosis for Rolling Bearings under Variable Conditions Based on Visual Cognition

PubMed Central

Cheng, Yujie; Zhou, Bo; Lu, Chen; Yang, Chao

2017-01-01

Fault diagnosis for rolling bearings has attracted increasing attention in recent years. However, few studies have focused on fault diagnosis for rolling bearings under variable conditions. This paper introduces a fault diagnosis method for rolling bearings under variable conditions based on visual cognition. The proposed method includes the following steps. First, the vibration signal data are transformed into a recurrence plot (RP), which is a two-dimensional image. Then, inspired by the visual invariance characteristic of the human visual system (HVS), we utilize speed up robust feature to extract fault features from the two-dimensional RP and generate a 64-dimensional feature vector, which is invariant to image translation, rotation, scaling variation, etc. Third, based on the manifold perception characteristic of HVS, isometric mapping, a manifold learning method that can reflect the intrinsic manifold embedded in the high-dimensional space, is employed to obtain a low-dimensional feature vector. Finally, a classical classification method, support vector machine, is utilized to realize fault diagnosis. Verification data were collected from Case Western Reserve University Bearing Data Center, and the experimental result indicates that the proposed fault diagnosis method based on visual cognition is highly effective for rolling bearings under variable conditions, thus providing a promising approach from the cognitive computing field. PMID:28772943

Optimal source coding, removable noise elimination, and natural coordinate system construction for general vector sources using replicator neural networks

NASA Astrophysics Data System (ADS)

Hecht-Nielsen, Robert

1997-04-01

A new universal one-chart smooth manifold model for vector information sources is introduced. Natural coordinates (a particular type of chart) for such data manifolds are then defined. Uniformly quantized natural coordinates form an optimal vector quantization code for a general vector source. Replicator neural networks (a specialized type of multilayer perceptron with three hidden layers) are the introduced. As properly configured examples of replicator networks approach minimum mean squared error (e.g., via training and architecture adjustment using randomly chosen vectors from the source), these networks automatically develop a mapping which, in the limit, produces natural coordinates for arbitrary source vectors. The new concept of removable noise (a noise model applicable to a wide variety of real-world noise processes) is then discussed. Replicator neural networks, when configured to approach minimum mean squared reconstruction error (e.g., via training and architecture adjustment on randomly chosen examples from a vector source, each with randomly chosen additive removable noise contamination), in the limit eliminate removable noise and produce natural coordinates for the data vector portions of the noise-corrupted source vectors. Consideration regarding selection of the dimension of a data manifold source model and the training/configuration of replicator neural networks are discussed.

Direct observation of multistep energy transfer in LHCII with fifth-order 3D electronic spectroscopy.

PubMed

Zhang, Zhengyang; Lambrev, Petar H; Wells, Kym L; Garab, Győző; Tan, Howe-Siang

2015-07-31

During photosynthesis, sunlight is efficiently captured by light-harvesting complexes, and the excitation energy is then funneled towards the reaction centre. These photosynthetic excitation energy transfer (EET) pathways are complex and proceed in a multistep fashion. Ultrafast two-dimensional electronic spectroscopy (2DES) is an important tool to study EET processes in photosynthetic complexes. However, the multistep EET processes can only be indirectly inferred by correlating different cross peaks from a series of 2DES spectra. Here we directly observe multistep EET processes in LHCII using ultrafast fifth-order three-dimensional electronic spectroscopy (3DES). We measure cross peaks in 3DES spectra of LHCII that directly indicate energy transfer from excitons in the chlorophyll b (Chl b) manifold to the low-energy level chlorophyll a (Chl a) via mid-level Chl a energy states. This new spectroscopic technique allows scientists to move a step towards mapping the complete complex EET processes in photosynthetic systems.

Beyond union of subspaces: Subspace pursuit on Grassmann manifold for data representation

DOE PAGES

Shen, Xinyue; Krim, Hamid; Gu, Yuantao

2016-03-01

Discovering the underlying structure of a high-dimensional signal or big data has always been a challenging topic, and has become harder to tackle especially when the observations are exposed to arbitrary sparse perturbations. Here in this paper, built on the model of a union of subspaces (UoS) with sparse outliers and inspired by a basis pursuit strategy, we exploit the fundamental structure of a Grassmann manifold, and propose a new technique of pursuing the subspaces systematically by solving a non-convex optimization problem using the alternating direction method of multipliers. This problem as noted is further complicated by non-convex constraints onmore » the Grassmann manifold, as well as the bilinearity in the penalty caused by the subspace bases and coefficients. Nevertheless, numerical experiments verify that the proposed algorithm, which provides elegant solutions to the sub-problems in each step, is able to de-couple the subspaces and pursue each of them under time-efficient parallel computation.« less

Multifractal vector fields and stochastic Clifford algebra.

PubMed

Schertzer, Daniel; Tchiguirinskaia, Ioulia

2015-12-01

In the mid 1980s, the development of multifractal concepts and techniques was an important breakthrough for complex system analysis and simulation, in particular, in turbulence and hydrology. Multifractals indeed aimed to track and simulate the scaling singularities of the underlying equations instead of relying on numerical, scale truncated simulations or on simplified conceptual models. However, this development has been rather limited to deal with scalar fields, whereas most of the fields of interest are vector-valued or even manifold-valued. We show in this paper that the combination of stable Lévy processes with Clifford algebra is a good candidate to bridge up the present gap between theory and applications. We show that it indeed defines a convenient framework to generate multifractal vector fields, possibly multifractal manifold-valued fields, based on a few fundamental and complementary properties of Lévy processes and Clifford algebra. In particular, the vector structure of these algebra is much more tractable than the manifold structure of symmetry groups while the Lévy stability grants a given statistical universality.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schertzer, Daniel, E-mail: Daniel.Schertzer@enpc.fr; Tchiguirinskaia, Ioulia, E-mail: Ioulia.Tchiguirinskaia@enpc.fr

In the mid 1980s, the development of multifractal concepts and techniques was an important breakthrough for complex system analysis and simulation, in particular, in turbulence and hydrology. Multifractals indeed aimed to track and simulate the scaling singularities of the underlying equations instead of relying on numerical, scale truncated simulations or on simplified conceptual models. However, this development has been rather limited to deal with scalar fields, whereas most of the fields of interest are vector-valued or even manifold-valued. We show in this paper that the combination of stable Lévy processes with Clifford algebra is a good candidate to bridge upmore » the present gap between theory and applications. We show that it indeed defines a convenient framework to generate multifractal vector fields, possibly multifractal manifold-valued fields, based on a few fundamental and complementary properties of Lévy processes and Clifford algebra. In particular, the vector structure of these algebra is much more tractable than the manifold structure of symmetry groups while the Lévy stability grants a given statistical universality.« less

Two-stage sparse coding of region covariance via Log-Euclidean kernels to detect saliency.

PubMed

Zhang, Ying-Ying; Yang, Cai; Zhang, Ping

2017-05-01

In this paper, we present a novel bottom-up saliency detection algorithm from the perspective of covariance matrices on a Riemannian manifold. Each superpixel is described by a region covariance matrix on Riemannian Manifolds. We carry out a two-stage sparse coding scheme via Log-Euclidean kernels to extract salient objects efficiently. In the first stage, given background dictionary on image borders, sparse coding of each region covariance via Log-Euclidean kernels is performed. The reconstruction error on the background dictionary is regarded as the initial saliency of each superpixel. In the second stage, an improvement of the initial result is achieved by calculating reconstruction errors of the superpixels on foreground dictionary, which is extracted from the first stage saliency map. The sparse coding in the second stage is similar to the first stage, but is able to effectively highlight the salient objects uniformly from the background. Finally, three post-processing methods-highlight-inhibition function, context-based saliency weighting, and the graph cut-are adopted to further refine the saliency map. Experiments on four public benchmark datasets show that the proposed algorithm outperforms the state-of-the-art methods in terms of precision, recall and mean absolute error, and demonstrate the robustness and efficiency of the proposed method. Copyright © 2017 Elsevier Ltd. All rights reserved.

Emergence of gravity, fermion, gauge and Chern-Simons fields during formation of N-dimensional manifolds from joining point-like ones

NASA Astrophysics Data System (ADS)

Sepehri, Alireza; Shoorvazi, Somayyeh

In this paper, we will consider the birth and evolution of fields during formation of N-dimensional manifolds from joining point-like ones. We will show that at the beginning, only there are point-like manifolds which some strings are attached to them. By joining these manifolds, 1-dimensional manifolds are appeared and gravity, fermion, and gauge fields are emerged. By coupling these manifolds, higher dimensional manifolds are produced and higher orders of fermion, gauge fields and gravity are emerged. By decaying N-dimensional manifold, two child manifolds and a Chern-Simons one are born and anomaly is emerged. The Chern-Simons manifold connects two child manifolds and leads to the energy transmission from the bulk to manifolds and their expansion. We show that F-gravity can be emerged during the formation of N-dimensional manifold from point-like manifolds. This type of F-gravity includes both type of fermionic and bosonic gravity. G-fields and also C-fields which are produced by fermionic strings produce extra energy and change the gravity.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Means, Gregory Scott; Boardman, Gregory Allen; Berry, Jonathan Dwight

A combustor for a gas turbine generally includes a radial flow fuel nozzle having a fuel distribution manifold, and a fuel injection manifold axially separated from the fuel distribution manifold. The fuel injection manifold generally includes an inner side portion, an outer side portion, and a plurality of circumferentially spaced fuel ports that extend through the outer side portion. A plurality of tubes provides axial separation between the fuel distribution manifold and the fuel injection manifold. Each tube defines a fluid communication path between the fuel distribution manifold and the fuel injection manifold.

Shapes and sounds as self-objects in learning geography.

PubMed

Baum, E A

1978-01-01

The pleasure which some children find in maps and map reading is manifold in origin. Children cathect patterns of configuration and color and derive joy from the visual mastery of these. This gratification is enhanced by the child's knowledge that the map represents something bigger than and external to itself. Likewise, some children take pleasure in the pronunciation of names themselves. The phonetic transcription of multisyllabic names is often a plearurable challenge. The vocalized name has its origin in the self, becomes barely external to self, and is self-monitored. Thus, in children both the configurations and the vocalizations associated with map reading have the properties of "self=objects" (Kohut, 1971). From the author's observation the delight which some children take in sounding out geographic names on a map may, in some instances, indicate pre-existing gratifying sound associations. Childish amusement in punning on cognomens may be an even greater stimulant for learning than visual configurations or artificial cognitive devices.

Neural constraints on learning.

PubMed

Sadtler, Patrick T; Quick, Kristin M; Golub, Matthew D; Chase, Steven M; Ryu, Stephen I; Tyler-Kabara, Elizabeth C; Yu, Byron M; Batista, Aaron P

2014-08-28

Learning, whether motor, sensory or cognitive, requires networks of neurons to generate new activity patterns. As some behaviours are easier to learn than others, we asked if some neural activity patterns are easier to generate than others. Here we investigate whether an existing network constrains the patterns that a subset of its neurons is capable of exhibiting, and if so, what principles define this constraint. We employed a closed-loop intracortical brain-computer interface learning paradigm in which Rhesus macaques (Macaca mulatta) controlled a computer cursor by modulating neural activity patterns in the primary motor cortex. Using the brain-computer interface paradigm, we could specify and alter how neural activity mapped to cursor velocity. At the start of each session, we observed the characteristic activity patterns of the recorded neural population. The activity of a neural population can be represented in a high-dimensional space (termed the neural space), wherein each dimension corresponds to the activity of one neuron. These characteristic activity patterns comprise a low-dimensional subspace (termed the intrinsic manifold) within the neural space. The intrinsic manifold presumably reflects constraints imposed by the underlying neural circuitry. Here we show that the animals could readily learn to proficiently control the cursor using neural activity patterns that were within the intrinsic manifold. However, animals were less able to learn to proficiently control the cursor using activity patterns that were outside of the intrinsic manifold. These results suggest that the existing structure of a network can shape learning. On a timescale of hours, it seems to be difficult to learn to generate neural activity patterns that are not consistent with the existing network structure. These findings offer a network-level explanation for the observation that we are more readily able to learn new skills when they are related to the skills that we already possess.

Image reconstruction by domain-transform manifold learning.

PubMed

Zhu, Bo; Liu, Jeremiah Z; Cauley, Stephen F; Rosen, Bruce R; Rosen, Matthew S

2018-03-21

Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction-automated transform by manifold approximation (AUTOMAP)-which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development of new acquisition strategies across imaging modalities.

Image reconstruction by domain-transform manifold learning

NASA Astrophysics Data System (ADS)

Zhu, Bo; Liu, Jeremiah Z.; Cauley, Stephen F.; Rosen, Bruce R.; Rosen, Matthew S.

2018-03-01

Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction—automated transform by manifold approximation (AUTOMAP)—which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development of new acquisition strategies across imaging modalities.

Deep learning beyond Lefschetz thimbles

NASA Astrophysics Data System (ADS)

Alexandru, Andrei; Bedaque, Paulo F.; Lamm, Henry; Lawrence, Scott

2017-11-01

The generalized thimble method to treat field theories with sign problems requires repeatedly solving the computationally expensive holomorphic flow equations. We present a machine learning technique to bypass this problem. The central idea is to obtain a few field configurations via the flow equations to train a feed-forward neural network. The trained network defines a new manifold of integration which reduces the sign problem and can be rapidly sampled. We present results for the 1 +1 dimensional Thirring model with Wilson fermions on sizable lattices. In addition to the gain in speed, the parametrization of the integration manifold we use avoids the "trapping" of Monte Carlo chains which plagues large-flow calculations, a considerable shortcoming of the previous attempts.

Microgravity Isolation Control System Design Via High-Order Sliding Mode Control

NASA Technical Reports Server (NTRS)

Shkolnikov, Ilya; Shtessel, Yuri; Whorton, Mark S.; Jackson, Mark

2000-01-01

Vibration isolation control system design for a microgravity experiment mount is considered. The controller design based on dynamic sliding manifold (DSM) technique is proposed to attenuate the accelerations transmitted to an isolated experiment mount either from a vibrating base or directly generated by the experiment, as well as to stabilize the internal dynamics of this nonminimum phase plant. An auxiliary DSM is employed to maintain the high-order sliding mode on the primary sliding manifold in the presence of uncertain actuator dynamics of second order. The primary DSM is designed for the closed-loop system in sliding mode to be a filter with given characteristics with respect to the input external disturbances.

A manifold independent approach to understanding transport in stochastic dynamical systems

NASA Astrophysics Data System (ADS)

Bollt, Erik M.; Billings, Lora; Schwartz, Ira B.

2002-12-01

We develop a new collection of tools aimed at studying stochastically perturbed dynamical systems. Specifically, in the setting of bi-stability, that is a two-attractor system, it has previously been numerically observed that a small noise volume is sufficient to destroy would be zero-noise case barriers in the phase space (pseudo-barriers), thus creating a pre-heteroclinic tangency chaos-like behavior. The stochastic dynamical system has a corresponding Frobenius-Perron operator with a stochastic kernel, which describes how densities of initial conditions move under the noisy map. Thus in studying the action of the Frobenius-Perron operator, we learn about the transport of the map; we have employed a Galerkin-Ulam-like method to project the Frobenius-Perron operator onto a discrete basis set of characteristic functions to highlight this action localized in specified regions of the phase space. Graph theoretic methods allow us to re-order the resulting finite dimensional Markov operator approximation so as to highlight the regions of the original phase space which are particularly active pseudo-barriers of the stochastic dynamics. Our toolbox allows us to find: (1) regions of high activity of transport, (2) flux across pseudo-barriers, and also (3) expected time of escape from pseudo-basins. Some of these quantities are also possible via the manifold dependent stochastic Melnikov method, but Melnikov only applies to a very special class of models for which the unperturbed homoclinic orbit is available. Our methods are unique in that they can essentially be considered as a “black-box” of tools which can be applied to a wide range of stochastic dynamical systems in the absence of a priori knowledge of manifold structures. We use here a model of childhood diseases to showcase our methods. Our tools will allow us to make specific observations of: (1) loss of reducibility between basins with increasing noise, (2) identification in the phase space of active regions of stochastic transport, (3) stochastic flux which essentially completes the heteroclinic tangle.

Experimental study of flow distribution and pressure loss with circumferential inlet and outlet manifolds

NASA Technical Reports Server (NTRS)

Dittrich, R. T.

1972-01-01

Water flow tests with circumferential inlet and outlet manifolds were conducted to determine factors affecting fluid distribution and pressure losses. Various orifice sizes and manifold geometries were tested over a range of flow velocities. With inlet manifolds, flow distribution was related directly to orifice discharge coefficients. A correlation indicated that nonuniform distribution resulted when the velocity head ratio at the orifice was not in the range of constant discharge coefficient. With outlet manifolds, nonuniform flow was related to static pressure variations along the manifold. Outlet manifolds had appreciably greater pressure losses than comparable inlet manifolds.

New Techniques for Hydrothermal Exploration: In Situ Chemical Sensors on AUVs - Preliminary Results From the Lau Basin

NASA Astrophysics Data System (ADS)

German, C. R.; Connelly, D. P.; Prien, R. D.; Yoerger, D.; Jakuba, M.; Bradley, A.; Shank, T. J.; Edmonds, H. N.; Langmuir, C. H.

2004-12-01

Less than one quarter of the global ridge-crest has yet received even cursory investigation for the presence or absence of hydrothermal activity. To improve exploration efficiency, particularly at high latitudes, new methodologies independent of tethered vehicles are required. To that end, we have begun the use of in situ chemical sensors allied to the increasing capabilities of autonomous underwater vehicles. Here, we present first results from our most recent efforts aboard the second R2K cruise to the Lau Basin (C.Langmuir, PI; Autumn 2004) to (a) map non-buoyant hydrothermal plumes, (b) intercept buoyant hydrothermal plumes and (c) locate and image novel hydrothermal fields on the seafloor. The AUV used for this work is ABE and the sensors deployed are direct extensions of the in situ Fe/Mn sensor deployed previously on SOC's AUTOSUB to investigate seasonally-reducing waters in Loch Etive, NW Scotland. Each in situ instrument comprises an electronics package that contains a tattletale control system with a flash memory card for on-board logging and a chemical manifold, consisting of a series of valves, pumps and a colorimetric cell. Analysis of iron is enabled by the determination of the coloured complex formed between iron II and ferrozine, manganese uses the colour change of PAN in the presence of reduced manganese. The system includes capacity for switching between sample, blank and two on-board samples for "in flight" calibrations with blanks and standards held in medical bags, outside of the pressure-balanced manifold, to attain in situ water-column temperatures. An in-line filter prevents large particle clogging and detection limits for both iron II and manganese II are ca.2nM.

A perspective on bridging scales and design of models using low-dimensional manifolds and data-driven model inference

PubMed Central

Zenil, Hector; Kiani, Narsis A.; Ball, Gordon; Gomez-Cabrero, David

2016-01-01

Systems in nature capable of collective behaviour are nonlinear, operating across several scales. Yet our ability to account for their collective dynamics differs in physics, chemistry and biology. Here, we briefly review the similarities and differences between mathematical modelling of adaptive living systems versus physico-chemical systems. We find that physics-based chemistry modelling and computational neuroscience have a shared interest in developing techniques for model reductions aiming at the identification of a reduced subsystem or slow manifold, capturing the effective dynamics. By contrast, as relations and kinetics between biological molecules are less characterized, current quantitative analysis under the umbrella of bioinformatics focuses on signal extraction, correlation, regression and machine-learning analysis. We argue that model reduction analysis and the ensuing identification of manifolds bridges physics and biology. Furthermore, modelling living systems presents deep challenges as how to reconcile rich molecular data with inherent modelling uncertainties (formalism, variables selection and model parameters). We anticipate a new generative data-driven modelling paradigm constrained by identified governing principles extracted from low-dimensional manifold analysis. The rise of a new generation of models will ultimately connect biology to quantitative mechanistic descriptions, thereby setting the stage for investigating the character of the model language and principles driving living systems. This article is part of the themed issue ‘Multiscale modelling at the physics–chemistry–biology interface’. PMID:27698038

Manifold learning in machine vision and robotics

NASA Astrophysics Data System (ADS)

Bernstein, Alexander

2017-02-01

Smart algorithms are used in Machine vision and Robotics to organize or extract high-level information from the available data. Nowadays, Machine learning is an essential and ubiquitous tool to automate extraction patterns or regularities from data (images in Machine vision; camera, laser, and sonar sensors data in Robotics) in order to solve various subject-oriented tasks such as understanding and classification of images content, navigation of mobile autonomous robot in uncertain environments, robot manipulation in medical robotics and computer-assisted surgery, and other. Usually such data have high dimensionality, however, due to various dependencies between their components and constraints caused by physical reasons, all "feasible and usable data" occupy only a very small part in high dimensional "observation space" with smaller intrinsic dimensionality. Generally accepted model of such data is manifold model in accordance with which the data lie on or near an unknown manifold (surface) of lower dimensionality embedded in an ambient high dimensional observation space; real-world high-dimensional data obtained from "natural" sources meet, as a rule, this model. The use of Manifold learning technique in Machine vision and Robotics, which discovers a low-dimensional structure of high dimensional data and results in effective algorithms for solving of a large number of various subject-oriented tasks, is the content of the conference plenary speech some topics of which are in the paper.

Performance of a supercharged direct-injection stratified-charge rotary combustion engine

NASA Technical Reports Server (NTRS)

Bartrand, Timothy A.; Willis, Edward A.

1990-01-01

A zero-dimensional thermodynamic performance computer model for direct-injection stratified-charge rotary combustion engines was modified and run for a single rotor supercharged engine. Operating conditions for the computer runs were a single boost pressure and a matrix of speeds, loads and engine materials. A representative engine map is presented showing the predicted range of efficient operation. After discussion of the engine map, a number of engine features are analyzed individually. These features are: heat transfer and the influence insulating materials have on engine performance and exhaust energy; intake manifold pressure oscillations and interactions with the combustion chamber; and performance losses and seal friction. Finally, code running times and convergence data are presented.

Development of a CAD Model Simplification Framework for Finite Element Analysis

DTIC Science & Technology

2012-01-01

A. Senthil Kumar , and KH Lee. Automatic solid decomposition and reduction for non-manifold geometric model generation. Computer-Aided Design, 36(13...CAD/CAM: concepts, techniques, and applications. Wiley-interscience, 1995. [38] Avneesh Sud, Mark Foskey, and Dinesh Manocha. Homotopy-preserving

One-dimensional super Calabi-Yau manifolds and their mirrors

NASA Astrophysics Data System (ADS)

Noja, S.; Cacciatori, S. L.; Piazza, F. Dalla; Marrani, A.; Re, R.

2017-04-01

We apply a definition of generalised super Calabi-Yau variety (SCY) to supermanifolds of complex dimension one. One of our results is that there are two SCY's having reduced manifold equal to P^1, namely the projective super space P^{.1|2} and the weighted projective super space W{P}_{(2)}^{.1|1} . Then we compute the corresponding sheaf cohomology of superforms, showing that the cohomology with picture number one is infinite dimensional, while the de Rham cohomology, which is what matters from a physical point of view, remains finite dimensional. Moreover, we provide the complete real and holomorphic de Rham cohomology for generic projective super spaces {P}^{.n|m} . We also determine the automorphism groups: these always match the dimension of the projective super group with the only exception of {P}^{.1|2} , whose automorphism group turns out to be larger than the projective super group. By considering the cohomology of the super tangent sheaf, we compute the deformations of {P}^{.1|m} , discovering that the presence of a fermionic structure allows for deformations even if the reduced manifold is rigid. Finally, we show that {P}^{.1|2} is self-mirror, whereas W{P}_{(2)}^{.1|1} has a zero dimensional mirror. Also, the mirror map for {P}^{.1|2} naturally endows it with a structure of N = 2 super Riemann surface.

Object Manifold Alignment for Multi-Temporal High Resolution Remote Sensing Images Classification

NASA Astrophysics Data System (ADS)

Gao, G.; Zhang, M.; Gu, Y.

2017-05-01

Multi-temporal remote sensing images classification is very useful for monitoring the land cover changes. Traditional approaches in this field mainly face to limited labelled samples and spectral drift of image information. With spatial resolution improvement, "pepper and salt" appears and classification results will be effected when the pixelwise classification algorithms are applied to high-resolution satellite images, in which the spatial relationship among the pixels is ignored. For classifying the multi-temporal high resolution images with limited labelled samples, spectral drift and "pepper and salt" problem, an object-based manifold alignment method is proposed. Firstly, multi-temporal multispectral images are cut to superpixels by simple linear iterative clustering (SLIC) respectively. Secondly, some features obtained from superpixels are formed as vector. Thirdly, a majority voting manifold alignment method aiming at solving high resolution problem is proposed and mapping the vector data to alignment space. At last, all the data in the alignment space are classified by using KNN method. Multi-temporal images from different areas or the same area are both considered in this paper. In the experiments, 2 groups of multi-temporal HR images collected by China GF1 and GF2 satellites are used for performance evaluation. Experimental results indicate that the proposed method not only has significantly outperforms than traditional domain adaptation methods in classification accuracy, but also effectively overcome the problem of "pepper and salt".

Formation of a Chern-Simons cylindrical wormhole during evolution of manifolds

NASA Astrophysics Data System (ADS)

Sepehri, Alireza; Ghaffary, Tooraj; Naimi, Yaghoob; Ghaforyan, Hossein; Ebrahimzadeh, Majid

In this paper, the formation of cylindrical wormhole during evolution of manifolds is studied. It is shown that this type of wormholes may be produced at two stages and then disappeared very fast at the third stage. First, one N-dimensional is formed by joining point-like manifolds. Then, this manifold is torn and two child manifolds plus one Chern-Simons manifold appeared. Our universe is born on one of the child manifolds and connected to the other one by Chern-Simons manifold. At the third stage, this Chern-Simons manifold-which plays the role of cylindrical wormhole, dissolves into universes and gives its energy to them and causes inflation. Thus, the Chern-Simons cylindrical wormhole is unstable and dissolves in our four-dimensional universes and another universe very fast.

Dual manifold heat pipe evaporator

DOEpatents

Adkins, Douglas R.; Rawlinson, K. Scott

1994-01-01

An improved evaporator section for a dual manifold heat pipe. Both the upper and lower manifolds can have surfaces exposed to the heat source which evaporate the working fluid. The tubes in the tube bank between the manifolds have openings in their lower extensions into the lower manifold to provide for the transport of evaporated working fluid from the lower manifold into the tubes and from there on into the upper manifold and on to the condenser portion of the heat pipe. A wick structure lining the inner walls of the evaporator tubes extends into both the upper and lower manifolds. At least some of the tubes also have overflow tubes contained within them to carry condensed working fluid from the upper manifold to pass to the lower without spilling down the inside walls of the tubes.

Solving Variational Problems and Partial Differential Equations Mapping into General Target Manifolds

DTIC Science & Technology

2002-01-01

1998. [36] T. Sakai, Riemannian Geometry, AMS Translations of Mathematical Monographs, vol 149. [37] N. Sochen, R . Kimmel, and R , Malladi , “A general...matical Physics 107, pp. 649-705, 1986. [5] V. Caselles, R . Kimmel, G. Sapiro, and C. Sbert, “Minimal surfaces based object segmentation,” IEEE- PAMI...June 2000 [9] R . Cohen, R . M. Hardt, D. Kinderlehrer, S. Y. Lin, and M. Luskin, “Minimum energy configurations for liquid crystals: Computational

Reprint of "Two-stage sparse coding of region covariance via Log-Euclidean kernels to detect saliency".

PubMed

Zhang, Ying-Ying; Yang, Cai; Zhang, Ping

2017-08-01

In this paper, we present a novel bottom-up saliency detection algorithm from the perspective of covariance matrices on a Riemannian manifold. Each superpixel is described by a region covariance matrix on Riemannian Manifolds. We carry out a two-stage sparse coding scheme via Log-Euclidean kernels to extract salient objects efficiently. In the first stage, given background dictionary on image borders, sparse coding of each region covariance via Log-Euclidean kernels is performed. The reconstruction error on the background dictionary is regarded as the initial saliency of each superpixel. In the second stage, an improvement of the initial result is achieved by calculating reconstruction errors of the superpixels on foreground dictionary, which is extracted from the first stage saliency map. The sparse coding in the second stage is similar to the first stage, but is able to effectively highlight the salient objects uniformly from the background. Finally, three post-processing methods-highlight-inhibition function, context-based saliency weighting, and the graph cut-are adopted to further refine the saliency map. Experiments on four public benchmark datasets show that the proposed algorithm outperforms the state-of-the-art methods in terms of precision, recall and mean absolute error, and demonstrate the robustness and efficiency of the proposed method. Copyright © 2017 Elsevier Ltd. All rights reserved.

Manifold seal structure for fuel cell stack

DOEpatents

Collins, William P.

1988-01-01

The seal between the sides of a fuel cell stack and the gas manifolds is improved by adding a mechanical interlock between the adhesive sealing strip and the abutting surface of the manifolds. The adhesive is a material which can flow to some extent when under compression, and the mechanical interlock is formed providing small openings in the portion of the manifold which abuts the adhesive strip. When the manifolds are pressed against the adhesive strips, the latter will flow into and through the manifold openings to form buttons or ribs which mechanically interlock with the manifolds. These buttons or ribs increase the bond between the manifolds and adhesive, which previously relied solely on the adhesive nature of the adhesive.

Nonlinear elastic inclusions in isotropic solids.

PubMed

Yavari, Arash; Goriely, Alain

2013-12-08

We introduce a geometric framework to calculate the residual stress fields and deformations of nonlinear solids with inclusions and eigenstrains. Inclusions are regions in a body with different reference configurations from the body itself and can be described by distributed eigenstrains. Geometrically, the eigenstrains define a Riemannian 3-manifold in which the body is stress-free by construction. The problem of residual stress calculation is then reduced to finding a mapping from the Riemannian material manifold to the ambient Euclidean space. Using this construction, we find the residual stress fields of three model systems with spherical and cylindrical symmetries in both incompressible and compressible isotropic elastic solids. In particular, we consider a finite spherical ball with a spherical inclusion with uniform pure dilatational eigenstrain and we show that the stress in the inclusion is uniform and hydrostatic. We also show how singularities in the stress distribution emerge as a consequence of a mismatch between radial and circumferential eigenstrains at the centre of a sphere or the axis of a cylinder.

Nonlinear elastic inclusions in isotropic solids

PubMed Central

Yavari, Arash; Goriely, Alain

2013-01-01

We introduce a geometric framework to calculate the residual stress fields and deformations of nonlinear solids with inclusions and eigenstrains. Inclusions are regions in a body with different reference configurations from the body itself and can be described by distributed eigenstrains. Geometrically, the eigenstrains define a Riemannian 3-manifold in which the body is stress-free by construction. The problem of residual stress calculation is then reduced to finding a mapping from the Riemannian material manifold to the ambient Euclidean space. Using this construction, we find the residual stress fields of three model systems with spherical and cylindrical symmetries in both incompressible and compressible isotropic elastic solids. In particular, we consider a finite spherical ball with a spherical inclusion with uniform pure dilatational eigenstrain and we show that the stress in the inclusion is uniform and hydrostatic. We also show how singularities in the stress distribution emerge as a consequence of a mismatch between radial and circumferential eigenstrains at the centre of a sphere or the axis of a cylinder. PMID:24353470

Dual manifold heat pipe evaporator

DOEpatents

Adkins, D.R.; Rawlinson, K.S.

1994-01-04

An improved evaporator section is described for a dual manifold heat pipe. Both the upper and lower manifolds can have surfaces exposed to the heat source which evaporate the working fluid. The tubes in the tube bank between the manifolds have openings in their lower extensions into the lower manifold to provide for the transport of evaporated working fluid from the lower manifold into the tubes and from there on into the upper manifold and on to the condenser portion of the heat pipe. A wick structure lining the inner walls of the evaporator tubes extends into both the upper and lower manifolds. At least some of the tubes also have overflow tubes contained within them to carry condensed working fluid from the upper manifold to pass to the lower without spilling down the inside walls of the tubes. 1 figure.

Global embeddings for branes at toric singularities

NASA Astrophysics Data System (ADS)

Balasubramanian, Vijay; Berglund, Per; Braun, Volker; García-Etxebarria, Iñaki

2012-10-01

We describe how local toric singularities, including the Toric Lego construction, can be embedded in compact Calabi-Yau manifolds. We study in detail the addition of D-branes, including non-compact flavor branes as typically used in semi-realistic model building. The global geometry provides constraints on allowable local models. As an illustration of our discussion we focus on D3 and D7-branes on (the partially resolved) ( dP 0)3 singularity, its embedding in a specific Calabi-Yau manifold as a hypersurface in a toric variety, the related type IIB orientifold compactification, as well as the corresponding F-theory uplift. Our techniques generalize naturally to complete intersections, and to a large class of F-theory backgrounds with singularities.

Gromov-Witten invariants and localization

NASA Astrophysics Data System (ADS)

Morrison, David R.

2017-11-01

We give a pedagogical review of the computation of Gromov-Witten invariants via localization in 2D gauged linear sigma models. We explain the relationship between the two-sphere partition function of the theory and the Kähler potential on the conformal manifold. We show how the Kähler potential can be assembled from classical, perturbative, and non-perturbative contributions, and explain how the non-perturbative contributions are related to the Gromov-Witten invariants of the corresponding Calabi-Yau manifold. We then explain how localization enables efficient calculation of the two-sphere partition function and, ultimately, the Gromov-Witten invariants themselves. This is a contribution to the review issue ‘Localization techniques in quantum field theories’ (ed V Pestun and M Zabzine) which contains 17 chapters, available at [1].

Power module assemblies with staggered coolant channels

DOEpatents

Herron, Nicholas Hayden; Mann, Brooks S; Korich, Mark D

2013-07-16

A manifold is provided for supporting a power module assembly with a plurality of power modules. The manifold includes a first manifold section. The first face of the first manifold section is configured to receive the first power module, and the second face of the first manifold section defines a first cavity with a first baseplate thermally coupled to the first power module. The first face of the second manifold section is configured to receive the second power module, and the second face of the second manifold section defines a second cavity with a second baseplate thermally coupled to the second power module. The second face of the first manifold section and the second face of the second manifold section are coupled together such that the first cavity and the second cavity form a coolant channel. The first cavity is at least partially staggered with respect to second cavity.

Using periodic orbits to compute chaotic transport rates between resonance zones.

PubMed

Sattari, Sulimon; Mitchell, Kevin A

2017-11-01

Transport properties of chaotic systems are computable from data extracted from periodic orbits. Given a sufficient number of periodic orbits, the escape rate can be computed using the spectral determinant, a function that incorporates the eigenvalues and periods of periodic orbits. The escape rate computed from periodic orbits converges to the true value as more and more periodic orbits are included. Escape from a given region of phase space can be computed by considering only periodic orbits that lie within the region. An accurate symbolic dynamics along with a corresponding partitioning of phase space is useful for systematically obtaining all periodic orbits up to a given period, to ensure that no important periodic orbits are missing in the computation. Homotopic lobe dynamics (HLD) is an automated technique for computing accurate partitions and symbolic dynamics for maps using the topological forcing of intersections of stable and unstable manifolds of a few periodic anchor orbits. In this study, we apply the HLD technique to compute symbolic dynamics and periodic orbits, which are then used to find escape rates from different regions of phase space for the Hénon map. We focus on computing escape rates in parameter ranges spanning hyperbolic plateaus, which are parameter intervals where the dynamics is hyperbolic and the symbolic dynamics does not change. After the periodic orbits are computed for a single parameter value within a hyperbolic plateau, periodic orbit continuation is used to compute periodic orbits over an interval that spans the hyperbolic plateau. The escape rates computed from a few thousand periodic orbits agree with escape rates computed from Monte Carlo simulations requiring hundreds of billions of orbits.

Controlling Structure and Properties of High Surface Area Nonwoven Materials via Hydroentangling

NASA Astrophysics Data System (ADS)

Luzius, Dennis

Hydroentangling describes a technique using a series of high-velocity water jets to mechanically interlock and entangle fibers. Over the last decades researchers worked on a fundamental understanding of the process and the factors influencing the properties of the final nonwoven material. Recent studies discovered hydroentangling to be capable to create unique, knot-like structures characterized by high- and low density regions, which are believed to have interesting properties for filtration applications. However, just little is known about the impact of hydroentangling parameters on the properties of filtration media to this day. In this study we report on the effect of various hydroentangling parameters, such as jet spacing, manifold pressure, number of manifolds but also specific energy on the structure and properties of high surface area nonwoven materials. Latter was achieved by different bicomponent fiber technologies and subsequent treatments removing the sacrificial compound from the structure. The highest BET surface area was measured to be 3.5 m2 g-1 and the smallest mean fiber size about 0.5 mum. Hydroentangling with large jet spacing was found to be a parameter significantly enhancing the filtration properties of caustic-treated island-in-the-sea nonwoven materials. Moreover, improved capture efficiencies and reduced pressure drops were achieved by reducing the manifold pressure and therefore specific energy during hydroentangling. Jet spacing but not island count was found to be the dominant factor influencing the structure and properties of island-in-the-sea nonwovens. Contrary to our initial expectations increasing the island count and thus decreasing the fiber size did not result in better filtration properties. Mixed media nonwoven structures made from homocomponent and island-in-the-sea fibers were found to have lower densities, higher air permeabilities and better quality factors compared to island-in-the-sea structures hydroentangled under the exact same conditions. Study showed the specific energy to not be an adequate measure for describing the process-structure relationship in hydroentangling. Hydroentangling with same specific energy but different manifold pressures revealed the structure and properties to be different and the peak manifold pressure to be the dominant parameter. It was further shown that hydroentangling with multiple manifolds but same water pressure influences the structure and properties of mono- and bicomponent nonwoven materials. Hydroentangling with three manifolds having the same water pressure resulted in stronger, less permeable fabrics compared to two manifolds or one manifold with the same water pressure. Necessary hydroentangling intensity for winged and island-in-the-sea nonwoven materials was found to be different. Winged fiber nonwovens required higher manifold pressures and a different energy ratio than island-in-in-the-sea nonwovens. Hydroentangling winged fiber webs with jet spacing larger than 600 mum resulted in materials too weak to withstand the caustic-treatment. Study indicated the charging potential of winged fiber nonwovens to be superior compared to island-in-the-sea-structures. In contrast to winged fiber nonwovens, island-in-the-sea structures showed higher pressure drops after corona discharge. Loading winged fiber nonwovens with potassium chloride revealed caustic-treated, IPA discharged materials to show the highest loading capacity.

Simplifying the representation of complex free-energy landscapes using sketch-map

PubMed Central

Ceriotti, Michele; Tribello, Gareth A.; Parrinello, Michele

2011-01-01

A new scheme, sketch-map, for obtaining a low-dimensional representation of the region of phase space explored during an enhanced dynamics simulation is proposed. We show evidence, from an examination of the distribution of pairwise distances between frames, that some features of the free-energy surface are inherently high-dimensional. This makes dimensionality reduction problematic because the data does not satisfy the assumptions made in conventional manifold learning algorithms We therefore propose that when dimensionality reduction is performed on trajectory data one should think of the resultant embedding as a quickly sketched set of directions rather than a road map. In other words, the embedding tells one about the connectivity between states but does not provide the vectors that correspond to the slow degrees of freedom. This realization informs the development of sketch-map, which endeavors to reproduce the proximity information from the high-dimensionality description in a space of lower dimensionality even when a faithful embedding is not possible. PMID:21730167

A Method for Reducing the Temperature of Exhaust Manifolds

NASA Technical Reports Server (NTRS)

Schey, Oscar W; Young, Alfred W

1931-01-01

This report describes tests conducted at the Langley Memorial Aeronautical Laboratory on an "air-inducting" exhaust manifold for aircraft engines. The exhaust gases from each cylinder port are discharged into the throat of an exhaust pipe which has a frontal bellmouth. Cooling air is drawn into the pipe, where it surrounds and mixes with the exhaust gases. Temperatures of the manifold shell and of the exhaust gases were obtained in flight for both a conventional manifold and the air-inducting manifold. The air-inducting manifold was installed on an engine which was placed on a test stand. Different fuels were sprayed on and into the manifold to determine whether the use of this manifold reduced the fire hazard. The flight tests showed reductions in manifold temperatures of several hundred degrees, to values below the ignition point of aviation gasoline. On the test stand when the engine was run at idling speeds fuels sprayed into the manifold ignited. It is believed that at low engine speeds the fuel remained in the manifold long enough to become thoroughly heated, and was then ignited by the exhaust gas which had not mixed with cooling air. The use of the air-inducting exhaust manifold must reduce the fire hazard by virtue of its lower operating temperature, but it is not a completely satisfactory solution of the problem.

Determination of Stability and Translation in a Boundary Layer

NASA Technical Reports Server (NTRS)

Crepeau, John; Tobak, Murray

1996-01-01

Reducing the infinite degrees of freedom inherent in fluid motion into a manageable number of modes to analyze fluid motion is presented. The concepts behind the center manifold technique are used. Study of the Blasius boundary layer and a precise description of stability within the flow field are discussed.

75 FR 901 - Airworthiness Directives; Honeywell International Inc. ALF502 Series and LF507 Series Turbofan...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-07

.... ALF502 series and LF507 series turbofan engines with certain fuel manifold assemblies installed. That AD... of certain part number (P/N) fuel manifold assemblies for cracks, and replacement of cracked fuel manifolds with serviceable manifolds. This AD continues to require inspecting those fuel manifolds for...

Experimental Analysis of Exhaust Manifold with Ceramic Coating for Reduction of Heat Dissipation

NASA Astrophysics Data System (ADS)

Saravanan, J.; Valarmathi, T. N.; Nathc, Rajdeep; Kumar, Prasanth

2017-05-01

Exhaust manifold plays an important role in the exhaust system, the manifold delivers the waste toxic gases to a safe distance and it is used to reduce the sound pollution and air pollution. Exhaust manifold suffers with lot of thermal stress, due to this blow holes occurs in the surface of the exhaust manifold and also more noise is developed. The waste toxic gases from the multiple cylinders are collected into a single pipe by the exhaust manifold. The waste toxic gases can damage the material of the manifold. In this study, to prevent the damage zirconia powder has been coated in the inner surface and alumina (60%) combined with titania (40%) has been used for coating the outer surface of the exhaust manifold. After coating experiments have been performed using a multiple-cylinder four stroke stationary petrol engine. The test results of hardness, emission, corrosion and temperature of the coated and uncoated manifolds have been compared. The result shows that the performance is improved and also emission is reduced in the coated exhaust manifold.

On the measure of conformal difference between Euclidean and Lobachevsky spaces

NASA Astrophysics Data System (ADS)

Zorich, Vladimir A.

2011-12-01

Euclidean space R^n and Lobachevsky space H^n are known to be not equivalent either conformally or quasiconformally. In this work we give exact asymptotics of the critical order of growth at infinity for the quasiconformality coefficient of a diffeomorphism f\\colon R^n\\to H^n for which such a mapping f is possible. We also consider the general case of immersions f\\colon M^n\\to N^n of conformally parabolic Riemannian manifolds. Bibliography: 17 titles.

AVGAS/AUTOGAS (Aviation Gasoline/Automobile Gasoline) Comparison. Winter Grade Fuels.

DTIC Science & Technology

1986-07-01

mass MAP Manifold pressure - inHg MON Motor Octane Number NIPER National Institute of Petroleum and Energy Resources Pamb Ambient pressure - inHg...pressure - psig si Sea level (used as a subscript) STC Supplemental Type Certificate Tamb Ambient temperature - degC or degF Tdew Dew point - degC or degF...temperature deg C #2 exhaust gas temperature deg C #3 exhaust gas temperature deg C #4 exhaust gas temperature deg C Ambient air temperature deg C 6

The world problem: on the computability of the topology of 4-manifolds

NASA Technical Reports Server (NTRS)

vanMeter, J. R.

2005-01-01

Topological classification of the 4-manifolds bridges computation theory and physics. A proof of the undecidability of the homeomorphy problem for 4-manifolds is outlined here in a clarifying way. It is shown that an arbitrary Turing machine with an arbitrary input can be encoded into the topology of a 4-manifold, such that the 4-manifold is homeomorphic to a certain other 4-manifold if and only if the corresponding Turing machine halts on the associated input. Physical implications are briefly discussed.

G-structures and domain walls in heterotic theories

NASA Astrophysics Data System (ADS)

Lukas, Andre; Matti, Cyril

2011-01-01

We consider heterotic string solutions based on a warped product of a four-dimensional domain wall and a six-dimensional internal manifold, preserving two supercharges. The constraints on the internal manifolds with SU(3) structure are derived. They are found to be generalized half-flat manifolds with a particular pattern of torsion classes and they include half-flat manifolds and Strominger's complex non-Kahler manifolds as special cases. We also verify that previous heterotic compactifications on half-flat mirror manifolds are based on this class of solutions.

Lattice functions, wavelet aliasing, and SO(3) mappings of orthonormal filters

NASA Astrophysics Data System (ADS)

John, Sarah

1998-01-01

A formulation of multiresolution in terms of a family of dyadic lattices {Sj;j∈Z} and filter matrices Mj⊂U(2)⊂GL(2,C) illuminates the role of aliasing in wavelets and provides exact relations between scaling and wavelet filters. By showing the {DN;N∈Z+} collection of compactly supported, orthonormal wavelet filters to be strictly SU(2)⊂U(2), its representation in the Euler angles of the rotation group SO(3) establishes several new results: a 1:1 mapping of the {DN} filters onto a set of orbits on the SO(3) manifold; an equivalence of D∞ to the Shannon filter; and a simple new proof for a criterion ruling out pathologically scaled nonorthonormal filters.

Efficient Stochastic Inversion Using Adjoint Models and Kernel-PCA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thimmisetty, Charanraj A.; Zhao, Wenju; Chen, Xiao

2017-10-18

Performing stochastic inversion on a computationally expensive forward simulation model with a high-dimensional uncertain parameter space (e.g. a spatial random field) is computationally prohibitive even when gradient information can be computed efficiently. Moreover, the ‘nonlinear’ mapping from parameters to observables generally gives rise to non-Gaussian posteriors even with Gaussian priors, thus hampering the use of efficient inversion algorithms designed for models with Gaussian assumptions. In this paper, we propose a novel Bayesian stochastic inversion methodology, which is characterized by a tight coupling between the gradient-based Langevin Markov Chain Monte Carlo (LMCMC) method and a kernel principal component analysis (KPCA). Thismore » approach addresses the ‘curse-of-dimensionality’ via KPCA to identify a low-dimensional feature space within the high-dimensional and nonlinearly correlated parameter space. In addition, non-Gaussian posterior distributions are estimated via an efficient LMCMC method on the projected low-dimensional feature space. We will demonstrate this computational framework by integrating and adapting our recent data-driven statistics-on-manifolds constructions and reduction-through-projection techniques to a linear elasticity model.« less

Critical frontier of the triangular Ising antiferromagnet in a field

NASA Astrophysics Data System (ADS)

Qian, Xiaofeng; Wegewijs, Maarten; Blöte, Henk W.

2004-03-01

We study the critical line of the triangular Ising antiferromagnet in an external magnetic field by means of a finite-size analysis of results obtained by transfer-matrix and Monte Carlo techniques. We compare the shape of the critical line with predictions of two different theoretical scenarios. Both scenarios, while plausible, involve assumptions. The first scenario is based on the generalization of the model to a vertex model, and the assumption that the exact analytic form of the critical manifold of this vertex model is determined by the zeroes of an O(2) gauge-invariant polynomial in the vertex weights. However, it is not possible to fit the coefficients of such polynomials of orders up to 10, such as to reproduce the numerical data for the critical points. The second theoretical prediction is based on the assumption that a renormalization mapping exists of the Ising model on the Coulomb gas, and analysis of the resulting renormalization equations. It leads to a shape of the critical line that is inconsistent with the first prediction, but consistent with the numerical data.

Functional renormalization group analysis of tensorial group field theories on Rd

NASA Astrophysics Data System (ADS)

Geloun, Joseph Ben; Martini, Riccardo; Oriti, Daniele

2016-07-01

Rank-d tensorial group field theories are quantum field theories (QFTs) defined on a group manifold G×d , which represent a nonlocal generalization of standard QFT and a candidate formalism for quantum gravity, since, when endowed with appropriate data, they can be interpreted as defining a field theoretic description of the fundamental building blocks of quantum spacetime. Their renormalization analysis is crucial both for establishing their consistency as quantum field theories and for studying the emergence of continuum spacetime and geometry from them. In this paper, we study the renormalization group flow of two simple classes of tensorial group field theories (TGFTs), defined for the group G =R for arbitrary rank, both without and with gauge invariance conditions, by means of functional renormalization group techniques. The issue of IR divergences is tackled by the definition of a proper thermodynamic limit for TGFTs. We map the phase diagram of such models, in a simple truncation, and identify both UV and IR fixed points of the RG flow. Encouragingly, for all the models we study, we find evidence for the existence of a phase transition of condensation type.

Configurable double-sided modular jet impingement assemblies for electronics cooling

DOEpatents

Zhou, Feng; Dede, Ercan Mehmet

2018-05-22

A modular jet impingement assembly includes an inlet tube fluidly coupled to a fluid inlet, an outlet tube fluidly coupled to a fluid outlet, and a modular manifold having a first distribution recess extending into a first side of the modular manifold, a second distribution recess extending into a second side of the modular manifold, a plurality of inlet connection tubes positioned at an inlet end of the modular manifold, and a plurality of outlet connection tubes positioned at an outlet end of the modular manifold. A first manifold insert is removably positioned within the first distribution recess, a second manifold insert is removably positioned within the second distribution recess, and a first and second heat transfer plate each removably coupled to the modular manifold. The first and second heat transfer plates each comprise an impingement surface.

The functional equation truncation method for approximating slow invariant manifolds: a rapid method for computing intrinsic low-dimensional manifolds.

PubMed

Roussel, Marc R; Tang, Terry

2006-12-07

A slow manifold is a low-dimensional invariant manifold to which trajectories nearby are rapidly attracted on the way to the equilibrium point. The exact computation of the slow manifold simplifies the model without sacrificing accuracy on the slow time scales of the system. The Maas-Pope intrinsic low-dimensional manifold (ILDM) [Combust. Flame 88, 239 (1992)] is frequently used as an approximation to the slow manifold. This approximation is based on a linearized analysis of the differential equations and thus neglects curvature. We present here an efficient way to calculate an approximation equivalent to the ILDM. Our method, called functional equation truncation (FET), first develops a hierarchy of functional equations involving higher derivatives which can then be truncated at second-derivative terms to explicitly neglect the curvature. We prove that the ILDM and FET-approximated (FETA) manifolds are identical for the one-dimensional slow manifold of any planar system. In higher-dimensional spaces, the ILDM and FETA manifolds agree to numerical accuracy almost everywhere. Solution of the FET equations is, however, expected to generally be faster than the ILDM method.

Automated Plantation Mapping in Indonesia Using Remote Sensing Data

NASA Astrophysics Data System (ADS)

Karpatne, A.; Jia, X.; Khandelwal, A.; Kumar, V.

2017-12-01

Plantation mapping is critical for understanding and addressing deforestation, a key driver of climate change and ecosystem degradation. Unfortunately, most plantation maps are limited to small areas for specific years because they rely on visual inspection of imagery. In this work, we propose a data-driven approach which automatically generates yearly plantation maps for large regions using MODIS multi-spectral data. While traditional machine learning algorithms face manifold challenges in this task, e.g. imperfect training labels, spatio-temporal data heterogeneity, noisy and high-dimensional data, lack of evaluation data, etc., we introduce a novel deep learning-based framework that combines existing imperfect plantation products as training labels and models the spatio-temporal relationships of land covers. We also explores the post-processing steps based on Hidden Markov Model that further improve the detection accuracy. Then we conduct extensive evaluation of the generated plantation maps. Specifically, by randomly sampling and comparing with high-resolution Digital Globe imagery, we demonstrate that the generated plantation maps achieve both high precision and high recall. When compared with existing plantation mapping products, our detection can avoid both false positives and false negatives. Finally, we utilize the generated plantation maps in analyzing the relationship between forest fires and growth of plantations, which assists in better understanding the cause of deforestation in Indonesia.

Flexible fuel cell gas manifold system

DOEpatents

Cramer, Michael; Shah, Jagdish; Hayes, Richard P.; Kelley, Dana A.

2005-05-03

A fuel cell stack manifold system in which a flexible manifold body includes a pan having a central area, sidewall extending outward from the periphery of the central area, and at least one compound fold comprising a central area fold connecting adjacent portions of the central area and extending between opposite sides of the central area, and a sidewall fold connecting adjacent portions of the sidewall. The manifold system further includes a rail assembly for attachment to the manifold body and adapted to receive pins by which dielectric insulators are joined to the manifold assembly.

Microchannel heat sink assembly

DOEpatents

Bonde, Wayne L.; Contolini, Robert J.

1992-01-01

The present invention provides a microchannel heat sink with a thermal range from cryogenic temperatures to several hundred degrees centigrade. The heat sink can be used with a variety of fluids, such as cryogenic or corrosive fluids, and can be operated at a high pressure. The heat sink comprises a microchannel layer preferably formed of silicon, and a manifold layer preferably formed of glass. The manifold layer comprises an inlet groove and outlet groove which define an inlet manifold and an outlet manifold. The inlet manifold delivers coolant to the inlet section of the microchannels, and the outlet manifold receives coolant from the outlet section of the microchannels. In one embodiment, the manifold layer comprises an inlet hole extending through the manifold layer to the inlet manifold, and an outlet hole extending through the manifold layer to the outlet manifold. Coolant is supplied to the heat sink through a conduit assembly connected to the heat sink. A resilient seal, such as a gasket or an O-ring, is disposed between the conduit and the hole in the heat sink in order to provide a watetight seal. In other embodiments, the conduit assembly may comprise a metal tube which is connected to the heat sink by a soft solder. In still other embodiments, the heat sink may comprise inlet and outlet nipples. The present invention has application in supercomputers, integrated circuits and other electronic devices, and is suitable for cooling materials to superconducting temperatures.

Orion Exploration Mission Entry Interface Target Line

NASA Technical Reports Server (NTRS)

Rea, Jeremy R.

2016-01-01

The Orion Multi-Purpose Crew Vehicle is required to return to the continental United States at any time during the month. In addition, it is required to provide a survivable entry from a wide range of trans-lunar abort trajectories. The Entry Interface (EI) state must be targeted to ensure that all requirements are met for all possible return scenarios, even in the event of no communication with the Mission Control Center to provide an updated EI target. The challenge then is to functionalize an EI state constraint manifold that can be used in the on-board targeting algorithm, as well as the ground-based trajectory optimization programs. This paper presents the techniques used to define the EI constraint manifold and to functionalize it as a set of polynomials in several dimensions.

Collisionless Dynamics and the Cosmic Web

NASA Astrophysics Data System (ADS)

Hahn, Oliver

2016-10-01

I review the nature of three-dimensional collapse in the Zeldovich approximation, how it relates to the underlying nature of the three-dimensional Lagrangian manifold and naturally gives rise to a hierarchical structure formation scenario that progresses through collapse from voids to pancakes, filaments and then halos. I then discuss how variations of the Zeldovich approximation (based on the gravitational or the velocity potential) have been used to define classifications of the cosmic large-scale structure into dynamically distinct parts. Finally, I turn to recent efforts to devise new approaches relying on tessellations of the Lagrangian manifold to follow the fine-grained dynamics of the dark matter fluid into the highly non-linear regime and both extract the maximum amount of information from existing simulations as well as devise new simulation techniques for cold collisionless dynamics.

Development of an Atmospheric Pressure Ionization Mass Spectrometer

NASA Technical Reports Server (NTRS)

1998-01-01

A commercial atmospheric pressure ionization mass spectrometer (APIMS) was purchased from EXTREL Mass Spectrometry, Inc. (Pittsburgh, PA). Our research objectives were to adapt this instrument and develop techniques for real-time determinations of the concentrations of trace species in the atmosphere. The prototype instrument is capable of making high frequency measurements with no sample preconcentrations. Isotopically labeled standards are used as an internal standard to obtain high precision and to compensate for changes in instrument sensitivity and analyte losses in the sampling manifold as described by Bandy and coworkers. The prototype instrument is capable of being deployed on NASA C130, Electra, P3, and DC8 aircraft. After purchasing and taking delivery by June 1994, we assembled the mass spectrometer, data acquisition, and manifold flow control instrumentation in electronic racks and performed tests.

Load compensation in a lean burn natural gas vehicle

NASA Astrophysics Data System (ADS)

Gangopadhyay, Anupam

A new multivariable PI tuning technique is developed in this research that is primarily developed for regulation purposes. Design guidelines are developed based on closed-loop stability. The new multivariable design is applied in a natural gas vehicle to combine idle and A/F ratio control loops. This results in better recovery during low idle operation of a vehicle under external step torques. A powertrain model of a natural gas engine is developed and validated for steady-state and transient operation. The nonlinear model has three states: engine speed, intake manifold pressure and fuel fraction in the intake manifold. The model includes the effect of fuel partial pressure in the intake manifold filling and emptying dynamics. Due to the inclusion of fuel fraction as a state, fuel flow rate into the cylinders is also accurately modeled. A linear system identification is performed on the nonlinear model. The linear model structure is predicted analytically from the nonlinear model and the coefficients of the predicted transfer function are shown to be functions of key physical parameters in the plant. Simulations of linear system and model parameter identification is shown to converge to the predicted values of the model coefficients. The multivariable controller developed in this research could be designed in an algebraic fashion once the plant model is known. It is thus possible to implement the multivariable PI design in an adaptive fashion combining the controller with identified plant model on-line. This will result in a self-tuning regulator (STR) type controller where the underlying design criteria is the multivariable tuning technique designed in this research.

Fluid delivery manifolds and microfluidic systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Renzi, Ronald F.; Sommer, Gregory J.; Singh, Anup K.

2017-02-28

Embodiments of fluid distribution manifolds, cartridges, and microfluidic systems are described herein. Fluid distribution manifolds may include an insert member and a manifold base and may define a substantially closed channel within the manifold when the insert member is press-fit into the base. Cartridges described herein may allow for simultaneous electrical and fluidic interconnection with an electrical multiplex board and may be held in place using magnetic attraction.

Application of Local Linear Embedding to Nonlinear Exploratory Latent Structure Analysis

ERIC Educational Resources Information Center

Wang, Haonan; Iyer, Hari

2007-01-01

In this paper we discuss the use of a recent dimension reduction technique called Locally Linear Embedding, introduced by Roweis and Saul, for performing an exploratory latent structure analysis. The coordinate variables from the locally linear embedding describing the manifold on which the data reside serve as the latent variable scores. We…

Driver Aid and Education Test Project. Final Report.

ERIC Educational Resources Information Center

Shadis, W.; Soucek, S. J.

A driver education project tested the hypothesis that measurable improvements in fleet fuel economy can be achieved by driver awareness training in fuel-efficient driving techniques and by a manifold vacuum gauge, used individually or in combination with each other. From April 1976 through December 1977 data were collected in the Las Vegas,…

An Experiment with Manifold Purposes: The Chemical Reactivity of Crystal Defects upon Crystal Dissolution.

ERIC Educational Resources Information Center

Lazzarini, Annaluisa Fantola; Lazzarini, Ennio

1983-01-01

Background information and procedures are provided for an experiment designed to introduce (1) crystal defects and their reactivity upon crystal dissolution; (2) hydrates electron and its reactivity; (3) application of radiochemical method of analysis; and (4) the technique of competitive kinetics. Suggested readings and additional experiments are…

Zeroth Poisson Homology, Foliated Cohomology and Perfect Poisson Manifolds

NASA Astrophysics Data System (ADS)

Martínez-Torres, David; Miranda, Eva

2018-01-01

We prove that, for compact regular Poisson manifolds, the zeroth homology group is isomorphic to the top foliated cohomology group, and we give some applications. In particular, we show that, for regular unimodular Poisson manifolds, top Poisson and foliated cohomology groups are isomorphic. Inspired by the symplectic setting, we define what a perfect Poisson manifold is. We use these Poisson homology computations to provide families of perfect Poisson manifolds.

Nose-only exposure system

DOEpatents

Cannon, William C.; Bass, Edward W.; Decker, Jr., John R.

1988-01-01

An exposure system for supplying a gaseous material, i.e. an aerosol, gas or a vapor, directly to the noses of experimental animals includes concentric vertical inner and outer manifolds. The outer manifold connects with the necks of a large number of bottles in which the animals are confined with their noses adjacent the bottle necks. Readily detachable small tubes communicate with the inner manifold and extend to the necks of the bottles. The upper end of the outer manifold and the lower end of the inner manifold are closed. Gaseous material is supplied to the upper end of the inner manifold, flows through the small tubes to points adjacent the noses of the individual animals, then is drawn out through the bottom of the outer manifold. The bottles are readily removable and the device can be disassembled, e.g., for cleaning, by removing the bottles, removing the small tubes, and lifting the inner manifold from the outer manifold. The bottles are supported by engagement of their necks with the outer manifold supplemented, if additional support is required, by individual wire cradles. The outer ends of the bottles are closed by plugs, through which pass metal tubes which receive the tails of the animals (usually rodents) and which serve to dissipate body heat. The entire device is mounted for rotation on turntable bearings.

Microchannel heat sink assembly

DOEpatents

Bonde, W.L.; Contolini, R.J.

1992-03-24

The present invention provides a microchannel heat sink with a thermal range from cryogenic temperatures to several hundred degrees centigrade. The heat sink can be used with a variety of fluids, such as cryogenic or corrosive fluids, and can be operated at a high pressure. The heat sink comprises a microchannel layer preferably formed of silicon, and a manifold layer preferably formed of glass. The manifold layer comprises an inlet groove and outlet groove which define an inlet manifold and an outlet manifold. The inlet manifold delivers coolant to the inlet section of the microchannels, and the outlet manifold receives coolant from the outlet section of the microchannels. In one embodiment, the manifold layer comprises an inlet hole extending through the manifold layer to the inlet manifold, and an outlet hole extending through the manifold layer to the outlet manifold. Coolant is supplied to the heat sink through a conduit assembly connected to the heat sink. A resilient seal, such as a gasket or an O-ring, is disposed between the conduit and the hole in the heat sink in order to provide a watertight seal. In other embodiments, the conduit assembly may comprise a metal tube which is connected to the heat sink by a soft solder. In still other embodiments, the heat sink may comprise inlet and outlet nipples. The present invention has application in supercomputers, integrated circuits and other electronic devices, and is suitable for cooling materials to superconducting temperatures. 13 figs.

Microwave waveguide manifold and method

DOEpatents

Staehlin, John H.

1987-01-01

A controllably electrically coupled, physically intersecting plural waveguide manifold assembly wherein the intersecting waveguide elements are fabricated in integral unitary relationship from a single piece of metal in order to avoid the inaccuracies and difficult-to-control fabrication steps associated with uniting separate waveguide elements into a unitary structure. An X-band aluminum airborne radar manifold example is disclosed, along with a fabrication sequence for the manifold and the electrical energy communicating apertures joining the manifold elements.

Microwave waveguide manifold and method

DOEpatents

Staehlin, John H.

1987-12-01

A controllably electrically coupled, physically intersecting plural waveguide manifold assembly wherein the intersecting waveguide elements are fabricated in integral unitary relationship from a single piece of metal in order to avoid the inaccuracies and difficult-to-control fabrication steps associated with uniting separate waveguide elements into a unitary structure. An X-band aluminum airborne radar manifold example is disclosed, along with a fabrication sequence for the manifold and the electrical energy communicating apertures joining the manifold elements.

Manifold learning-based subspace distance for machinery damage assessment

NASA Astrophysics Data System (ADS)

Sun, Chuang; Zhang, Zhousuo; He, Zhengjia; Shen, Zhongjie; Chen, Binqiang

2016-03-01

Damage assessment is very meaningful to keep safety and reliability of machinery components, and vibration analysis is an effective way to carry out the damage assessment. In this paper, a damage index is designed by performing manifold distance analysis on vibration signal. To calculate the index, vibration signal is collected firstly, and feature extraction is carried out to obtain statistical features that can capture signal characteristics comprehensively. Then, manifold learning algorithm is utilized to decompose feature matrix to be a subspace, that is, manifold subspace. The manifold learning algorithm seeks to keep local relationship of the feature matrix, which is more meaningful for damage assessment. Finally, Grassmann distance between manifold subspaces is defined as a damage index. The Grassmann distance reflecting manifold structure is a suitable metric to measure distance between subspaces in the manifold. The defined damage index is applied to damage assessment of a rotor and the bearing, and the result validates its effectiveness for damage assessment of machinery component.

Dictionary Pair Learning on Grassmann Manifolds for Image Denoising.

PubMed

Zeng, Xianhua; Bian, Wei; Liu, Wei; Shen, Jialie; Tao, Dacheng

2015-11-01

Image denoising is a fundamental problem in computer vision and image processing that holds considerable practical importance for real-world applications. The traditional patch-based and sparse coding-driven image denoising methods convert 2D image patches into 1D vectors for further processing. Thus, these methods inevitably break down the inherent 2D geometric structure of natural images. To overcome this limitation pertaining to the previous image denoising methods, we propose a 2D image denoising model, namely, the dictionary pair learning (DPL) model, and we design a corresponding algorithm called the DPL on the Grassmann-manifold (DPLG) algorithm. The DPLG algorithm first learns an initial dictionary pair (i.e., the left and right dictionaries) by employing a subspace partition technique on the Grassmann manifold, wherein the refined dictionary pair is obtained through a sub-dictionary pair merging. The DPLG obtains a sparse representation by encoding each image patch only with the selected sub-dictionary pair. The non-zero elements of the sparse representation are further smoothed by the graph Laplacian operator to remove the noise. Consequently, the DPLG algorithm not only preserves the inherent 2D geometric structure of natural images but also performs manifold smoothing in the 2D sparse coding space. We demonstrate that the DPLG algorithm also improves the structural SIMilarity values of the perceptual visual quality for denoised images using the experimental evaluations on the benchmark images and Berkeley segmentation data sets. Moreover, the DPLG also produces the competitive peak signal-to-noise ratio values from popular image denoising algorithms.

Geodesic Monte Carlo on Embedded Manifolds

PubMed Central

Byrne, Simon; Girolami, Mark

2013-01-01

Markov chain Monte Carlo methods explicitly defined on the manifold of probability distributions have recently been established. These methods are constructed from diffusions across the manifold and the solution of the equations describing geodesic flows in the Hamilton–Jacobi representation. This paper takes the differential geometric basis of Markov chain Monte Carlo further by considering methods to simulate from probability distributions that themselves are defined on a manifold, with common examples being classes of distributions describing directional statistics. Proposal mechanisms are developed based on the geodesic flows over the manifolds of support for the distributions, and illustrative examples are provided for the hypersphere and Stiefel manifold of orthonormal matrices. PMID:25309024

Modular robot

DOEpatents

Ferrante, Todd A.

1997-01-01

A modular robot may comprise a main body having a structure defined by a plurality of stackable modules. The stackable modules may comprise a manifold, a valve module, and a control module. The manifold may comprise a top surface and a bottom surface having a plurality of fluid passages contained therein, at least one of the plurality of fluid passages terminating in a valve port located on the bottom surface of the manifold. The valve module is removably connected to the manifold and selectively fluidically connects the plurality of fluid passages contained in the manifold to a supply of pressurized fluid and to a vent. The control module is removably connected to the valve module and actuates the valve module to selectively control a flow of pressurized fluid through different ones of the plurality of fluid passages in the manifold. The manifold, valve module, and control module are mounted together in a sandwich-like manner and comprise a main body. A plurality of leg assemblies are removably connected to the main body and are removably fluidically connected to the fluid passages in the manifold so that each of the leg assemblies can be selectively actuated by the flow of pressurized fluid in different ones of the plurality of fluid passages in the manifold.

Brazing retort manifold design concept may minimize air contamination and enhance uniform gas flow

NASA Technical Reports Server (NTRS)

Ruppe, E. P.

1966-01-01

Brazing retort manifold minimizes air contamination, prevents gas entrapment during purging, and provides uniform gas flow into the retort bell. The manifold is easily cleaned and turbulence within the bell is minimized because all manifold construction lies outside the main enclosure.

The geometry of discombinations and its applications to semi-inverse problems in anelasticity

PubMed Central

Yavari, Arash; Goriely, Alain

2014-01-01

The geometrical formulation of continuum mechanics provides us with a powerful approach to understand and solve problems in anelasticity where an elastic deformation is combined with a non-elastic component arising from defects, thermal stresses, growth effects or other effects leading to residual stresses. The central idea is to assume that the material manifold, prescribing the reference configuration for a body, has an intrinsic, non-Euclidean, geometrical structure. Residual stresses then naturally arise when this configuration is mapped into Euclidean space. Here, we consider the problem of discombinations (a new term that we introduce in this paper), that is, a combined distribution of fields of dislocations, disclinations and point defects. Given a discombination, we compute the geometrical characteristics of the material manifold (curvature, torsion, non-metricity), its Cartan's moving frames and structural equations. This identification provides a powerful algorithm to solve semi-inverse problems with non-elastic components. As an example, we calculate the residual stress field of a cylindrically symmetric distribution of discombinations in an infinite circular cylindrical bar made of an incompressible hyperelastic isotropic elastic solid. PMID:25197257

Quaternionic Kähler Detour Complexes and {mathcal{N} = 2} Supersymmetric Black Holes

NASA Astrophysics Data System (ADS)

Cherney, D.; Latini, E.; Waldron, A.

2011-03-01

We study a class of supersymmetric spinning particle models derived from the radial quantization of stationary, spherically symmetric black holes of four dimensional {{mathcal N} = 2} supergravities. By virtue of the c-map, these spinning particles move in quaternionic Kähler manifolds. Their spinning degrees of freedom describe mini-superspace-reduced supergravity fermions. We quantize these models using BRST detour complex technology. The construction of a nilpotent BRST charge is achieved by using local (worldline) supersymmetry ghosts to generate special holonomy transformations. (An interesting byproduct of the construction is a novel Dirac operator on the superghost extended Hilbert space.) The resulting quantized models are gauge invariant field theories with fields equaling sections of special quaternionic vector bundles. They underly and generalize the quaternionic version of Dolbeault cohomology discovered by Baston. In fact, Baston’s complex is related to the BPS sector of the models we write down. Our results rely on a calculus of operators on quaternionic Kähler manifolds that follows from BRST machinery, and although directly motivated by black hole physics, can be broadly applied to any model relying on quaternionic geometry.

A vacuum manifold for rapid world-to-chip connectivity of complex PDMS microdevices.

PubMed

Cooksey, Gregory A; Plant, Anne L; Atencia, Javier

2009-05-07

The lack of simple interfaces for microfluidic devices with a large number of inlets significantly limits production and utilization of these devices. In this article, we describe the fabrication of a reusable manifold that provides rapid world-to-chip connectivity. A vacuum network milled into a rigid manifold holds microdevices and prevents leakage of fluids injected into the device from ports in the manifold. A number of different manifold designs were explored, and all performed similarly, yielding an average of 100 kPa (15 psi) fluid holding pressure. The wide applicability of this manifold concept is demonstrated by interfacing with a 51-inlet microfluidic chip containing 144 chambers and hundreds of embedded pneumatic valves. Due to the speed of connectivity, the manifolds are ideal for rapid prototyping and are well suited to serve as "universal" interfaces.

21 CFR 870.4290 - Cardiopulmonary bypass adaptor, stopcock, manifold, or fitting.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Cardiopulmonary bypass adaptor, stopcock, manifold... Devices § 870.4290 Cardiopulmonary bypass adaptor, stopcock, manifold, or fitting. (a) Identification. A cardiopulmonary bypass adaptor, stopcock, manifold, or fitting is a device used in cardiovascular diagnostic...

21 CFR 870.4290 - Cardiopulmonary bypass adaptor, stopcock, manifold, or fitting.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Cardiopulmonary bypass adaptor, stopcock, manifold... Devices § 870.4290 Cardiopulmonary bypass adaptor, stopcock, manifold, or fitting. (a) Identification. A cardiopulmonary bypass adaptor, stopcock, manifold, or fitting is a device used in cardiovascular diagnostic...

Brain Surface Conformal Parameterization Using Riemann Surface Structure

PubMed Central

Wang, Yalin; Lui, Lok Ming; Gu, Xianfeng; Hayashi, Kiralee M.; Chan, Tony F.; Toga, Arthur W.; Thompson, Paul M.; Yau, Shing-Tung

2011-01-01

In medical imaging, parameterized 3-D surface models are useful for anatomical modeling and visualization, statistical comparisons of anatomy, and surface-based registration and signal processing. Here we introduce a parameterization method based on Riemann surface structure, which uses a special curvilinear net structure (conformal net) to partition the surface into a set of patches that can each be conformally mapped to a parallelogram. The resulting surface subdivision and the parameterizations of the components are intrinsic and stable (their solutions tend to be smooth functions and the boundary conditions of the Dirichlet problem can be enforced). Conformal parameterization also helps transform partial differential equations (PDEs) that may be defined on 3-D brain surface manifolds to modified PDEs on a two-dimensional parameter domain. Since the Jacobian matrix of a conformal parameterization is diagonal, the modified PDE on the parameter domain is readily solved. To illustrate our techniques, we computed parameterizations for several types of anatomical surfaces in 3-D magnetic resonance imaging scans of the brain, including the cerebral cortex, hippocampi, and lateral ventricles. For surfaces that are topologically homeomorphic to each other and have similar geometrical structures, we show that the parameterization results are consistent and the subdivided surfaces can be matched to each other. Finally, we present an automatic sulcal landmark location algorithm by solving PDEs on cortical surfaces. The landmark detection results are used as constraints for building conformal maps between surfaces that also match explicitly defined landmarks. PMID:17679336

Gradient-based adaptation of general gaussian kernels.

PubMed

Glasmachers, Tobias; Igel, Christian

2005-10-01

Gradient-based optimizing of gaussian kernel functions is considered. The gradient for the adaptation of scaling and rotation of the input space is computed to achieve invariance against linear transformations. This is done by using the exponential map as a parameterization of the kernel parameter manifold. By restricting the optimization to a constant trace subspace, the kernel size can be controlled. This is, for example, useful to prevent overfitting when minimizing radius-margin generalization performance measures. The concepts are demonstrated by training hard margin support vector machines on toy data.

Geometry of quantum state manifolds generated by the Lie algebra operators

NASA Astrophysics Data System (ADS)

Kuzmak, A. R.

2018-03-01

The Fubini-Study metric of quantum state manifold generated by the operators which satisfy the Heisenberg Lie algebra is calculated. The similar problem is studied for the manifold generated by the so(3) Lie algebra operators. Using these results, we calculate the Fubini-Study metrics of state manifolds generated by the position and momentum operators. Also the metrics of quantum state manifolds generated by some spin systems are obtained. Finally, we generalize this problem for operators of an arbitrary Lie algebra.

Radiolabeled Microsphere Technique in Conscious Subjects during Acceleration Exposures on the USAFSAM Centrifuge.

DTIC Science & Technology

1980-03-01

function even though the pump is pumping air into the blood manifold. R-2 is secured to the plate with two thumb screws, and when the syringes are...the scapula . The animals were allowed 2-4 weeks of surgical recovery before the acceleration studies were performed. Experimental Protocol--On the day

Fuel-Optimal Trajectories in a Planet-Moon Environment Using Multiple Gravity Assists

NASA Technical Reports Server (NTRS)

Ross, Shane D.; Grover, Piyush

2007-01-01

For low energy spacecraft trajectories such as multi-moon orbiters for the Jupiter system, multiple gravity assists by moons could be used in conjunction with ballistic capture to drastically decrease fuel usage. In this paper, we outline a procedure to obtain a family of zero-fuel multi-moon orbiter trajectories, using a family of Keplerian maps derived by the first author previously. The maps capture well the dynamics of the full equations of motion; the phase space contains a connected chaotic zone where intersections between unstable resonant orbit manifolds provide the template for lanes of fast migration between orbits of different semimajor axes. Patched three body approach is used and the four body problem is broken down into two three-body problems, and the search space is considerably reduced by the use of properties of the Keplerian maps. We also introduce the notion of Switching Region where the perturbations due to the two perturbing moons are of comparable strength, and which separates the domains of applicability of the corresponding two Keplerian maps.

Special ergodic theorems and dynamical large deviations

NASA Astrophysics Data System (ADS)

Kleptsyn, Victor; Ryzhov, Dmitry; Minkov, Stanislav

2012-11-01

Let f : M → M be a self-map of a compact Riemannian manifold M, admitting a global SRB measure μ. For a continuous test function \\varphi\\colon M\\to R and a constant α > 0, consider the set Kφ,α of the initial points for which the Birkhoff time averages of the function φ differ from its μ-space average by at least α. As the measure μ is a global SRB one, the set Kφ,α should have zero Lebesgue measure. The special ergodic theorem, whenever it holds, claims that, moreover, this set has a Hausdorff dimension less than the dimension of M. We prove that for Lipschitz maps, the special ergodic theorem follows from the dynamical large deviations principle. We also define and prove analogous result for flows. Applying the theorems of Young and of Araújo and Pacifico, we conclude that the special ergodic theorem holds for transitive hyperbolic attractors of C2-diffeomorphisms, as well as for some other known classes of maps (including the one of partially hyperbolic non-uniformly expanding maps) and flows.

Dual manifold system and method for fluid transfer

DOEpatents

Doktycz, Mitchel J [Knoxville, TN; Bryan, William Louis [Knoxville, TN; Kress, Reid [Oak Ridge, TN

2003-05-27

A dual-manifold assembly is provided for the rapid, parallel transfer of liquid reagents from a microtiter plate to a solid state microelectronic device having biological sensors integrated thereon. The assembly includes aspiration and dispense manifolds connected by a plurality of conduits. In operation, the aspiration manifold is actuated such that the aspiration manifold is seated onto an array of reagent-filled wells of the microtiter plate. The wells are pressurized to force reagent through conduits toward the dispense manifold. A pressure pulse provided by a standard ink-jet printhead ejects nanoliter-to-picoliter droplets of reagent through an array of printhead orifices and onto test sites on the surface of the microelectronic device.

Dual manifold system and method for fluid transfer

DOEpatents

Doktycz, Mitchel J.; Bryan, William Louis; Kress, Reid

2003-09-30

A dual-manifold assembly is provided for the rapid, parallel transfer of liquid reagents from a microtiter plate to a solid state microelectronic device having biological sensors integrated thereon. The assembly includes aspiration and dispense manifolds connected by a plurality of conduits. In operation, the aspiration manifold is actuated such that the aspiration manifold is seated onto an array of reagent-filled wells of the microtiter plate. The wells are pressurized to force reagent through conduits toward the dispense manifold. A pressure pulse provided by a standard ink-jet printhead ejects nanoliter-to-picoliter droplets of reagent through an array of printhead orifices and onto test sites on the surface of the microelectronic device.

Test of the Hill Stability Criterion against Chaos Indicators

NASA Astrophysics Data System (ADS)

Satyal, Suman; Quarles, Billy; Hinse, Tobias

2012-10-01

The efficacy of Hill Stability (HS) criterion is tested against other known chaos indicators such as Maximum Lyapunov Exponents (MLE) and Mean Exponential Growth of Nearby Orbits (MEGNO) maps. First, orbits of four observationally verified binary star systems: γ Cephei, Gliese-86, HD41004, and HD196885 are integrated using standard integration packages (MERCURY, SWIFTER, NBI, C/C++). The HS which measures orbital perturbation of a planet around the primary star due to the secondary star is calculated for each system. The LEs spectra are generated to measure the divergence/convergence rate of stable manifolds and the MEGNO maps are generated by using the variational equations of the system during the integration process. These maps allow to accurately differentiate between stable and unstable dynamical systems. Then the results obtained from the analysis of HS, MLE, and MEGNO maps are checked for their dynamical variations and resemblance. The HS of most of the planets seems to be stable, quasi-periodic for at least ten million years. The MLE and the MEGNO maps also indicate the local quasi-periodicity and global stability in relatively short integration period. The HS criterion is found to be a comparably efficient tool to measure the stability of planetary orbits.

Monopolar fuel cell stack coupled together without use of top or bottom cover plates or tie rods

NASA Technical Reports Server (NTRS)

Narayanan, Sekharipuram R. (Inventor); Valdez, Thomas I. (Inventor)

2009-01-01

A monopolar fuel cell stack comprises a plurality of sealed unit cells coupled together. Each unit cell comprises two outer cathodes adjacent to corresponding membrane electrode assemblies and a center anode plate. An inlet and outlet manifold are coupled to the anode plate and communicate with a channel therein. Fuel flows from the inlet manifold through the channel in contact with the anode plate and flows out through the outlet manifold. The inlet and outlet manifolds are arranged to couple to the inlet and outlet manifolds respectively of an adjacent one of the plurality of unit cells to permit fuel flow in common into all of the inlet manifolds of the plurality of the unit cells when coupled together in a stack and out of all of the outlet manifolds of the plurality of unit cells when coupled together in a stack.

Towards a double field theory on para-Hermitian manifolds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vaisman, Izu

In a previous paper, we have shown that the geometry of double field theory has a natural interpretation on flat para-Kähler manifolds. In this paper, we show that the same geometric constructions can be made on any para-Hermitian manifold. The field is interpreted as a compatible (pseudo-)Riemannian metric. The tangent bundle of the manifold has a natural, metric-compatible bracket that extends the C-bracket of double field theory. In the para-Kähler case, this bracket is equal to the sum of the Courant brackets of the two Lagrangian foliations of the manifold. Then, we define a canonical connection and an action ofmore » the field that correspond to similar objects of double field theory. Another section is devoted to the Marsden-Weinstein reduction in double field theory on para-Hermitian manifolds. Finally, we give examples of fields on some well-known para-Hermitian manifolds.« less

Multipoint Fuel Injection Arrangements

NASA Technical Reports Server (NTRS)

Prociw, Lev Alexander (Inventor)

2017-01-01

A multipoint fuel injection system includes a plurality of fuel manifolds. Each manifold is in fluid communication with a plurality of injectors arranged circumferentially about a longitudinal axis for multipoint fuel injection. The injectors of separate respective manifolds are spaced radially apart from one another for separate radial staging of fuel flow to each respective manifold.

Optimal transfers between unstable periodic orbits using invariant manifolds

NASA Astrophysics Data System (ADS)

Davis, Kathryn E.; Anderson, Rodney L.; Scheeres, Daniel J.; Born, George H.

2011-03-01

This paper presents a method to construct optimal transfers between unstable periodic orbits of differing energies using invariant manifolds. The transfers constructed in this method asymptotically depart the initial orbit on a trajectory contained within the unstable manifold of the initial orbit and later, asymptotically arrive at the final orbit on a trajectory contained within the stable manifold of the final orbit. Primer vector theory is applied to a transfer to determine the optimal maneuvers required to create the bridging trajectory that connects the unstable and stable manifold trajectories. Transfers are constructed between unstable periodic orbits in the Sun-Earth, Earth-Moon, and Jupiter-Europa three-body systems. Multiple solutions are found between the same initial and final orbits, where certain solutions retrace interior portions of the trajectory. All transfers created satisfy the conditions for optimality. The costs of transfers constructed using manifolds are compared to the costs of transfers constructed without the use of manifolds. In all cases, the total cost of the transfer is significantly lower when invariant manifolds are used in the transfer construction. In many cases, the transfers that employ invariant manifolds are three times more efficient, in terms of fuel expenditure, than the transfer that do not. The decrease in transfer cost is accompanied by an increase in transfer time of flight.

Modular robot

DOEpatents

Ferrante, T.A.

1997-11-11

A modular robot may comprise a main body having a structure defined by a plurality of stackable modules. The stackable modules may comprise a manifold, a valve module, and a control module. The manifold may comprise a top surface and a bottom surface having a plurality of fluid passages contained therein, at least one of the plurality of fluid passages terminating in a valve port located on the bottom surface of the manifold. The valve module is removably connected to the manifold and selectively fluidically connects the plurality of fluid passages contained in the manifold to a supply of pressurized fluid and to a vent. The control module is removably connected to the valve module and actuates the valve module to selectively control a flow of pressurized fluid through different ones of the plurality of fluid passages in the manifold. The manifold, valve module, and control module are mounted together in a sandwich-like manner and comprise a main body. A plurality of leg assemblies are removably connected to the main body and are removably fluidically connected to the fluid passages in the manifold so that each of the leg assemblies can be selectively actuated by the flow of pressurized fluid in different ones of the plurality of fluid passages in the manifold. 12 figs.

Interactive Spacecraft Trajectory Design Strategies Featuring Poincare Map Topology

NASA Astrophysics Data System (ADS)

Schlei, Wayne R.

Space exploration efforts are shifting towards inexpensive and more agile vehicles. Versatility regarding spacecraft trajectories refers to the agility to correct deviations from an intended path or even the ability to adapt the future path to a new destination--all with limited spaceflight resources (i.e., small DeltaV budgets). Trajectory design methods for such nimble vehicles incorporate equally versatile procedures that allow for rapid and interactive decision making while attempting to reduce Delta V budgets, leading to a versatile trajectory design platform. A versatile design paradigm requires the exploitation of Poincare map topology , or the interconnected web of dynamical structures, existing within the chaotic dynamics of multi-body gravitational models to outline low-Delta V transfer options residing nearby to a current path. This investigation details an autonomous procedure to extract the periodic orbits (topology nodes) and correlated asymptotic flow structures (or the invariant manifolds representing topology links). The autonomous process summarized in this investigation (termed PMATE) overcomes discontinuities on the Poincare section that arise in the applied multi-body model (the planar circular restricted three-body problem) and detects a wide variety of novel periodic orbits. New interactive capabilities deliver a visual analytics foundation for versatile spaceflight design, especially for initial guess generation and manipulation. Such interactive strategies include the selection of states and arcs from Poincare section visualizations and the capabilities to draw and drag trajectories to remove dependency on initial state input. Furthermore, immersive selection is expanded to cull invariant manifold structures, yielding low-DeltaV or even DeltaV-free transfers between periodic orbits. The application of interactive design strategies featuring a dense extraction of Poincare map topology is demonstrated for agile spaceflight with a simple spacecraft rerouting scenario incorporating a very limited Delta V budget. In the Earth-Moon system, a low-DeltaV transfer from low Earth orbit (LEO) to the distant retrograde orbit (DRO) vicinity is derived with interactive topology-based design tactics. Finally, Poincare map topology is exploited in the Saturn-Enceladus system to explore a possible ballistic capture scenario around Enceladus.

Engine Air Intake Manifold Having Built In Intercooler

DOEpatents

Freese, V, Charles E.

2000-09-12

A turbocharged V type engine can be equipped with an exhaust gas recirculation cooler integrated into the intake manifold, so as to achieve efficiency, cost reductions and space economization improvements. The cooler can take the form of a tube-shell heat exchanger that utilizes a cylindrical chamber in the air intake manifold as the heat exchanger housing. The intake manifold depends into the central space formed by the two banks of cylinders on the V type engine, such that the central space is effectively utilized for containing the manifold and cooler.

Modeling low-thrust transfers between periodic orbits about five libration points: Manifolds and hierarchical design

NASA Astrophysics Data System (ADS)

Zeng, Hao; Zhang, Jingrui

2018-04-01

The low-thrust version of the fuel-optimal transfers between periodic orbits with different energies in the vicinity of five libration points is exploited deeply in the Circular Restricted Three-Body Problem. Indirect optimization technique incorporated with constraint gradients is employed to further improve the computational efficiency and accuracy of the algorithm. The required optimal thrust magnitude and direction can be determined to create the bridging trajectory that connects the invariant manifolds. A hierarchical design strategy dividing the constraint set is proposed to seek the optimal solution when the problem cannot be solved directly. Meanwhile, the solution procedure and the value ranges of used variables are summarized. To highlight the effectivity of the transfer scheme and aim at different types of libration point orbits, transfer trajectories between some sample orbits, including Lyapunov orbits, planar orbits, halo orbits, axial orbits, vertical orbits and butterfly orbits for collinear and triangular libration points, are investigated with various time of flight. Numerical results show that the fuel consumption varies from a few kilograms to tens of kilograms, related to the locations and the types of mission orbits as well as the corresponding invariant manifold structures, and indicates that the low-thrust transfers may be a beneficial option for the extended science missions around different libration points.

A simple proof of orientability in colored group field theory.

PubMed

Caravelli, Francesco

2012-01-01

Group field theory is an emerging field at the boundary between Quantum Gravity, Statistical Mechanics and Quantum Field Theory and provides a path integral for the gluing of n-simplices. Colored group field theory has been introduced in order to improve the renormalizability of the theory and associates colors to the faces of the simplices. The theory of crystallizations is instead a field at the boundary between graph theory and combinatorial topology and deals with n-simplices as colored graphs. Several techniques have been introduced in order to study the topology of the pseudo-manifold associated to the colored graph. Although of the similarity between colored group field theory and the theory of crystallizations, the connection between the two fields has never been made explicit. In this short note we use results from the theory of crystallizations to prove that color in group field theories guarantees orientability of the piecewise linear pseudo-manifolds associated to each graph generated perturbatively. Colored group field theories generate orientable pseudo-manifolds. The origin of orientability is the presence of two interaction vertices in the action of colored group field theories. In order to obtain the result, we made the connection between the theory of crystallizations and colored group field theory.

A non-linear dimension reduction methodology for generating data-driven stochastic input models

NASA Astrophysics Data System (ADS)

Ganapathysubramanian, Baskar; Zabaras, Nicholas

2008-06-01

Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem of manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space Rn. An isometric mapping F from M to a low-dimensional, compact, connected set A⊂Rd(d≪n) is constructed. Given only a finite set of samples of the data, the methodology uses arguments from graph theory and differential geometry to construct the isometric transformation F:M→A. Asymptotic convergence of the representation of M by A is shown. This mapping F serves as an accurate, low-dimensional, data-driven representation of the property variations. The reduced-order model of the material topology and thermal diffusivity variations is subsequently used as an input in the solution of stochastic partial differential equations that describe the evolution of dependant variables. A sparse grid collocation strategy (Smolyak algorithm) is utilized to solve these stochastic equations efficiently. We showcase the methodology by constructing low-dimensional input stochastic models to represent thermal diffusivity in two-phase microstructures. This model is used in analyzing the effect of topological variations of two-phase microstructures on the evolution of temperature in heat conduction processes.

Wave equations on anti self dual (ASD) manifolds

NASA Astrophysics Data System (ADS)

Bashingwa, Jean-Juste; Kara, A. H.

2017-11-01

In this paper, we study and perform analyses of the wave equation on some manifolds with non diagonal metric g_{ij} which are of neutral signatures. These include the invariance properties, variational symmetries and conservation laws. In the recent past, wave equations on the standard (space time) Lorentzian manifolds have been performed but not on the manifolds from metrics of neutral signatures.

Manifold gasket accommodating differential movement of fuel cell stack

DOEpatents

Kelley, Dana A.; Farooque, Mohammad

2007-11-13

A gasket for use in a fuel cell system having at least one externally manifolded fuel cell stack, for sealing the manifold edge and the stack face. In accordance with the present invention, the gasket accommodates differential movement between the stack and manifold by promoting slippage at interfaces between the gasket and the dielectric and between the gasket and the stack face.

Scalable microreactors and methods for using same

DOEpatents

Lawal, Adeniyi; Qian, Dongying

2010-03-02

The present invention provides a scalable microreactor comprising a multilayered reaction block having alternating reaction plates and heat exchanger plates that have a plurality of microchannels; a multilaminated reactor input manifold, a collecting reactor output manifold, a heat exchange input manifold and a heat exchange output manifold. The present invention also provides methods of using the microreactor for multiphase chemical reactions.

Masking Strategies for Image Manifolds.

PubMed

Dadkhahi, Hamid; Duarte, Marco F

2016-07-07

We consider the problem of selecting an optimal mask for an image manifold, i.e., choosing a subset of the pixels of the image that preserves the manifold's geometric structure present in the original data. Such masking implements a form of compressive sensing through emerging imaging sensor platforms for which the power expense grows with the number of pixels acquired. Our goal is for the manifold learned from masked images to resemble its full image counterpart as closely as possible. More precisely, we show that one can indeed accurately learn an image manifold without having to consider a large majority of the image pixels. In doing so, we consider two masking methods that preserve the local and global geometric structure of the manifold, respectively. In each case, the process of finding the optimal masking pattern can be cast as a binary integer program, which is computationally expensive but can be approximated by a fast greedy algorithm. Numerical experiments show that the relevant manifold structure is preserved through the datadependent masking process, even for modest mask sizes.

Properties of Principal TL (Thermoluminescence) Dosimeters.

DTIC Science & Technology

1983-10-01

thermoluminescence dosimetry ( TLD ) emerged as the preferred means because of convenience of batch evaluation, reusability, large detection range, linearity and...personnel dosimetry , thermoluminescence dosimetry has emerged as a superior technique due to its manifold advantages over other methods of dose...their suitability for dosimetry . A brief description of important TL materials and their properties is documented in this report. DD ,JN 1473 EDITION 0

Heterotic model building: 16 special manifolds

NASA Astrophysics Data System (ADS)

He, Yang-Hui; Lee, Seung-Joo; Lukas, Andre; Sun, Chuang

2014-06-01

We study heterotic model building on 16 specific Calabi-Yau manifolds constructed as hypersurfaces in toric four-folds. These 16 manifolds are the only ones among the more than half a billion manifolds in the Kreuzer-Skarke list with a non-trivial first fundamental group. We classify the line bundle models on these manifolds, both for SU(5) and SO(10) GUTs, which lead to consistent supersymmetric string vacua and have three chiral families. A total of about 29000 models is found, most of them corresponding to SO(10) GUTs. These models constitute a starting point for detailed heterotic model building on Calabi-Yau manifolds in the Kreuzer-Skarke list. The data for these models can be downloaded from http://www-thphys.physics.ox.ac.uk/projects/CalabiYau/toricdata/index.html.

Heat shield manifold system for a midframe case of a gas turbine engine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayer, Clinton A.; Eng, Jesse; Schopf, Cheryl A.

A heat shield manifold system for an inner casing between a compressor and turbine assembly is disclosed. The heat shield manifold system protects the outer case from high temperature compressor discharge air, thereby enabling the outer case extending between a compressor and a turbine assembly to be formed from less expensive materials than otherwise would be required. In addition, the heat shield manifold system may be configured such that compressor bleed air is passed from the compressor into the heat shield manifold system without passing through a conventional flange to flange joint that is susceptible to leakage.

Doran-Harder-Thompson Conjecture via SYZ Mirror Symmetry: Elliptic Curves

NASA Astrophysics Data System (ADS)

Kanazawa, Atsushi

2017-04-01

We prove the Doran-Harder-Thompson conjecture in the case of elliptic curves by using ideas from SYZ mirror symmetry. The conjecture claims that when a Calabi-Yau manifold X degenerates to a union of two quasi-Fano manifolds (Tyurin degeneration), a mirror Calabi-Yau manifold of X can be constructed by gluing the two mirror Landau-Ginzburg models of the quasi-Fano manifolds. The two crucial ideas in our proof are to obtain a complex structure by gluing the underlying affine manifolds and to construct the theta functions from the Landau-Ginzburg superpotentials.

Heating and thermal squeezing in parametrically driven oscillators with added noise.

PubMed

Batista, Adriano A

2012-11-01

In this paper we report a theoretical model based on Green's functions, Floquet theory, and averaging techniques up to second order that describes the dynamics of parametrically driven oscillators with added thermal noise. Quantitative estimates for heating and quadrature thermal noise squeezing near and below the transition line of the first parametric instability zone of the oscillator are given. Furthermore, we give an intuitive explanation as to why heating and thermal squeezing occur. For small amplitudes of the parametric pump the Floquet multipliers are complex conjugate of each other with a constant magnitude. As the pump amplitude is increased past a threshold value in the stable zone near the first parametric instability, the two Floquet multipliers become real and have different magnitudes. This creates two different effective dissipation rates (one smaller and the other larger than the real dissipation rate) along the stable manifolds of the first-return Poincaré map. We also show that the statistical average of the input power due to thermal noise is constant and independent of the pump amplitude and frequency. The combination of these effects causes most of heating and thermal squeezing. Very good agreement between analytical and numerical estimates of the thermal fluctuations is achieved.

Manifold seal for fuel cell stack assembly

DOEpatents

Schmitten, Phillip F.; Wright, Maynard K.

1989-01-01

An assembly for sealing a manifold to a stack of fuel cells includes a first resilient member for providing a first sealing barrier between the manifold and the stack. A second resilient member provides a second sealing barrier between the manifold and the stack. The first and second resilient members are retained in such a manner as to define an area therebetween adapted for retaining a sealing composition.

Duct flow nonuniformities study for space shuttle main engine

NASA Technical Reports Server (NTRS)

Thoenes, J.

1985-01-01

To improve the Space Shuttle Main Engine (SSME) design and for future use in the development of generation rocket engines, a combined experimental/analytical study was undertaken with the goals of first, establishing an experimental data base for the flow conditions in the SSME high pressure fuel turbopump (HPFTP) hot gas manifold (HGM) and, second, setting up a computer model of the SSME HGM flow field. Using the test data to verify the computer model it should be possible in the future to computationally scan contemplated advanced design configurations and limit costly testing to the most promising design. The effort of establishing and using the computer model is detailed. The comparison of computational results and experimental data observed clearly demonstrate that computational fluid mechanics (CFD) techniques can be used successfully to predict the gross features of three dimensional fluid flow through configurations as intricate as the SSME turbopump hot gas manifold.

High pressure jet flame numerical analysis of CO emissions by means of the flamelet generated manifolds technique

NASA Astrophysics Data System (ADS)

Donini, A.; Martin, S. M.; Bastiaans, R. J. M.; van Oijen, J. A.; de Goey, L. P. H.

2013-10-01

In the present paper a computational analysis of a high pressure confined premixed turbulent methane/air jet flames is presented. In this scope, chemistry is reduced by the use of the Flamelet Generated Manifold method [1] and the fluid flow is modeled in an LES and RANS context. The reaction evolution is described by the reaction progress variable, the heat loss is described by the enthalpy and the turbulence effect on the reaction is represented by the progress variable variance. The interaction between chemistry and turbulence is considered through a presumed probability density function (PDF) approach. The use of FGM as a combustion model shows that combustion features at gas turbine conditions can be satisfactorily reproduced with a reasonable computational effort. Furthermore, the present analysis indicates that the physical and chemical processes controlling carbon monoxide (CO) emissions can be captured only by means of unsteady simulations.

Defining functional distance using manifold embeddings of gene ontology annotations

PubMed Central

Lerman, Gilad; Shakhnovich, Boris E.

2007-01-01

Although rigorous measures of similarity for sequence and structure are now well established, the problem of defining functional relationships has been particularly daunting. Here, we present several manifold embedding techniques to compute distances between Gene Ontology (GO) functional annotations and consequently estimate functional distances between protein domains. To evaluate accuracy, we correlate the functional distance to the well established measures of sequence, structural, and phylogenetic similarities. Finally, we show that manual classification of structures into folds and superfamilies is mirrored by proximity in the newly defined function space. We show how functional distances place structure–function relationships in biological context resulting in insight into divergent and convergent evolution. The methods and results in this paper can be readily generalized and applied to a wide array of biologically relevant investigations, such as accuracy of annotation transference, the relationship between sequence, structure, and function, or coherence of expression modules. PMID:17595300

Canards and black swans in a model of a 3-D autocatalator

NASA Astrophysics Data System (ADS)

Shchepakina, E.

2005-01-01

The mathematical model of a 3-D autocatalator is studied using the geometric theory of singular perturbations, namely, the black swan and canard techniques. Critical regimes are modeled by canards (one-dimensional stable-unstable slow integral manifolds). The meaning of criticality here is as follows. The critical regime corresponds to a chemical reaction which separates the domain of self-accelerating reactions from the domain of slow reactions. A two-dimensional stable-unstable slow integral manifold (black swan) consisting entirely of canards, which simulate the critical phenomena for different initial data of the dynamical system, is constructed. It is shown that this procedure leads to the phenomenon of auto-oscillations in the chemical system. The geometric approach combined with asymptotic and numerical methods permits us to explain the strong parametric sensitivity and to obtain asymptotic representations of the critical behavior of the chemical system.

Failure Investigation of an Intra-Manifold Explosion in a Horizontally-Mounted 870 lbf Reaction Control Thruster

NASA Technical Reports Server (NTRS)

Durning, Joseph G., III; Westover, Shayne C.; Cone, Darren M.

2011-01-01

In June 2010, an 870 lbf Space Shuttle Orbiter Reaction Control System Primary Thruster experienced an unintended shutdown during a test being performed at the NASA White Sands Test Facility. Subsequent removal and inspection of the thruster revealed permanent deformation and misalignment of the thruster valve mounting plate. Destructive evaluation determined that after three nominal firing sequences, the thruster had experienced an energetic event within the fuel (monomethylhydrazine) manifold at the start of the fourth firing sequence. The current understanding of the phenomenon of intra-manifold explosions in hypergolic bipropellant thrusters is documented in literature where it is colloquially referred to as a ZOT. The typical ZOT scenario involves operation of a thruster in a gravitational field with environmental pressures above the triple point pressure of the propellants. Post-firing, when the thruster valves are commanded closed, there remains a residual quantity of propellant in both the fuel and oxidizer (nitrogen tetroxide) injector manifolds known as the "dribble volume". In an ambient ground test configuration, these propellant volumes will drain from the injector manifolds but are impeded by the local atmospheric pressure. The evacuation of propellants from the thruster injector manifolds relies on the fluids vapor pressure to expel the liquid. The higher vapor pressure oxidizer will evacuate from the manifold before the lower vapor pressure fuel. The localized cooling resulting from the oxidizer boiling during manifold draining can result in fuel vapor migration and condensation in the oxidizer passage. The liquid fuel will then react with the oxidizer that enters the manifold during the next firing and may produce a localized high pressure reaction or explosion within the confines of the oxidizer injector manifold. The typical ZOT scenario was considered during this failure investigation, but was ultimately ruled out as a cause of the explosion. Converse to the typical ZOT failure mechanism, the failure of this particular thruster was determined to be the result of liquid oxidizer being present within the fuel manifold.

Machine learning for autonomous crystal structure identification.

PubMed

Reinhart, Wesley F; Long, Andrew W; Howard, Michael P; Ferguson, Andrew L; Panagiotopoulos, Athanassios Z

2017-07-21

We present a machine learning technique to discover and distinguish relevant ordered structures from molecular simulation snapshots or particle tracking data. Unlike other popular methods for structural identification, our technique requires no a priori description of the target structures. Instead, we use nonlinear manifold learning to infer structural relationships between particles according to the topology of their local environment. This graph-based approach yields unbiased structural information which allows us to quantify the crystalline character of particles near defects, grain boundaries, and interfaces. We demonstrate the method by classifying particles in a simulation of colloidal crystallization, and show that our method identifies structural features that are missed by standard techniques.

Fuel cell manifold sealing system

DOEpatents

Grevstad, Paul E.; Johnson, Carl K.; Mientek, Anthony P.

1980-01-01

A manifold-to-stack seal and sealing method for fuel cell stacks. This seal system solves the problem of maintaining a low leak rate manifold seal as the fuel cell stack undergoes compressive creep. The seal system eliminates the problem of the manifold-to-stack seal sliding against the rough stack surface as the stack becomes shorter because of cell creep, which relative motion destroys the seal. The seal system described herein utilizes a polymer seal frame firmly clamped between the manifold and the stack such that the seal frame moves with the stack. Thus, as the stack creeps, the seal frame creeps with it, and there is no sliding at the rough, tough to seal, stack-to-seal frame interface. Here the sliding is on a smooth easy to seal location between the seal frame and the manifold.

Method for producing a fuel cell manifold seal

DOEpatents

Grevstad, Paul E.; Johnson, Carl K.; Mientek, Anthony P.

1982-01-01

A manifold-to-stack seal and sealing method for fuel cell stacks. This seal system solves the problem of maintaining a low leak rate manifold seal as the fuel cell stack undergoes compressive creep. The seal system eliminates the problem of the manifold-to-stack seal sliding against the rough stack surface as the stack becomes shorter because of cell creep, which relative motion destroys the seal. The seal system described herein utilizes a polymer seal frame firmly clamped between the manifold and the stack such that the seal frame moves with the stack. Thus, as the stack creeps, the seal frame creeps with it, and there is no sliding at the rough, tough to seal, stack-to-seal frame interface. Here the sliding is on a smooth easy to seal location between the seal frame and the manifold.

Quantification, Distribution, and Possible Source of Bacterial Biofilm in Mouse Automated Watering Systems

PubMed Central

Meier, Thomas R; Maute, Carrie J; Cadillac, Joan M; Lee, Ji Young; Righter, Daniel J; Hugunin, Kelly MS; Deininger, Rolf A; Dysko, Robert C

2008-01-01

The use of automated watering systems for providing drinking water to rodents has become commonplace in the research setting. Little is known regarding bacterial biofilm growth within the water piping attached to the racks (manifolds). The purposes of this project were to determine whether the mouse oral flora contributed to the aerobic bacterial component of the rack biofilm, quantify bacterial growth in rack manifolds over 6 mo, assess our rack sanitation practices, and quantify bacterial biofilm development within sections of the manifold. By using standard methods of bacterial identification, the aerobic oral flora of 8 strains and stocks of mice were determined on their arrival at our animal facility. Ten rack manifolds were sampled before, during, and after sanitation and monthly for 6 mo. Manifolds were evaluated for aerobic bacterial growth by culture on R2A and trypticase soy agar, in addition to bacterial ATP quantification by bioluminescence. In addition, 6 racks were sampled at 32 accessible sites for evaluation of biofilm distribution within the watering manifold. The identified aerobic bacteria in the oral flora were inconsistent with the bacteria from the manifold, suggesting that the mice do not contribute to the biofilm bacteria. Bacterial growth in manifolds increased while they were in service, with exponential growth of the biofilm from months 3 to 6 and a significant decrease after sanitization. Bacterial biofilm distribution was not significantly different across location quartiles of the rack manifold, but bacterial levels differed between the shelf pipe and connecting elbow pipes. PMID:18351724

Quantification, distribution, and possible source of bacterial biofilm in mouse automated watering systems.

PubMed

Meier, Thomas R; Maute, Carrie J; Cadillac, Joan M; Lee, Ji Young; Righter, Daniel J; Hugunin, Kelly M S; Deininger, Rolf A; Dysko, Robert C

2008-03-01

The use of automated watering systems for providing drinking water to rodents has become commonplace in the research setting. Little is known regarding bacterial biofilm growth within the water piping attached to the racks (manifolds). The purposes of this project were to determine whether the mouse oral flora contributed to the aerobic bacterial component of the rack biofilm, quantify bacterial growth in rack manifolds over 6 mo, assess our rack sanitation practices, and quantify bacterial biofilm development within sections of the manifold. By using standard methods of bacterial identification, the aerobic oral flora of 8 strains and stocks of mice were determined on their arrival at our animal facility. Ten rack manifolds were sampled before, during, and after sanitation and monthly for 6 mo. Manifolds were evaluated for aerobic bacterial growth by culture on R2A and trypticase soy agar, in addition to bacterial ATP quantification by bioluminescence. In addition, 6 racks were sampled at 32 accessible sites for evaluation of biofilm distribution within the watering manifold. The identified aerobic bacteria in the oral flora were inconsistent with the bacteria from the manifold, suggesting that the mice do not contribute to the biofilm bacteria. Bacterial growth in manifolds increased while they were in service, with exponential growth of the biofilm from months 3 to 6 and a significant decrease after sanitization. Bacterial biofilm distribution was not significantly different across location quartiles of the rack manifold, but bacterial levels differed between the shelf pipe and connecting elbow pipes.

Discriminative clustering on manifold for adaptive transductive classification.

PubMed

Zhang, Zhao; Jia, Lei; Zhang, Min; Li, Bing; Zhang, Li; Li, Fanzhang

2017-10-01

In this paper, we mainly propose a novel adaptive transductive label propagation approach by joint discriminative clustering on manifolds for representing and classifying high-dimensional data. Our framework seamlessly combines the unsupervised manifold learning, discriminative clustering and adaptive classification into a unified model. Also, our method incorporates the adaptive graph weight construction with label propagation. Specifically, our method is capable of propagating label information using adaptive weights over low-dimensional manifold features, which is different from most existing studies that usually predict the labels and construct the weights in the original Euclidean space. For transductive classification by our formulation, we first perform the joint discriminative K-means clustering and manifold learning to capture the low-dimensional nonlinear manifolds. Then, we construct the adaptive weights over the learnt manifold features, where the adaptive weights are calculated through performing the joint minimization of the reconstruction errors over features and soft labels so that the graph weights can be joint-optimal for data representation and classification. Using the adaptive weights, we can easily estimate the unknown labels of samples. After that, our method returns the updated weights for further updating the manifold features. Extensive simulations on image classification and segmentation show that our proposed algorithm can deliver the state-of-the-art performance on several public datasets. Copyright © 2017 Elsevier Ltd. All rights reserved.

Geometric chaos indicators and computations of the spherical hypertube manifolds of the spatial circular restricted three-body problem

NASA Astrophysics Data System (ADS)

Guzzo, Massimiliano; Lega, Elena

2018-06-01

The circular restricted three-body problem has five relative equilibria L1 ,L2, . . . ,L5. The invariant stable-unstable manifolds of the center manifolds originating at the partially hyperbolic equilibria L1 ,L2 have been identified as the separatrices for the motions which transit between the regions of the phase-space which are internal or external with respect to the two massive bodies. While the stable and unstable manifolds of the planar problem have been extensively studied both theoretically and numerically, the spatial case has not been as deeply investigated. This paper is devoted to the global computation of these manifolds in the spatial case with a suitable finite time chaos indicator. The definition of the chaos indicator is not trivial, since the mandatory use of the regularizing Kustaanheimo-Stiefel variables may introduce discontinuities in the finite time chaos indicators. From the study of such discontinuities, we define geometric chaos indicators which are globally defined and smooth, and whose ridges sharply approximate the stable and unstable manifolds of the center manifolds of L1 ,L2. We illustrate the method for the Sun-Jupiter mass ratio, and represent the topology of the asymptotic manifolds using sections and three-dimensional representations.

Learning an intrinsic-variable preserving manifold for dynamic visual tracking.

PubMed

Qiao, Hong; Zhang, Peng; Zhang, Bo; Zheng, Suiwu

2010-06-01

Manifold learning is a hot topic in the field of computer science, particularly since nonlinear dimensionality reduction based on manifold learning was proposed in Science in 2000. The work has achieved great success. The main purpose of current manifold-learning approaches is to search for independent intrinsic variables underlying high dimensional inputs which lie on a low dimensional manifold. In this paper, a new manifold is built up in the training step of the process, on which the input training samples are set to be close to each other if the values of their intrinsic variables are close to each other. Then, the process of dimensionality reduction is transformed into a procedure of preserving the continuity of the intrinsic variables. By utilizing the new manifold, the dynamic tracking of a human who can move and rotate freely is achieved. From the theoretical point of view, it is the first approach to transfer the manifold-learning framework to dynamic tracking. From the application point of view, a new and low dimensional feature for visual tracking is obtained and successfully applied to the real-time tracking of a free-moving object from a dynamic vision system. Experimental results from a dynamic tracking system which is mounted on a dynamic robot validate the effectiveness of the new algorithm.

Independent-Cluster Parametrizations of Wave Functions in Model Field Theories III. The Coupled-Cluster Phase Spaces and Their Geometrical Structure

NASA Astrophysics Data System (ADS)

Arponen, J. S.; Bishop, R. F.

1993-11-01

In this third paper of a series we study the structure of the phase spaces of the independent-cluster methods. These phase spaces are classical symplectic manifolds which provide faithful descriptions of the quantum mechanical pure states of an arbitrary system. They are "superspaces" in the sense that the full physical many-body or field-theoretic system is described by a point of the space, in contrast to "ordinary" spaces for which the state of the physical system is described rather by the whole space itself. We focus attention on the normal and extended coupled-cluster methods (NCCM and ECCM). Both methods provide parametrizations of the Hilbert space which take into account in increasing degrees of completeness the connectivity properties of the associated perturbative diagram structure. This corresponds to an increasing incorporation of locality into the description of the quantum system. As a result the degree of nonlinearity increases in the dynamical equations that govern the temporal evolution and determine the equilibrium state. Because of the nonlinearity, the structure of the manifold becomes geometrically complicated. We analyse the neighbourhood of the ground state of the one-mode anharmonic bosonic field theory and derive the nonlinear expansion beyond the linear response regime. The expansion is given in terms of normal-mode amplitudes, which provide the best local coordinate system close to the ground state. We generalize the treatment to other nonequilibrium states by considering the similarly defined normal coordinates around the corresponding phase space point. It is pointed out that the coupled-cluster method (CCM) maps display such features as (an)holonomy, or geometric phase. For example, a physical state may be represented by a number of different points on the CCM manifold. For this reason the whole phase spaces in the NCCM or ECCM cannot be covered by a single chart. To account for this non-Euclidean nature we introduce a suitable pseudo-Riemannian metric structure which is compatible with an important subset of all canonical transformations. It is then shown that the phase space of the configuration-interaction method is flat, namely the complex Euclidean space; that the NCCM manifold has zero curvature even though its Reimann tensor does not vanish; and that the ECCM manifold is intrinsically curved. It is pointed out that with the present metrization many of the dimensions of the ECCM phase space are effectively compactified and that the overall topological structure of the space is related to the distribution of the zeros of the Bargmann wave function.

A general Kastler-Kalau-Walze type theorem for manifolds with boundary

NASA Astrophysics Data System (ADS)

Wang, Jian; Wang, Yong

2016-11-01

In this paper, we establish a general Kastler-Kalau-Walze type theorem for any dimensional manifolds with boundary which generalizes the results in [Y. Wang, Lower-dimensional volumes and Kastler-Kalau-Walze type theorem for manifolds with boundary, Commun. Theor. Phys. 54 (2010) 38-42]. This solves a problem of the referee of [J. Wang and Y. Wang, A Kastler-Kalau-Walze type theorem for five-dimensional manifolds with boundary, Int. J. Geom. Meth. Mod. Phys. 12(5) (2015), Article ID: 1550064, 34 pp.], which is a general expression of the lower dimensional volumes in terms of the geometric data on the manifold.

LCK rank of locally conformally Kähler manifolds with potential

NASA Astrophysics Data System (ADS)

Ornea, Liviu; Verbitsky, Misha

2016-09-01

An LCK manifold with potential is a quotient of a Kähler manifold X equipped with a positive Kähler potential f, such that the monodromy group acts on X by holomorphic homotheties and multiplies f by a character. The LCK rank is the rank of the image of this character, considered as a function from the monodromy group to real numbers. We prove that an LCK manifold with potential can have any rank between 1 and b1(M) . Moreover, LCK manifolds with proper potential (ones with rank 1) are dense. Two errata to our previous work are given in the last section.

Conical diffuser for fuel cells

NASA Technical Reports Server (NTRS)

Craft, D. W.

1976-01-01

Diffuser is inserted into inlet manifold, producing smooth transition of flow from pipe diameter to manifold diameter. Expected pressure gradient and resulting cell-to-cell temperature gradient are reduced. Outlet manifold has nozzle insert that reduces exit losses.

Localization of a mobile laser scanner via dimensional reduction

NASA Astrophysics Data System (ADS)

Lehtola, Ville V.; Virtanen, Juho-Pekka; Vaaja, Matti T.; Hyyppä, Hannu; Nüchter, Andreas

2016-11-01

We extend the concept of intrinsic localization from a theoretical one-dimensional (1D) solution onto a 2D manifold that is embedded in a 3D space, and then recover the full six degrees of freedom for a mobile laser scanner with a simultaneous localization and mapping algorithm (SLAM). By intrinsic localization, we mean that no reference coordinate system, such as global navigation satellite system (GNSS), nor inertial measurement unit (IMU) are used. Experiments are conducted with a 2D laser scanner mounted on a rolling prototype platform, VILMA. The concept offers potential in being extendable to other wheeled platforms.

Equivariant Gromov-Witten Invariants of Algebraic GKM Manifolds

NASA Astrophysics Data System (ADS)

Liu, Chiu-Chu Melissa; Sheshmani, Artan

2017-07-01

An algebraic GKM manifold is a non-singular algebraic variety equipped with an algebraic action of an algebraic torus, with only finitely many torus fixed points and finitely many 1-dimensional orbits. In this expository article, we use virtual localization to express equivariant Gromov-Witten invariants of any algebraic GKM manifold (which is not necessarily compact) in terms of Hodge integrals over moduli stacks of stable curves and the GKM graph of the GKM manifold.

Modular jet impingement assemblies with passive and active flow control for electronics cooling

DOEpatents

Zhou, Feng; Dede, Ercan Mehmet; Joshi, Shailesh

2016-09-13

Power electronics modules having modular jet impingement assembly utilized to cool heat generating devices are disclosed. The modular jet impingement assemblies include a modular manifold having a distribution recess, one or more angled inlet connection tubes positioned at an inlet end of the modular manifold that fluidly couple the inlet tube to the distribution recess and one or more outlet connection tubes positioned at an outlet end of the modular manifold that fluidly coupling the outlet tube to the distribution recess. The modular jet impingement assemblies include a manifold insert removably positioned within the distribution recess and include one or more inlet branch channels each including an impinging slot and one or more outlet branch channels each including a collecting slot. Further a heat transfer plate coupled to the modular manifold, the heat transfer plate comprising an impingement surface including an array of fins that extend toward the manifold insert.

Compact, singular G 2-holonomy manifolds and M/heterotic/F-theory duality

NASA Astrophysics Data System (ADS)

Braun, Andreas P.; Schäfer-Nameki, Sakura

2018-04-01

We study the duality between M-theory on compact holonomy G 2-manifolds and the heterotic string on Calabi-Yau three-folds. The duality is studied for K3-fibered G 2-manifolds, called twisted connected sums, which lend themselves to an application of fiber-wise M-theory/Heterotic Duality. For a large class of such G 2-manifolds we are able to identify the dual heterotic as well as F-theory realizations. First we establish this chain of dualities for smooth G 2-manifolds. This has a natural generalization to situations with non-abelian gauge groups, which correspond to singular G 2-manifolds, where each of the K3-fibers degenerates. We argue for their existence through the chain of dualities, supported by non-trivial checks of the spectra. The corresponding 4d gauge groups can be both Higgsable and non-Higgsable, and we provide several explicit examples of the general construction.

Halo orbit transfer trajectory design using invariant manifold in the Sun-Earth system accounting radiation pressure and oblateness

NASA Astrophysics Data System (ADS)

Srivastava, Vineet K.; Kumar, Jai; Kushvah, Badam Singh

2018-01-01

In this paper, we study the invariant manifold and its application in transfer trajectory problem from a low Earth parking orbit to the Sun-Earth L1 and L2-halo orbits with the inclusion of radiation pressure and oblateness. Invariant manifold of the halo orbit provides a natural entrance to travel the spacecraft in the solar system along some specific paths due to its strong hyperbolic character. In this regard, the halo orbits near both collinear Lagrangian points are computed first. The manifold's approximation near the nominal halo orbit is computed using the eigenvectors of the monodromy matrix. The obtained local approximation provides globalization of the manifold by applying backward time propagation to the governing equations of motion. The desired transfer trajectory well suited for the transfer is explored by looking at a possible intersection between the Earth's parking orbit of the spacecraft and the manifold.

Extrinsic local regression on manifold-valued data

PubMed Central

Lin, Lizhen; St Thomas, Brian; Zhu, Hongtu; Dunson, David B.

2017-01-01

We propose an extrinsic regression framework for modeling data with manifold valued responses and Euclidean predictors. Regression with manifold responses has wide applications in shape analysis, neuroscience, medical imaging and many other areas. Our approach embeds the manifold where the responses lie onto a higher dimensional Euclidean space, obtains a local regression estimate in that space, and then projects this estimate back onto the image of the manifold. Outside the regression setting both intrinsic and extrinsic approaches have been proposed for modeling i.i.d manifold-valued data. However, to our knowledge our work is the first to take an extrinsic approach to the regression problem. The proposed extrinsic regression framework is general, computationally efficient and theoretically appealing. Asymptotic distributions and convergence rates of the extrinsic regression estimates are derived and a large class of examples are considered indicating the wide applicability of our approach. PMID:29225385

Edge compression manifold apparatus

DOEpatents

Renzi, Ronald F.

2004-12-21

A manifold for connecting external capillaries to the inlet and/or outlet ports of a microfluidic device for high pressure applications is provided. The fluid connector for coupling at least one fluid conduit to a corresponding port of a substrate that includes: (i) a manifold comprising one or more channels extending therethrough wherein each channel is at least partially threaded, (ii) one or more threaded ferrules each defining a bore extending therethrough with each ferrule supporting a fluid conduit wherein each ferrule is threaded into a channel of the manifold, (iii) a substrate having one or more ports on its upper surface wherein the substrate is positioned below the manifold so that the one or more ports is aligned with the one or more channels of the manifold, and (iv) device to apply an axial compressive force to the substrate to couple the one or more ports of the substrate to a corresponding proximal end of a fluid conduit.

Edge compression manifold apparatus

DOEpatents

Renzi, Ronald F [Tracy, CA

2007-02-27

A manifold for connecting external capillaries to the inlet and/or outlet ports of a microfluidic device for high pressure applications is provided. The fluid connector for coupling at least one fluid conduit to a corresponding port of a substrate that includes: (i) a manifold comprising one or more channels extending therethrough wherein each channel is at least partially threaded, (ii) one or more threaded ferrules each defining a bore extending therethrough with each ferrule supporting a fluid conduit wherein each ferrule is threaded into a channel of the manifold, (iii) a substrate having one or more ports on its upper surface wherein the substrate is positioned below the manifold so that the one or more ports is aligned with the one or more channels of the manifold, and (iv) device to apply an axial compressive force to the substrate to couple the one or more ports of the substrate to a corresponding proximal end of a fluid conduit.

A Class of Manifold Regularized Multiplicative Update Algorithms for Image Clustering.

PubMed

Yang, Shangming; Yi, Zhang; He, Xiaofei; Li, Xuelong

2015-12-01

Multiplicative update algorithms are important tools for information retrieval, image processing, and pattern recognition. However, when the graph regularization is added to the cost function, different classes of sample data may be mapped to the same subspace, which leads to the increase of data clustering error rate. In this paper, an improved nonnegative matrix factorization (NMF) cost function is introduced. Based on the cost function, a class of novel graph regularized NMF algorithms is developed, which results in a class of extended multiplicative update algorithms with manifold structure regularization. Analysis shows that in the learning, the proposed algorithms can efficiently minimize the rank of the data representation matrix. Theoretical results presented in this paper are confirmed by simulations. For different initializations and data sets, variation curves of cost functions and decomposition data are presented to show the convergence features of the proposed update rules. Basis images, reconstructed images, and clustering results are utilized to present the efficiency of the new algorithms. Last, the clustering accuracies of different algorithms are also investigated, which shows that the proposed algorithms can achieve state-of-the-art performance in applications of image clustering.

Topology of quantum discord

NASA Astrophysics Data System (ADS)

Nguyen, Nga T. T.; Joynt, Robert

2017-04-01

Quantum discord is an important measure of quantum correlations that can serve as a resource for certain types of quantum information processing. Like entanglement, discord is subject to destruction by external noise. The routes by which this destruction can take place depends on the shape of the hypersurface of zero discord C in the space of generalized Bloch vectors. For 2 qubits, we show that with a few points subtracted, this hypersurface is a simply-connected 9-dimensional manifold embedded in a 15-dimensional background space. We do this by constructing an explicit homeomorphism from a known manifold to the subtracted version of C . We also construct a coordinate map on C that can be used for integration or other purposes. This topological characterization of C has important implications for the classification of the possible time evolutions of discord in physical models. The classification for discord contrasts sharply with the possible evolutions of entanglement. We classify the possible joint evolutions of entanglement and discord. There are 9 allowed categories: 6 categories for a Markovian process and 3 categories for a non-Markovian process, respectively. We illustrate these conclusions with an anisotropic XY spin model. All 9 categories can be obtained by adjusting parameters in this model.

Modeling and enhanced sampling of molecular systems with smooth and nonlinear data-driven collective variables

NASA Astrophysics Data System (ADS)

Hashemian, Behrooz; Millán, Daniel; Arroyo, Marino

2013-12-01

Collective variables (CVs) are low-dimensional representations of the state of a complex system, which help us rationalize molecular conformations and sample free energy landscapes with molecular dynamics simulations. Given their importance, there is need for systematic methods that effectively identify CVs for complex systems. In recent years, nonlinear manifold learning has shown its ability to automatically characterize molecular collective behavior. Unfortunately, these methods fail to provide a differentiable function mapping high-dimensional configurations to their low-dimensional representation, as required in enhanced sampling methods. We introduce a methodology that, starting from an ensemble representative of molecular flexibility, builds smooth and nonlinear data-driven collective variables (SandCV) from the output of nonlinear manifold learning algorithms. We demonstrate the method with a standard benchmark molecule, alanine dipeptide, and show how it can be non-intrusively combined with off-the-shelf enhanced sampling methods, here the adaptive biasing force method. We illustrate how enhanced sampling simulations with SandCV can explore regions that were poorly sampled in the original molecular ensemble. We further explore the transferability of SandCV from a simpler system, alanine dipeptide in vacuum, to a more complex system, alanine dipeptide in explicit water.

Rotary engine performance limits predicted by a zero-dimensional model

NASA Technical Reports Server (NTRS)

Bartrand, Timothy A.; Willis, Edward A.

1992-01-01

A parametric study was performed to determine the performance limits of a rotary combustion engine. This study shows how well increasing the combustion rate, insulating, and turbocharging increase brake power and decrease fuel consumption. Several generalizations can be made from the findings. First, it was shown that the fastest combustion rate is not necessarily the best combustion rate. Second, several engine insulation schemes were employed for a turbocharged engine. Performance improved only for a highly insulated engine. Finally, the variability of turbocompounding and the influence of exhaust port shape were calculated. Rotary engines performance was predicted by an improved zero-dimensional computer model based on a model developed at the Massachusetts Institute of Technology in the 1980's. Independent variables in the study include turbocharging, manifold pressures, wall thermal properties, leakage area, and exhaust port geometry. Additions to the computer programs since its results were last published include turbocharging, manifold modeling, and improved friction power loss calculation. The baseline engine for this study is a single rotor 650 cc direct-injection stratified-charge engine with aluminum housings and a stainless steel rotor. Engine maps are provided for the baseline and turbocharged versions of the engine.

Modeling and enhanced sampling of molecular systems with smooth and nonlinear data-driven collective variables.

PubMed

Hashemian, Behrooz; Millán, Daniel; Arroyo, Marino

2013-12-07

Collective variables (CVs) are low-dimensional representations of the state of a complex system, which help us rationalize molecular conformations and sample free energy landscapes with molecular dynamics simulations. Given their importance, there is need for systematic methods that effectively identify CVs for complex systems. In recent years, nonlinear manifold learning has shown its ability to automatically characterize molecular collective behavior. Unfortunately, these methods fail to provide a differentiable function mapping high-dimensional configurations to their low-dimensional representation, as required in enhanced sampling methods. We introduce a methodology that, starting from an ensemble representative of molecular flexibility, builds smooth and nonlinear data-driven collective variables (SandCV) from the output of nonlinear manifold learning algorithms. We demonstrate the method with a standard benchmark molecule, alanine dipeptide, and show how it can be non-intrusively combined with off-the-shelf enhanced sampling methods, here the adaptive biasing force method. We illustrate how enhanced sampling simulations with SandCV can explore regions that were poorly sampled in the original molecular ensemble. We further explore the transferability of SandCV from a simpler system, alanine dipeptide in vacuum, to a more complex system, alanine dipeptide in explicit water.

Fluid control structures in microfluidic devices

DOEpatents

Mathies, Richard A.; Grover, William H.; Skelley, Alison; Lagally, Eric; Liu, Chung N.

2008-11-04

Methods and apparatus for implementing microfluidic analysis devices are provided. A monolithic elastomer membrane associated with an integrated pneumatic manifold allows the placement and actuation of a variety of fluid control structures, such as structures for pumping, isolating, mixing, routing, merging, splitting, preparing, and storing volumes of fluid. The fluid control structures can be used to implement a variety of sample introduction, preparation, processing, and storage techniques.

Curvature of Super Diff(S/sup 1/)/S/sup 1/

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oh, P.; Ramond, P.

Motivated by the work of Bowick and Rajeev, we calculate the curvature of the infinite-dimensional flag manifolds DiffS/sup 1//S/sup 1/ and Super DiffS/sup 1//S/sup 1/ using standard finite-dimensional coset space techniques. We regularize the infinity by zeta-function regularization and recover the conformal and superconformal anomalies respectively for a specific choice of the torsion.

Fluid control structures in microfluidic devices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mathies, Richard A.; Grover, William H.; Skelley, Alison

2017-05-09

Methods and apparatus for implementing microfluidic analysis devices are provided. A monolithic elastomer membrane associated with an integrated pneumatic manifold allows the placement and actuation of a variety of fluid control structures, such as structures for pumping, isolating, mixing, routing, merging, splitting, preparing, and storing volumes of fluid. The fluid control structures can be used to implement a variety of sample introduction, preparation, processing, and storage techniques.

Fluid control structures in microfluidic devices

NASA Technical Reports Server (NTRS)

Skelley, Alison (Inventor); Mathies, Richard A. (Inventor); Lagally, Eric (Inventor); Grover, William H. (Inventor); Liu, Chung N. (Inventor)

2008-01-01

Methods and apparatus for implementing microfluidic analysis devices are provided. A monolithic elastomer membrane associated with an integrated pneumatic manifold allows the placement and actuation of a variety of fluid control structures, such as structures for pumping, isolating, mixing, routing, merging, splitting, preparing, and storing volumes of fluid. The fluid control structures can be used to implement a variety of sample introduction, preparation, processing, and storage techniques.

Self-duality of the compactified Ruijsenaars-Schneider system from quasi-Hamiltonian reduction

NASA Astrophysics Data System (ADS)

Fehér, L.; Klimčík, C.

2012-07-01

The Delzant theorem of symplectic topology is used to derive the completely integrable compactified Ruijsenaars-Schneider IIIb system from a quasi-Hamiltonian reduction of the internally fused double SU(n)×SU(n). In particular, the reduced spectral functions depending respectively on the first and second SU(n) factor of the double engender two toric moment maps on the IIIb phase space CP(n-1) that play the roles of action-variables and particle-positions. A suitable central extension of the SL(2,Z) mapping class group of the torus with one boundary component is shown to act on the quasi-Hamiltonian double by automorphisms and, upon reduction, the standard generator S of the mapping class group is proved to descend to the Ruijsenaars self-duality symplectomorphism that exchanges the toric moment maps. We give also two new presentations of this duality map: one as the composition of two Delzant symplectomorphisms and the other as the composition of three Dehn twist symplectomorphisms realized by Goldman twist flows. Through the well-known relation between quasi-Hamiltonian manifolds and moduli spaces, our results rigorously establish the validity of the interpretation [going back to Gorsky and Nekrasov] of the IIIb system in terms of flat SU(n) connections on the one-holed torus.

Combustor with two stage primary fuel assembly

DOEpatents

Sharifi, Mehran; Zolyomi, Wendel; Whidden, Graydon Lane

2000-01-01

A combustor for a gas turbine having first and second passages for pre-mixing primary fuel and air supplied to a primary combustion zone. The flow of fuel to the first and second pre-mixing passages is separately regulated using a single annular fuel distribution ring having first and second row of fuel discharge ports. The interior portion of the fuel distribution ring is divided by a baffle into first and second fuel distribution manifolds and is located upstream of the inlets to the two pre-mixing passages. The annular fuel distribution ring is supplied with fuel by an annular fuel supply manifold, the interior portion of which is divided by a baffle into first and second fuel supply manifolds. A first flow of fuel is regulated by a first control valve and directed to the first fuel supply manifold, from which the fuel is distributed to first fuel supply tubes that direct it to the first fuel distribution manifold. From the first fuel distribution manifold, the first flow of fuel is distributed to the first row of fuel discharge ports, which direct it into the first pre-mixing passage. A second flow of fuel is regulated by a second control valve and directed to the second fuel supply manifold, from which the fuel is distributed to second fuel supply tubes that direct it to the second fuel distribution manifold. From the second fuel distribution manifold, the second flow of fuel is distributed to the second row of fuel discharge ports, which direct it into the second pre-mixing passage.

An investigation of electronic states of some molecules and molecular cations using mass analyzed threshold ionization and photoinduced Rydberg ionization spectroscopy

NASA Astrophysics Data System (ADS)

Hofstein, Jason David

1999-11-01

Mass analyzed threshold ionization (MATI) experiments have enabled mapping of the n-dependent Rydberg state survival probability for a series of molecules. Utilizing vacuum and extreme ultraviolet (VUV/XUV) photons, one photon Rydberg manifold spectra of argon, hydrogen chloride, nitrogen, benzene, and oxygen were produced, and the prospects of photoinduced Rydberg ionization (PIRI) experiments examined. It was found that the widths of Rydberg manifolds for the molecules studied are quite different. Hydrogen chloride and nitrogen have the narrowest manifold width, followed by benzene, and then oxygen. These varying widths are most strongly correlated with the angular momentum (i.e., quantum defect) of the initially prepared Rydberg orbital. PIRI experiments required the use of a static cell, rather than a molecular jet assembly, for the more efficient production of higher amounts of VUV/XUV radiation, and hence more Rydberg signal needed to observe PIRI. Armed with the ability to produce tunable VUV/XUV radiation, and to determine the feasibility of a PIRI experiment, the MATI and fragment PIRI spectra of trans-1,3-butadiene (BD) were recorded. The MATI spectrum is vibrationally resolved and was analyzed with the help of ab initio calculations and other published results. The fragment PIRI spectrum of the A<==X transition of BD+ is not vibrationally resolved, but information regarding the wavelength dependence of fragmentation pathways has been gathered and interpreted. It was found that at low photodissociation photon energies, production of C3H3+ dominates, but at higher photon energies, C2H4 + is also produced. The production of each fragment showed a definite PIRI wavelength dependence.

Multi-temporal and multi-source remote sensing image classification by nonlinear relative normalization

NASA Astrophysics Data System (ADS)

Tuia, Devis; Marcos, Diego; Camps-Valls, Gustau

2016-10-01

Remote sensing image classification exploiting multiple sensors is a very challenging problem: data from different modalities are affected by spectral distortions and mis-alignments of all kinds, and this hampers re-using models built for one image to be used successfully in other scenes. In order to adapt and transfer models across image acquisitions, one must be able to cope with datasets that are not co-registered, acquired under different illumination and atmospheric conditions, by different sensors, and with scarce ground references. Traditionally, methods based on histogram matching have been used. However, they fail when densities have very different shapes or when there is no corresponding band to be matched between the images. An alternative builds upon manifold alignment. Manifold alignment performs a multidimensional relative normalization of the data prior to product generation that can cope with data of different dimensionality (e.g. different number of bands) and possibly unpaired examples. Aligning data distributions is an appealing strategy, since it allows to provide data spaces that are more similar to each other, regardless of the subsequent use of the transformed data. In this paper, we study a methodology that aligns data from different domains in a nonlinear way through kernelization. We introduce the Kernel Manifold Alignment (KEMA) method, which provides a flexible and discriminative projection map, exploits only a few labeled samples (or semantic ties) in each domain, and reduces to solving a generalized eigenvalue problem. We successfully test KEMA in multi-temporal and multi-source very high resolution classification tasks, as well as on the task of making a model invariant to shadowing for hyperspectral imaging.

On the dualization of scalars into ( d - 2)-forms in supergravity. Momentum maps, R-symmetry and gauged supergravity

NASA Astrophysics Data System (ADS)

Bandos, Igor A.; Ortín, Tomás

2016-08-01

We review and investigate different aspects of scalar fields in supergravity theories both when they parametrize symmetric spaces and when they parametrize spaces of special holonomy which are not necessarily symmetric (Kähler and Quaternionic-Kähler spaces): their rôle in the definition of derivatives of the fermions covariant under the R-symmetry group and (in gauged supergravities) under some gauge group, their dualization into ( d - 2)-forms, their role in the supersymmetry transformation rules (via fermion shifts, for instance) etc. We find a general definition of momentum map that applies to any manifold admitting a Killing vector and coincides with those of the holomorphic and tri-holomorphic momentum maps in Kähler and quaternionic-Kähler spaces and with an independent definition that can be given in symmetric spaces. We show how the momen-tum map occurs ubiquitously: in gauge-covariant derivatives of fermions, in fermion shifts, in the supersymmetry transformation rules of ( d - 2)-forms etc. We also give the general structure of the Noether-Gaillard-Zumino conserved currents in theories with fields of different ranks in any dimension.

Engine Cylinder Temperature Control

DOEpatents

Kilkenny, Jonathan Patrick; Duffy, Kevin Patrick

2005-09-27

A method and apparatus for controlling a temperature in a combustion cylinder in an internal combustion engine. The cylinder is fluidly connected to an intake manifold and an exhaust manifold. The method and apparatus includes increasing a back pressure associated with the exhaust manifold to a level sufficient to maintain a desired quantity of residual exhaust gas in the cylinder, and varying operation of an intake valve located between the intake manifold and the cylinder to an open duration sufficient to maintain a desired quantity of fresh air from the intake manifold to the cylinder, wherein controlling the quantities of residual exhaust gas and fresh air are performed to maintain the temperature in the cylinder at a desired level.

Conjugate Heat Transfer Analyses on the Manifold for Ramjet Fuel Injectors

NASA Technical Reports Server (NTRS)

Wang, Xiao-Yen J.

2006-01-01

Three-dimensional conjugate heat transfer analyses on the manifold located upstream of the ramjet fuel injector are performed using CFdesign, a finite-element computational fluid dynamics (CFD) software. The flow field of the hot fuel (JP-7) flowing through the manifold is simulated and the wall temperature of the manifold is computed. The three-dimensional numerical results of the fuel temperature are compared with those obtained using a one-dimensional analysis based on empirical equations, and they showed a good agreement. The numerical results revealed that it takes around 30 to 40 sec to reach the equilibrium where the fuel temperature has dropped about 3 F from the inlet to the exit of the manifold.

The role of invariant manifolds in lowthrust trajectory design (part III)

NASA Technical Reports Server (NTRS)

Lo, Martin W.; Anderson, Rodney L.; Lam, Try; Whiffen, Greg

2006-01-01

This paper is the third in a series to explore the role of invariant manifolds in the design of low thrust trajectories. In previous papers, we analyzed an impulsive thrust resonant gravity assist flyby trajectory to capture into Europa orbit using the invariant manifolds of unstable resonant periodic orbits and libration orbits. The energy savings provided by the gravity assist may be interpreted dynamically as the result of a finite number of intersecting invariant manifolds. In this paper we demonstrate that the same dynamics is at work for low thrust trajectories with resonant flybys and low energy capture. However, in this case, the flybys and capture are effected by continuous families of intersecting invariant manifolds.

Ceramic matrix composite article and process of fabricating a ceramic matrix composite article

DOEpatents

Cairo, Ronald Robert; DiMascio, Paul Stephen; Parolini, Jason Robert

2016-01-12

A ceramic matrix composite article and a process of fabricating a ceramic matrix composite are disclosed. The ceramic matrix composite article includes a matrix distribution pattern formed by a manifold and ceramic matrix composite plies laid up on the matrix distribution pattern, includes the manifold, or a combination thereof. The manifold includes one or more matrix distribution channels operably connected to a delivery interface, the delivery interface configured for providing matrix material to one or more of the ceramic matrix composite plies. The process includes providing the manifold, forming the matrix distribution pattern by transporting the matrix material through the manifold, and contacting the ceramic matrix composite plies with the matrix material.

Manifold and method of batch measurement of Hg-196 concentration using a mass spectrometer

DOEpatents

Grossman, Mark W.; Evans, Roger

1991-01-01

A sample manifold and method of its use has been developed so that milligram quantities of mercury can be analyzed mass spectroscopically to determine the .sup.196 Hg concentration to less than 0.02 atomic percent. Using natural mercury as a standard, accuracy of .+-.0.002 atomic percent can be obtained. The mass spectrometer preferably used is a commercially available GC/MS manufactured by Hewlett Packard. A novel sample manifold is contained within an oven allowing flow rate control of Hg into the MS. Another part of the manifold connects to an auxiliary pumping system which facilitates rapid clean up of residual Hg in the manifold. Sample cycle time is about 1 hour.

A modified technique for the preparation of SO2 from sulphates and sulphides for sulphur isotope analyses.

PubMed

Han, L; Tanweer, A; Szaran, J; Halas, S

2002-09-01

A modified technique for the conversion of sulphates and sulphides to SO2 with the mixture of V2O5-SiO2 for sulphur isotopic analyses is described. This technique is more suitable for routine analysis of large number of samples. Modification of the reaction vessel and using manifold inlet system allows to analyse up to 24 samples every day. The modified technique assures the complete yield of SO2, consistent oxygen isotope composition of the SO2 gas and reproducibility of delta34S measurements being within 0.10 per thousand. It is observed, however, oxygen in SO2 produced from sulphides differs in delta18O with respect to that produced from sulphates.

Atomizing nozzle and process

DOEpatents

Anderson, I.E.; Figliola, R.S.; Molnar, H.M.

1993-07-20

High pressure atomizing nozzle includes a high pressure gas manifold having a divergent expansion chamber between a gas inlet and arcuate manifold segment to minimize standing shock wave patterns in the manifold and thereby improve filling of the manifold with high pressure gas for improved melt atomization. The atomizing nozzle is especially useful in atomizing rare earth-transition metal alloys to form fine powder particles wherein a majority of the powder particles exhibit particle sizes having near-optimum magnetic properties.

Atomizing nozzle and process

DOEpatents

Anderson, Iver E.; Figliola, Richard S.; Molnar, Holly M.

1992-06-30

High pressure atomizing nozzle includes a high pressure gas manifold having a divergent expansion chamber between a gas inlet and arcuate manifold segment to minimize standing shock wave patterns in the manifold and thereby improve filling of the manifold with high pressure gas for improved melt atomization. The atomizing nozzle is especially useful in atomizing rare earth-transition metal alloys to form fine powder particles wherein a majority of the powder particles exhibit particle sizes having near-optimum magnetic properties.

Covariant balance laws in continua with microstructure

NASA Astrophysics Data System (ADS)

Yavari, Arash; Marsden, Jerrold E.

2009-02-01

The purpose of this paper is to extend the Green-Naghdi-Rivlin balance of energy method to continua with microstructure. The key idea is to replace the group of Galilean transformations with the group of diffeomorphisms of the ambient space. A key advantage is that one obtains in a natural way all the needed balance laws on both the macro and micro levels along with two Doyle-Erickson formulas. We model a structured continuum as a triplet of Riemannian manifolds: a material manifold, the ambient space manifold of material particles and a director field manifold. The Green-Naghdi-Rivlin theorem and its extensions for structured continua are critically reviewed. We show that when the ambient space is Euclidean and when the microstructure manifold is the tangent space of the ambient space manifold, postulating a single balance of energy law and its invariance under time-dependent isometries of the ambient space, one obtains conservation of mass, balances of linear and angular momenta but not a separate balance of linear momentum. We develop a covariant elasticity theory for structured continua by postulating that energy balance is invariant under time-dependent spatial diffeomorphisms of the ambient space, which in this case is the product of two Riemannian manifolds. We then introduce two types of constrained continua in which microstructure manifold is linked to the reference and ambient space manifolds. In the case when at every material point, the microstructure manifold is the tangent space of the ambient space manifold at the image of the material point, we show that the assumption of covariance leads to balances of linear and angular momenta with contributions from both forces and micro-forces along with two Doyle-Ericksen formulas. We show that generalized covariance leads to two balances of linear momentum and a single coupled balance of angular momentum. Using this theory, we covariantly obtain the balance laws for two specific examples, namely elastic solids with distributed voids and mixtures. Finally, the Lagrangian field theory of structured elasticity is revisited and a connection is made between covariance and Noether's theorem.

Preliminary integrated geologic map databases for the United States: Digital data for the geology of southeast Alaska

USGS Publications Warehouse

Gehrels, George E.; Berg, Henry C.

2006-01-01

The growth in the use of Geographic Information Systems (GIS) has highlighted the need for digital geologic maps that have been attributed with information about age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. This report is part of a series of integrated geologic map databases that cover the entire United States. Three national-scale geologic maps that portray most or all of the United States already exist; for the conterminous U.S., King and Beikman (1974a,b) compiled a map at a scale of 1:2,500,000, Beikman (1980) compiled a map for Alaska at 1:2,500,000 scale, and for the entire U.S., Reed and others (2005a,b) compiled a map at a scale of 1:5,000,000. A digital version of the King and Beikman map was published by Schruben and others (1994). Reed and Bush (2004) produced a digital version of the Reed and others (2005a) map for the conterminous U.S. The present series of maps is intended to provide the next step in increased detail. State geologic maps that range in scale from 1:100,000 to 1:1,000,000 are available for most of the country, and digital versions of these state maps are the basis of this product. The digital geologic maps presented here are in a standardized format as ARC/INFO export files and as ArcView shape files. Data tables that relate the map units to detailed lithologic and age information accompany these GIS files. The map is delivered as a set of 1:250,000-scale quadrangle files. To the best of our ability, these quadrangle files are edge-matched with respect to geology. When the maps are merged, the combined attribute tables can be used directly with the merged maps to make derivative maps.

Digital Data for the reconnaissance geologic map for the Kuskokwim Bay Region of Southwest Alaska

USGS Publications Warehouse

Wilson, Frederic H.; Hults, Chad P.; Mohadjer, Solmaz; Coonrad, Warren L.; Shew, Nora B.; Labay, Keith A.

2008-01-01

INTRODUCTION The growth in the use of Geographic Information Systems (GIS) has highlighted the need for digital geologic maps that have been attributed with information about age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. This report is part of a series of integrated geologic map databases that cover the entire United States. Three national-scale geologic maps that portray most or all of the United States already exist; for the conterminous U.S., King and Beikman (1974a,b) compiled a map at a scale of 1:2,500,000, Beikman (1980) compiled a map for Alaska at 1:2,500,000 scale, and for the entire U.S., Reed and others (2005a,b) compiled a map at a scale of 1:5,000,000. A digital version of the King and Beikman map was published by Schruben and others (1994). Reed and Bush (2004) produced a digital version of the Reed and others (2005a) map for the conterminous U.S. The present series of maps is intended to provide the next step in increased detail. State geologic maps that range in scale from 1:100,000 to 1:1,000,000 are available for most of the country, and digital versions of these state maps are the basis of this product. The digital geologic maps presented here are in a standardized format as ARC/INFO export files and as ArcView shape files. Data tables that relate the map units to detailed lithologic and age information accompany these GIS files. The map is delivered as a set 1:250,000-scale quadrangle files. To the best of our ability, these quadrangle files are edge-matched with respect to geology. When the maps are merged, the combined attribute tables can be used directly with the merged maps to make derivative maps.

Bifurcation Analysis Using Rigorous Branch and Bound Methods

NASA Technical Reports Server (NTRS)

Smith, Andrew P.; Crespo, Luis G.; Munoz, Cesar A.; Lowenberg, Mark H.

2014-01-01

For the study of nonlinear dynamic systems, it is important to locate the equilibria and bifurcations occurring within a specified computational domain. This paper proposes a new approach for solving these problems and compares it to the numerical continuation method. The new approach is based upon branch and bound and utilizes rigorous enclosure techniques to yield outer bounding sets of both the equilibrium and local bifurcation manifolds. These sets, which comprise the union of hyper-rectangles, can be made to be as tight as desired. Sufficient conditions for the existence of equilibrium and bifurcation points taking the form of algebraic inequality constraints in the state-parameter space are used to calculate their enclosures directly. The enclosures for the bifurcation sets can be computed independently of the equilibrium manifold, and are guaranteed to contain all solutions within the computational domain. A further advantage of this method is the ability to compute a near-maximally sized hyper-rectangle of high dimension centered at a fixed parameter-state point whose elements are guaranteed to exclude all bifurcation points. This hyper-rectangle, which requires a global description of the bifurcation manifold within the computational domain, cannot be obtained otherwise. A test case, based on the dynamics of a UAV subject to uncertain center of gravity location, is used to illustrate the efficacy of the method by comparing it with numerical continuation and to evaluate its computational complexity.

Center manifolds, normal forms and bifurcations of vector fields with application to coupling between periodic and steady motions

NASA Astrophysics Data System (ADS)

Holmes, Philip J.

1981-06-01

We study the instabilities known to aeronautical engineers as flutter and divergence. Mathematically, these states correspond to bifurcations to limit cycles and multiple equilibrium points in a differential equation. Making use of the center manifold and normal form theorems, we concentrate on the situation in which flutter and divergence become coupled, and show that there are essentially two ways in which this is likely to occur. In the first case the system can be reduced to an essential model which takes the form of a single degree of freedom nonlinear oscillator. This system, which may be analyzed by conventional phase-plane techniques, captures all the qualitative features of the full system. We discuss the reduction and show how the nonlinear terms may be simplified and put into normal form. Invariant manifold theory and the normal form theorem play a major role in this work and this paper serves as an introduction to their application in mechanics. Repeating the approach in the second case, we show that the essential model is now three dimensional and that far more complex behavior is possible, including nonperiodic and ‘chaotic’ motions. Throughout, we take a two degree of freedom system as an example, but the general methods are applicable to multi- and even infinite degree of freedom problems.

Diffeomorphic Sulcal Shape Analysis on the Cortex

PubMed Central

Joshi, Shantanu H.; Cabeen, Ryan P.; Joshi, Anand A.; Sun, Bo; Dinov, Ivo; Narr, Katherine L.; Toga, Arthur W.; Woods, Roger P.

2014-01-01

We present a diffeomorphic approach for constructing intrinsic shape atlases of sulci on the human cortex. Sulci are represented as square-root velocity functions of continuous open curves in ℝ3, and their shapes are studied as functional representations of an infinite-dimensional sphere. This spherical manifold has some advantageous properties – it is equipped with a Riemannian metric on the tangent space and facilitates computational analyses and correspondences between sulcal shapes. Sulcal shape mapping is achieved by computing geodesics in the quotient space of shapes modulo scales, translations, rigid rotations and reparameterizations. The resulting sulcal shape atlas preserves important local geometry inherently present in the sample population. The sulcal shape atlas is integrated in a cortical registration framework and exhibits better geometric matching compared to the conventional euclidean method. We demonstrate experimental results for sulcal shape mapping, cortical surface registration, and sulcal classification for two different surface extraction protocols for separate subject populations. PMID:22328177

Integrated high pressure manifold for thermoplastic microfluidic devices

NASA Astrophysics Data System (ADS)

Aghvami, S. Ali; Fraden, Seth

2017-11-01

We introduce an integrated tubing manifold for thermoplastic microfluidic chips that tolerates high pressure. In contrast to easy tubing in PDMS microfluidic devices, tube connection has been challenging for plastic microfluidics. Our integrated manifold connection tolerates 360 psi while conventional PDMS connections fail at 50 psi. Important design considerations are incorporation of a quick-connect, leak-free and high-pressure manifold for the inlets and outlets on the lid and registration marks that allow the precise alignment of the inlets and outlets. In our method, devices are comprised of two molded pieces joined together to create a sealed device. The first piece contains the microfluidic features and the second contains the inlet and outlet manifold, a frame for rigidity and a viewing window. The mold for the lid with integrated manifold is CNC milled from aluminium. A cone shape PDMS component which acts as an O-ring, seals the connection between molded manifold and tubing. The lid piece with integrated inlet and outlets will be a standard piece and can be used for different chips and designs. Sealing the thermoplastic device is accomplished by timed immersion of the lid in a mixture of volatile and non-volatile solvents followed by application of heat and pressure.

Manifold learning of brain MRIs by deep learning.

PubMed

Brosch, Tom; Tam, Roger

2013-01-01

Manifold learning of medical images plays a potentially important role for modeling anatomical variability within a population with pplications that include segmentation, registration, and prediction of clinical parameters. This paper describes a novel method for learning the manifold of 3D brain images that, unlike most existing manifold learning methods, does not require the manifold space to be locally linear, and does not require a predefined similarity measure or a prebuilt proximity graph. Our manifold learning method is based on deep learning, a machine learning approach that uses layered networks (called deep belief networks, or DBNs) and has received much attention recently in the computer vision field due to their success in object recognition tasks. DBNs have traditionally been too computationally expensive for application to 3D images due to the large number of trainable parameters. Our primary contributions are (1) a much more computationally efficient training method for DBNs that makes training on 3D medical images with a resolution of up to 128 x 128 x 128 practical, and (2) the demonstration that DBNs can learn a low-dimensional manifold of brain volumes that detects modes of variations that correlate to demographic and disease parameters.

Semiautomated solid-phase extraction manifold with a solvent-level sensor.

PubMed

Orlando, R M; Rath, S; Rohwedder, J J R

2013-11-15

A semiautomated solid-phase extraction manifold for multiple extractions is presented. The manifold utilizes commercial solid-phase syringe cartridges and automatically introduces and elutes all the solvents during the extraction, reducing the typical workload and stress of the analyst. The manifold consists of a peristaltic pump with solenoid valves in a flow circuit that contains transmissive photomicrosensors. The photomicrosensors were used to control the solvent dispenser and the solvent level inside the cartridge. As solvent-level sensors, the photomicrosensors determined the exact time the solvent reached the top frit to avoid sorbent drying and accurately perform the solvent exchange. The repeatability of the manifold to introduce a particular volume of solvent into the cartridges was measured, and the precisions were between 0.05 and 2.89% (RSD). To evaluate the manifold, the amount of two fluoroquinolones in a fortified blank milk sample was determined. The results of the intra- and inter-day precision of multiple extractions from the fortified milk samples resulted in precisions better than 9.0% (RSD) and confirmed that the arrangement of the semiautomated manifold could adequately be used in solid-phase extraction with commercial cartridges. Copyright © 2013 Elsevier B.V. All rights reserved.

Semisupervised Support Vector Machines With Tangent Space Intrinsic Manifold Regularization.

PubMed

Sun, Shiliang; Xie, Xijiong

2016-09-01

Semisupervised learning has been an active research topic in machine learning and data mining. One main reason is that labeling examples is expensive and time-consuming, while there are large numbers of unlabeled examples available in many practical problems. So far, Laplacian regularization has been widely used in semisupervised learning. In this paper, we propose a new regularization method called tangent space intrinsic manifold regularization. It is intrinsic to data manifold and favors linear functions on the manifold. Fundamental elements involved in the formulation of the regularization are local tangent space representations, which are estimated by local principal component analysis, and the connections that relate adjacent tangent spaces. Simultaneously, we explore its application to semisupervised classification and propose two new learning algorithms called tangent space intrinsic manifold regularized support vector machines (TiSVMs) and tangent space intrinsic manifold regularized twin SVMs (TiTSVMs). They effectively integrate the tangent space intrinsic manifold regularization consideration. The optimization of TiSVMs can be solved by a standard quadratic programming, while the optimization of TiTSVMs can be solved by a pair of standard quadratic programmings. The experimental results of semisupervised classification problems show the effectiveness of the proposed semisupervised learning algorithms.

Hidden symmetries on toric Sasaki-Einstein spaces

NASA Astrophysics Data System (ADS)

Slesar, V.; Visinescu, M.; Vîlcu, G. E.

2015-05-01

We describe the construction of Killing-Yano tensors on toric Sasaki-Einstein manifolds. We use the fact that the metric cones of these spaces are Calabi-Yau manifolds. The description of the Calabi-Yau manifolds in terms of toric data, using the Delzant approach to toric geometries, allows us to find explicitly the complex coordinates and write down the Killing-Yano tensors. As a concrete example we present the complete set of special Killing forms on the five-dimensional homogeneous Sasaki-Einstein manifold T 1,1.

Desynchronization of chaos in coupled logistic maps.

PubMed

Maistrenko, Y L; Maistrenko, V L; Popovych, O; Mosekilde, E

1999-09-01

When identical chaotic oscillators interact, a state of complete or partial synchronization may be attained in which the motion is restricted to an invariant manifold of lower dimension than the full phase space. Riddling of the basin of attraction arises when particular orbits embedded in the synchronized chaotic state become transversely unstable while the state remains attracting on the average. Considering a system of two coupled logistic maps, we show that the transition to riddling will be soft or hard, depending on whether the first orbit to lose its transverse stability undergoes a supercritical or subcritical bifurcation. A subcritical bifurcation can lead directly to global riddling of the basin of attraction for the synchronized chaotic state. A supercritical bifurcation, on the other hand, is associated with the formation of a so-called mixed absorbing area that stretches along the synchronized chaotic state, and from which trajectories cannot escape. This gives rise to locally riddled basins of attraction. We present three different scenarios for the onset of riddling and for the subsequent transformations of the basins of attraction. Each scenario is described by following the type and location of the relevant asynchronous cycles, and determining their stable and unstable invariant manifolds. One scenario involves a contact bifurcation between the boundary of the basin of attraction and the absorbing area. Another scenario involves a long and interesting series of bifurcations starting with the stabilization of the asynchronous cycle produced in the riddling bifurcation and ending in a boundary crisis where the stability of an asynchronous chaotic state is destroyed. Finally, a phase diagram is presented to illustrate the parameter values at which the various transitions occur.

Super-resolution imaging using multi- electrode CMUTs: theoretical design and simulation using point targets.

PubMed

You, Wei; Cretu, Edmond; Rohling, Robert

2013-11-01

This paper investigates a low computational cost, super-resolution ultrasound imaging method that leverages the asymmetric vibration mode of CMUTs. Instead of focusing on the broadband received signal on the entire CMUT membrane, we utilize the differential signal received on the left and right part of the membrane obtained by a multi-electrode CMUT structure. The differential signal reflects the asymmetric vibration mode of the CMUT cell excited by the nonuniform acoustic pressure field impinging on the membrane, and has a resonant component in immersion. To improve the resolution, we propose an imaging method as follows: a set of manifold matrices of CMUT responses for multiple focal directions are constructed off-line with a grid of hypothetical point targets. During the subsequent imaging process, the array sequentially steers to multiple angles, and the amplitudes (weights) of all hypothetical targets at each angle are estimated in a maximum a posteriori (MAP) process with the manifold matrix corresponding to that angle. Then, the weight vector undergoes a directional pruning process to remove the false estimation at other angles caused by the side lobe energy. Ultrasound imaging simulation is performed on ring and linear arrays with a simulation program adapted with a multi-electrode CMUT structure capable of obtaining both average and differential received signals. Because the differential signals from all receiving channels form a more distinctive temporal pattern than the average signals, better MAP estimation results are expected than using the average signals. The imaging simulation shows that using differential signals alone or in combination with the average signals produces better lateral resolution than the traditional phased array or using the average signals alone. This study is an exploration into the potential benefits of asymmetric CMUT responses for super-resolution imaging.

Trisections in Three and Four Dimensions

NASA Astrophysics Data System (ADS)

Koenig, Dale R.

Every closed orientable three dimensional manifold has a Heegaard splitting, a decomposition into two handlebodies. Any two Heegaard splittings of the same manifold can be made isotopic after a finite number of stabilization operations. The notion of trisections, developed by Gay and Kirby, provided an analogue in four dimensions. They showed that any closed smooth orientable four dimensional manifold can be broken into three four dimensional handlebodies, with "niceness" conditions on their intersections, and showed that any two trisections are isotopic after stabilizations. In this thesis we investigate the notion of trisections in both three and four dimensions. In dimension three we define trisections of 3-manifolds and stabilization on these trisections. We use this to define the trisection genus of a 3-manifold. We then present several examples, showing among other things that the trisection genus is not additive under connect sum. We prove a stable equivalence theorem for trisections of 3-manifolds, showing that any two trisections of the same three-manifold can be made isotopic after stabilizations. We also show that trisections of S3 can be very complicated, so there is no analogue of Waldhausen's theorem for trisections of three manifolds. We then move on to trisections in four dimensions. We first show that if there exist four manifolds with unbalanced trisection genus lower than their balanced trisection genus, then trisection genus as defined by Gay and Kirby is not additive under connect sum. We produce several new classes of trisections, including several likely such examples. We include a class of examples that are provably minimal genus. We provide trisection diagrams for many of these trisections, and summarize some methods for quickly checking that these diagrams produce valid trisections.

Constructive methods of invariant manifolds for kinetic problems

NASA Astrophysics Data System (ADS)

Gorban, Alexander N.; Karlin, Iliya V.; Zinovyev, Andrei Yu.

2004-06-01

The concept of the slow invariant manifold is recognized as the central idea underpinning a transition from micro to macro and model reduction in kinetic theories. We present the Constructive Methods of Invariant Manifolds for model reduction in physical and chemical kinetics, developed during last two decades. The physical problem of reduced description is studied in the most general form as a problem of constructing the slow invariant manifold. The invariance conditions are formulated as the differential equation for a manifold immersed in the phase space ( the invariance equation). The equation of motion for immersed manifolds is obtained ( the film extension of the dynamics). Invariant manifolds are fixed points for this equation, and slow invariant manifolds are Lyapunov stable fixed points, thus slowness is presented as stability. A collection of methods to derive analytically and to compute numerically the slow invariant manifolds is presented. Among them, iteration methods based on incomplete linearization, relaxation method and the method of invariant grids are developed. The systematic use of thermodynamics structures and of the quasi-chemical representation allow to construct approximations which are in concordance with physical restrictions. The following examples of applications are presented: nonperturbative deviation of physically consistent hydrodynamics from the Boltzmann equation and from the reversible dynamics, for Knudsen numbers Kn∼1; construction of the moment equations for nonequilibrium media and their dynamical correction (instead of extension of list of variables) to gain more accuracy in description of highly nonequilibrium flows; determination of molecules dimension (as diameters of equivalent hard spheres) from experimental viscosity data; model reduction in chemical kinetics; derivation and numerical implementation of constitutive equations for polymeric fluids; the limits of macroscopic description for polymer molecules, etc.

Pattern formation and geometry of the manifold

NASA Astrophysics Data System (ADS)

Haji, Amir Hossein; Mahzoon, Mojtaba; Javadpour, Sirus

2011-03-01

The objective of the present work is to investigate how pattern formation in the Cahn-Hilliard system can be influenced by geometry of the manifold. This is in contrast to control methods in which the physical field is modified and the pattern formation of the original system changes in response to control inputs. The idea begins with the cylindrical manifold symmetry leading to circumferential rolls while the torus manifold can be used to produce and control helical rolls. The next step is to search for a weaker restriction on the geometry of the manifold in order to reduce its dimension. In particular a short amplitude sinusoidal modulation on a flat surface is studied. At the final step a sequential pattern formation is presented.

Manifold and method of batch measurement of Hg-196 concentration using a mass spectrometer

DOEpatents

Grossman, M.W.; Evans, R.

1991-11-26

A sample manifold and method of its use has been developed so that milligram quantities of mercury can be analyzed mass spectroscopically to determine the [sup 196]Hg concentration to less than 0.02 atomic percent. Using natural mercury as a standard, accuracy of [+-]0.002 atomic percent can be obtained. The mass spectrometer preferably used is a commercially available GC/MS manufactured by Hewlett Packard. A novel sample manifold is contained within an oven allowing flow rate control of Hg into the MS. Another part of the manifold connects to an auxiliary pumping system which facilitates rapid clean up of residual Hg in the manifold. Sample cycle time is about 1 hour. 8 figures.

Impulsive perturbations to differential equations: stable/unstable pseudo-manifolds, heteroclinic connections, and flux

NASA Astrophysics Data System (ADS)

Balasuriya, Sanjeeva

2016-12-01

State-dependent time-impulsive perturbations to a two-dimensional autonomous flow with stable and unstable manifolds are analysed by posing in terms of an integral equation which is valid in both forwards- and backwards-time. The impulses destroy the smooth invariant manifolds, necessitating new definitions for stable and unstable pseudo-manifolds. Their time-evolution is characterised by solving a Volterra integral equation of the second kind with discontinuous inhomogeniety. A criteria for heteroclinic trajectory persistence in this impulsive context is developed, as is a quantification of an instantaneous flux across broken heteroclinic manifolds. Several examples, including a kicked Duffing oscillator and an underwater explosion in the vicinity of an eddy, are used to illustrate the theory.

77 FR 49386 - Airworthiness Directives; Airbus Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-16

... prompted by reports of silicon particles inside the oxygen generator manifolds, which had chafed from the... the part number and serial number of each passenger oxygen container, replacing the oxygen generator manifold of the affected oxygen container with a serviceable manifold, and performing an operational check...

Stability of Kinesthetic Perception in Efferent-Afferent Spaces: The Concept of Iso-perceptual Manifold.

PubMed

Latash, Mark L

2018-02-21

The main goal of this paper is to introduce the concept of iso-perceptual manifold for perception of body configuration and related variables (kinesthetic perception) and to discuss its relation to the equilibrium-point hypothesis and the concepts of reference coordinate and uncontrolled manifold. Hierarchical control of action is postulated with abundant transformations between sets of spatial reference coordinates for salient effectors at different levels. Iso-perceptual manifold is defined in the combined space of afferent and efferent variables as the subspace corresponding to a stable percept. Examples of motion along an iso-perceptual manifold (perceptually equivalent motion) are considered during various natural actions. Some combinations of afferent and efferent signals, in particular those implying a violation of body's integrity, give rise to variable percepts by artificial projection onto iso-perceptual manifolds. This framework is used to interpret unusual features of vibration-induced kinesthetic illusions and to predict new illusions not yet reported in the literature. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Minimal models of compact symplectic semitoric manifolds

NASA Astrophysics Data System (ADS)

Kane, D. M.; Palmer, J.; Pelayo, Á.

2018-02-01

A symplectic semitoric manifold is a symplectic 4-manifold endowed with a Hamiltonian (S1 × R) -action satisfying certain conditions. The goal of this paper is to construct a new symplectic invariant of symplectic semitoric manifolds, the helix, and give applications. The helix is a symplectic analogue of the fan of a nonsingular complete toric variety in algebraic geometry, that takes into account the effects of the monodromy near focus-focus singularities. We give two applications of the helix: first, we use it to give a classification of the minimal models of symplectic semitoric manifolds, where "minimal" is in the sense of not admitting any blowdowns. The second application is an extension to the compact case of a well known result of Vũ Ngọc about the constraints posed on a symplectic semitoric manifold by the existence of focus-focus singularities. The helix permits to translate a symplectic geometric problem into an algebraic problem, and the paper describes a method to solve this type of algebraic problem.

Using Global Invariant Manifolds to Understand Metastability in the Burgers Equation With Small Viscosity

NASA Astrophysics Data System (ADS)

Beck, Margaret; Wayne, C. Eugene

2009-01-01

The large-time behavior of solutions to the Burgers equation with small viscosity is described using invariant manifolds. In particular, a geometric explanation is provided for a phenomenon known as metastability, which in the present context means that solutions spend a very long time near the family of solutions known as diffusive N-waves before finally converging to a stable self-similar diffusion wave. More precisely, it is shown that in terms of similarity, or scaling, variables in an algebraically weighted L^2 space, the self-similar diffusion waves correspond to a one-dimensional global center manifold of stationary solutions. Through each of these fixed points there exists a one-dimensional, global, attractive, invariant manifold corresponding to the diffusive N-waves. Thus, metastability corresponds to a fast transient in which solutions approach this metastable manifold of diffusive N-waves, followed by a slow decay along this manifold, and, finally, convergence to the self-similar diffusion wave.

Coupled multiview autoencoders with locality sensitivity for three-dimensional human pose estimation

NASA Astrophysics Data System (ADS)

Yu, Jialin; Sun, Jifeng; Luo, Shasha; Duan, Bichao

2017-09-01

Estimating three-dimensional (3D) human poses from a single camera is usually implemented by searching pose candidates with image descriptors. Existing methods usually suppose that the mapping from feature space to pose space is linear, but in fact, their mapping relationship is highly nonlinear, which heavily degrades the performance of 3D pose estimation. We propose a method to recover 3D pose from a silhouette image. It is based on the multiview feature embedding (MFE) and the locality-sensitive autoencoders (LSAEs). On the one hand, we first depict the manifold regularized sparse low-rank approximation for MFE and then the input image is characterized by a fused feature descriptor. On the other hand, both the fused feature and its corresponding 3D pose are separately encoded by LSAEs. A two-layer back-propagation neural network is trained by parameter fine-tuning and then used to map the encoded 2D features to encoded 3D poses. Our LSAE ensures a good preservation of the local topology of data points. Experimental results demonstrate the effectiveness of our proposed method.

Manifold Coal-Slurry Transport System

NASA Technical Reports Server (NTRS)

Liddle, S. G.; Estus, J. M.; Lavin, M. L.

1986-01-01

Feeding several slurry pipes into main pipeline reduces congestion in coal mines. System based on manifold concept: feeder pipelines from each working entry joined to main pipeline that carries coal slurry out of panel and onto surface. Manifold concept makes coal-slurry haulage much simpler than existing slurry systems.

40 CFR 86.884-8 - Dynamometer and engine equipment.

Code of Federal Regulations, 2014 CFR

2014-07-01

... appropriate type of smokemeter placed no more than 32 feet from the exhaust manifold(s), turbocharger outlet(s..., turbocharger outlet, or exhaust aftertreatment device, whichever is farthest downstream. (3) For engines with... 10 to 32 feet downstream from the exhaust manifold, turbocharger outlet, or exhaust aftertreatment...

46 CFR 153.285 - Valving for cargo pump manifolds.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 5 2010-10-01 2010-10-01 false Valving for cargo pump manifolds. 153.285 Section 153... SHIPS CARRYING BULK LIQUID, LIQUEFIED GAS, OR COMPRESSED GAS HAZARDOUS MATERIALS Design and Equipment Piping Systems and Cargo Handling Equipment § 153.285 Valving for cargo pump manifolds. (a) When cargo...

30 CFR 250.444 - What are the choke manifold requirements?

Code of Federal Regulations, 2014 CFR

2014-07-01

... THE INTERIOR OFFSHORE OIL AND GAS AND SULPHUR OPERATIONS IN THE OUTER CONTINENTAL SHELF Oil and Gas Drilling Operations Blowout Preventer (bop) System Requirements § 250.444 What are the choke manifold..., and abrasiveness of drilling fluids and well fluids that you may encounter. (b) Choke manifold...

30 CFR 250.444 - What are the choke manifold requirements?

Code of Federal Regulations, 2013 CFR

2013-07-01

... THE INTERIOR OFFSHORE OIL AND GAS AND SULPHUR OPERATIONS IN THE OUTER CONTINENTAL SHELF Oil and Gas Drilling Operations Blowout Preventer (bop) System Requirements § 250.444 What are the choke manifold..., and abrasiveness of drilling fluids and well fluids that you may encounter. (b) Choke manifold...

30 CFR 250.444 - What are the choke manifold requirements?

Code of Federal Regulations, 2012 CFR

2012-07-01

... THE INTERIOR OFFSHORE OIL AND GAS AND SULPHUR OPERATIONS IN THE OUTER CONTINENTAL SHELF Oil and Gas Drilling Operations Blowout Preventer (bop) System Requirements § 250.444 What are the choke manifold..., and abrasiveness of drilling fluids and well fluids that you may encounter. (b) Choke manifold...

LIFE CYCLE DESIGN OF AIR INTAKE MANIFOLDS; PHASE I: 2.0 L FORD CONTOUR AIR INTAKE MANIFOLD

EPA Science Inventory

The project team applied the life cycle design methodology to the design analysis of three alternative air intake manifolds: a sand cast aluminum, brazed aluminum tubular, and nylon composite. The design analysis included a life cycle inventory analysis, environmental regulatory...

Manifold to uniformly distribute a solid-liquid slurry

DOEpatents

Kern, Kenneth C.

1983-01-01

This invention features a manifold that divides a stream of coal particles and liquid into several smaller streams maintaining equal or nearly equal mass compositions. The manifold consists of a horizontal, variable area header having sharp-edged, right-angled take-offs which are oriented on the bottom of the header.

Long Time Quantum Evolution of Observables on Cusp Manifolds

NASA Astrophysics Data System (ADS)

Bonthonneau, Yannick

2016-04-01

The Eisenstein functions {E(s)} are some generalized eigenfunctions of the Laplacian on manifolds with cusps. We give a version of Quantum Unique Ergodicity for them, for {|{I}s| to ∞} and {R}s to d/2} with {{R}s - d/2 ≥ log log |{I}s| / log |{I}s|}. For the purpose of the proof, we build a semi-classical quantization procedure for finite volume manifolds with hyperbolic cusps, adapted to a geometrical class of symbols. We also prove an Egorov Lemma until Ehrenfest times on such manifolds.

Fuel cell system including a unit for electrical isolation of a fuel cell stack from a manifold assembly and method therefor

DOEpatents

Kelley; Dana A. , Farooque; Mohammad , Davis; Keith

2007-10-02

A fuel cell system with improved electrical isolation having a fuel cell stack with a positive potential end and a negative potential, a manifold for use in coupling gases to and from a face of the fuel cell stack, an electrical isolating assembly for electrically isolating the manifold from the stack, and a unit for adjusting an electrical potential of the manifold such as to impede the flow of electrolyte from the stack across the isolating assembly.

Adjustable flow rate controller for polymer solutions

DOEpatents

Jackson, Kenneth M.

1981-01-01

An adjustable device for controlling the flow rate of polymer solutions which results in only little shearing of the polymer molecules, said device comprising an inlet manifold, an outlet manifold, a plurality of tubes capable of providing communication between said inlet and outlet manifolds, said tubes each having an internal diameter that is smaller than that of the inlet manifold and large enough to insure that viscosity of the polymer solution passing through each said tube will not be reduced more than about 25 percent, and a valve associated with each tube, said valve being capable of opening or closing communication in that tube between the inlet and outlet manifolds, each said valve when fully open having a diameter that is substantially at least as great as that of the tube with which it is associated.

High specific power, direct methanol fuel cell stack

DOEpatents

Ramsey, John C [Los Alamos, NM; Wilson, Mahlon S [Los Alamos, NM

2007-05-08

The present invention is a fuel cell stack including at least one direct methanol fuel cell. A cathode manifold is used to convey ambient air to each fuel cell, and an anode manifold is used to convey liquid methanol fuel to each fuel cell. Tie-bolt penetrations and tie-bolts are spaced evenly around the perimeter to hold the fuel cell stack together. Each fuel cell uses two graphite-based plates. One plate includes a cathode active area that is defined by serpentine channels connecting the inlet manifold with an integral flow restrictor to the outlet manifold. The other plate includes an anode active area defined by serpentine channels connecting the inlet and outlet of the anode manifold. Located between the two plates is the fuel cell active region.

Control of soft machines using actuators operated by a Braille display.

PubMed

Mosadegh, Bobak; Mazzeo, Aaron D; Shepherd, Robert F; Morin, Stephen A; Gupta, Unmukt; Sani, Idin Zhalehdoust; Lai, David; Takayama, Shuichi; Whitesides, George M

2014-01-07

One strategy for actuating soft machines (e.g., tentacles, grippers, and simple walkers) uses pneumatic inflation of networks of small channels in an elastomeric material. Although the management of a few pneumatic inputs and valves to control pressurized gas is straightforward, the fabrication and operation of manifolds containing many (>50) independent valves is an unsolved problem. Complex pneumatic manifolds-often built for a single purpose-are not easily reconfigured to accommodate the specific inputs (i.e., multiplexing of many fluids, ranges of pressures, and changes in flow rates) required by pneumatic systems. This paper describes a pneumatic manifold comprising a computer-controlled Braille display and a micropneumatic device. The Braille display provides a compact array of 64 piezoelectric actuators that actively close and open elastomeric valves of a micropneumatic device to route pressurized gas within the manifold. The positioning and geometries of the valves and channels in the micropneumatic device dictate the functionality of the pneumatic manifold, and the use of multi-layer soft lithography permits the fabrication of networks in a wide range of configurations with many possible functions. Simply exchanging micropneumatic devices of different designs enables rapid reconfiguration of the pneumatic manifold. As a proof of principle, a pneumatic manifold controlled a soft machine containing 32 independent actuators to move a ball above a flat surface.

Second order sliding mode control for a quadrotor UAV.

PubMed

Zheng, En-Hui; Xiong, Jing-Jing; Luo, Ji-Liang

2014-07-01

A method based on second order sliding mode control (2-SMC) is proposed to design controllers for a small quadrotor UAV. For the switching sliding manifold design, the selection of the coefficients of the switching sliding manifold is in general a sophisticated issue because the coefficients are nonlinear. In this work, in order to perform the position and attitude tracking control of the quadrotor perfectly, the dynamical model of the quadrotor is divided into two subsystems, i.e., a fully actuated subsystem and an underactuated subsystem. For the former, a sliding manifold is defined by combining the position and velocity tracking errors of one state variable, i.e., the sliding manifold has two coefficients. For the latter, a sliding manifold is constructed via a linear combination of position and velocity tracking errors of two state variables, i.e., the sliding manifold has four coefficients. In order to further obtain the nonlinear coefficients of the sliding manifold, Hurwitz stability analysis is used to the solving process. In addition, the flight controllers are derived by using Lyapunov theory, which guarantees that all system state trajectories reach and stay on the sliding surfaces. Extensive simulation results are given to illustrate the effectiveness of the proposed control method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

An intercomparison of nitric oxide measurement techniques

NASA Technical Reports Server (NTRS)

Hoell, J. M., Jr.; Gregory, G. L.; Mcdougal, D. S.; Carroll, M. A.; Mcfarland, M.; Ridley, B. A.; Davis, D. D.; Bradshaw, J.; Rodgers, M. O.; Torres, A. L.

1985-01-01

Results from an intercomparison of techniques to measure tropospheric levels of nitric oxide (NO) are discussed. The intercomparison was part of the National Aeronautics and Space Administration's Global Tropospheric Experiment and was conducted at Wallops Island, VA, in July 1983. Instruments intercompared included a laser-induced fluorescence system and two chemiluminescence instruments. The intercomparisons were performed with ambient air at NO mixing ratios ranging from 10 to 60 pptv and NO-enriched ambient air at mixing ratios from 20 to 170 pptv. All instruments sampled from a common manifold. The techniques exhibited a high degree of correlation among themselves and with changes in the NO mixing ratio. Agreement among the three techniques was placed at approximately + or - 30 percent. Within this level of agreement, no artifacts or species interferences were identified.

Origami: Delineating Cosmic Structures with Phase-Space Folds

NASA Astrophysics Data System (ADS)

Neyrinck, Mark C.; Falck, Bridget L.; Szalay, Alex S.

2015-01-01

Structures like galaxies and filaments of galaxies in the Universe come about from the origami-like folding of an initially flat three-dimensional manifold in 6D phase space. The ORIGAMI method identifies these structures in a cosmological simulation, delineating the structures according to their outer folds. Structure identification is a crucial step in comparing cosmological simulations to observed maps of the Universe. The ORIGAMI definition is objective, dynamical and geometric: filament, wall and void particles are classified according to the number of orthogonal axes along which dark-matter streams have crossed. Here, we briefly review these ideas, and speculate on how ORIGAMI might be useful to find cosmic voids.

Development and Experimental Evaluation of Passive Fuel Cell Thermal Control

NASA Technical Reports Server (NTRS)

Colozza, Anthony J.; Jakupca, Ian J.; Castle, Charles H.; Burke, Kenneth A.

2014-01-01

To provide uniform cooling for a fuel cell stack, a cooling plate concept was evaluated. This concept utilized thin cooling plates to extract heat from the interior of a fuel cell stack and move this heat to a cooling manifold where it can be transferred to an external cooling fluid. The advantages of this cooling approach include a reduced number of ancillary components and the ability to directly utilize an external cooling fluid loop for cooling the fuel cell stack. A number of different types of cooling plates and manifolds were developed. The cooling plates consisted of two main types; a plate based on thermopyrolytic graphite (TPG) and a planar (or flat plate) heat pipe. The plates, along with solid metal control samples, were tested for both thermal and electrical conductivity. To transfer heat from the cooling plates to the cooling fluid, a number of manifold designs utilizing various materials were devised, constructed, and tested. A key aspect of the manifold was that it had to be electrically nonconductive so it would not short out the fuel cell stack during operation. Different manifold and cooling plate configurations were tested in a vacuum chamber to minimize convective heat losses. Cooling plates were placed in the grooves within the manifolds and heated with surface-mounted electric pad heaters. The plate temperature and its thermal distribution were recorded for all tested combinations of manifold cooling flow rates and heater power loads. This testing simulated the performance of the cooling plates and manifold within an operational fuel cell stack. Different types of control valves and control schemes were tested and evaluated based on their ability to maintain a constant temperature of the cooling plates. The control valves regulated the cooling fluid flow through the manifold, thereby controlling the heat flow to the cooling fluid. Through this work, a cooling plate and manifold system was developed that could maintain the cooling plates within a minimal temperature band with negligible thermal gradients over power profiles that would be experienced within an operating fuel cell stack.

Tails and bridges in the parabolic restricted three-body problem

NASA Astrophysics Data System (ADS)

Barrabés, Esther; Cors, Josep M.; Garcia-Taberner, Laura; Ollé, Mercè

2017-12-01

After a close encounter of two galaxies, bridges and tails can be seen between or around them. A bridge would be a spiral arm between a galaxy and its companion, whereas a tail would correspond to a long and curving set of debris escaping from the galaxy. The goal of this paper is to present a mechanism, applying techniques of dynamical systems theory, that explains the formation of tails and bridges between galaxies in a simple model, the so-called parabolic restricted three-body problem, i.e. we study the motion of a particle under the gravitational influence of two primaries describing parabolic orbits. The equilibrium points and the final evolutions in this problem are recalled,and we show that the invariant manifolds of the collinear equilibrium points and the ones of the collision manifold explain the formation of bridges and tails. Massive numerical simulations are carried out and their application to recover previous results are also analysed.

Local digital control of power electronic converters in a dc microgrid based on a-priori derivation of switching surfaces

NASA Astrophysics Data System (ADS)

Banerjee, Bibaswan

In power electronic basedmicrogrids, the computational requirements needed to implement an optimized online control strategy can be prohibitive. The work presented in this dissertation proposes a generalized method of derivation of geometric manifolds in a dc microgrid that is based on the a-priori computation of the optimal reactions and trajectories for classes of events in a dc microgrid. The proposed states are the stored energies in all the energy storage elements of the dc microgrid and power flowing into them. It is anticipated that calculating a large enough set of dissimilar transient scenarios will also span many scenarios not specifically used to develop the surface. These geometric manifolds will then be used as reference surfaces in any type of controller, such as a sliding mode hysteretic controller. The presence of switched power converters in microgrids involve different control actions for different system events. The control of the switch states of the converters is essential for steady state and transient operations. A digital memory look-up based controller that uses a hysteretic sliding mode control strategy is an effective technique to generate the proper switch states for the converters. An example dcmicrogrid with three dc-dc boost converters and resistive loads is considered for this work. The geometric manifolds are successfully generated for transient events, such as step changes in the loads and the sources. The surfaces corresponding to a specific case of step change in the loads are then used as reference surfaces in an EEPROM for experimentally validating the control strategy. The required switch states corresponding to this specific transient scenario are programmed in the EEPROM as a memory table. This controls the switching of the dc-dc boost converters and drives the system states to the reference manifold. In this work, it is shown that this strategy effectively controls the system for a transient condition such as step changes in the loads for the example case.

F-theory on all toric hypersurface fibrations and its Higgs branches

DOE PAGES

Klevers, Denis; Mayorga Pena, Damian Kaloni; Oehlmann, Paul-Konstantin; ...

2015-01-27

We consider F-theory compactifications on genus-one fibered Calabi-Yau manifolds with their fibers realized as hypersurfaces in the toric varieties associated to the 16 reflexive 2D polyhedra. We present a base-independent analysis of the codimension one, two and three singularities of these fibrations. We use these geometric results to determine the gauge groups, matter representations, 6D matter multiplicities and 4D Yukawa couplings of the corresponding effective theories. All these theories have a non-trivial gauge group and matter content. We explore the network of Higgsings relating these theories. Such Higgsings geometrically correspond to extremal transitions induced by blow-ups in the 2D toric varieties. We recover the 6D effective theories of all 16 toric hypersurface fibrations by repeatedly Higgsing the theories that exhibit Mordell-Weil torsion. We find that the three Calabi-Yau manifolds without section, whose fibers are given by the toric hypersurfaces inmore » $$\\mathbb P^{2}$$, $$\\mathbb P^{1}$$ × $$\\mathbb P^{1}$$ and the recently studied $$\\mathbb P^{2}$$ (1,1, 2) , yield F-theory realizations of SUGRA theories with discrete gauge groups $$\\mathbb Z$$ 3, $$\\mathbb Z$$ 2 and $$\\mathbb Z$$ 4.This opens up a whole new arena for model building with discrete global symmetries in F-theory. In these three manifolds, we also find codimension two I 2-fibers supporting matter charged only under these discrete gauge groups. Their 6D matter multiplicities are computed employing ideal techniques and the associated Jacobian fibrations. Here, we also show that the Jacobian of the biquadric fibration has one rational section, yielding one U(1)-gauge field in F-theory. Furthermore, the elliptically fibered Calabi-Yau manifold based on dP 1 has a U(1)-gauge field induced by a non-toric rational section. In this model, we find the first F-theory realization of matter with U(1)-charge q = 3.« less

Ricci curvature of Diff S/sup 1//SL(2,R)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bowick, M.J.; Lahiri, A.

Previous calculations of the Ricci curvature for the manifold Diff Diff(S/sup 1/)/S/sup 1/ are extended to Diff(S/sup 1/)/SL(2R). These manifolds are distinguished by being coadjoint orbits of Diff(S/sup 1/) which admit compatible symphectic and complex structures, making them Kaehler manifolds.

77 FR 72200 - Airworthiness Directives; The Boeing Company Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-05

... correctly on the engine fuel feed manifold couplings. This AD also requires inspecting the assembly of the engine fuel feed manifold rigid and full flexible couplings. This AD was prompted by reports of fuel leaks due to improperly assembled engine fuel feed manifold couplings. We are issuing this AD to detect...

Legendre submanifolds in contact manifolds as attractors and geometric nonequilibrium thermodynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goto, Shin-itiro, E-mail: sgoto@ims.ac.jp

It has been proposed that equilibrium thermodynamics is described on Legendre submanifolds in contact geometry. It is shown in this paper that Legendre submanifolds embedded in a contact manifold can be expressed as attractors in phase space for a certain class of contact Hamiltonian vector fields. By giving a physical interpretation that points outside the Legendre submanifold can represent nonequilibrium states of thermodynamic variables, in addition to that points of a given Legendre submanifold can represent equilibrium states of the variables, this class of contact Hamiltonian vector fields is physically interpreted as a class of relaxation processes, in which thermodynamicmore » variables achieve an equilibrium state from a nonequilibrium state through a time evolution, a typical nonequilibrium phenomenon. Geometric properties of such vector fields on contact manifolds are characterized after introducing a metric tensor field on a contact manifold. It is also shown that a contact manifold and a strictly convex function induce a lower dimensional dually flat space used in information geometry where a geometrization of equilibrium statistical mechanics is constructed. Legendre duality on contact manifolds is explicitly stated throughout.« less

Manifold regularized multitask learning for semi-supervised multilabel image classification.

PubMed

Luo, Yong; Tao, Dacheng; Geng, Bo; Xu, Chao; Maybank, Stephen J

2013-02-01

It is a significant challenge to classify images with multiple labels by using only a small number of labeled samples. One option is to learn a binary classifier for each label and use manifold regularization to improve the classification performance by exploring the underlying geometric structure of the data distribution. However, such an approach does not perform well in practice when images from multiple concepts are represented by high-dimensional visual features. Thus, manifold regularization is insufficient to control the model complexity. In this paper, we propose a manifold regularized multitask learning (MRMTL) algorithm. MRMTL learns a discriminative subspace shared by multiple classification tasks by exploiting the common structure of these tasks. It effectively controls the model complexity because different tasks limit one another's search volume, and the manifold regularization ensures that the functions in the shared hypothesis space are smooth along the data manifold. We conduct extensive experiments, on the PASCAL VOC'07 dataset with 20 classes and the MIR dataset with 38 classes, by comparing MRMTL with popular image classification algorithms. The results suggest that MRMTL is effective for image classification.

Hamiltonian stability for weighted measure and generalized Lagrangian mean curvature flow

NASA Astrophysics Data System (ADS)

Kajigaya, Toru; Kunikawa, Keita

2018-06-01

In this paper, we generalize several results for the Hamiltonian stability and the mean curvature flow of Lagrangian submanifolds in a Kähler-Einstein manifold to more general Kähler manifolds including a Fano manifold equipped with a Kähler form ω ∈ 2 πc1(M) by using the method proposed by Behrndt (2011). Namely, we first consider a weighted measure on a Lagrangian submanifold L in a Kähler manifold M and investigate the variational problem of L for the weighted volume functional. We call a stationary point of the weighted volume functional f-minimal, and define the notion of Hamiltonian f-stability as a local minimizer under Hamiltonian deformations. We show such examples naturally appear in a toric Fano manifold. Moreover, we consider the generalized Lagrangian mean curvature flow in a Fano manifold which is introduced by Behrndt and Smoczyk-Wang. We generalize the result of H. Li, and show that if the initial Lagrangian submanifold is a small Hamiltonian deformation of an f-minimal and Hamiltonian f-stable Lagrangian submanifold, then the generalized MCF converges exponentially fast to an f-minimal Lagrangian submanifold.

Effectiveness of Rack Sanitation Procedures for Elimination of Bacteria from Automatic Watering Manifolds.

PubMed

Costello, Terry; Watkins, Linda; Straign, Mike; Bean, William; Toth, Linda; Rehg, Jerold

1998-03-01

An important responsibility of animal care programs is to protect research animals from exposure to potentially pathogenic microorganisms. To validate the need for steam sterilization of rodent automatic watering racks, we evaluate the post-sanitation microbial contamination of experimentally inoculated racks and of racks that had been used to house conventional mice. We tested three sanitation protocols: rack-washer sanitation without manifold flush, sanitation that included manifold flush, and sanitation that included manifold flush followed by autoclaving. Rack sanitation, with or without manifold flush, did not reliably eliminate microbial flora from the lixits or manifold drainage water. A total of 43% of all non-autoclaved racks were positive for bacterial contamination after sanitation, and racks that had been used for conventional animal housing were more frequently positive than were experimentally inoculated racks (79% vs 18%). These data indicate that steam sterilization is necessary for eliminating bacteria from automatic watering systems. These observations are particularly important in light of increasing numbers of immune-impaired rodents that may be inadvertently and unnecessarily exposed to microbial pathogens via the automatic watering system.

Access to Mars from Earth-Moon Libration Point Orbits:. [Manifold and Direct Options

NASA Technical Reports Server (NTRS)

Kakoi, Masaki; Howell, Kathleen C.; Folta, David

2014-01-01

This investigation is focused specifically on transfers from Earth-Moon L(sub 1)/L(sub 2) libration point orbits to Mars. Initially, the analysis is based in the circular restricted three-body problem to utilize the framework of the invariant manifolds. Various departure scenarios are compared, including arcs that leverage manifolds associated with the Sun-Earth L(sub 2) orbits as well as non-manifold trajectories. For the manifold options, ballistic transfers from Earth-Moon L(sub 2) libration point orbits to Sun-Earth L(sub 1)/L(sub 2) halo orbits are first computed. This autonomous procedure applies to both departure and arrival between the Earth-Moon and Sun-Earth systems. Departure times in the lunar cycle, amplitudes and types of libration point orbits, manifold selection, and the orientation/location of the surface of section all contribute to produce a variety of options. As the destination planet, the ephemeris position for Mars is employed throughout the analysis. The complete transfer is transitioned to the ephemeris model after the initial design phase. Results for multiple departure/arrival scenarios are compared.

On the asymptotically Poincaré-Einstein 4-manifolds with harmonic curvature

NASA Astrophysics Data System (ADS)

Hu, Xue

2018-06-01

In this paper, we discuss the mass aspect tensor and the rigidity of an asymptotically Poincaré-Einstein (APE) 4-manifold with harmonic curvature. We prove that the trace-free part of the mass aspect tensor of an APE 4-manifold with harmonic curvature and normalized Einstein conformal infinity is zero. As to the rigidity, we first show that a complete noncompact Riemannian 4-manifold with harmonic curvature and positive Yamabe constant as well as a L2-pinching condition is Einstein. As an application, we then obtain that an APE 4-manifold with harmonic curvature and positive Yamabe constant is isometric to the hyperbolic space provided that the L2-norm of the traceless Ricci tensor or the Weyl tensor is small enough and the conformal infinity is a standard round 3-sphere.

Fixed points, stable manifolds, weather regimes, and their predictability

DOE PAGES

Deremble, Bruno; D'Andrea, Fabio; Ghil, Michael

2009-10-27

In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the model’s fixed points in phase space. The model dynamics is characterized by the coexistence of multiple ''weather regimes.'' To investigate the transitions from one regime to another, we focus on the identification of stable manifolds associated with fixed points. We show that these manifolds act as separatrices between regimes. We track each manifold by making use of two local predictability measures arising from the meteorological applications of nonlinear dynamics, namely, ''bred vectors'' and singular vectors. These results are then verified in the framework of ensemblemore » forecasts issued from clouds (ensembles) of initial states. The divergence of the trajectories allows us to establish the connections between zones of low predictability, the geometry of the stable manifolds, and transitions between regimes.« less

Polynomial chaos representation of databases on manifolds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Soize, C., E-mail: christian.soize@univ-paris-est.fr; Ghanem, R., E-mail: ghanem@usc.edu

2017-04-15

Characterizing the polynomial chaos expansion (PCE) of a vector-valued random variable with probability distribution concentrated on a manifold is a relevant problem in data-driven settings. The probability distribution of such random vectors is multimodal in general, leading to potentially very slow convergence of the PCE. In this paper, we build on a recent development for estimating and sampling from probabilities concentrated on a diffusion manifold. The proposed methodology constructs a PCE of the random vector together with an associated generator that samples from the target probability distribution which is estimated from data concentrated in the neighborhood of the manifold. Themore » method is robust and remains efficient for high dimension and large datasets. The resulting polynomial chaos construction on manifolds permits the adaptation of many uncertainty quantification and statistical tools to emerging questions motivated by data-driven queries.« less

Fixed points, stable manifolds, weather regimes, and their predictability.

PubMed

Deremble, Bruno; D'Andrea, Fabio; Ghil, Michael

2009-12-01

In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the model's fixed points in phase space. The model dynamics is characterized by the coexistence of multiple "weather regimes." To investigate the transitions from one regime to another, we focus on the identification of stable manifolds associated with fixed points. We show that these manifolds act as separatrices between regimes. We track each manifold by making use of two local predictability measures arising from the meteorological applications of nonlinear dynamics, namely, "bred vectors" and singular vectors. These results are then verified in the framework of ensemble forecasts issued from "clouds" (ensembles) of initial states. The divergence of the trajectories allows us to establish the connections between zones of low predictability, the geometry of the stable manifolds, and transitions between regimes.

A non-linear dimension reduction methodology for generating data-driven stochastic input models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ganapathysubramanian, Baskar; Zabaras, Nicholas

Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem ofmore » manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space R{sup n}. An isometric mapping F from M to a low-dimensional, compact, connected set A is contained in R{sup d}(d<

Solid Freeform Fabrication Symposium Proceedings Held in Austin, Texas on August 9-11, 1993

DTIC Science & Technology

1993-09-01

between the accuracy and the size of the geometric description. Highly non-linear surfaces, such as those that comprise turbine blades , manifolds...flange. The fan blades were modeled using different surfacing techniques. Seven blades are then combined with the rotor to make the completed fan. Figure...successfully cast in aluminum, titanium , beryllium-copper, and stainless steel, with RMS surface finish as low as 1 micrometer, without any subsequent

Recent developments in the structural design and optimization of ITER neutral beam manifold

NASA Astrophysics Data System (ADS)

Chengzhi, CAO; Yudong, PAN; Zhiwei, XIA; Bo, LI; Tao, JIANG; Wei, LI

2018-02-01

This paper describes a new design of the neutral beam manifold based on a more optimized support system. A proposed alternative scheme has presented to replace the former complex manifold supports and internal pipe supports in the final design phase. Both the structural reliability and feasibility were confirmed with detailed analyses. Comparative analyses between two typical types of manifold support scheme were performed. All relevant results of mechanical analyses for typical operation scenarios and fault conditions are presented. Future optimization activities are described, which will give useful information for a refined setting of components in the next phase.

Complete integrability of geodesics in toric Sasaki-Einstein spaces

NASA Astrophysics Data System (ADS)

Visinescu, Mihai

2016-01-01

We describe a method for constructing Killing-Yano tensors on toric Sasaki- Einstein manifolds using their geometrical properties. We take advantage of the fact that the metric cones of these spaces are Calabi-Yau manifolds. The complete list of special Killing forms can be extracted making use of the description of the Calabi-Yau manifolds in terms of toric data. This general procedure for toric Sasaki-Einstein manifolds is exemplified in the case of the 5-dimensional spaces Yp,q and T1,1. Finally we discuss the integrability of geodesic motion in these spaces.

Hidden Symmetries of Euclideanised Kerr-NUT-(A)dS Metrics in Certain Scaling Limits

NASA Astrophysics Data System (ADS)

Visinescu, Mihai; Vîlcu, Eduard

2012-08-01

The hidden symmetries of higher dimensional Kerr-NUT-(A)dS metrics are investigated. In certain scaling limits these metrics are related to the Einstein-Sasaki ones. The complete set of Killing-Yano tensors of the Einstein-Sasaki spaces are presented. For this purpose the Killing forms of the Calabi-Yau cone over the Einstein-Sasaki manifold are constructed. Two new Killing forms on Einstein-Sasaki manifolds are identified associated with the complex volume form of the cone manifolds. Finally the Killing forms on mixed 3-Sasaki manifolds are briefly described.

Role of computed tomography angiography in detection and staging of small bowel carcinoid tumors

PubMed Central

Bonekamp, David; Raman, Siva P; Horton, Karen M; Fishman, Elliot K

2015-01-01

Small-bowel carcinoid tumors are the most common form (42%) of gastrointestinal carcinoids, which by themselves comprise 70% of neuroendocrine tumors. Although primary small bowel neoplasms are overall rare (3%-6% of all gastrointestinal neoplasms), carcinoids still represent the second most common (20%-30%) primary small-bowel malignancy after small bowel adenocarcinoma. Their imaging evaluation is often challenging. State-of-the-art high-resolution multiphasic computed tomography together with advanced postprocessing methods provides an excellent tool for their depiction. The manifold interactive parameter choices however require knowledge of when to use which technique. Here, we discuss the imaging appearance and evaluation of duodenal, jejunal and ileal carcinoid tumors, including the imaging features of the primary tumor, locoregional mesenteric nodal metastases, and distant metastatic disease. A protocol for optimal lesion detection is presented, including the use of computed tomography enterography, volume acquisition, computed tomography angiography and three-dimensional mapping. Imaging findings are illustrated with a series of challenging cases which illustrate the spectrum of possible disease in the small bowel and mesentery, the range of possible appearances in the bowel itself on multiphase data and extraluminal findings such as the desmoplastic reaction in mesentery and hypervascular liver metastases. Typical imaging pitfalls and pearls are illustrated. PMID:26435774

Manifold learning for automatically predicting articular cartilage morphology in the knee with data from the osteoarthritis initiative (OAI)

NASA Astrophysics Data System (ADS)

Donoghue, C.; Rao, A.; Bull, A. M. J.; Rueckert, D.

2011-03-01

Osteoarthritis (OA) is a degenerative, debilitating disease with a large socio-economic impact. This study looks to manifold learning as an automatic approach to harness the plethora of data provided by the Osteoarthritis Initiative (OAI). We construct several Laplacian Eigenmap embeddings of articular cartilage appearance from MR images of the knee using multiple MR sequences. A region of interest (ROI) defined as the weight bearing medial femur is automatically located in all images through non-rigid registration. A pairwise intensity based similarity measure is computed between all images, resulting in a fully connected graph, where each vertex represents an image and the weight of edges is the similarity measure. Spectral analysis is then applied to these pairwise similarities, which acts to reduce the dimensionality non-linearly and embeds these images in a manifold representation. In the manifold space, images that are close to each other are considered to be more "similar" than those far away. In the experiment presented here we use manifold learning to automatically predict the morphological changes in the articular cartilage by using the co-ordinates of the images in the manifold as independent variables for multiple linear regression. In the study presented here five manifolds are generated from five sequences of 390 distinct knees. We find statistically significant correlations (up to R2 = 0.75), between our predictors and the results presented in the literature.

Positivity of the universal pairing in 3 dimensions

NASA Astrophysics Data System (ADS)

Calegari, Danny; Freedman, Michael H.; Walker, Kevin

2010-01-01

Associated to a closed, oriented surface S is the complex vector space with basis the set of all compact, oriented 3 -manifolds which it bounds. Gluing along S defines a Hermitian pairing on this space with values in the complex vector space with basis all closed, oriented 3 -manifolds. The main result in this paper is that this pairing is positive, i.e. that the result of pairing a nonzero vector with itself is nonzero. This has bearing on the question of what kinds of topological information can be extracted in principle from unitary (2+1) -dimensional TQFTs. The proof involves the construction of a suitable complexity function c on all closed 3 -manifolds, satisfying a gluing axiom which we call the topological Cauchy-Schwarz inequality, namely that c(AB) le max(c(AA),c(BB)) for all A,B which bound S , with equality if and only if A=B . The complexity function c involves input from many aspects of 3 -manifold topology, and in the process of establishing its key properties we obtain a number of results of independent interest. For example, we show that when two finite-volume hyperbolic 3 -manifolds are glued along an incompressible acylindrical surface, the resulting hyperbolic 3 -manifold has minimal volume only when the gluing can be done along a totally geodesic surface; this generalizes a similar theorem for closed hyperbolic 3 -manifolds due to Agol-Storm-Thurston.

Nonlinear dynamical modes of climate variability: from curves to manifolds

NASA Astrophysics Data System (ADS)

Gavrilov, Andrey; Mukhin, Dmitry; Loskutov, Evgeny; Feigin, Alexander

2016-04-01

The necessity of efficient dimensionality reduction methods capturing dynamical properties of the system from observed data is evident. Recent study shows that nonlinear dynamical mode (NDM) expansion is able to solve this problem and provide adequate phase variables in climate data analysis [1]. A single NDM is logical extension of linear spatio-temporal structure (like empirical orthogonal function pattern): it is constructed as nonlinear transformation of hidden scalar time series to the space of observed variables, i. e. projection of observed dataset onto a nonlinear curve. Both the hidden time series and the parameters of the curve are learned simultaneously using Bayesian approach. The only prior information about the hidden signal is the assumption of its smoothness. The optimal nonlinearity degree and smoothness are found using Bayesian evidence technique. In this work we do further extension and look for vector hidden signals instead of scalar with the same smoothness restriction. As a result we resolve multidimensional manifolds instead of sum of curves. The dimension of the hidden manifold is optimized using also Bayesian evidence. The efficiency of the extension is demonstrated on model examples. Results of application to climate data are demonstrated and discussed. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510

Homoclinic chaos in axisymmetric Bianchi-IX cosmological models with an ad hoc quantum potential

DOE Office of Scientific and Technical Information (OSTI.GOV)

Correa, G. C.; Stuchi, T. J.; Joras, S. E.

2010-04-15

In this work we study the dynamics of the axisymmetric Bianchi-IX cosmological model with a term of quantum potential added. As it is well known, this class of Bianchi-IX models is homogeneous and anisotropic with two scale factors, A(t) and B(t), derived from the solution of Einstein's equation for general relativity. The model we use in this work has a cosmological constant and the matter content is dust. To this model we add a quantum-inspired potential that is intended to represent short-range effects due to the general relativistic behavior of matter in small scales and play the role of amore » repulsive force near the singularity. We find that this potential restricts the dynamics of the model to positive values of A(t) and B(t) and alters some qualitative and quantitative characteristics of the dynamics studied previously by several authors. We make a complete analysis of the phase space of the model finding critical points, periodic orbits, stable/unstable manifolds using numerical techniques such as Poincare section, numerical continuation of orbits, and numerical globalization of invariant manifolds. We compare the classical and the quantum models. Our main result is the existence of homoclinic crossings of the stable and unstable manifolds in the physically meaningful region of the phase space [where both A(t) and B(t) are positive], indicating chaotic escape to inflation and bouncing near the singularity.« less

Massively parallel unsupervised single-particle cryo-EM data clustering via statistical manifold learning

PubMed Central

Wu, Jiayi; Ma, Yong-Bei; Congdon, Charles; Brett, Bevin; Chen, Shuobing; Xu, Yaofang; Ouyang, Qi

2017-01-01

Structural heterogeneity in single-particle cryo-electron microscopy (cryo-EM) data represents a major challenge for high-resolution structure determination. Unsupervised classification may serve as the first step in the assessment of structural heterogeneity. However, traditional algorithms for unsupervised classification, such as K-means clustering and maximum likelihood optimization, may classify images into wrong classes with decreasing signal-to-noise-ratio (SNR) in the image data, yet demand increased computational costs. Overcoming these limitations requires further development of clustering algorithms for high-performance cryo-EM data processing. Here we introduce an unsupervised single-particle clustering algorithm derived from a statistical manifold learning framework called generative topographic mapping (GTM). We show that unsupervised GTM clustering improves classification accuracy by about 40% in the absence of input references for data with lower SNRs. Applications to several experimental datasets suggest that our algorithm can detect subtle structural differences among classes via a hierarchical clustering strategy. After code optimization over a high-performance computing (HPC) environment, our software implementation was able to generate thousands of reference-free class averages within hours in a massively parallel fashion, which allows a significant improvement on ab initio 3D reconstruction and assists in the computational purification of homogeneous datasets for high-resolution visualization. PMID:28786986

Massively parallel unsupervised single-particle cryo-EM data clustering via statistical manifold learning.

PubMed

Wu, Jiayi; Ma, Yong-Bei; Congdon, Charles; Brett, Bevin; Chen, Shuobing; Xu, Yaofang; Ouyang, Qi; Mao, Youdong

2017-01-01

Structural heterogeneity in single-particle cryo-electron microscopy (cryo-EM) data represents a major challenge for high-resolution structure determination. Unsupervised classification may serve as the first step in the assessment of structural heterogeneity. However, traditional algorithms for unsupervised classification, such as K-means clustering and maximum likelihood optimization, may classify images into wrong classes with decreasing signal-to-noise-ratio (SNR) in the image data, yet demand increased computational costs. Overcoming these limitations requires further development of clustering algorithms for high-performance cryo-EM data processing. Here we introduce an unsupervised single-particle clustering algorithm derived from a statistical manifold learning framework called generative topographic mapping (GTM). We show that unsupervised GTM clustering improves classification accuracy by about 40% in the absence of input references for data with lower SNRs. Applications to several experimental datasets suggest that our algorithm can detect subtle structural differences among classes via a hierarchical clustering strategy. After code optimization over a high-performance computing (HPC) environment, our software implementation was able to generate thousands of reference-free class averages within hours in a massively parallel fashion, which allows a significant improvement on ab initio 3D reconstruction and assists in the computational purification of homogeneous datasets for high-resolution visualization.

Online dimensionality reduction using competitive learning and Radial Basis Function network.

PubMed

Tomenko, Vladimir

2011-06-01

The general purpose dimensionality reduction method should preserve data interrelations at all scales. Additional desired features include online projection of new data, processing nonlinearly embedded manifolds and large amounts of data. The proposed method, called RBF-NDR, combines these features. RBF-NDR is comprised of two modules. The first module learns manifolds by utilizing modified topology representing networks and geodesic distance in data space and approximates sampled or streaming data with a finite set of reference patterns, thus achieving scalability. Using input from the first module, the dimensionality reduction module constructs mappings between observation and target spaces. Introduction of specific loss function and synthesis of the training algorithm for Radial Basis Function network results in global preservation of data structures and online processing of new patterns. The RBF-NDR was applied for feature extraction and visualization and compared with Principal Component Analysis (PCA), neural network for Sammon's projection (SAMANN) and Isomap. With respect to feature extraction, the method outperformed PCA and yielded increased performance of the model describing wastewater treatment process. As for visualization, RBF-NDR produced superior results compared to PCA and SAMANN and matched Isomap. For the Topic Detection and Tracking corpus, the method successfully separated semantically different topics. Copyright © 2011 Elsevier Ltd. All rights reserved.

Process and system - A dual definition, revisited with consequences in metrology

NASA Astrophysics Data System (ADS)

Ruhm, K. H.

2010-07-01

Lets assert that metrology life could be easier scientifically as well as technologically, if we, intentionally, would make an explicit distinction between two outstanding domains, namely the given, really existent domain of processes and the just virtually existent domain of systems, the latter of which is designed and used by the human mind. The abstract domain of models, by which we map the manifold reality of processes, is itself part of the domain of systems. Models support comprehension and communication, although they are normally extreme simplifications of properties and behaviour of a concrete reality. So, systems and signals represent processes and quantities, which are described by means of Signal and System Theory as well as by Stochastics and Statistics. The following presentation of this new, demanding and somehow irritating definition of the terms process and system as a dual pair is unusual indeed, but it opens the door widely to a better and more consistent discussion and understanding of manifold scientific tools in many areas. Metrology [4] is one of the important fields of concern due to many reasons: One group of the soft and hard links between the domain of processes and the domain of systems is realised by concepts of measurement science on the one hand and by instrumental tools of measurement technology on the other hand.

Numerical Estimation of Balanced and Falling States for Constrained Legged Systems

NASA Astrophysics Data System (ADS)

Mummolo, Carlotta; Mangialardi, Luigi; Kim, Joo H.

2017-08-01

Instability and risk of fall during standing and walking are common challenges for biped robots. While existing criteria from state-space dynamical systems approach or ground reference points are useful in some applications, complete system models and constraints have not been taken into account for prediction and indication of fall for general legged robots. In this study, a general numerical framework that estimates the balanced and falling states of legged systems is introduced. The overall approach is based on the integration of joint-space and Cartesian-space dynamics of a legged system model. The full-body constrained joint-space dynamics includes the contact forces and moments term due to current foot (or feet) support and another term due to altered contact configuration. According to the refined notions of balanced, falling, and fallen, the system parameters, physical constraints, and initial/final/boundary conditions for balancing are incorporated into constrained nonlinear optimization problems to solve for the velocity extrema (representing the maximum perturbation allowed to maintain balance without changing contacts) in the Cartesian space at each center-of-mass (COM) position within its workspace. The iterative algorithm constructs the stability boundary as a COM state-space partition between balanced and falling states. Inclusion in the resulting six-dimensional manifold is a necessary condition for a state of the given system to be balanced under the given contact configuration, while exclusion is a sufficient condition for falling. The framework is used to analyze the balance stability of example systems with various degrees of complexities. The manifold for a 1-degree-of-freedom (DOF) legged system is consistent with the experimental and simulation results in the existing studies for specific controller designs. The results for a 2-DOF system demonstrate the dependency of the COM state-space partition upon joint-space configuration (elbow-up vs. elbow-down). For both 1- and 2-DOF systems, the results are validated in simulation environments. Finally, the manifold for a biped walking robot is constructed and illustrated against its single-support walking trajectories. The manifold identified by the proposed framework for any given legged system can be evaluated beforehand as a system property and serves as a map for either a specified state or a specific controller's performance.

Variable volume combustor with nested fuel manifold system

DOEpatents

McConnaughhay, Johnie Franklin; Keener, Christopher Paul; Johnson, Thomas Edward; Ostebee, Heath Michael

2016-09-13

The present application provides a combustor for use with a gas turbine engine. The combustor may include a number of micro-mixer fuel nozzles, a fuel manifold system in communication with the micro-mixer fuel nozzles to deliver a flow of fuel thereto, and a linear actuator to maneuver the micro-mixer fuel nozzles and the fuel manifold system.

Compressed gas manifold

DOEpatents

Hildebrand, Richard J.; Wozniak, John J.

2001-01-01

A compressed gas storage cell interconnecting manifold including a thermally activated pressure relief device, a manual safety shut-off valve, and a port for connecting the compressed gas storage cells to a motor vehicle power source and to a refueling adapter. The manifold is mechanically and pneumatically connected to a compressed gas storage cell by a bolt including a gas passage therein.

LCD OF AIR INTAKE MANIFOLDS PHASE 2: FORD F250 AIR INTAKE MANIFOLD

EPA Science Inventory

The life cycle design methodology was applied to the design analysis of three alternatives for the lower plehum of the air intake manifold for us with a 5.4L F-250 truck engine: a sand cast aluminum, a lost core molded nylon composite, and a vibration welded nylon composite. The ...

Capillary interconnect device

DOEpatents

Renzi, Ronald F.

2007-12-25

A manifold for connecting external capillaries to the inlet and/or outlet ports of a microfluidic device for high pressure applications is provided. The fluid connector for coupling at least one fluid conduit to a corresponding port of a substrate that includes: (i) a manifold comprising one or more channels extending therethrough wherein each channel is at least partially threaded, (ii) one or more threaded ferrules each defining a bore extending therethrough with each ferrule supporting a fluid conduit wherein each ferrule is threaded into a channel of the manifold, (iii) a substrate having one or more ports on its upper surface wherein the substrate is positioned below the manifold so that the one or more ports is aligned with the one or more channels of the manifold, and (iv) means for applying an axial compressive force to the substrate to couple the one or more ports of the substrate to a corresponding proximal end of a fluid conduit.

Swimming invariant manifolds and the motion of bacteria in a fluid flow

NASA Astrophysics Data System (ADS)

Yoest, Helena; Mitchell, Kevin; Solomon, Tom

2017-11-01

We present experiments on the motion of both wild-type and smooth-swimming bacillus subtilis in a hyperbolic, microfluidic fluid flow. Passive invariant manifolds crossing the fixed point in the flow act as barriers that block inert tracers in the flow. Self-propelled tracers can cross these passive manifolds, but are blocked by and attracted to swimming invariant manifolds (SWIMs) that split from the passive manifolds with larger and larger non-dimensional swimming speed v0 ≡V0 / U , where V0 is the swimming speed in the absence of a flow and U is a characteristic flos speed. We present the theory that predicts these SWIMs for smooth-swimming tracers, along with experiments that we are conducting to test these theories. We also discuss potential effects of rheotaxis and chemotaxis on the phenomena. Supported by NSF Grant DMR-1361881.

Remtech SSME nozzle design TPS

NASA Technical Reports Server (NTRS)

Bancroft, Steven A.; Engel, Carl D.; Pond, John E.

1990-01-01

Thermal damage to the Space Shuttle Main Engine (SSME) aft manifold Thermal Protection System (TPS) has been observed for flights STS-8 through STS-13. This damaged area is located on the ME2 and ME3 and extends over a region of approximately one square foot. Total failure or burn-through of the TPS could lead to severe thermal damage of the SSME manifold and loss of an engine nozzle necessitating nozzle replacement causing significant schedule delays and cost increases. Thermal damage to the manifold can be defined as a situation where the manifold temperature becomes greater than 1300 F; thereby causing loss of heat treatment in the nozzle. Results of Orbiter/nozzle wind tunnel tests and Hot Gas Facility tests of the TPS are presented. Aerothermal and thermal analysis models for the SSME aft manifold are discussed along with the flight predictions, design trajectory and design environment. Finally, the TPS design concept and TPS thermal response are addressed.

Preliminary integrated geologic map databases for the United States: Digital data for the reconnaissance bedrock geologic map for the northern Alaska peninsula area, southwest Alaska

USGS Publications Warehouse

,

2006-01-01

he growth in the use of Geographic Information Systems (GIS) has highlighted the need for digital geologic maps that have been attributed with information about age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. This report is part of a series of integrated geologic map databases that cover the entire United States. Three national-scale geologic maps that portray most or all of the United States already exist; for the conterminous U.S., King and Beikman (1974a,b) compiled a map at a scale of 1:2,500,000, Beikman (1980) compiled a map for Alaska at 1:2,500,000 scale, and for the entire U.S., Reed and others (2005a,b) compiled a map at a scale of 1:5,000,000. A digital version of the King and Beikman map was published by Schruben and others (1994). Reed and Bush (2004) produced a digital version of the Reed and others (2005a) map for the conterminous U.S. The present series of maps is intended to provide the next step in increased detail. State geologic maps that range in scale from 1:100,000 to 1:1,000,000 are available for most of the country, and digital versions of these state maps are the basis of this product. The digital geologic maps presented here are in a standardized format as ARC/INFO export files and as ArcView shape files. Data tables that relate the map units to detailed lithologic and age information accompany these GIS files. The map is delivered as a set 1:250,000-scale quadrangle files. To the best of our ability, these quadrangle files are edge-matched with respect to geology. When the maps are merged, the combined attribute tables can be used directly with the merged maps to make derivative maps.

Preliminary integrated geologic map databases for the United States: Digital data for the reconnaissance geologic map of the western Aleutian Islands, Alaska

USGS Publications Warehouse

,

2006-01-01

The growth in the use of Geographic Information Systems (GIS) has highlighted the need for digital geologic maps that have been attributed with information about age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. This report is part of a series of integrated geologic map databases that cover the entire United States. Three national-scale geologic maps that portray most or all of the United States already exist; for the conterminous U.S., King and Beikman (1974a,b) compiled a map at a scale of 1:2,500,000, Beikman (1980) compiled a map for Alaska at 1:2,500,000 scale, and for the entire U.S., Reed and others (2005a,b) compiled a map at a scale of 1:5,000,000. A digital version of the King and Beikman map was published by Schruben and others (1994). Reed and Bush (2004) produced a digital version of the Reed and others (2005a) map for the conterminous U.S. The present series of maps is intended to provide the next step in increased detail. State geologic maps that range in scale from 1:100,000 to 1:1,000,000 are available for most of the country, and digital versions of these state maps are the basis of this product. The digital geologic maps presented here are in a standardized format as ARC/INFO Exportfiles/ and as ArcView shape files. Data tables that relate the map units to detailed lithologic and age information accompany these GIS files. The map is delivered as a set 1:250,000-scale quadrangle files. To the best of our ability, these quadrangle files are edge-matched with respect to geology. When the maps are merged, the combined attribute tables can be used directly with the merged maps to make derivative maps.

Preliminary integrated geologic map databases for the United States: Digital data for the generalized bedrock geologic map, Yukon Flats region, east-central Alaska

USGS Publications Warehouse

Till, Alison B.; Dumoulin, Julie A.; Phillips, Jeffrey D.; Stanley, Richard G.; Crews, Jessie

2006-01-01

The growth in the use of Geographic Information Systems (GIS) has highlighted the need for digital geologic maps that have been attributed with information about age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. This report is part of a series of integrated geologic map databases that cover the entire United States. Three national-scale geologic maps that portray most or all of the United States already exist; for the conterminous U.S., King and Beikman (1974a,b) compiled a map at a scale of 1:2,500,000, Beikman (1980) compiled a map for Alaska at 1:2,500,000 scale, and for the entire U.S., Reed and others (2005a,b) compiled a map at a scale of 1:5,000,000. A digital version of the King and Beikman map was published by Schruben and others (1994). Reed and Bush (2004) produced a digital version of the Reed and others (2005a) map for the conterminous U.S. The present series of maps is intended to provide the next step in increased detail. State geologic maps that range in scale from 1:100,000 to 1:1,000,000 are available for most of the country, and digital versions of these state maps are the basis of this product. The digital geologic maps presented here are in a standardized format as ARC/INFO export files and as ArcView shape files. Data tables that relate the map units to detailed lithologic and age information accompany these GIS files. The map is delivered as a set 1:250,000-scale quadrangle files. To the best of our ability, these quadrangle files are edge-matched with respect to geology. When the maps are merged, the combined attribute tables can be used directly with the merged maps to make derivative maps.

Preliminary integrated geologic map databases for the United States: Digital data for the reconnaissance geologic map of the lower Yukon River region, Alaska

USGS Publications Warehouse

,

2006-01-01

The growth in the use of Geographic Information Systems (GIS) has highlighted the need for digital geologic maps that have been attributed with information about age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. This report is part of a series of integrated geologic map databases that cover the entire United States. Three national-scale geologic maps that portray most or all of the United States already exist; for the conterminous U.S., King and Beikman (1974a,b) compiled a map at a scale of 1:2,500,000, Beikman (1980) compiled a map for Alaska at 1:2,500,000 scale, and for the entire U.S., Reed and others (2005a,b) compiled a map at a scale of 1:5,000,000. A digital version of the King and Beikman map was published by Schruben and others (1994). Reed and Bush (2004) produced a digital version of the Reed and others (2005a) map for the conterminous U.S. The present series of maps is intended to provide the next step in increased detail. State geologic maps that range in scale from 1:100,000 to 1:1,000,000 are available for most of the country, and digital versions of these state maps are the basis of this product. The digital geologic maps presented here are in a standardized format as ARC/INFO export files and as ArcView shape files. Data tables that relate the map units to detailed lithologic and age information accompany these GIS files. The map is delivered as a set 1:250,000-scale quadrangle files. To the best of our ability, these quadrangle files are edge-matched with respect to geology. When the maps are merged, the combined attribute tables can be used directly with the merged maps to make derivative maps.

A Survey of Ballistic Transfers to the Lunar Surface

NASA Technical Reports Server (NTRS)

Anderson, Rodney L.; Parker, Jeffrey S.

2011-01-01

In this study techniques are developed which allow an analysis of a range of different types of transfer trajectories from the Earth to the lunar surface. Trajectories ranging from those obtained using the invariant manifolds of unstable orbits to those derived from collision orbits are analyzed. These techniques allow the computation of trajectories encompassing low-energy trajectories as well as more direct transfers. The range of possible trajectory options is summarized, and a broad range of trajectories that exist as a result of the Sun's influence are computed and analyzed. The results are then classified by type, and trades between different measures of cost are discussed.

L1-norm locally linear representation regularization multi-source adaptation learning.

PubMed

Tao, Jianwen; Wen, Shiting; Hu, Wenjun

2015-09-01

In most supervised domain adaptation learning (DAL) tasks, one has access only to a small number of labeled examples from target domain. Therefore the success of supervised DAL in this "small sample" regime needs the effective utilization of the large amounts of unlabeled data to extract information that is useful for generalization. Toward this end, we here use the geometric intuition of manifold assumption to extend the established frameworks in existing model-based DAL methods for function learning by incorporating additional information about the target geometric structure of the marginal distribution. We would like to ensure that the solution is smooth with respect to both the ambient space and the target marginal distribution. In doing this, we propose a novel L1-norm locally linear representation regularization multi-source adaptation learning framework which exploits the geometry of the probability distribution, which has two techniques. Firstly, an L1-norm locally linear representation method is presented for robust graph construction by replacing the L2-norm reconstruction measure in LLE with L1-norm one, which is termed as L1-LLR for short. Secondly, considering the robust graph regularization, we replace traditional graph Laplacian regularization with our new L1-LLR graph Laplacian regularization and therefore construct new graph-based semi-supervised learning framework with multi-source adaptation constraint, which is coined as L1-MSAL method. Moreover, to deal with the nonlinear learning problem, we also generalize the L1-MSAL method by mapping the input data points from the input space to a high-dimensional reproducing kernel Hilbert space (RKHS) via a nonlinear mapping. Promising experimental results have been obtained on several real-world datasets such as face, visual video and object. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cycle expansions: From maps to turbulence

NASA Astrophysics Data System (ADS)

Lan, Y.

2010-03-01

We present a derivation, a physical explanation and applications of cycle expansions in different dynamical systems, ranging from simple one-dimensional maps to turbulence in fluids. Cycle expansion is a newly devised powerful tool for computing averages of physical observables in nonlinear chaotic systems which combines many innovative ideas developed in dynamical systems, such as hyperbolicity, invariant manifolds, symbolic dynamics, measure theory and thermodynamic formalism. The concept of cycle expansion has a deep root in theoretical physics, bearing a close analogy to cumulant expansion in statistical physics and effective action functional in quantum field theory, the essence of which is to represent a physical system in a hierarchical way by utilizing certain multiplicative structures such that the dominant parts of physical observables are captured by compact, maneuverable objects while minor detailed variations are described by objects with a larger space and time scale. The technique has been successfully applied to many low-dimensional dynamical systems and much effort has recently been made to extend its use to spatially extended systems. For one-dimensional systems such as the Kuramoto-Sivashinsky equation, the method turns out to be very effective while for more complex real-world systems including the Navier-Stokes equation, the method is only starting to yield its first fruits and much more work is needed to enable practical computations. However, the experience and knowledge accumulated so far is already very useful to a large set of research problems. Several such applications are briefly described in what follows. As more research effort is devoted to the study of complex dynamics of nonlinear systems, cycle expansion will undergo a fast development and find wide applications.

Computing and Visualizing Reachable Volumes for Maneuvering Satellites

NASA Astrophysics Data System (ADS)

Jiang, M.; de Vries, W.; Pertica, A.; Olivier, S.

2011-09-01

Detecting and predicting maneuvering satellites is an important problem for Space Situational Awareness. The spatial envelope of all possible locations within reach of such a maneuvering satellite is known as the Reachable Volume (RV). As soon as custody of a satellite is lost, calculating the RV and its subsequent time evolution is a critical component in the rapid recovery of the satellite. In this paper, we present a Monte Carlo approach to computing the RV for a given object. Essentially, our approach samples all possible trajectories by randomizing thrust-vectors, thrust magnitudes and time of burn. At any given instance, the distribution of the "point-cloud" of the virtual particles defines the RV. For short orbital time-scales, the temporal evolution of the point-cloud can result in complex, multi-reentrant manifolds. Visualization plays an important role in gaining insight and understanding into this complex and evolving manifold. In the second part of this paper, we focus on how to effectively visualize the large number of virtual trajectories and the computed RV. We present a real-time out-of-core rendering technique for visualizing the large number of virtual trajectories. We also examine different techniques for visualizing the computed volume of probability density distribution, including volume slicing, convex hull and isosurfacing. We compare and contrast these techniques in terms of computational cost and visualization effectiveness, and describe the main implementation issues encountered during our development process. Finally, we will present some of the results from our end-to-end system for computing and visualizing RVs using examples of maneuvering satellites.

Single-Shot Rotational Raman Thermometry for Turbulent Flames Using a Low-Resolution Bandwidth Technique

NASA Technical Reports Server (NTRS)

Kojima, Jun; Nguyen, Quang-Viet

2007-01-01

An alternative optical thermometry technique that utilizes the low-resolution (order 10(exp 1)/cm) pure-rotational spontaneous Raman scattering of air is developed to aid single-shot multiscalar measurements in turbulent combustion studies. Temperature measurements are realized by correlating the measured envelope bandwidth of the pure-rotational manifold of the N2/O2 spectrum with a theoretical prediction of a species-weighted bandwidth. By coupling this thermometry technique with conventional vibrational Raman scattering for species determination, we demonstrate quantitative spatially resolved, single-shot measurements of the temperature and fuel/oxidizer concentrations in a high-pressure turbulent Cf4-air flame. Our technique provides not only an effective means of validating other temperature measurement methods, but also serves as a secondary thermometry technique in cases where the anti-Stokes vibrational N2 Raman signals are too low for a conventional vibrational temperature analysis.

Digital Data for the reconnaissance geologic map for Prince William Sound and the Kenai Peninsula, Alaska

USGS Publications Warehouse

Wilson, Frederic H.; Hults, Chad P.; Labay, Keith A.; Shew, Nora B.

2007-01-01

The growth in the use of Geographic Information Systems (GIS) has highlighted the need for digital geologic maps that have been attributed with information about age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. This report is part of a series of integrated geologic map databases that cover the entire United States. Three national-scale geologic maps that portray most or all of the United States already exist; for the conterminous U.S., King and Beikman (1974a,b) compiled a map at a scale of 1:2,500,000, Beikman (1980) compiled a map for Alaska at 1:2,500,000 scale, and for the entire U.S., Reed and others (2005a,b) compiled a map at a scale of 1:5,000,000. A digital version of the King and Beikman map was published by Schruben and others (1994). Reed and Bush (2004) produced a digital version of the Reed and others (2005a) map for the conterminous U.S. The present series of maps is intended to provide the next step in increased detail. State geologic maps that range in scale from 1:100,000 to 1:1,000,000 are available for most of the country, and digital versions of these state maps are the basis of this product. The digital geologic maps presented here are in a standardized format as ARC/INFO export files and as ArcView shape files. The files named __geol contain geologic polygons and line (contact) attributes; files named __fold contain fold axes; files named __lin contain lineaments; and files named __dike contain dikes as lines. Data tables that relate the map units to detailed lithologic and age information accompany these GIS files. The map is delivered as a set 1:250,000-scale quadrangle files. To the best of our ability, these quadrangle files are edge-matched with respect to geology. When the maps are merged, the combined attribute tables can be used directly with the merged maps to make derivative maps.

Interference evaluation between manifold and wet Christmas tree CP systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brasil, S.L.D.C.; Baptista, W.

2000-05-01

Offshore production wells are controlled by valves installed in the marine soil, called wet Christmas trees (WCTs). A manifold receives the production of several wells and transports it to the platform. The manifold is cathodically protected by Al anodes and the WCT by Zn anodes. A computer simulation was carried out to evaluate the interference between the equipment cathodic protection systems.

Classical BV Theories on Manifolds with Boundary

NASA Astrophysics Data System (ADS)

Cattaneo, Alberto S.; Mnev, Pavel; Reshetikhin, Nicolai

2014-12-01

In this paper we extend the classical BV framework to gauge theories on spacetime manifolds with boundary. In particular, we connect the BV construction in the bulk with the BFV construction on the boundary and we develop its extension to strata of higher codimension in the case of manifolds with corners. We present several examples including electrodynamics, Yang-Mills theory and topological field theories coming from the AKSZ construction, in particular, the Chern-Simons theory, the BF theory, and the Poisson sigma model. This paper is the first step towards developing the perturbative quantization of such theories on manifolds with boundary in a way consistent with gluing.

On a program manifold's stability of one contour automatic control systems

NASA Astrophysics Data System (ADS)

Zumatov, S. S.

2017-12-01

Methodology of analysis of stability is expounded to the one contour systems automatic control feedback in the presence of non-linearities. The methodology is based on the use of the simplest mathematical models of the nonlinear controllable systems. Stability of program manifolds of one contour automatic control systems is investigated. The sufficient conditions of program manifold's absolute stability of one contour automatic control systems are obtained. The Hurwitz's angle of absolute stability was determined. The sufficient conditions of program manifold's absolute stability of control systems by the course of plane in the mode of autopilot are obtained by means Lyapunov's second method.

Mechanical systems with closed orbits on manifolds of revolution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kudryavtseva, E A; Fedoseev, D A

We study natural mechanical systems describing the motion of a particle on a two-dimensional Riemannian manifold of revolution in the field of a central smooth potential. We obtain a classification of Riemannian manifolds of revolution and central potentials on them that have the strong Bertrand property: any nonsingular (that is, not contained in a meridian) orbit is closed. We also obtain a classification of manifolds of revolution and central potentials on them that have the 'stable' Bertrand property: every parallel is an 'almost stable' circular orbit, and any nonsingular bounded orbit is closed. Bibliography: 14 titles.

Scientific data interpolation with low dimensional manifold model

NASA Astrophysics Data System (ADS)

Zhu, Wei; Wang, Bao; Barnard, Richard; Hauck, Cory D.; Jenko, Frank; Osher, Stanley

2018-01-01

We propose to apply a low dimensional manifold model to scientific data interpolation from regular and irregular samplings with a significant amount of missing information. The low dimensionality of the patch manifold for general scientific data sets has been used as a regularizer in a variational formulation. The problem is solved via alternating minimization with respect to the manifold and the data set, and the Laplace-Beltrami operator in the Euler-Lagrange equation is discretized using the weighted graph Laplacian. Various scientific data sets from different fields of study are used to illustrate the performance of the proposed algorithm on data compression and interpolation from both regular and irregular samplings.

Encoding quantum information in a stabilized manifold of a superconducting cavity

NASA Astrophysics Data System (ADS)

Touzard, S.; Leghtas, Z.; Mundhada, S. O.; Axline, C.; Reagor, M.; Chou, K.; Blumoff, J.; Sliwa, K. M.; Shankar, S.; Frunzio, L.; Schoelkopf, R. J.; Mirrahimi, M.; Devoret, M. H.

In a superconducting Josephson circuit architecture, we activate a multi-photon process between two modes by applying microwave drives at specific frequencies. This creates a pairwise exchange of photons between a high-Q cavity and the environment. The resulting open dynamical system develops a two-dimensional quasi-energy ground state manifold. Can we encode, protect and manipulate quantum information in this manifold? We experimentally investigate the convergence and escape rates in and out of this confined subspace. Finally, using quantum Zeno dynamics, we aim to perform gates which maintain the state in the protected manifold at all times. Work supported by: ARO, ONR, AFOSR and YINQE.

Invariant Manifolds, the Spatial Three-Body Problem and Space Mission Design

NASA Technical Reports Server (NTRS)

Gomez, G.; Koon, W. S.; Lo, Martin W.; Marsden, J. E.; Masdemont, J.; Ross, S. D.

2001-01-01

The invariant manifold structures of the collinear libration points for the spatial restricted three-body problem provide the framework for understanding complex dynamical phenomena from a geometric point of view. In particular, the stable and unstable invariant manifold 'tubes' associated to libration point orbits are the phase space structures that provide a conduit for orbits between primary bodies for separate three-body systems. These invariant manifold tubes can be used to construct new spacecraft trajectories, such as 'Petit Grand Tour' of the moons of Jupiter. Previous work focused on the planar circular restricted three-body problem. The current work extends the results to the spatial case.

Pluripotential theory on quaternionic manifolds

NASA Astrophysics Data System (ADS)

Alesker, Semyon

2012-05-01

On any quaternionic manifold of dimension greater than 4 a class of plurisubharmonic functions (or, rather, sections of an appropriate line bundle) is introduced. Then a Monge-Ampère operator is defined. It is shown that it satisfies a version of the theorems of A. D. Alexandrov and Chern-Levine-Nirenberg. For more special classes of manifolds analogous results were previously obtained in Alesker (2003) [1] for the flat quaternionic space Hn and in Alesker and Verbitsky (2006) [5] for hypercomplex manifolds. One of the new technical aspects of the present paper is the systematic use of the Baston differential operators, for which we also prove a new multiplicativity property.

Analysis on singular spaces: Lie manifolds and operator algebras

NASA Astrophysics Data System (ADS)

Nistor, Victor

2016-07-01

We discuss and develop some connections between analysis on singular spaces and operator algebras, as presented in my sequence of four lectures at the conference Noncommutative geometry and applications, Frascati, Italy, June 16-21, 2014. Therefore this paper is mostly a survey paper, but the presentation is new, and there are included some new results as well. In particular, Sections 3 and 4 provide a complete short introduction to analysis on noncompact manifolds that is geared towards a class of manifolds-called ;Lie manifolds; -that often appears in practice. Our interest in Lie manifolds is due to the fact that they provide the link between analysis on singular spaces and operator algebras. The groupoids integrating Lie manifolds play an important background role in establishing this link because they provide operator algebras whose structure is often well understood. The initial motivation for the work surveyed here-work that spans over close to two decades-was to develop the index theory of stratified singular spaces. Meanwhile, several other applications have emerged as well, including applications to Partial Differential Equations and Numerical Methods. These will be mentioned only briefly, however, due to the lack of space. Instead, we shall concentrate on the applications to Index theory.

Feedback Integrators

NASA Astrophysics Data System (ADS)

Chang, Dong Eui; Jiménez, Fernando; Perlmutter, Matthew

2016-12-01

A new method is proposed to numerically integrate a dynamical system on a manifold such that the trajectory stably remains on the manifold and preserves the first integrals of the system. The idea is that given an initial point in the manifold we extend the dynamics from the manifold to its ambient Euclidean space and then modify the dynamics outside the intersection of the manifold and the level sets of the first integrals containing the initial point such that the intersection becomes a unique local attractor of the resultant dynamics. While the modified dynamics theoretically produces the same trajectory as the original dynamics, it yields a numerical trajectory that stably remains on the manifold and preserves the first integrals. The big merit of our method is that the modified dynamics can be integrated with any ordinary numerical integrator such as Euler or Runge-Kutta. We illustrate this method by applying it to three famous problems: the free rigid body, the Kepler problem and a perturbed Kepler problem with rotational symmetry. We also carry out simulation studies to demonstrate the excellence of our method and make comparisons with the standard projection method, a splitting method and Störmer-Verlet schemes.

Methods for disassembling, replacing and assembling parts of a steam cooling system for a gas turbine

DOEpatents

Wilson, Ian D.; Wesorick, Ronald R.

2002-01-01

The steam cooling circuit for a gas turbine includes a bore tube assembly supplying steam to circumferentially spaced radial tubes coupled to supply elbows for transitioning the radial steam flow in an axial direction along steam supply tubes adjacent the rim of the rotor. The supply tubes supply steam to circumferentially spaced manifold segments located on the aft side of the 1-2 spacer for supplying steam to the buckets of the first and second stages. Spent return steam from these buckets flows to a plurality of circumferentially spaced return manifold segments disposed on the forward face of the 1-2 spacer. Crossover tubes couple the steam supply from the steam supply manifold segments through the 1-2 spacer to the buckets of the first stage. Crossover tubes through the 1-2 spacer also return steam from the buckets of the second stage to the return manifold segments. Axially extending return tubes convey spent cooling steam from the return manifold segments to radial tubes via return elbows. The bore tube assembly, radial tubes, elbows, manifold segments and crossover tubes are removable from the turbine rotor and replaceable.

Principal Curves on Riemannian Manifolds.

PubMed

Hauberg, Soren

2016-09-01

Euclidean statistics are often generalized to Riemannian manifolds by replacing straight-line interpolations with geodesic ones. While these Riemannian models are familiar-looking, they are restricted by the inflexibility of geodesics, and they rely on constructions which are optimal only in Euclidean domains. We consider extensions of Principal Component Analysis (PCA) to Riemannian manifolds. Classic Riemannian approaches seek a geodesic curve passing through the mean that optimizes a criteria of interest. The requirements that the solution both is geodesic and must pass through the mean tend to imply that the methods only work well when the manifold is mostly flat within the support of the generating distribution. We argue that instead of generalizing linear Euclidean models, it is more fruitful to generalize non-linear Euclidean models. Specifically, we extend the classic Principal Curves from Hastie & Stuetzle to data residing on a complete Riemannian manifold. We show that for elliptical distributions in the tangent of spaces of constant curvature, the standard principal geodesic is a principal curve. The proposed model is simple to compute and avoids many of the pitfalls of traditional geodesic approaches. We empirically demonstrate the effectiveness of the Riemannian principal curves on several manifolds and datasets.

3D spine reconstruction of postoperative patients from multi-level manifold ensembles.

PubMed

Kadoury, Samuel; Labelle, Hubert; Parent, Stefan

2014-01-01

The quantitative assessment of surgical outcomes using personalized anatomical models is an essential task for the treatment of spinal deformities such as adolescent idiopathic scoliosis. However an accurate 3D reconstruction of the spine from postoperative X-ray images remains challenging due to presence of instrumentation (metallic rods and screws) occluding vertebrae on the spine. In this paper, we formulate the reconstruction problem as an optimization over a manifold of articulated spine shapes learned from pathological training data. The manifold itself is represented using a novel data structure, a multi-level manifold ensemble, which contains links between nodes in a single hierarchical structure, as well as links between different hierarchies, representing overlapping partitions. We show that this data structure allows both efficient localization and navigation on the manifold, for on-the-fly building of local nonlinear models (manifold charting). Our reconstruction framework was tested on pre- and postoperative X-ray datasets from patients who underwent spinal surgery. Compared to manual ground-truth, our method achieves a 3D reconstruction accuracy of 2.37 +/- 0.85 mm for postoperative spine models and can deal with severe cases of scoliosis.

Digital data for the geology of the Southern Brooks Range, Alaska

USGS Publications Warehouse

Till, Alison B.; Dumoulin, Julie A.; Harris, Anita G.; Moore, Thomas E.; Bleick, Heather A.; Siwiec, Benjamin; Labay, Keith A.; Wilson, Frederic H.; Shew, Nora B.

2008-01-01

The growth in the use of Geographic Information Systems (GIS) has highlighted the need for digital geologic maps that have been attributed with information about age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. This report is part of a series of integrated geologic map databases that cover the entire United States. Three national-scale geologic maps that portray most or all of the United States already exist; for the conterminous U.S., King and Beikman (1974a,b) compiled a map at a scale of 1:2,500,000, Beikman (1980) compiled a map for Alaska at 1:2,500,000 scale, and for the entire U.S., Reed and others (2005a,b) compiled a map at a scale of 1:5,000,000. A digital version of the King and Beikman map was published by Schruben and others (1994). Reed and Bush (2004) produced a digital version of the Reed and others (2005a) map for the conterminous U.S. The present series of maps is intended to provide the next step in increased detail. State geologic maps that range in scale from 1:100,000 to 1:1,000,000 are available for most of the country, and digital versions of these state maps are the basis of this product. The digital geologic maps presented here are in a standardized format as ARC/INFO export files and as ArcView shape files. The files named __geol contain geologic polygons and line (contact) attributes; files named __fold contain fold axes; files named __lin contain lineaments; and files named __dike contain dikes as lines. Data tables that relate the map units to detailed lithologic and age information accompany these GIS files. The map is delivered as a set 1:250,000-scale quadrangle files. To the best of our ability, these quadrangle files are edge-matched with respect to geology. When the maps are merged, the combined attribute tables can be used directly with the merged maps to make derivative maps.

Algebraic and geometric structures of analytic partial differential equations

NASA Astrophysics Data System (ADS)

Kaptsov, O. V.

2016-11-01

We study the problem of the compatibility of nonlinear partial differential equations. We introduce the algebra of convergent power series, the module of derivations of this algebra, and the module of Pfaffian forms. Systems of differential equations are given by power series in the space of infinite jets. We develop a technique for studying the compatibility of differential systems analogous to the Gröbner bases. Using certain assumptions, we prove that compatible systems generate infinite manifolds.

Application of Tube Dynamics to Non-Statistical Reaction Processes

NASA Astrophysics Data System (ADS)

Gabern, F.; Koon, W. S.; Marsden, J. E.; Ross, S. D.; Yanao, T.

2006-06-01

A technique based on dynamical systems theory is introduced for the computation of lifetime distributions and rates of chemical reactions and scattering phenomena, even in systems that exhibit non-statistical behavior. In particular, we merge invariant manifold tube dynamics with Monte Carlo volume determination for accurate rate calculations. This methodology is applied to a three-degree-of-freedom model problem and some ideas on how it might be extended to higher-degree-of-freedom systems are presented.

The Shock and Vibration Digest. Volume 12, Number 6,

DTIC Science & Technology

1980-06-01

I 20 .. I%25 1.4~ iu±.6 MICROCOPY RESOLUTION TESI CHARI 1 AIIONAL BURtAU Ua SIANDARDS I63 4 i’U 00 SVIC NOTES The weight saving advantages of...34Theoretical and Manifolds by Using Lumped Parameter De - Experimental Investigation of Valve Movement scriptions," J. Sound Vib., 64 (3), pp 387-402 and...COMPUTATIONAL TECHNIQUES work for the textbook through definitions and de - FOR INTERFACE PROBLEMS scriptions of dynamic systems, modeling procedures

Computer calculation of Witten's 3-manifold invariant

NASA Astrophysics Data System (ADS)

Freed, Daniel S.; Gompf, Robert E.

1991-10-01

Witten's 2+1 dimensional Chern-Simons theory is exactly solvable. We compute the partition function, a topological invariant of 3-manifolds, on generalized Seifert spaces. Thus we test the path integral using the theory of 3-manifolds. In particular, we compare the exact solution with the asymptotic formula predicted by perturbation theory. We conclude that this path integral works as advertised and gives an effective topological invariant.

Manifold Learning for 3D Shape Description and Classification

DTIC Science & Technology

2014-06-09

sportswear, personal protection clothing and equipment, office and health care device, etc. Therefore it is desirable to develop an effective shape...Modeling Figure 2: Toy example for submanifold decomposition. (a) The original data on the top are fused by two uncorrelated manifolds, blue and red... developed which is effective to extract two linear submanifolds. We demonstrated that comparing with existing manifold learning methods that only

Singularities and non-hyperbolic manifolds do not coincide

NASA Astrophysics Data System (ADS)

Simányi, Nándor

2013-06-01

We consider the billiard flow of elastically colliding hard balls on the flat ν-torus (ν ⩾ 2), and prove that no singularity manifold can even locally coincide with a manifold describing future non-hyperbolicity of the trajectories. As a corollary, we obtain the ergodicity (actually the Bernoulli mixing property) of all such systems, i.e. the verification of the Boltzmann-Sinai ergodic hypothesis.

The relative isoperimetric inequality on a conformally parabolic manifold with boundary

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kesel'man, Vladimir M

2011-07-31

For an arbitrary noncompact n-dimensional Riemannian manifold with a boundary of conformally parabolic type it is proved that there exists a conformal change of metric such that a relative isoperimetric inequality of the same form as in the closed n-dimensional Euclidean half-space holds on the manifold with the new metric. This isoperimetric inequality is asymptotically sharp. Bibliography: 6 titles.

Orbifold genera, product formulas and power operations

NASA Astrophysics Data System (ADS)

Ganter, Nora

2004-07-01

We generalize the definition of orbifold elliptic genus, and introduce orbifold genera of chromatic level h, using h-tuples rather than pairs of commuting elements. We show that our genera are in fact orbifold invariants, and we prove integrality results for them. If the genus arises from an H-infinity-map into the Morava-Lubin-Tate theory E_h, then we give a formula expressing the orbifold genus of the symmetric powers of a stably almost complex manifold M in terms of the genus of M itself. Our formula is the p-typical analogue of the Dijkgraaf-Moore-Verlinde-Verlinde formula for the orbifold elliptic genus. It depends only on h and not on the genus.

Parity and cobordism of free knots

DOE Office of Scientific and Technical Information (OSTI.GOV)

Manturov, Vassily O

2012-02-28

A simple invariant is constructed which obstructs a free knot to be truncated. In particular, this invariant provides an obstruction to the truncatedness of curves immersed in two-dimensional surfaces. A curve on an oriented two-dimensional surface S{sub g} is referred to as truncated (null-cobordant) if there exists a three-dimensional manifold M with boundary S{sub g} and a smooth proper map of a two-disc to M such that the image of the boundary of the disc coincides with the curve. The problem of truncatedness for free knots is solved in this paper using the notion of parity recently introduced by themore » author. Bibliography: 12 titles.« less

Bifurcation Analysis and Application for Impulsive Systems with Delayed Impulses

NASA Astrophysics Data System (ADS)

Church, Kevin E. M.; Liu, Xinzhi

In this article, we present a systematic approach to bifurcation analysis of impulsive systems with autonomous or periodic right-hand sides that may exhibit delayed impulse terms. Methods include Lyapunov-Schmidt reduction and center manifold reduction. Both methods are presented abstractly in the context of the stroboscopic map associated to a given impulsive system, and are illustrated by way of two in-depth examples: the analysis of a SIR model of disease transmission with seasonality and unevenly distributed moments of treatment, and a scalar logistic differential equation with a delayed census impulsive harvesting effort. It is proven that in some special cases, the logistic equation can exhibit a codimension two bifurcation at a 1:1 resonance point.

Aplanatic Two-Surface Systems: The Optics Of Our Grandfathers

NASA Astrophysics Data System (ADS)

Krautter, Martin

1986-10-01

Karl Schwarzschild (1873 - 1916)1 has set up the 2-mirror systems as a 2-parameter mani-fold. He constructed them for primary aplanatism with conic section surfaces, and for finite aplanatism with numerically determined surfaces of revolution. Developing from the still older 2-paraboloid telescopes, conceived by Marin Mersenne, the systems since designed fill three domains of existence. The grazing incidence systems too (the Wolter-Schwarz-schild systems) have their loci on this map. Martin Linnemann (born 1880), student of Karl Schwarzschild, designed the first lenses, made aplanatic with two general surfaces of revolution2. For later authors remained only to vary image scale to non-zero values, and to adapt the design method to computer use.

Scientific data interpolation with low dimensional manifold model

DOE PAGES

Zhu, Wei; Wang, Bao; Barnard, Richard C.; ...

2017-09-28

Here, we propose to apply a low dimensional manifold model to scientific data interpolation from regular and irregular samplings with a significant amount of missing information. The low dimensionality of the patch manifold for general scientific data sets has been used as a regularizer in a variational formulation. The problem is solved via alternating minimization with respect to the manifold and the data set, and the Laplace–Beltrami operator in the Euler–Lagrange equation is discretized using the weighted graph Laplacian. Various scientific data sets from different fields of study are used to illustrate the performance of the proposed algorithm on datamore » compression and interpolation from both regular and irregular samplings.« less

Center manifolds for a class of degenerate evolution equations and existence of small-amplitude kinetic shocks

NASA Astrophysics Data System (ADS)

Pogan, Alin; Zumbrun, Kevin

2018-06-01

We construct center manifolds for a class of degenerate evolution equations including the steady Boltzmann equation and related kinetic models, establishing in the process existence and behavior of small-amplitude kinetic shock and boundary layers. Notably, for Boltzmann's equation, we show that elements of the center manifold decay in velocity at near-Maxwellian rate, in accord with the formal Chapman-Enskog picture of near-equilibrium flow as evolution along the manifold of Maxwellian states, or Grad moment approximation via Hermite polynomials in velocity. Our analysis is from a classical dynamical systems point of view, with a number of interesting modifications to accommodate ill-posedness of the underlying evolution equation.

Numerical Manifold Method for the Forced Vibration of Thin Plates during Bending

PubMed Central

Jun, Ding; Song, Chen; Wei-Bin, Wen; Shao-Ming, Luo; Xia, Huang

2014-01-01

A novel numerical manifold method was derived from the cubic B-spline basis function. The new interpolation function is characterized by high-order coordination at the boundary of a manifold element. The linear elastic-dynamic equation used to solve the bending vibration of thin plates was derived according to the principle of minimum instantaneous potential energy. The method for the initialization of the dynamic equation and its solution process were provided. Moreover, the analysis showed that the calculated stiffness matrix exhibited favorable performance. Numerical results showed that the generalized degrees of freedom were significantly fewer and that the calculation accuracy was higher for the manifold method than for the conventional finite element method. PMID:24883403

Slow Invariant Manifolds in Chemically Reactive Systems

NASA Astrophysics Data System (ADS)

Paolucci, Samuel; Powers, Joseph M.

2006-11-01

The scientific design of practical gas phase combustion devices has come to rely on the use of mathematical models which include detailed chemical kinetics. Such models intrinsically admit a wide range of scales which renders their accurate numerical approximation difficult. Over the past decade, rational strategies, such as Intrinsic Low Dimensional Manifolds (ILDM) or Computational Singular Perturbations (CSP), for equilibrating fast time scale events have been successfully developed, though their computation can be challenging and their accuracy in most cases uncertain. Both are approximations to the preferable slow invariant manifold which best describes how the system evolves in the long time limit. Strategies for computing the slow invariant manifold are examined, and results are presented for practical combustion systems.

Scientific data interpolation with low dimensional manifold model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Wei; Wang, Bao; Barnard, Richard C.

Here, we propose to apply a low dimensional manifold model to scientific data interpolation from regular and irregular samplings with a significant amount of missing information. The low dimensionality of the patch manifold for general scientific data sets has been used as a regularizer in a variational formulation. The problem is solved via alternating minimization with respect to the manifold and the data set, and the Laplace–Beltrami operator in the Euler–Lagrange equation is discretized using the weighted graph Laplacian. Various scientific data sets from different fields of study are used to illustrate the performance of the proposed algorithm on datamore » compression and interpolation from both regular and irregular samplings.« less

Unimodularity criteria for Poisson structures on foliated manifolds

NASA Astrophysics Data System (ADS)

Pedroza, Andrés; Velasco-Barreras, Eduardo; Vorobiev, Yury

2018-03-01

We study the behavior of the modular class of an orientable Poisson manifold and formulate some unimodularity criteria in the semilocal context, around a (singular) symplectic leaf. Our results generalize some known unimodularity criteria for regular Poisson manifolds related to the notion of the Reeb class. In particular, we show that the unimodularity of the transverse Poisson structure of the leaf is a necessary condition for the semilocal unimodular property. Our main tool is an explicit formula for a bigraded decomposition of modular vector fields of a coupling Poisson structure on a foliated manifold. Moreover, we also exploit the notion of the modular class of a Poisson foliation and its relationship with the Reeb class.

Evolution and polymorphism in the multilocus Levene model with no or weak epistasis.

PubMed

Bürger, Reinhard

2010-09-01

Evolution and the maintenance of polymorphism under the multilocus Levene model with soft selection are studied. The number of loci and alleles, the number of demes, the linkage map, and the degree of dominance are arbitrary, but epistasis is absent or weak. We prove that, without epistasis and under mild, generic conditions, every trajectory converges to a stationary point in linkage equilibrium. Consequently, the equilibrium and stability structure can be determined by investigating the much simpler gene-frequency dynamics on the linkage-equilibrium manifold. For a haploid species an analogous result is shown. For weak epistasis, global convergence to quasi-linkage equilibrium is established. As an application, the maintenance of multilocus polymorphism is explored if the degree of dominance is intermediate at every locus and epistasis is absent or weak. If there are at least two demes, then arbitrarily many multiallelic loci can be maintained polymorphic at a globally asymptotically stable equilibrium. Because this holds for an open set of parameters, such equilibria are structurally stable. If the degree of dominance is not only intermediate but also deme independent, and loci are diallelic, an open set of parameters yielding an internal equilibrium exists only if the number of loci is strictly less than the number of demes. Otherwise, a fully polymorphic equilibrium exists only nongenerically, and if it exists, it consists of a manifold of equilibria. Its dimension is determined. In the absence of genotype-by-environment interaction, however, a manifold of equilibria occurs for an open set of parameters. In this case, the equilibrium structure is not robust to small deviations from no genotype-by-environment interaction. In a quantitative-genetic setting, the assumptions of no epistasis and intermediate dominance are equivalent to assuming that in every deme directional selection acts on a trait that is determined additively, i.e., by nonepistatic loci with dominance. Some of our results are exemplified in this quantitative-genetic context. Copyright 2010 Elsevier Inc. All rights reserved.

Towards representation of a perceptual color manifold using associative memory for color constancy.

PubMed

Seow, Ming-Jung; Asari, Vijayan K

2009-01-01

In this paper, we propose the concept of a manifold of color perception through empirical observation that the center-surround properties of images in a perceptually similar environment define a manifold in the high dimensional space. Such a manifold representation can be learned using a novel recurrent neural network based learning algorithm. Unlike the conventional recurrent neural network model in which the memory is stored in an attractive fixed point at discrete locations in the state space, the dynamics of the proposed learning algorithm represent memory as a nonlinear line of attraction. The region of convergence around the nonlinear line is defined by the statistical characteristics of the training data. This learned manifold can then be used as a basis for color correction of the images having different color perception to the learned color perception. Experimental results show that the proposed recurrent neural network learning algorithm is capable of color balance the lighting variations in images captured in different environments successfully.

Methodology for CFD Design Analysis of National Launch System Nozzle Manifold

NASA Technical Reports Server (NTRS)

Haire, Scot L.

1993-01-01

The current design environment dictates that high technology CFD (Computational Fluid Dynamics) analysis produce quality results in a timely manner if it is to be integrated into the design process. The design methodology outlined describes the CFD analysis of an NLS (National Launch System) nozzle film cooling manifold. The objective of the analysis was to obtain a qualitative estimate for the flow distribution within the manifold. A complex, 3D, multiple zone, structured grid was generated from a 3D CAD file of the geometry. A Euler solution was computed with a fully implicit compressible flow solver. Post processing consisted of full 3D color graphics and mass averaged performance. The result was a qualitative CFD solution that provided the design team with relevant information concerning the flow distribution in and performance characteristics of the film cooling manifold within an effective time frame. Also, this design methodology was the foundation for a quick turnaround CFD analysis of the next iteration in the manifold design.

Topological invariants and fibration structure of complete intersection Calabi-Yau four-folds

NASA Astrophysics Data System (ADS)

Gray, James; Haupt, Alexander S.; Lukas, Andre

2014-09-01

We investigate the mathematical properties of the class of Calabi-Yau four-folds recently found in ref. [1]. This class consists of 921,497 configuration matrices which correspond to manifolds that are described as complete intersections in products of projective spaces. For each manifold in the list, we compute the full Hodge diamond as well as additional topological invariants such as Chern classes and intersection numbers. Using this data, we conclude that there are at least 36,779 topologically distinct manifolds in our list. We also study the fibration structure of these manifolds and find that 99.95 percent can be described as elliptic fibrations. In total, we find 50,114,908 elliptic fibrations, demonstrating the multitude of ways in which many manifolds are fibered. A sub-class of 26,088,498 fibrations satisfy necessary conditions for admitting sections. The complete data set can be downloaded from http://www-thphys.physics.ox.ac.uk/projects/CalabiYau/Cicy4folds/index.html.

Narrow groove welding gas diffuser assembly and welding torch

DOEpatents

Rooney, Stephen J.

2001-01-01

A diffuser assembly is provided for narrow groove welding using an automatic gas tungsten arc welding torch. The diffuser assembly includes a manifold adapted for adjustable mounting on the welding torch which is received in a central opening in the manifold. Laterally extending manifold sections communicate with a shield gas inlet such that shield gas supplied to the inlet passes to gas passages of the manifold sections. First and second tapered diffusers are respectively connected to the manifold sections in fluid communication with the gas passages thereof. The diffusers extend downwardly along the torch electrode on opposite sides thereof so as to release shield gas along the length of the electrode and at the distal tip of the electrode. The diffusers are of a transverse width which is on the order of the thickness of the electrode so that the diffusers can, in use, be inserted into a narrow welding groove before and after the electrode in the direction of the weld operation.

Steam cooling system for a gas turbine

DOEpatents

Wilson, Ian David; Barb, Kevin Joseph; Li, Ming Cheng; Hyde, Susan Marie; Mashey, Thomas Charles; Wesorick, Ronald Richard; Glynn, Christopher Charles; Hemsworth, Martin C.

2002-01-01

The steam cooling circuit for a gas turbine includes a bore tube assembly supplying steam to circumferentially spaced radial tubes coupled to supply elbows for transitioning the radial steam flow in an axial direction along steam supply tubes adjacent the rim of the rotor. The supply tubes supply steam to circumferentially spaced manifold segments located on the aft side of the 1-2 spacer for supplying steam to the buckets of the first and second stages. Spent return steam from these buckets flows to a plurality of circumferentially spaced return manifold segments disposed on the forward face of the 1-2 spacer. Crossover tubes couple the steam supply from the steam supply manifold segments through the 1-2 spacer to the buckets of the first stage. Crossover tubes through the 1-2 spacer also return steam from the buckets of the second stage to the return manifold segments. Axially extending return tubes convey spent cooling steam from the return manifold segments to radial tubes via return elbows.

Corners in M-theory

NASA Astrophysics Data System (ADS)

Sati, Hisham

2011-06-01

M-theory can be defined on closed manifolds as well as on manifolds with boundary. As an extension, we show that manifolds with corners appear naturally in M-theory. We illustrate this with four situations: the lift to bounding 12 dimensions of M-theory on anti-de Sitter spaces, ten-dimensional heterotic string theory in relation to 12 dimensions, and the two M-branes within M-theory in the presence of a boundary. The M2-brane is taken with (or as) a boundary and the worldvolume of the M5-brane is viewed as a tubular neighborhood. We then concentrate on the (variant) of the heterotic theory as a corner and explore analytical and geometric consequences. In particular, we formulate and study the phase of the partition function in this setting and identify the corrections due to the corner(s). The analysis involves considering M-theory on disconnected manifolds and makes use of the extension of the Atiyah-Patodi-Singer index theorem to manifolds with corners and the b-calculus of Melrose.

Integral manifolding structure for fuel cell core having parallel gas flow

DOEpatents

Herceg, Joseph E.

1984-01-01

Disclosed herein are manifolding means for directing the fuel and oxidant gases to parallel flow passageways in a fuel cell core. Each core passageway is defined by electrolyte and interconnect walls. Each electrolyte and interconnect wall consists respectively of anode and cathode materials layered on the opposite sides of electrolyte material, or on the opposite sides of interconnect material. A core wall projects beyond the open ends of the defined core passageways and is disposed approximately midway between and parallel to the adjacent overlaying and underlying interconnect walls to define manifold chambers therebetween on opposite sides of the wall. Each electrolyte wall defining the flow passageways is shaped to blend into and be connected to this wall in order to redirect the corresponding fuel and oxidant passageways to the respective manifold chambers either above or below this intermediate wall. Inlet and outlet connections are made to these separate manifold chambers respectively, for carrying the fuel and oxidant gases to the core, and for carrying their reaction products away from the core.

Integral manifolding structure for fuel cell core having parallel gas flow

DOEpatents

Herceg, J.E.

1983-10-12

Disclosed herein are manifolding means for directing the fuel and oxidant gases to parallel flow passageways in a fuel cell core. Each core passageway is defined by electrolyte and interconnect walls. Each electrolyte and interconnect wall consists respectively of anode and cathode materials layered on the opposite sides of electrolyte material, or on the opposite sides of interconnect material. A core wall projects beyond the open ends of the defined core passageways and is disposed approximately midway between and parallel to the adjacent overlaying and underlying interconnect walls to define manifold chambers therebetween on opposite sides of the wall. Each electrolyte wall defining the flow passageways is shaped to blend into and be connected to this wall in order to redirect the corresponding fuel and oxidant passageways to the respective manifold chambers either above or below this intermediate wall. Inlet and outlet connections are made to these separate manifold chambers respectively, for carrying the fuel and oxidant gases to the core, and for carrying their reaction products away from the core.

Minimal measures for Euler-Lagrange flows on finite covering spaces

NASA Astrophysics Data System (ADS)

Wang, Fang; Xia, Zhihong

2016-12-01

In this paper we study the minimal measures for positive definite Lagrangian systems on compact manifolds. We are particularly interested in manifolds with more complicated fundamental groups. Mather’s theory classifies the minimal or action-minimizing measures according to the first (co-)homology group of a given manifold. We extend Mather’s notion of minimal measures to a larger class for compact manifolds with non-commutative fundamental groups, and use finite coverings to study the structure of these extended minimal measures. We also define action-minimizers and minimal measures in the homotopical sense. Our program is to study the structure of homotopical minimal measures by considering Mather’s minimal measures on finite covering spaces. Our goal is to show that, in general, manifolds with a non-commutative fundamental group have a richer set of minimal measures, hence a richer dynamical structure. As an example, we study the geodesic flow on surfaces of higher genus. Indeed, by going to the finite covering spaces, the set of minimal measures is much larger and more interesting.

Steiner minimal trees in small neighbourhoods of points in Riemannian manifolds

NASA Astrophysics Data System (ADS)

Chikin, V. M.

2017-07-01

In contrast to the Euclidean case, almost no Steiner minimal trees with concrete boundaries on Riemannian manifolds are known. A result describing the types of Steiner minimal trees on a Riemannian manifold for arbitrary small boundaries is obtained. As a consequence, it is shown that for sufficiently small regular n-gons with n≥ 7 their boundaries without a longest side are Steiner minimal trees. Bibliography: 22 titles.

Solid state optical refrigeration using stark manifold resonances in crystals

DOEpatents

Seletskiy, Denis V.; Epstein, Richard; Hehlen, Markus P.; Sheik-Bahae, Mansoor

2017-02-21

A method and device for cooling electronics is disclosed. The device includes a doped crystal configured to resonate at a Stark manifold resonance capable of cooling the crystal to a temperature of from about 110K to about 170K. The crystal host resonates in response to input from an excitation laser tuned to exploit the Stark manifold resonance corresponding to the cooling of the crystal.

Environmental continuous air monitor inlet with combined preseparator and virtual impactor

DOEpatents

Rodgers, John C [Santa Fe, NM

2007-06-19

An inlet for an environmental air monitor is described wherein a pre-separator interfaces with ambient environment air and removes debris and insects commonly associated with high wind outdoors and a deflector plate in communication with incoming air from the pre-separator stage, that directs the air radially and downward uniformly into a plurality of accelerator jets located in a manifold of a virtual impactor, the manifold being cylindrical and having a top, a base, and a wall, with the plurality of accelerator jets being located in the top of the manifold and receiving the directed air and accelerating directed air, thereby creating jets of air penetrating into the manifold, where a major flow is deflected to the walls of the manifold and extracted through ports in the walls. A plurality of receiver nozzles are located in the base of the manifold coaxial with the accelerator jets, and a plurality of matching flow restrictor elements are located in the plurality of receiver nozzles for balancing and equalizing the total minor flow among all the plurality of receiver nozzles, through which a lower, fractional flow extracts large particle constituents of the air for collection on a sample filter after passing through the plurality of receiver nozzles and the plurality of matching flow restrictor elements.

Fedosov Deformation Quantization as a BRST Theory

NASA Astrophysics Data System (ADS)

Grigoriev, M. A.; Lyakhovich, S. L.

The relationship is established between the Fedosov deformation quantization of a general symplectic manifold and the BFV-BRST quantization of constrained dynamical systems. The original symplectic manifold M is presented as a second class constrained surface in the fibre bundle ?*ρM which is a certain modification of a usual cotangent bundle equipped with a natural symplectic structure. The second class system is converted into the first class one by continuation of the constraints into the extended manifold, being a direct sum of ?*ρM and the tangent bundle TM. This extended manifold is equipped with a nontrivial Poisson bracket which naturally involves two basic ingredients of Fedosov geometry: the symplectic structure and the symplectic connection. The constructed first class constrained theory, being equivalent to the original symplectic manifold, is quantized through the BFV-BRST procedure. The existence theorem is proven for the quantum BRST charge and the quantum BRST invariant observables. The adjoint action of the quantum BRST charge is identified with the Abelian Fedosov connection while any observable, being proven to be a unique BRST invariant continuation for the values defined in the original symplectic manifold, is identified with the Fedosov flat section of the Weyl bundle. The Fedosov fibrewise star multiplication is thus recognized as a conventional product of the quantum BRST invariant observables.

Nonlinear dynamic model for visual object tracking on Grassmann manifolds with partial occlusion handling.

PubMed

Khan, Zulfiqar Hasan; Gu, Irene Yu-Hua

2013-12-01

This paper proposes a novel Bayesian online learning and tracking scheme for video objects on Grassmann manifolds. Although manifold visual object tracking is promising, large and fast nonplanar (or out-of-plane) pose changes and long-term partial occlusions of deformable objects in video remain a challenge that limits the tracking performance. The proposed method tackles these problems with the main novelties on: 1) online estimation of object appearances on Grassmann manifolds; 2) optimal criterion-based occlusion handling for online updating of object appearances; 3) a nonlinear dynamic model for both the appearance basis matrix and its velocity; and 4) Bayesian formulations, separately for the tracking process and the online learning process, that are realized by employing two particle filters: one is on the manifold for generating appearance particles and another on the linear space for generating affine box particles. Tracking and online updating are performed in an alternating fashion to mitigate the tracking drift. Experiments using the proposed tracker on videos captured by a single dynamic/static camera have shown robust tracking performance, particularly for scenarios when target objects contain significant nonplanar pose changes and long-term partial occlusions. Comparisons with eight existing state-of-the-art/most relevant manifold/nonmanifold trackers with evaluations have provided further support to the proposed scheme.

Investigation of the Behavior of Fuel in the Intake Manifold and its Relation to S. I. Engines, 1980-1983

NASA Astrophysics Data System (ADS)

Servati, Hamid Beyragh

A liquid fuel film formation on the walls of an intake manifold adversely affects the engine performance and alters the overall air/fuel ratio from that scheduled by a fuel injector or carburetor and leads to adverse effects in vehicle driveability, exhaust emissions, and fuel economy. In this dissertation, the intake manifold is simulated by a horizontal circular duct. A model is provided to predict the rate of deposition and evaporation of the droplets in the intake manifold. The liquid fuel flow rate into the cylinders, mean film velocity and film thickness are determined as functions of engine parameters for both steady and transient operating conditions of the engine. A mathematical engine model is presented to simulate the dynamic interactions of the various engine components such as the air/fuel inlet element, intake manifold, combustion, dynamics and exhaust emissions. Inputs of the engine model are the intake manifold pressure and temperature, throttle angle, and air/fuel ratio. The observed parameters are the histories of fuel film thickness and velocity, fuel consumption, engine speed, engine speed hesitation time, and histories of CO, CO(,2), NO(,x), CH(,n), and O(,2). The effects of different air/fuel ratio control strategies on engine performance and observed parameters are also shown.

Liver DCE-MRI Registration in Manifold Space Based on Robust Principal Component Analysis.

PubMed

Feng, Qianjin; Zhou, Yujia; Li, Xueli; Mei, Yingjie; Lu, Zhentai; Zhang, Yu; Feng, Yanqiu; Liu, Yaqin; Yang, Wei; Chen, Wufan

2016-09-29

A technical challenge in the registration of dynamic contrast-enhanced magnetic resonance (DCE-MR) imaging in the liver is intensity variations caused by contrast agents. Such variations lead to the failure of the traditional intensity-based registration method. To address this problem, a manifold-based registration framework for liver DCE-MR time series is proposed. We assume that liver DCE-MR time series are located on a low-dimensional manifold and determine intrinsic similarities between frames. Based on the obtained manifold, the large deformation of two dissimilar images can be decomposed into a series of small deformations between adjacent images on the manifold through gradual deformation of each frame to the template image along the geodesic path. Furthermore, manifold construction is important in automating the selection of the template image, which is an approximation of the geodesic mean. Robust principal component analysis is performed to separate motion components from intensity changes induced by contrast agents; the components caused by motion are used to guide registration in eliminating the effect of contrast enhancement. Visual inspection and quantitative assessment are further performed on clinical dataset registration. Experiments show that the proposed method effectively reduces movements while preserving the topology of contrast-enhancing structures and provides improved registration performance.

Control of Soft Machines using Actuators Operated by a Braille Display

PubMed Central

Mosadegh, Bobak; Mazzeo, Aaron D.; Shepherd, Robert F.; Morin, Stephen A.; Gupta, Unmukt; Sani, Idin Zhalehdoust; Lai, David; Takayama, Shuichi; Whitesides, George M.

2013-01-01

One strategy for actuating soft machines (e.g., tentacles, grippers, and simple walkers) uses pneumatic inflation of networks of small channels in an elastomeric material. Although the management of a few pneumatic inputs and valves to control pressurized gas is straightforward, the fabrication and operation of manifolds containing many (>50) independent valves is an unsolved problem. Complex pneumatic manifolds—often built for a single purpose—are not easily reconfigured to accommodate the specific inputs (i.e., multiplexing of many fluids, ranges of pressures, and changes in flow rates) required by pneumatic systems. This paper describes a pneumatic manifold comprising a computer-controlled braille display and a micropneumatic device. The braille display provides a compact array of 64 piezoelectric actuators that actively close and open elastomeric valves of a micropneumatic device to route pressurized gas within the manifold. The positioning and geometries of the valves and channels in the micropneumatic device dictate the functionality of the pneumatic manifold, and the use of multi-layer soft lithography permits the fabrication of networks in a wide range of configurations with many possible functions. Simply exchanging micropneumatic devices of different designs enables rapid reconfiguration of the pneumatic manifold. As a proof of principle, a pneumatic manifold controlled a soft machine containing 32 independent actuators to move a ball above a flat surface. PMID:24196070

On the Ck-embedding of Lorentzian manifolds in Ricci-flat spaces

NASA Astrophysics Data System (ADS)

Avalos, R.; Dahia, F.; Romero, C.

2018-05-01

In this paper, we investigate the problem of non-analytic embeddings of Lorentzian manifolds in Ricci-flat semi-Riemannian spaces. In order to do this, we first review some relevant results in the area and then motivate both the mathematical and physical interests in this problem. We show that any n-dimensional compact Lorentzian manifold (Mn, g), with g in the Sobolev space Hs+3, s >n/2 , admits an isometric embedding in a (2n + 2)-dimensional Ricci-flat semi-Riemannian manifold. The sharpest result available for these types of embeddings, in the general setting, comes as a corollary of Greene's remarkable embedding theorems R. Greene [Mem. Am. Math. Soc. 97, 1 (1970)], which guarantee the embedding of a compact n-dimensional semi-Riemannian manifold into an n(n + 5)-dimensional semi-Euclidean space, thereby guaranteeing the embedding into a Ricci-flat space with the same dimension. The theorem presented here improves this corollary in n2 + 3n - 2 codimensions by replacing the Riemann-flat condition with the Ricci-flat one from the beginning. Finally, we will present a corollary of this theorem, which shows that a compact strip in an n-dimensional globally hyperbolic space-time can be embedded in a (2n + 2)-dimensional Ricci-flat semi-Riemannian manifold.

Parts-based stereoscopic image assessment by learning binocular manifold color visual properties

NASA Astrophysics Data System (ADS)

Xu, Haiyong; Yu, Mei; Luo, Ting; Zhang, Yun; Jiang, Gangyi

2016-11-01

Existing stereoscopic image quality assessment (SIQA) methods are mostly based on the luminance information, in which color information is not sufficiently considered. Actually, color is part of the important factors that affect human visual perception, and nonnegative matrix factorization (NMF) and manifold learning are in line with human visual perception. We propose an SIQA method based on learning binocular manifold color visual properties. To be more specific, in the training phase, a feature detector is created based on NMF with manifold regularization by considering color information, which not only allows parts-based manifold representation of an image, but also manifests localized color visual properties. In the quality estimation phase, visually important regions are selected by considering different human visual attention, and feature vectors are extracted by using the feature detector. Then the feature similarity index is calculated and the parts-based manifold color feature energy (PMCFE) for each view is defined based on the color feature vectors. The final quality score is obtained by considering a binocular combination based on PMCFE. The experimental results on LIVE I and LIVE Π 3-D IQA databases demonstrate that the proposed method can achieve much higher consistency with subjective evaluations than the state-of-the-art SIQA methods.

The efficacy of the 'mind map' study technique.

PubMed

Farrand, Paul; Hussain, Fearzana; Hennessy, Enid

2002-05-01

To examine the effectiveness of using the 'mind map' study technique to improve factual recall from written information. To obtain baseline data, subjects completed a short test based on a 600-word passage of text prior to being randomly allocated to form two groups: 'self-selected study technique' and 'mind map'. After a 30-minute interval the self-selected study technique group were exposed to the same passage of text previously seen and told to apply existing study techniques. Subjects in the mind map group were trained in the mind map technique and told to apply it to the passage of text. Recall was measured after an interfering task and a week later. Measures of motivation were taken. Barts and the London School of Medicine and Dentistry, University of London. 50 second- and third-year medical students. Recall of factual material improved for both the mind map and self-selected study technique groups at immediate test compared with baseline. However this improvement was only robust after a week for those in the mind map group. At 1 week, the factual knowledge in the mind map group was greater by 10% (adjusting for baseline) (95% CI -1% to 22%). However motivation for the technique used was lower in the mind map group; if motivation could have been made equal in the groups, the improvement with mind mapping would have been 15% (95% CI 3% to 27%). Mind maps provide an effective study technique when applied to written material. However before mind maps are generally adopted as a study technique, consideration has to be given towards ways of improving motivation amongst users.

A novel approach for fire recognition using hybrid features and manifold learning-based classifier

NASA Astrophysics Data System (ADS)

Zhu, Rong; Hu, Xueying; Tang, Jiajun; Hu, Sheng

2018-03-01

Although image/video based fire recognition has received growing attention, an efficient and robust fire detection strategy is rarely explored. In this paper, we propose a novel approach to automatically identify the flame or smoke regions in an image. It is composed to three stages: (1) a block processing is applied to divide an image into several nonoverlapping image blocks, and these image blocks are identified as suspicious fire regions or not by using two color models and a color histogram-based similarity matching method in the HSV color space, (2) considering that compared to other information, the flame and smoke regions have significant visual characteristics, so that two kinds of image features are extracted for fire recognition, where local features are obtained based on the Scale Invariant Feature Transform (SIFT) descriptor and the Bags of Keypoints (BOK) technique, and texture features are extracted based on the Gray Level Co-occurrence Matrices (GLCM) and the Wavelet-based Analysis (WA) methods, and (3) a manifold learning-based classifier is constructed based on two image manifolds, which is designed via an improve Globular Neighborhood Locally Linear Embedding (GNLLE) algorithm, and the extracted hybrid features are used as input feature vectors to train the classifier, which is used to make decision for fire images or non fire images. Experiments and comparative analyses with four approaches are conducted on the collected image sets. The results show that the proposed approach is superior to the other ones in detecting fire and achieving a high recognition accuracy and a low error rate.

Investigation of the Rock Fragmentation Process by a Single TBM Cutter Using a Voronoi Element-Based Numerical Manifold Method

NASA Astrophysics Data System (ADS)

Liu, Quansheng; Jiang, Yalong; Wu, Zhijun; Xu, Xiangyu; Liu, Qi

2018-04-01

In this study, a two-dimensional Voronoi element-based numerical manifold method (VE-NMM) is developed to analyze the granite fragmentation process by a single tunnel boring machine (TBM) cutter under different confining stresses. A Voronoi tessellation technique is adopted to generate the polygonal grain assemblage to approximate the microstructure of granite sample from the Gubei colliery of Huainan mining area in China. A modified interface contact model with cohesion and tensile strength is embedded into the numerical manifold method (NMM) to interpret the interactions between the rock grains. Numerical uniaxial compression and Brazilian splitting tests are first conducted to calibrate and validate the VE-NMM models based on the laboratory experiment results using a trial-and-error method. On this basis, numerical simulations of rock fragmentation by a single TBM cutter are conducted. The simulated crack initiation and propagation process as well as the indentation load-penetration depth behaviors in the numerical models accurately predict the laboratory indentation test results. The influence of confining stress on rock fragmentation is also investigated. Simulation results show that radial tensile cracks are more likely to be generated under a low confining stress, eventually coalescing into a major fracture along the loading axis. However, with the increase in confining stress, more side cracks initiate and coalesce, resulting in the formation of rock chips at the upper surface of the model. In addition, the peak indentation load also increases with the increasing confining stress, indicating that a higher thrust force is usually needed during the TBM boring process in deep tunnels.

Extending topological surgery to natural processes and dynamical systems.

PubMed

Antoniou, Stathis; Lambropoulou, Sofia

2017-01-01

Topological surgery is a mathematical technique used for creating new manifolds out of known ones. We observe that it occurs in natural phenomena where a sphere of dimension 0 or 1 is selected, forces are applied and the manifold in which they occur changes type. For example, 1-dimensional surgery happens during chromosomal crossover, DNA recombination and when cosmic magnetic lines reconnect, while 2-dimensional surgery happens in the formation of tornadoes, in the phenomenon of Falaco solitons, in drop coalescence and in the cell mitosis. Inspired by such phenomena, we introduce new theoretical concepts which enhance topological surgery with the observed forces and dynamics. To do this, we first extend the formal definition to a continuous process caused by local forces. Next, for modeling phenomena which do not happen on arcs or surfaces but are 2-dimensional or 3-dimensional, we fill in the interior space by defining the notion of solid topological surgery. We further introduce the notion of embedded surgery in S3 for modeling phenomena which involve more intrinsically the ambient space, such as the appearance of knotting in DNA and phenomena where the causes and effect of the process lies beyond the initial manifold, such as the formation of black holes. Finally, we connect these new theoretical concepts with a dynamical system and we present it as a model for both 2-dimensional 0-surgery and natural phenomena exhibiting a 'hole drilling' behavior. We hope that through this study, topology and dynamics of many natural phenomena, as well as topological surgery itself, will be better understood.

Extending topological surgery to natural processes and dynamical systems

PubMed Central

Antoniou, Stathis; Lambropoulou, Sofia

2017-01-01

Topological surgery is a mathematical technique used for creating new manifolds out of known ones. We observe that it occurs in natural phenomena where a sphere of dimension 0 or 1 is selected, forces are applied and the manifold in which they occur changes type. For example, 1-dimensional surgery happens during chromosomal crossover, DNA recombination and when cosmic magnetic lines reconnect, while 2-dimensional surgery happens in the formation of tornadoes, in the phenomenon of Falaco solitons, in drop coalescence and in the cell mitosis. Inspired by such phenomena, we introduce new theoretical concepts which enhance topological surgery with the observed forces and dynamics. To do this, we first extend the formal definition to a continuous process caused by local forces. Next, for modeling phenomena which do not happen on arcs or surfaces but are 2-dimensional or 3-dimensional, we fill in the interior space by defining the notion of solid topological surgery. We further introduce the notion of embedded surgery in S3 for modeling phenomena which involve more intrinsically the ambient space, such as the appearance of knotting in DNA and phenomena where the causes and effect of the process lies beyond the initial manifold, such as the formation of black holes. Finally, we connect these new theoretical concepts with a dynamical system and we present it as a model for both 2-dimensional 0-surgery and natural phenomena exhibiting a ‘hole drilling’ behavior. We hope that through this study, topology and dynamics of many natural phenomena, as well as topological surgery itself, will be better understood. PMID:28915271

Data-Driven Modeling of Complex Systems by means of a Dynamical ANN

NASA Astrophysics Data System (ADS)

Seleznev, A.; Mukhin, D.; Gavrilov, A.; Loskutov, E.; Feigin, A.

2017-12-01

The data-driven methods for modeling and prognosis of complex dynamical systems become more and more popular in various fields due to growth of high-resolution data. We distinguish the two basic steps in such an approach: (i) determining the phase subspace of the system, or embedding, from available time series and (ii) constructing an evolution operator acting in this reduced subspace. In this work we suggest a novel approach combining these two steps by means of construction of an artificial neural network (ANN) with special topology. The proposed ANN-based model, on the one hand, projects the data onto a low-dimensional manifold, and, on the other hand, models a dynamical system on this manifold. Actually, this is a recurrent multilayer ANN which has internal dynamics and capable of generating time series. Very important point of the proposed methodology is the optimization of the model allowing us to avoid overfitting: we use Bayesian criterion to optimize the ANN structure and estimate both the degree of evolution operator nonlinearity and the complexity of nonlinear manifold which the data are projected on. The proposed modeling technique will be applied to the analysis of high-dimensional dynamical systems: Lorenz'96 model of atmospheric turbulence, producing high-dimensional space-time chaos, and quasi-geostrophic three-layer model of the Earth's atmosphere with the natural orography, describing the dynamics of synoptical vortexes as well as mesoscale blocking systems. The possibility of application of the proposed methodology to analyze real measured data is also discussed. The study was supported by the Russian Science Foundation (grant #16-12-10198).

Neighboring extremal optimal control design including model mismatch errors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, T.J.; Hull, D.G.

1994-11-01

The mismatch control technique that is used to simplify model equations of motion in order to determine analytic optimal control laws is extended using neighboring extremal theory. The first variation optimal control equations are linearized about the extremal path to account for perturbations in the initial state and the final constraint manifold. A numerical example demonstrates that the tuning procedure inherent in the mismatch control method increases the performance of the controls to the level of a numerically-determined piecewise-linear controller.

Electronic Equipment Cold Plates

DTIC Science & Technology

1976-04-01

using fans or blowers to force the air through the cooling device». ^J^lJ^^i 5!°^ it ia ’«"^"o^ve. nonto«ic. nonfla—able, *nd possesses good ...Techniques GENERAL THERMAL CONTROL SYSTEMS AND THEIR REgUIREMENTS FLON DISTRIBUTION IN MANIFOLDS THE COLD PLATE IA ,! 1 3 S 12 15 33 32 32... IA .1 132 132 132 155 169 179 183 r (1) Air-Cooled Cold Plate No. (2) Air-Cooled Cold Plate No. (3) Air-cooled Cold Plate No. (4) Air-Cooled

Finite-time barriers to front propagation in two-dimensional fluid flows

NASA Astrophysics Data System (ADS)

Mahoney, John R.; Mitchell, Kevin A.

2015-08-01

Recent theoretical and experimental investigations have demonstrated the role of certain invariant manifolds, termed burning invariant manifolds (BIMs), as one-way dynamical barriers to reaction fronts propagating within a flowing fluid. These barriers form one-dimensional curves in a two-dimensional fluid flow. In prior studies, the fluid velocity field was required to be either time-independent or time-periodic. In the present study, we develop an approach to identify prominent one-way barriers based only on fluid velocity data over a finite time interval, which may have arbitrary time-dependence. We call such a barrier a burning Lagrangian coherent structure (bLCS) in analogy to Lagrangian coherent structures (LCSs) commonly used in passive advection. Our approach is based on the variational formulation of LCSs using curves of stationary "Lagrangian shear," introduced by Farazmand et al. [Physica D 278-279, 44 (2014)] in the context of passive advection. We numerically validate our technique by demonstrating that the bLCS closely tracks the BIM for a time-independent, double-vortex channel flow with an opposing "wind."

Discriminant analysis of resting-state functional connectivity patterns on the Grassmann manifold

NASA Astrophysics Data System (ADS)

Fan, Yong; Liu, Yong; Jiang, Tianzi; Liu, Zhening; Hao, Yihui; Liu, Haihong

2010-03-01

The functional networks, extracted from fMRI images using independent component analysis, have been demonstrated informative for distinguishing brain states of cognitive functions and neurological diseases. In this paper, we propose a novel algorithm for discriminant analysis of functional networks encoded by spatial independent components. The functional networks of each individual are used as bases for a linear subspace, referred to as a functional connectivity pattern, which facilitates a comprehensive characterization of temporal signals of fMRI data. The functional connectivity patterns of different individuals are analyzed on the Grassmann manifold by adopting a principal angle based subspace distance. In conjunction with a support vector machine classifier, a forward component selection technique is proposed to select independent components for constructing the most discriminative functional connectivity pattern. The discriminant analysis method has been applied to an fMRI based schizophrenia study with 31 schizophrenia patients and 31 healthy individuals. The experimental results demonstrate that the proposed method not only achieves a promising classification performance for distinguishing schizophrenia patients from healthy controls, but also identifies discriminative functional networks that are informative for schizophrenia diagnosis.

Low Energy Transfer to the Moon

NASA Astrophysics Data System (ADS)

Koon, W. S.; Lo, M. W.; Marsden, J. E.; Ross, S. D.

In 1991, the Japanese Hiten mission used a low energy transfer with a ballistic capture at the Moon which required less Δ V than a standard Hohmann transfer. In this paper, we apply the dynamical systems techniques developed in our earlier work to reproduce systematically a Hiten-like mission. We approximate the Sun-Earth-Moon-spacecraft 4-body system as two 3-body systems. Using the invariant manifold structures of the Lagrange points of the 3-body systems, we are able to construct low energy transfer trajectories from the Earth which execute ballistic capture at the Moon. The techniques used in the design and construction of this trajectory may be applied in many situations.

A lower bound on the solutions of Kapustin-Witten equations

NASA Astrophysics Data System (ADS)

Huang, Teng

2016-11-01

In this article, we consider the Kapustin-Witten equations on a closed four-manifold. We study certain analytic properties of solutions to the equations on a closed manifold. The main result is that there exists an L2 -lower bound on the extra fields over a closed four-manifold satisfying certain conditions if the connections are not ASD connections. Furthermore, we also obtain a similar result about the Vafa-Witten equations.

Dehumidifying Heat Pipe

NASA Technical Reports Server (NTRS)

Khattar, Mukesh K.

1993-01-01

U-shaped heat pipe partly dehumidifies air leaving air conditioner. Fits readily in air-handling unit of conditioner. Evaporator and condenser sections of heat pipe consist of finned tubes in comb pattern. Each tube sealed at one end and joined to manifold at other. Sections connected by single pipe carrying vapor to condenser manifold and liquid to evaporator manifold. Simple on/off or proportional valve used to control flow of working fluid. Valve actuated by temperature/humidity sensor.

Topology of codimension-one foliations of nonnegative curvature

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bolotov, Dmitry V

We show that a transversely oriented C{sup 2}-foliation of codimension one with nonnegative Ricci curvature on a closed orientable manifold is a foliation with almost no holonomy. This allows us to decompose the manifold into blocks on which this foliation has a simple structure. We also show that a manifold homeomorphic to a 5-dimensional sphere does not admit a codimension-one C{sup 2}-foliation with nonnegative sectional curvature. Bibliography: 29 titles.

Large N Limits in Tensor Models: Towards More Universality Classes of Colored Triangulations in Dimension d≥2

NASA Astrophysics Data System (ADS)

Bonzom, Valentin

2016-07-01

We review an approach which aims at studying discrete (pseudo-)manifolds in dimension d≥ 2 and called random tensor models. More specifically, we insist on generalizing the two-dimensional notion of p-angulations to higher dimensions. To do so, we consider families of triangulations built out of simplices with colored faces. Those simplices can be glued to form new building blocks, called bubbles which are pseudo-manifolds with boundaries. Bubbles can in turn be glued together to form triangulations. The main challenge is to classify the triangulations built from a given set of bubbles with respect to their numbers of bubbles and simplices of codimension two. While the colored triangulations which maximize the number of simplices of codimension two at fixed number of simplices are series-parallel objects called melonic triangulations, this is not always true anymore when restricting attention to colored triangulations built from specific bubbles. This opens up the possibility of new universality classes of colored triangulations. We present three existing strategies to find those universality classes. The first two strategies consist in building new bubbles from old ones for which the problem can be solved. The third strategy is a bijection between those colored triangulations and stuffed, edge-colored maps, which are some sort of hypermaps whose hyperedges are replaced with edge-colored maps. We then show that the present approach can lead to enumeration results and identification of universality classes, by working out the example of quartic tensor models. They feature a tree-like phase, a planar phase similar to two-dimensional quantum gravity and a phase transition between them which is interpreted as a proliferation of baby universes. While this work is written in the context of random tensors, it is almost exclusively of combinatorial nature and we hope it is accessible to interested readers who are not familiar with random matrices, tensors and quantum field theory.

Parameter-dependent behaviour of periodic channels in a locus of boundary crisis

NASA Astrophysics Data System (ADS)

Rankin, James; Osinga, Hinke M.

2017-06-01

A boundary crisis occurs when a chaotic attractor outgrows its basin of attraction and suddenly disappears. As previously reported, the locus of a boundary crisis is organised by homo- or heteroclinic tangencies between the stable and unstable manifolds of saddle periodic orbits. In two parameters, such tangencies lead to curves, but the locus of boundary crisis along those curves exhibits gaps or channels, in which other non-chaotic attractors persist. These attractors are stable periodic orbits which themselves can undergo a cascade of period-doubling bifurcations culminating in multi-component chaotic attractors. The canonical diffeomorphic two-dimensional Hénon map exhibits such periodic channels, which are structured in a particular ordered way: each channel is bounded on one side by a saddle-node bifurcation and on the other by a period-doubling cascade to chaos; furthermore, all channels seem to have the same orientation, with the saddle-node bifurcation always on the same side. We investigate the locus of boundary crisis in the Ikeda map, which models the dynamics of energy levels in a laser ring cavity. We find that the Ikeda map features periodic channels with a richer and more general organisation than for the Hénon map. Using numerical continuation, we investigate how the periodic channels depend on a third parameter and characterise how they split into multiple channels with different properties.