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Sample records for constrained shape optimization

  1. Constrained Aeroacoustic Shape Optimization Using the Surrogate Management Framework

    NASA Technical Reports Server (NTRS)

    Marsden, Alison L.; Wang, Meng; Dennis, John E., Jr.

    2003-01-01

    Reduction of noise generated by turbulent flow past the trailing-edge of a lifting surface is a challenge in many aeronautical and naval applications. Numerical predictions of trailing-edge noise necessitate the use of advanced simulation techniques such as large-eddy simulation (LES) in order to capture a wide range of turbulence scales which are the source of broadband noise. Aeroacoustic calculations of the flow over a model airfoil trailing edge using LES and aeroacoustic theory have been presented in Wang and Moin and were shown to agree favorably with experiments. The goal of the present work is to apply shape optimization to the trailing edge flow previously studied, in order to control aerodynamic noise.

  2. Constrained Multipoint Aerodynamic Shape Optimization Using an Adjoint Formulation and Parallel Computers

    NASA Technical Reports Server (NTRS)

    Reuther, James; Jameson, Antony; Alonso, Juan Jose; Rimlinger, Mark J.; Saunders, David

    1997-01-01

    An aerodynamic shape optimization method that treats the design of complex aircraft configurations subject to high fidelity computational fluid dynamics (CFD), geometric constraints and multiple design points is described. The design process will be greatly accelerated through the use of both control theory and distributed memory computer architectures. Control theory is employed to derive the adjoint differential equations whose solution allows for the evaluation of design gradient information at a fraction of the computational cost required by previous design methods. The resulting problem is implemented on parallel distributed memory architectures using a domain decomposition approach, an optimized communication schedule, and the MPI (Message Passing Interface) standard for portability and efficiency. The final result achieves very rapid aerodynamic design based on a higher order CFD method. In order to facilitate the integration of these high fidelity CFD approaches into future multi-disciplinary optimization (NW) applications, new methods must be developed which are capable of simultaneously addressing complex geometries, multiple objective functions, and geometric design constraints. In our earlier studies, we coupled the adjoint based design formulations with unconstrained optimization algorithms and showed that the approach was effective for the aerodynamic design of airfoils, wings, wing-bodies, and complex aircraft configurations. In many of the results presented in these earlier works, geometric constraints were satisfied either by a projection into feasible space or by posing the design space parameterization such that it automatically satisfied constraints. Furthermore, with the exception of reference 9 where the second author initially explored the use of multipoint design in conjunction with adjoint formulations, our earlier works have focused on single point design efforts. Here we demonstrate that the same methodology may be extended to treat

  3. Constrained Multiobjective Biogeography Optimization Algorithm

    PubMed Central

    Mo, Hongwei; Xu, Zhidan; Xu, Lifang; Wu, Zhou; Ma, Haiping

    2014-01-01

    Multiobjective optimization involves minimizing or maximizing multiple objective functions subject to a set of constraints. In this study, a novel constrained multiobjective biogeography optimization algorithm (CMBOA) is proposed. It is the first biogeography optimization algorithm for constrained multiobjective optimization. In CMBOA, a disturbance migration operator is designed to generate diverse feasible individuals in order to promote the diversity of individuals on Pareto front. Infeasible individuals nearby feasible region are evolved to feasibility by recombining with their nearest nondominated feasible individuals. The convergence of CMBOA is proved by using probability theory. The performance of CMBOA is evaluated on a set of 6 benchmark problems and experimental results show that the CMBOA performs better than or similar to the classical NSGA-II and IS-MOEA. PMID:25006591

  4. Constrained multiobjective biogeography optimization algorithm.

    PubMed

    Mo, Hongwei; Xu, Zhidan; Xu, Lifang; Wu, Zhou; Ma, Haiping

    2014-01-01

    Multiobjective optimization involves minimizing or maximizing multiple objective functions subject to a set of constraints. In this study, a novel constrained multiobjective biogeography optimization algorithm (CMBOA) is proposed. It is the first biogeography optimization algorithm for constrained multiobjective optimization. In CMBOA, a disturbance migration operator is designed to generate diverse feasible individuals in order to promote the diversity of individuals on Pareto front. Infeasible individuals nearby feasible region are evolved to feasibility by recombining with their nearest nondominated feasible individuals. The convergence of CMBOA is proved by using probability theory. The performance of CMBOA is evaluated on a set of 6 benchmark problems and experimental results show that the CMBOA performs better than or similar to the classical NSGA-II and IS-MOEA. PMID:25006591

  5. Quantum Annealing for Constrained Optimization

    NASA Astrophysics Data System (ADS)

    Hen, Itay; Spedalieri, Federico

    Recent advances in quantum technology have led to the development and manufacturing of experimental programmable quantum annealers that could potentially solve certain quadratic unconstrained binary optimization problems faster than their classical analogues. The applicability of such devices for many theoretical and practical optimization problems, which are often constrained, is severely limited by the sparse, rigid layout of the devices' quantum bits. Traditionally, constraints are addressed by the addition of penalty terms to the Hamiltonian of the problem, which in turn requires prohibitively increasing physical resources while also restricting the dynamical range of the interactions. Here we propose a method for encoding constrained optimization problems on quantum annealers that eliminates the need for penalty terms and thereby removes many of the obstacles associated with the implementation of these. We argue the advantages of the proposed technique and illustrate its effectiveness. We then conclude by discussing the experimental feasibility of the suggested method as well as its potential to boost the encodability of other optimization problems.

  6. Quantum Annealing for Constrained Optimization

    NASA Astrophysics Data System (ADS)

    Hen, Itay; Spedalieri, Federico M.

    2016-03-01

    Recent advances in quantum technology have led to the development and manufacturing of experimental programmable quantum annealers that promise to solve certain combinatorial optimization problems of practical relevance faster than their classical analogues. The applicability of such devices for many theoretical and real-world optimization problems, which are often constrained, is severely limited by the sparse, rigid layout of the devices' quantum bits. Traditionally, constraints are addressed by the addition of penalty terms to the Hamiltonian of the problem, which, in turn, requires prohibitively increasing physical resources while also restricting the dynamical range of the interactions. Here, we propose a method for encoding constrained optimization problems on quantum annealers that eliminates the need for penalty terms and thereby reduces the number of required couplers and removes the need for minor embedding, greatly reducing the number of required physical qubits. We argue the advantages of the proposed technique and illustrate its effectiveness. We conclude by discussing the experimental feasibility of the suggested method as well as its potential to appreciably reduce the resource requirements for implementing optimization problems on quantum annealers and its significance in the field of quantum computing.

  7. General shape optimization capability

    NASA Technical Reports Server (NTRS)

    Chargin, Mladen K.; Raasch, Ingo; Bruns, Rudolf; Deuermeyer, Dawson

    1991-01-01

    A method is described for calculating shape sensitivities, within MSC/NASTRAN, in a simple manner without resort to external programs. The method uses natural design variables to define the shape changes in a given structure. Once the shape sensitivities are obtained, the shape optimization process is carried out in a manner similar to property optimization processes. The capability of this method is illustrated by two examples: the shape optimization of a cantilever beam with holes, loaded by a point load at the free end (with the shape of the holes and the thickness of the beam selected as the design variables), and the shape optimization of a connecting rod subjected to several different loading and boundary conditions.

  8. Shape optimization for DSA

    NASA Astrophysics Data System (ADS)

    Ouaknin, Gaddiel; Laachi, Nabil; Delaney, Kris; Fredrickson, Glenn; Gibou, Frederic

    2016-03-01

    Directed self-assembly using block copolymers for positioning vertical interconnect access in integrated circuits relies on the proper shape of a confined domain in which polymers will self-assemble into the targeted design. Finding that shape, i.e., solving the inverse problem, is currently mainly based on trial and error approaches. We introduce a level-set based algorithm that makes use of a shape optimization strategy coupled with self-consistent field theory to solve the inverse problem in an automated way. It is shown that optimal shapes are found for different targeted topologies with accurate placement and distances between the different components.

  9. Shape optimization and CAD

    NASA Technical Reports Server (NTRS)

    Rasmussen, John

    1990-01-01

    Structural optimization has attracted the attention since the days of Galileo. Olhoff and Taylor have produced an excellent overview of the classical research within this field. However, the interest in structural optimization has increased greatly during the last decade due to the advent of reliable general numerical analysis methods and the computer power necessary to use them efficiently. This has created the possibility of developing general numerical systems for shape optimization. Several authors, eg., Esping; Braibant & Fleury; Bennet & Botkin; Botkin, Yang, and Bennet; and Stanton have published practical and successful applications of general optimization systems. Ding and Homlein have produced extensive overviews of available systems. Furthermore, a number of commercial optimization systems based on well-established finite element codes have been introduced. Systems like ANSYS, IDEAS, OASIS, and NISAOPT are widely known examples. In parallel to this development, the technology of computer aided design (CAD) has gained a large influence on the design process of mechanical engineering. The CAD technology has already lived through a rapid development driven by the drastically growing capabilities of digital computers. However, the systems of today are still considered as being only the first generation of a long row of computer integrated manufacturing (CIM) systems. These systems to come will offer an integrated environment for design, analysis, and fabrication of products of almost any character. Thus, the CAD system could be regarded as simply a database for geometrical information equipped with a number of tools with the purpose of helping the user in the design process. Among these tools are facilities for structural analysis and optimization as well as present standard CAD features like drawing, modeling, and visualization tools. The state of the art of structural optimization is that a large amount of mathematical and mechanical techniques are

  10. Constrained optimization via artificial immune system.

    PubMed

    Zhang, Weiwei; Yen, Gary G; He, Zhongshi

    2014-02-01

    An artificial immune system inspired by the fundamental principle of the vertebrate immune system, for solving constrained optimization problems, is proposed. The analogy between the mechanism of biological immune response and constrained optimization formulation is drawn. Individuals in population are classified into feasible and infeasible groups according to their constraint violations that closely match with the two states, inactivated and activated, of B-cells in the immune response. Feasible group focuses on exploitation in the feasible areas through clonal selection, recombination, and hypermutation, while infeasible group facilitates exploration along the feasibility boundary via location update. Direction information is extracted to promote the interactions between these two groups. This approach is validated by the benchmark functions proposed most recently and compared with those of the state of the art from various branches of evolutionary computation paradigms. The performance achieved is considered fairly competitive and promising. PMID:23757542

  11. Mixed-Strategy Chance Constrained Optimal Control

    NASA Technical Reports Server (NTRS)

    Ono, Masahiro; Kuwata, Yoshiaki; Balaram, J.

    2013-01-01

    This paper presents a novel chance constrained optimal control (CCOC) algorithm that chooses a control action probabilistically. A CCOC problem is to find a control input that minimizes the expected cost while guaranteeing that the probability of violating a set of constraints is below a user-specified threshold. We show that a probabilistic control approach, which we refer to as a mixed control strategy, enables us to obtain a cost that is better than what deterministic control strategies can achieve when the CCOC problem is nonconvex. The resulting mixed-strategy CCOC problem turns out to be a convexification of the original nonconvex CCOC problem. Furthermore, we also show that a mixed control strategy only needs to "mix" up to two deterministic control actions in order to achieve optimality. Building upon an iterative dual optimization, the proposed algorithm quickly converges to the optimal mixed control strategy with a user-specified tolerance.

  12. Constrained Graph Optimization: Interdiction and Preservation Problems

    SciTech Connect

    Schild, Aaron V

    2012-07-30

    The maximum flow, shortest path, and maximum matching problems are a set of basic graph problems that are critical in theoretical computer science and applications. Constrained graph optimization, a variation of these basic graph problems involving modification of the underlying graph, is equally important but sometimes significantly harder. In particular, one can explore these optimization problems with additional cost constraints. In the preservation case, the optimizer has a budget to preserve vertices or edges of a graph, preventing them from being deleted. The optimizer wants to find the best set of preserved edges/vertices in which the cost constraints are satisfied and the basic graph problems are optimized. For example, in shortest path preservation, the optimizer wants to find a set of edges/vertices within which the shortest path between two predetermined points is smallest. In interdiction problems, one deletes vertices or edges from the graph with a particular cost in order to impede the basic graph problems as much as possible (for example, delete edges/vertices to maximize the shortest path between two predetermined vertices). Applications of preservation problems include optimal road maintenance, power grid maintenance, and job scheduling, while interdiction problems are related to drug trafficking prevention, network stability assessment, and counterterrorism. Computational hardness results are presented, along with heuristic methods for approximating solutions to the matching interdiction problem. Also, efficient algorithms are presented for special cases of graphs, including on planar graphs. The graphs in many of the listed applications are planar, so these algorithms have important practical implications.

  13. Social Emotional Optimization Algorithm for Nonlinear Constrained Optimization Problems

    NASA Astrophysics Data System (ADS)

    Xu, Yuechun; Cui, Zhihua; Zeng, Jianchao

    Nonlinear programming problem is one important branch in operational research, and has been successfully applied to various real-life problems. In this paper, a new approach called Social emotional optimization algorithm (SEOA) is used to solve this problem which is a new swarm intelligent technique by simulating the human behavior guided by emotion. Simulation results show that the social emotional optimization algorithm proposed in this paper is effective and efficiency for the nonlinear constrained programming problems.

  14. Distributed Constrained Optimization with Semicoordinate Transformations

    NASA Technical Reports Server (NTRS)

    Macready, William; Wolpert, David

    2006-01-01

    Recent work has shown how information theory extends conventional full-rationality game theory to allow bounded rational agents. The associated mathematical framework can be used to solve constrained optimization problems. This is done by translating the problem into an iterated game, where each agent controls a different variable of the problem, so that the joint probability distribution across the agents moves gives an expected value of the objective function. The dynamics of the agents is designed to minimize a Lagrangian function of that joint distribution. Here we illustrate how the updating of the Lagrange parameters in the Lagrangian is a form of automated annealing, which focuses the joint distribution more and more tightly about the joint moves that optimize the objective function. We then investigate the use of "semicoordinate" variable transformations. These separate the joint state of the agents from the variables of the optimization problem, with the two connected by an onto mapping. We present experiments illustrating the ability of such transformations to facilitate optimization. We focus on the special kind of transformation in which the statistically independent states of the agents induces a mixture distribution over the optimization variables. Computer experiment illustrate this for &sat constraint satisfaction problems and for unconstrained minimization of NK functions.

  15. Robust, Optimal Subsonic Airfoil Shapes

    NASA Technical Reports Server (NTRS)

    Rai, Man Mohan

    2014-01-01

    A method has been developed to create an airfoil robust enough to operate satisfactorily in different environments. This method determines a robust, optimal, subsonic airfoil shape, beginning with an arbitrary initial airfoil shape, and imposes the necessary constraints on the design. Also, this method is flexible and extendible to a larger class of requirements and changes in constraints imposed.

  16. Optimization of constrained density functional theory

    NASA Astrophysics Data System (ADS)

    O'Regan, David D.; Teobaldi, Gilberto

    2016-07-01

    Constrained density functional theory (cDFT) is a versatile electronic structure method that enables ground-state calculations to be performed subject to physical constraints. It thereby broadens their applicability and utility. Automated Lagrange multiplier optimization is necessary for multiple constraints to be applied efficiently in cDFT, for it to be used in tandem with geometry optimization, or with molecular dynamics. In order to facilitate this, we comprehensively develop the connection between cDFT energy derivatives and response functions, providing a rigorous assessment of the uniqueness and character of cDFT stationary points while accounting for electronic interactions and screening. In particular, we provide a nonperturbative proof that stable stationary points of linear density constraints occur only at energy maxima with respect to their Lagrange multipliers. We show that multiple solutions, hysteresis, and energy discontinuities may occur in cDFT. Expressions are derived, in terms of convenient by-products of cDFT optimization, for quantities such as the dielectric function and a condition number quantifying ill definition in multiple constraint cDFT.

  17. Constrained filter optimization for subsurface landmine detection

    NASA Astrophysics Data System (ADS)

    Torrione, Peter A.; Collins, Leslie; Clodfelter, Fred; Lulich, Dan; Patrikar, Ajay; Howard, Peter; Weaver, Richard; Rosen, Erik

    2006-05-01

    Previous large-scale blind tests of anti-tank landmine detection utilizing the NIITEK ground penetrating radar indicated the potential for very high anti-tank landmine detection probabilities at very low false alarm rates for algorithms based on adaptive background cancellation schemes. Recent data collections under more heterogeneous multi-layered road-scenarios seem to indicate that although adaptive solutions to background cancellation are effective, the adaptive solutions to background cancellation under different road conditions can differ significantly, and misapplication of these adaptive solutions can reduce landmine detection performance in terms of PD/FAR. In this work we present a framework for the constrained optimization of background-estimation filters that specifically seeks to optimize PD/FAR performance as measured by the area under the ROC curve between two FARs. We also consider the application of genetic algorithms to the problem of filter optimization for landmine detection. Results indicate robust results for both static and adaptive background cancellation schemes, and possible real-world advantages and disadvantages of static and adaptive approaches are discussed.

  18. Multiplier-continuation algorthms for constrained optimization

    NASA Technical Reports Server (NTRS)

    Lundberg, Bruce N.; Poore, Aubrey B.; Bing, Yang

    1989-01-01

    Several path following algorithms based on the combination of three smooth penalty functions, the quadratic penalty for equality constraints and the quadratic loss and log barrier for inequality constraints, their modern counterparts, augmented Lagrangian or multiplier methods, sequential quadratic programming, and predictor-corrector continuation are described. In the first phase of this methodology, one minimizes the unconstrained or linearly constrained penalty function or augmented Lagrangian. A homotopy path generated from the functions is then followed to optimality using efficient predictor-corrector continuation methods. The continuation steps are asymptotic to those taken by sequential quadratic programming which can be used in the final steps. Numerical test results show the method to be efficient, robust, and a competitive alternative to sequential quadratic programming.

  19. Traveltime tomography and nonlinear constrained optimization

    SciTech Connect

    Berryman, J.G.

    1988-10-01

    Fermat's principle of least traveltime states that the first arrivals follow ray paths with the smallest overall traveltime from the point of transmission to the point of reception. This principle determines a definite convex set of feasible slowness models - depending only on the traveltime data - for the fully nonlinear traveltime inversion problem. The existence of such a convex set allows us to transform the inversion problem into a nonlinear constrained optimization problem. Fermat's principle also shows that the standard undamped least-squares solution to the inversion problem always produces a slowness model with many ray paths having traveltime shorter than the measured traveltime (an impossibility even if the trial ray paths are not the true ray paths). In a damped least-squares inversion, the damping parameter may be varied to allow efficient location of a slowness model on the feasibility boundary. 13 refs., 1 fig., 1 tab.

  20. Solving constrained optimization problems with hybrid particle swarm optimization

    NASA Astrophysics Data System (ADS)

    Zahara, Erwie; Hu, Chia-Hsin

    2008-11-01

    Constrained optimization problems (COPs) are very important in that they frequently appear in the real world. A COP, in which both the function and constraints may be nonlinear, consists of the optimization of a function subject to constraints. Constraint handling is one of the major concerns when solving COPs with particle swarm optimization (PSO) combined with the Nelder-Mead simplex search method (NM-PSO). This article proposes embedded constraint handling methods, which include the gradient repair method and constraint fitness priority-based ranking method, as a special operator in NM-PSO for dealing with constraints. Experiments using 13 benchmark problems are explained and the NM-PSO results are compared with the best known solutions reported in the literature. Comparison with three different meta-heuristics demonstrates that NM-PSO with the embedded constraint operator is extremely effective and efficient at locating optimal solutions.

  1. Constraining Cometary Crystal Shapes from IR Spectral Features

    NASA Technical Reports Server (NTRS)

    Wooden, Diane H.; Lindsay, Sean; Harker, David E.; Kelley, Michael S. P.; Woodward, Charles E.; Murphy, James Richard

    2013-01-01

    A major challenge in deriving the silicate mineralogy of comets is ascertaining how the anisotropic nature of forsterite crystals affects the spectral features' wavelength, relative intensity, and asymmetry. Forsterite features are identified in cometary comae near 10, 11.05-11.2, 16, 19, 23.5, 27.5 and 33 microns [1-10], so accurate models for forsterite's absorption efficiency (Qabs) are a primary requirement to compute IR spectral energy distributions (SEDs, lambdaF lambda vs. lambda) and constrain the silicate mineralogy of comets. Forsterite is an anisotropic crystal, with three crystallographic axes with distinct indices of refraction for the a-, b-, and c-axis. The shape of a forsterite crystal significantly affects its spectral features [13-16]. We need models that account for crystal shape. The IR absorption efficiencies of forsterite are computed using the discrete dipole approximation (DDA) code DDSCAT [11,12]. Starting from a fiducial crystal shape of a cube, we systematically elongate/reduce one of the crystallographic axes. Also, we elongate/reduce one axis while the lengths of the other two axes are slightly asymmetric (0.8:1.2). The most significant grain shape characteristic that affects the crystalline spectral features is the relative lengths of the crystallographic axes. The second significant grain shape characteristic is breaking the symmetry of all three axes [17]. Synthetic spectral energy distributions using seven crystal shape classes [17] are fit to the observed SED of comet C/1995 O1 (Hale-Bopp). The Hale-Bopp crystalline residual better matches equant, b-platelets, c-platelets, and b-columns spectral shape classes, while a-platelets, a-columns and c-columns worsen the spectral fits. Forsterite condensation and partial evaporation experiments demonstrate that environmental temperature and grain shape are connected [18-20]. Thus, grain shape is a potential probe for protoplanetary disk temperatures where the cometary crystalline

  2. Using Simple Shapes to Constrain Asteroid Thermal Inertia

    NASA Astrophysics Data System (ADS)

    MacLennan, Eric M.; Emery, Joshua P.

    2015-11-01

    With the use of remote thermal infrared observations and a thermophysical model (TPM), the thermal inertia of an asteroid surface can be determined. The thermal inertia, in turn, can be used to infer physical properties of the surface, specifically to estimate the average regolith grain size. Since asteroids are often non-spherical techniques for incorporating modeled (non-spherical) shapes into calculating thermal inertia have been established. However, using a sphere as input for TPM is beneficial in reducing running time and shape models are not generally available for all (or most) objects that are observed in the thermal-IR. This is particularly true, as the pace of infrared observations has recently dramatically increased, notably due to the WISE mission, while the time to acquire sufficient light curves for accurate shape inversion remains relatively long. Here, we investigate the accuracy of using both a spherical and ellipsoidal TPM, with infrared observations obtained at pre- and post-opposition (hereafter multi-epoch) geometries to constrain the thermal inertias of a large number of asteroids.We test whether using multi-epoch observations combined with a spherical and ellipsoidal shape TPM can constrain the thermal inertia of an object without a priori knowledge of its shape or spin state. The effectiveness of this technique is tested for 16 objects with shape models from DAMIT and WISE multi-epoch observations. For each object, the shape model is used as input for the TPM to generate synthetic fluxes for different values of thermal inertia. The input spherical and ellipsoidal shapes are then stepped through different spin vectors as the TPM is used to generate best-fit thermal inertia and diameter to the synthetically generated fluxes, allowing for a direct test of the approach’s effectiveness. We will discuss whether the precision of the thermal inertia constraints from the spherical TPM analysis of multi- epoch observations is comparable to works

  3. Shape optimization of corrugated airfoils

    NASA Astrophysics Data System (ADS)

    Jain, Sambhav; Bhatt, Varun Dhananjay; Mittal, Sanjay

    2015-12-01

    The effect of corrugations on the aerodynamic performance of a Mueller C4 airfoil, placed at a 5° angle of attack and Re=10{,}000, is investigated. A stabilized finite element method is employed to solve the incompressible flow equations in two dimensions. A novel parameterization scheme is proposed that enables representation of corrugations on the surface of the airfoil, and their spontaneous appearance in the shape optimization loop, if indeed they improve aerodynamic performance. Computations are carried out for different location and number of corrugations, while holding their height fixed. The first corrugation causes an increase in lift and drag. Each of the later corrugations leads to a reduction in drag. Shape optimization of the Mueller C4 airfoil is carried out using various objective functions and optimization strategies, based on controlling airfoil thickness and camber. One of the optimal shapes leads to 50 % increase in lift coefficient and 23 % increase in aerodynamic efficiency compared to the Mueller C4 airfoil.

  4. Optimal shapes for self-propelled swimmers

    NASA Astrophysics Data System (ADS)

    Koumoutsakos, Petros; van Rees, Wim; Gazzola, Mattia

    2011-11-01

    We optimize swimming shapes of three-dimensional self-propelled swimmers by combining the CMA- Evolution Strategy with a remeshed vortex method. We analyze the robustness of optimal shapes and discuss the near wake vortex dynamics for optimal speed and efficiency at Re=550. We also report preliminary results of optimal shapes and arrangements for multiple coordinated swimmers.

  5. Constraining Cometary Crystal Shapes from IR Spectral Features

    NASA Astrophysics Data System (ADS)

    Wooden, D. H.; Lindsay, S.; Harker, D. E.; Kelley, M. S.; Woodward, C. E.; Murphy, J. R.

    2013-12-01

    A major challenge in deriving the silicate mineralogy of comets is ascertaining how the anisotropic nature of forsterite crystals affects the spectral features' wavelength, relative intensity, and asymmetry. Forsterite features are identified in cometary comae near 10, 11.05-11.2, 16, 19, 23.5, 27.5 and 33 μm [1-10], so accurate models for forsterite's absorption efficiency (Qabs) are a primary requirement to compute IR spectral energy distributions (SEDs, λFλ vs. λ) and constrain the silicate mineralogy of comets. Forsterite is an anisotropic crystal, with three crystallographic axes with distinct indices of refraction for the a-, b-, and c-axis. The shape of a forsterite crystal significantly affects its spectral features [13-16]. We need models that account for crystal shape. The IR absorption efficiencies of forsterite are computed using the discrete dipole approximation (DDA) code DDSCAT [11,12]. Starting from a fiducial crystal shape of a cube, we systematically elongate/reduce one of the crystallographic axes. Also, we elongate/reduce one axis while the lengths of the other two axes are slightly asymmetric (0.8:1.2). The most significant grain shape characteristic that affects the crystalline spectral features is the relative lengths of the crystallographic axes. The second significant grain shape characteristic is breaking the symmetry of all three axes [17]. Synthetic spectral energy distributions using seven crystal shape classes [17] are fit to the observed SED of comet C/1995 O1 (Hale-Bopp). The Hale-Bopp crystalline residual better matches equant, b-platelets, c-platelets, and b-columns spectral shape classes, while a-platelets, a-columns and c-columns worsen the spectral fits. Forsterite condensation and partial evaporation experiments demonstrate that environmental temperature and grain shape are connected [18-20]. Thus, grain shape is a potential probe for protoplanetary disk temperatures where the cometary crystalline forsterite formed. The

  6. Asynchronous parallel generating set search for linearly-constrained optimization.

    SciTech Connect

    Lewis, Robert Michael; Griffin, Joshua D.; Kolda, Tamara Gibson

    2006-08-01

    Generating set search (GSS) is a family of direct search methods that encompasses generalized pattern search and related methods. We describe an algorithm for asynchronous linearly-constrained GSS, which has some complexities that make it different from both the asynchronous bound-constrained case as well as the synchronous linearly-constrained case. The algorithm has been implemented in the APPSPACK software framework and we present results from an extensive numerical study using CUTEr test problems. We discuss the results, both positive and negative, and conclude that GSS is a reliable method for solving small-to-medium sized linearly-constrained optimization problems without derivatives.

  7. A spatial shape constrained clustering method for mammographic mass segmentation.

    PubMed

    Lou, Jian-Yong; Yang, Xu-Lei; Cao, Ai-Ze

    2015-01-01

    A novel clustering method is proposed for mammographic mass segmentation on extracted regions of interest (ROIs) by using deterministic annealing incorporating circular shape function (DACF). The objective function reported in this study uses both intensity and spatial shape information, and the dominant dissimilarity measure is controlled by two weighting parameters. As a result, pixels having similar intensity information but located in different regions can be differentiated. Experimental results shows that, by using DACF, the mass segmentation results in digitized mammograms are improved with optimal mass boundaries, less number of noisy patches, and computational efficiency. An average probability of segmentation error of 7.18% for well-defined masses (or 8.06% for ill-defined masses) was obtained by using DACF on MiniMIAS database, with 5.86% (or 5.55%) and 6.14% (or 5.27%) improvements as compared to the standard DA and fuzzy c-means methods. PMID:25737739

  8. Shape optimization of self-avoiding curves

    NASA Astrophysics Data System (ADS)

    Walker, Shawn W.

    2016-04-01

    This paper presents a softened notion of proximity (or self-avoidance) for curves. We then derive a sensitivity result, based on shape differential calculus, for the proximity. This is combined with a gradient-based optimization approach to compute three-dimensional, parameterized curves that minimize the sum of an elastic (bending) energy and a proximity energy that maintains self-avoidance by a penalization technique. Minimizers are computed by a sequential-quadratic-programming (SQP) method where the bending energy and proximity energy are approximated by a finite element method. We then apply this method to two problems. First, we simulate adsorbed polymer strands that are constrained to be bound to a surface and be (locally) inextensible. This is a basic model of semi-flexible polymers adsorbed onto a surface (a current topic in material science). Several examples of minimizing curve shapes on a variety of surfaces are shown. An advantage of the method is that it can be much faster than using molecular dynamics for simulating polymer strands on surfaces. Second, we apply our proximity penalization to the computation of ideal knots. We present a heuristic scheme, utilizing the SQP method above, for minimizing rope-length and apply it in the case of the trefoil knot. Applications of this method could be for generating good initial guesses to a more accurate (but expensive) knot-tightening algorithm.

  9. Robust, optimal subsonic airfoil shapes

    NASA Technical Reports Server (NTRS)

    Rai, Man Mohan (Inventor)

    2008-01-01

    Method system, and product from application of the method, for design of a subsonic airfoil shape, beginning with an arbitrary initial airfoil shape and incorporating one or more constraints on the airfoil geometric parameters and flow characteristics. The resulting design is robust against variations in airfoil dimensions and local airfoil shape introduced in the airfoil manufacturing process. A perturbation procedure provides a class of airfoil shapes, beginning with an initial airfoil shape.

  10. Constrained ripple optimization of Tokamak bundle divertors

    SciTech Connect

    Hively, L.M.; Rome, J.A.; Lynch, V.E.; Lyon, J.F.; Fowler, R.H.; Peng, Y-K.M.; Dory, R.A.

    1983-02-01

    Magnetic field ripple from a tokamak bundle divertor is localized to a small toroidal sector and must be treated differently from the usual (distributed) toroidal field (TF) coil ripple. Generally, in a tokamak with an unoptimized divertor design, all of the banana-trapped fast ions are quickly lost due to banana drift diffusion or to trapping between the 1/R variation in absolute value vector B ..xi.. B and local field maxima due to the divertor. A computer code has been written to optimize automatically on-axis ripple subject to these constraints, while varying up to nine design parameters. Optimum configurations have low on-axis ripple (<0.2%) so that, now, most banana-trapped fast ions are confined. Only those ions with banana tips near the outside region (absolute value theta < or equal to 45/sup 0/) are lost. However, because finite-sized TF coils have not been used in this study, the flux bundle is not expanded.

  11. Torque-Matched Aerodynamic Shape Optimization of HAWT Rotor

    NASA Astrophysics Data System (ADS)

    Al-Abadi, Ali; Ertunç, Özgür; Beyer, Florian; Delgado, Antonio

    2014-12-01

    Schmitz and Blade Element Momentum (BEM) theories are integrated to a gradient based optimization algorithm to optimize the blade shape of a horizontal axis wind turbine (HAWT). The Schmitz theory is used to generate an initial blade design. BEM theory is used to calculate the forces, torque and power extracted by the turbine. The airfoil shape (NREL S809) is kept the same, so that the shape optimization comprises only the chord and the pitch angle distribution. The gradient based optimization of the blade shape is constrained to the torque-rotational speed characteristic of the generator, which is going to be a part of the experimental set-up used to validate the results of the optimization study. Hence, the objective of the optimization is the maximization of the turbines power coefficient Cp while keeping the torque matched to that of the generator. The wind velocities and the rotational speeds are limited to those achievable in the wind tunnel and by the generator, respectively. After finding the optimum blade shape with the maximum Cp within the given range of parameters, the Cp of the turbine is evaluated at wind-speeds deviating from the optimum operating condition. For this purpose, a second optimization algorithm is used to find out the correct rotational speed for a given wind-speed, which is again constrained to the generator's torque rotational speed characteristic. The design and optimization procedures are later validated by high-fidelity numerical simulations. The agreement between the design and the numerical simulations is very satisfactory.

  12. Spectral finite-element methods for parametric constrained optimization problems.

    SciTech Connect

    Anitescu, M.; Mathematics and Computer Science

    2009-01-01

    We present a method to approximate the solution mapping of parametric constrained optimization problems. The approximation, which is of the spectral finite element type, is represented as a linear combination of orthogonal polynomials. Its coefficients are determined by solving an appropriate finite-dimensional constrained optimization problem. We show that, under certain conditions, the latter problem is solvable because it is feasible for a sufficiently large degree of the polynomial approximation and has an objective function with bounded level sets. In addition, the solutions of the finite-dimensional problems converge for an increasing degree of the polynomials considered, provided that the solutions exhibit a sufficiently large and uniform degree of smoothness. Our approach solves, in the case of optimization problems with uncertain parameters, the most computationally intensive part of stochastic finite-element approaches. We demonstrate that our framework is applicable to parametric eigenvalue problems.

  13. A heuristic for constrained T-shape cutting patterns of circular items

    NASA Astrophysics Data System (ADS)

    Cui, Yaodong; Huang, Baixiong

    2011-08-01

    The cutting and stamping process is often used to divide metal plate into circular items. It contains the cutting and stamping stages. A guillotine machine divides the plate into strips at the cutting stage. Each strip contains items of the same type. A press stamps out the items from the strips at the stamping stage. T-shape patterns are often used at the cutting stage. A cut divides a T-shape pattern into an X-segment of horizontal strips and a Y-segment of vertical strips. The position of the dividing cut should be determined such that the pattern value is maximized. A heuristic for constrained T-shape patterns is presented. For each position of the dividing cut, it generates an optimal strip layout on the Y-segment using all items, and generates another optimal strip layout on the X-segment using the remaining items. Computational results indicate that the algorithm is efficient in improving material utilization.

  14. Regularized Primal-Dual Subgradient Method for Distributed Constrained Optimization.

    PubMed

    Yuan, Deming; Ho, Daniel W C; Xu, Shengyuan

    2016-09-01

    In this paper, we study the distributed constrained optimization problem where the objective function is the sum of local convex cost functions of distributed nodes in a network, subject to a global inequality constraint. To solve this problem, we propose a consensus-based distributed regularized primal-dual subgradient method. In contrast to the existing methods, most of which require projecting the estimates onto the constraint set at every iteration, only one projection at the last iteration is needed for our proposed method. We establish the convergence of the method by showing that it achieves an O ( K (-1/4) ) convergence rate for general distributed constrained optimization, where K is the iteration counter. Finally, a numerical example is provided to validate the convergence of the propose method. PMID:26285232

  15. Metal artifact reduction in x-ray computed tomography (CT) by constrained optimization

    SciTech Connect

    Zhang Xiaomeng; Wang Jing; Xing Lei

    2011-02-15

    Purpose: The streak artifacts caused by metal implants have long been recognized as a problem that limits various applications of CT imaging. In this work, the authors propose an iterative metal artifact reduction algorithm based on constrained optimization. Methods: After the shape and location of metal objects in the image domain is determined automatically by the binary metal identification algorithm and the segmentation of ''metal shadows'' in projection domain is done, constrained optimization is used for image reconstruction. It minimizes a predefined function that reflects a priori knowledge of the image, subject to the constraint that the estimated projection data are within a specified tolerance of the available metal-shadow-excluded projection data, with image non-negativity enforced. The minimization problem is solved through the alternation of projection-onto-convex-sets and the steepest gradient descent of the objective function. The constrained optimization algorithm is evaluated with a penalized smoothness objective. Results: The study shows that the proposed method is capable of significantly reducing metal artifacts, suppressing noise, and improving soft-tissue visibility. It outperforms the FBP-type methods and ART and EM methods and yields artifacts-free images. Conclusions: Constrained optimization is an effective way to deal with CT reconstruction with embedded metal objects. Although the method is presented in the context of metal artifacts, it is applicable to general ''missing data'' image reconstruction problems.

  16. Optimization of multi-constrained structures based on optimality criteria

    NASA Technical Reports Server (NTRS)

    Rizzi, P.

    1976-01-01

    A weight-reduction algorithm is developed for the optimal design of structures subject to several multibehavioral inequality constraints. The structural weight is considered to depend linearly on the design variables. The algorithm incorporates a simple recursion formula derived from the Kuhn-Tucker necessary conditions for optimality, associated with a procedure to delete nonactive constraints based on the Gauss-Seidel iterative method for linear systems. A number of example problems is studied, including typical truss structures and simplified wings subject to static loads and with constraints imposed on stresses and displacements. For one of the latter structures, constraints on the fundamental natural frequency and flutter speed are also imposed. The results obtained show that the method is fast, efficient, and general when compared to other competing techniques. Extensions to the generality of the method to include equality constraints and nonlinear merit functions is discussed.

  17. Thermally-Constrained Fuel-Optimal ISS Maneuvers

    NASA Technical Reports Server (NTRS)

    Bhatt, Sagar; Svecz, Andrew; Alaniz, Abran; Jang, Jiann-Woei; Nguyen, Louis; Spanos, Pol

    2015-01-01

    Optimal Propellant Maneuvers (OPMs) are now being used to rotate the International Space Station (ISS) and have saved hundreds of kilograms of propellant over the last two years. The savings are achieved by commanding the ISS to follow a pre-planned attitude trajectory optimized to take advantage of environmental torques. The trajectory is obtained by solving an optimal control problem. Prior to use on orbit, OPM trajectories are screened to ensure a static sun vector (SSV) does not occur during the maneuver. The SSV is an indicator that the ISS hardware temperatures may exceed thermal limits, causing damage to the components. In this paper, thermally-constrained fuel-optimal trajectories are presented that avoid an SSV and can be used throughout the year while still reducing propellant consumption significantly.

  18. Shape Optimization of Swimming Sheets

    SciTech Connect

    Wilkening, J.; Hosoi, A.E.

    2005-03-01

    The swimming behavior of a flexible sheet which moves by propagating deformation waves along its body was first studied by G. I. Taylor in 1951. In addition to being of theoretical interest, this problem serves as a useful model of the locomotion of gastropods and various micro-organisms. Although the mechanics of swimming via wave propagation has been studied extensively, relatively little work has been done to define or describe optimal swimming by this mechanism.We carry out this objective for a sheet that is separated from a rigid substrate by a thin film of viscous Newtonian fluid. Using a lubrication approximation to model the dynamics, we derive the relevant Euler-Lagrange equations to optimize swimming speed and efficiency. The optimization equations are solved numerically using two different schemes: a limited memory BFGS method that uses cubic splines to represent the wave profile, and a multi-shooting Runge-Kutta approach that uses the Levenberg-Marquardt method to vary the parameters of the equations until the constraints are satisfied. The former approach is less efficient but generalizes nicely to the non-lubrication setting. For each optimization problem we obtain a one parameter family of solutions that becomes singular in a self-similar fashion as the parameter approaches a critical value. We explore the validity of the lubrication approximation near this singular limit by monitoring higher order corrections to the zeroth order theory and by comparing the results with finite element solutions of the full Stokes equations.

  19. Structural shape optimization in multidisciplinary system synthesis

    NASA Technical Reports Server (NTRS)

    Sobieszczanski-Sobieski, Jaroslaw

    1988-01-01

    Structural shape optimization couples with other discipline optimization in the design of complex engineering systems. For instance, the wing structural weight and elastic deformations couple to aerodynamic loads and aircraft performance through drag. This coupling makes structural shape optimization a subtask in the overall vehicle synthesis. Decomposition methods for optimization and sensitivity analysis allow the specialized disciplinary methods to be used while the disciplines are temporarily decoupled, after which the interdisciplinary couplings are restored at the system level. Application of decomposition methods to structures-aerodynamics coupling in aircraft is outlined and illustrated with a numerical example of a transport aircraft. It is concluded that these methods may integrate structural and aerodynamic shape optimizations with the unified objective of the maximum aircraft performance.

  20. Shape optimization including finite element grid adaptation

    NASA Technical Reports Server (NTRS)

    Kikuchi, N.; Taylor, J. E.

    1984-01-01

    The prediction of optimal shape design for structures depends on having a sufficient level of precision in the computation of structural response. These requirements become critical in situations where the region to be designed includes stress concentrations or unilateral contact surfaces, for example. In the approach to shape optimization discussed here, a means to obtain grid adaptation is incorporated into the finite element procedures. This facility makes it possible to maintain a level of quality in the computational estimate of response that is surely adequate for the shape design problem.

  1. Spectrum reconstruction based on the constrained optimal linear inverse methods.

    PubMed

    Ren, Wenyi; Zhang, Chunmin; Mu, Tingkui; Dai, Haishan

    2012-07-01

    The dispersion effect of birefringent material results in spectrally varying Nyquist frequency for the Fourier transform spectrometer based on birefringent prism. Correct spectral information cannot be retrieved from the observed interferogram if the dispersion effect is not appropriately compensated. Some methods, such as nonuniform fast Fourier transforms and compensation method, were proposed to reconstruct the spectrum. In this Letter, an alternative constrained spectrum reconstruction method is suggested for the stationary polarization interference imaging spectrometer (SPIIS) based on the Savart polariscope. In the theoretical model of the interferogram, the noise and the total measurement error are included, and the spectrum reconstruction is performed by using the constrained optimal linear inverse methods. From numerical simulation, it is found that the proposed method is much more effective and robust than the nonconstrained spectrum reconstruction method proposed by Jian, and provides a useful spectrum reconstruction approach for the SPIIS. PMID:22743461

  2. Evolutionary pattern search algorithms for unconstrained and linearly constrained optimization

    SciTech Connect

    HART,WILLIAM E.

    2000-06-01

    The authors describe a convergence theory for evolutionary pattern search algorithms (EPSAs) on a broad class of unconstrained and linearly constrained problems. EPSAs adaptively modify the step size of the mutation operator in response to the success of previous optimization steps. The design of EPSAs is inspired by recent analyses of pattern search methods. The analysis significantly extends the previous convergence theory for EPSAs. The analysis applies to a broader class of EPSAs,and it applies to problems that are nonsmooth, have unbounded objective functions, and which are linearly constrained. Further, they describe a modest change to the algorithmic framework of EPSAs for which a non-probabilistic convergence theory applies. These analyses are also noteworthy because they are considerably simpler than previous analyses of EPSAs.

  3. What Constrains Children's Learning of Novel Shape Terms?

    ERIC Educational Resources Information Center

    O'Hanlon, Catherine G.; Roberson, Debi

    2007-01-01

    In this study, 3-year-olds matched on vocabulary score were taught three new shape terms by one of three types of linguistic contrast: corrective, semantic, or referential. A 5-week training paradigm implemented four training sessions and four assessment sessions. Corrective contrast ("This is concave, it is not square," where "square" is the…

  4. Adaptive Multi-Agent Systems for Constrained Optimization

    NASA Technical Reports Server (NTRS)

    Macready, William; Bieniawski, Stefan; Wolpert, David H.

    2004-01-01

    Product Distribution (PD) theory is a new framework for analyzing and controlling distributed systems. Here we demonstrate its use for distributed stochastic optimization. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. The updating of the Lagrange parameters in the Lagrangian can be viewed as a form of automated annealing, that focuses the MAS more and more on the optimal pure strategy. This provides a simple way to map the solution of any constrained optimization problem onto the equilibrium of a Multi-Agent System (MAS). We present computer experiments involving both the Queen s problem and K-SAT validating the predictions of PD theory and its use for off-the-shelf distributed adaptive optimization.

  5. Domain decomposition in time for PDE-constrained optimization

    SciTech Connect

    Barker, Andrew T.; Stoll, Martin

    2015-08-28

    Here, PDE-constrained optimization problems have a wide range of applications, but they lead to very large and ill-conditioned linear systems, especially if the problems are time dependent. In this paper we outline an approach for dealing with such problems by decomposing them in time and applying an additive Schwarz preconditioner in time, so that we can take advantage of parallel computers to deal with the very large linear systems. We then illustrate the performance of our method on a variety of problems.

  6. Reduced order constrained optimization (ROCO): Clinical application to lung IMRT

    PubMed Central

    Stabenau, Hans; Rivera, Linda; Yorke, Ellen; Yang, Jie; Lu, Renzhi; Radke, Richard J.; Jackson, Andrew

    2011-01-01

    Purpose: The authors use reduced-order constrained optimization (ROCO) to create clinically acceptable IMRT plans quickly and automatically for advanced lung cancer patients. Their new ROCO implementation works with the treatment planning system and full dose calculation used at Memorial Sloan-Kettering Cancer Center (MSKCC). The authors have implemented mean dose hard constraints, along with the point-dose and dose-volume constraints that the authors used for our previous work on the prostate.Methods: ROCO consists of three major steps. First, the space of treatment plans is sampled by solving a series of optimization problems using penalty-based quadratic objective functions. Next, an efficient basis for this space is found via principal component analysis (PCA); this reduces the dimensionality of the problem. Finally, a constrained optimization problem is solved over this basis to find a clinically acceptable IMRT plan. Dimensionality reduction makes constrained optimization computationally efficient.Results: The authors apply ROCO to 12 stage III non-small-cell lung cancer (NSCLC) cases, generating IMRT plans that meet all clinical constraints and are clinically acceptable, and demonstrate that they are competitive with the clinical treatment plans. The authors also test how many samples and PCA modes are necessary to achieve an adequate lung plan, demonstrate the importance of long-range dose calculation for ROCO, and evaluate the performance of nonspecific normal tissue (“rind”) constraints in ROCO treatment planning for the lung. Finally, authors show that ROCO can save time for planners, and they estimate that in the clinic, planning using their approach would save a median of 105 min for the patients in the study.Conclusions: New challenges arise when applying ROCO to the lung site, which include the lack of a class solution, a larger treatment site, an increased number of parameters and beamlets, a variable number of beams and beam arrangement, and

  7. Teaching-learning-based optimization algorithm for unconstrained and constrained real-parameter optimization problems

    NASA Astrophysics Data System (ADS)

    Rao, R. V.; Savsani, V. J.; Balic, J.

    2012-12-01

    An efficient optimization algorithm called teaching-learning-based optimization (TLBO) is proposed in this article to solve continuous unconstrained and constrained optimization problems. The proposed method is based on the effect of the influence of a teacher on the output of learners in a class. The basic philosophy of the method is explained in detail. The algorithm is tested on 25 different unconstrained benchmark functions and 35 constrained benchmark functions with different characteristics. For the constrained benchmark functions, TLBO is tested with different constraint handling techniques such as superiority of feasible solutions, self-adaptive penalty, ɛ-constraint, stochastic ranking and ensemble of constraints. The performance of the TLBO algorithm is compared with that of other optimization algorithms and the results show the better performance of the proposed algorithm.

  8. Constrained genetic algorithms for optimizing multi-use reservoir operation

    NASA Astrophysics Data System (ADS)

    Chang, Li-Chiu; Chang, Fi-John; Wang, Kuo-Wei; Dai, Shin-Yi

    2010-08-01

    To derive an optimal strategy for reservoir operations to assist the decision-making process, we propose a methodology that incorporates the constrained genetic algorithm (CGA) where the ecological base flow requirements are considered as constraints to water release of reservoir operation when optimizing the 10-day reservoir storage. Furthermore, a number of penalty functions designed for different types of constraints are integrated into reservoir operational objectives to form the fitness function. To validate the applicability of this proposed methodology for reservoir operations, the Shih-Men Reservoir and its downstream water demands are used as a case study. By implementing the proposed CGA in optimizing the operational performance of the Shih-Men Reservoir for the last 20 years, we find this method provides much better performance in terms of a small generalized shortage index (GSI) for human water demands and greater ecological base flows for most of the years than historical operations do. We demonstrate the CGA approach can significantly improve the efficiency and effectiveness of water supply capability to both human and ecological base flow requirements and thus optimize reservoir operations for multiple water users. The CGA can be a powerful tool in searching for the optimal strategy for multi-use reservoir operations in water resources management.

  9. Total energy control system autopilot design with constrained parameter optimization

    NASA Technical Reports Server (NTRS)

    Ly, Uy-Loi; Voth, Christopher

    1990-01-01

    A description is given of the application of a multivariable control design method (SANDY) based on constrained parameter optimization to the design of a multiloop aircraft flight control system. Specifically, the design method is applied to the direct synthesis of a multiloop AFCS inner-loop feedback control system based on total energy control system (TECS) principles. The design procedure offers a structured approach for the determination of a set of stabilizing controller design gains that meet design specifications in closed-loop stability, command tracking performance, disturbance rejection, and limits on control activities. The approach can be extended to a broader class of multiloop flight control systems. Direct tradeoffs between many real design goals are rendered systematic by proper formulation of the design objectives and constraints. Satisfactory designs are usually obtained in few iterations. Performance characteristics of the optimized TECS design have been improved, particularly in the areas of closed-loop damping and control activity in the presence of turbulence.

  10. Constrained optimization of gradient waveforms for generalized diffusion encoding.

    PubMed

    Sjölund, Jens; Szczepankiewicz, Filip; Nilsson, Markus; Topgaard, Daniel; Westin, Carl-Fredrik; Knutsson, Hans

    2015-12-01

    Diffusion MRI is a useful probe of tissue microstructure. The conventional diffusion encoding sequence, the single pulsed field gradient, has recently been challenged as more general gradient waveforms have been introduced. Out of these, we focus on q-space trajectory imaging, which generalizes the scalar b-value to a tensor valued entity. To take full advantage of its capabilities, it is imperative to respect the constraints imposed by the hardware, while at the same time maximizing the diffusion encoding strength. We provide a tool that achieves this by solving a constrained optimization problem that accommodates constraints on maximum gradient amplitude, slew rate, coil heating and positioning of radio frequency pulses. The method's efficacy and flexibility is demonstrated both experimentally and by comparison with previous work on optimization of isotropic diffusion sequences. PMID:26583528

  11. Constrained optimization of gradient waveforms for generalized diffusion encoding

    NASA Astrophysics Data System (ADS)

    Sjölund, Jens; Szczepankiewicz, Filip; Nilsson, Markus; Topgaard, Daniel; Westin, Carl-Fredrik; Knutsson, Hans

    2015-12-01

    Diffusion MRI is a useful probe of tissue microstructure. The conventional diffusion encoding sequence, the single pulsed field gradient, has recently been challenged as more general gradient waveforms have been introduced. Out of these, we focus on q-space trajectory imaging, which generalizes the scalar b-value to a tensor valued entity. To take full advantage of its capabilities, it is imperative to respect the constraints imposed by the hardware, while at the same time maximizing the diffusion encoding strength. We provide a tool that achieves this by solving a constrained optimization problem that accommodates constraints on maximum gradient amplitude, slew rate, coil heating and positioning of radio frequency pulses. The method's efficacy and flexibility is demonstrated both experimentally and by comparison with previous work on optimization of isotropic diffusion sequences.

  12. Nonlinearly-constrained optimization using asynchronous parallel generating set search.

    SciTech Connect

    Griffin, Joshua D.; Kolda, Tamara Gibson

    2007-05-01

    Many optimization problems in computational science and engineering (CS&E) are characterized by expensive objective and/or constraint function evaluations paired with a lack of derivative information. Direct search methods such as generating set search (GSS) are well understood and efficient for derivative-free optimization of unconstrained and linearly-constrained problems. This paper addresses the more difficult problem of general nonlinear programming where derivatives for objective or constraint functions are unavailable, which is the case for many CS&E applications. We focus on penalty methods that use GSS to solve the linearly-constrained problems, comparing different penalty functions. A classical choice for penalizing constraint violations is {ell}{sub 2}{sup 2}, the squared {ell}{sub 2} norm, which has advantages for derivative-based optimization methods. In our numerical tests, however, we show that exact penalty functions based on the {ell}{sub 1}, {ell}{sub 2}, and {ell}{sub {infinity}} norms converge to good approximate solutions more quickly and thus are attractive alternatives. Unfortunately, exact penalty functions are discontinuous and consequently introduce theoretical problems that degrade the final solution accuracy, so we also consider smoothed variants. Smoothed-exact penalty functions are theoretically attractive because they retain the differentiability of the original problem. Numerically, they are a compromise between exact and {ell}{sub 2}{sup 2}, i.e., they converge to a good solution somewhat quickly without sacrificing much solution accuracy. Moreover, the smoothing is parameterized and can potentially be adjusted to balance the two considerations. Since many CS&E optimization problems are characterized by expensive function evaluations, reducing the number of function evaluations is paramount, and the results of this paper show that exact and smoothed-exact penalty functions are well-suited to this task.

  13. Constrained Multi-Level Algorithm for Trajectory Optimization

    NASA Astrophysics Data System (ADS)

    Adimurthy, V.; Tandon, S. R.; Jessy, Antony; Kumar, C. Ravi

    The emphasis on low cost access to space inspired many recent developments in the methodology of trajectory optimization. Ref.1 uses a spectral patching method for optimization, where global orthogonal polynomials are used to describe the dynamical constraints. A two-tier approach of optimization is used in Ref.2 for a missile mid-course trajectory optimization. A hybrid analytical/numerical approach is described in Ref.3, where an initial analytical vacuum solution is taken and gradually atmospheric effects are introduced. Ref.4 emphasizes the fact that the nonlinear constraints which occur in the initial and middle portions of the trajectory behave very nonlinearly with respect the variables making the optimization very difficult to solve in the direct and indirect shooting methods. The problem is further made complex when different phases of the trajectory have different objectives of optimization and also have different path constraints. Such problems can be effectively addressed by multi-level optimization. In the multi-level methods reported so far, optimization is first done in identified sub-level problems, where some coordination variables are kept fixed for global iteration. After all the sub optimizations are completed, higher-level optimization iteration with all the coordination and main variables is done. This is followed by further sub system optimizations with new coordination variables. This process is continued until convergence. In this paper we use a multi-level constrained optimization algorithm which avoids the repeated local sub system optimizations and which also removes the problem of non-linear sensitivity inherent in the single step approaches. Fall-zone constraints, structural load constraints and thermal constraints are considered. In this algorithm, there is only a single multi-level sequence of state and multiplier updates in a framework of an augmented Lagrangian. Han Tapia multiplier updates are used in view of their special role in

  14. Optimized shaped pupil masks for pupil with obscuration

    NASA Astrophysics Data System (ADS)

    Carlotti, Alexis; Kasdin, N. Jeremy; Vanderbei, Robert J.; Delorme, Jacques-Robert

    2012-09-01

    The main components of the SPICA coronagraphic instrument have initially been bar-code apodizing masks, i.e. shaped pupils optimized in one dimension. Their free-standing designs make them manufacturable without a glass substrate, which implies an absolute achromaticity and no additional wavefront errors. However, shaped pupils can now be optimized in two dimensions and can thus take full advantage of the geometry of any arbitrary aperture, in particular obstructed apertures such as SPICA's. Hence, 2D shaped pupils often have higher throughputs while offering the same angular resolutions and contrast. Alternatively, better resolutions or contrast can be obtained for the same throughput. Although some of these new masks are free-standing, this property cannot be constrained if the optimization problem has to remain convex linear. We propose to address this issue in different ways, and we present here examples of freestanding masks for a variety of contrasts, and inner working angles. Moreover, in all other coronagraphic instruments, contrast smaller than 10-5 can only be obtained if a dedicated adaptive optics system uses one or several deformable mirrors to compensate for wavefront aberrations. The finite number of actuators sets the size of the angular area in which quasi-static speckles can be corrected. This puts a natural limit on the outer working angle for which the shaped pupils are designed. The limited number of actuators is also responsible for an additional diffracted energy, or quilting orders, that can prevent faint companions to be detected. This effect can and must be taken into account in the optimization process. Finally, shaped pupils can be computed for a given nominal phase aberration pattern in the pupil plane, although the solutions depend in this case on the observation wavelength. We illustrate this possibility by optimizing an apodizer for the James Webb space telescope, and by testing its chromaticity and its robustness to phase changes.

  15. Shape optimization of tibial prosthesis components

    NASA Technical Reports Server (NTRS)

    Saravanos, D. A.; Mraz, P. J.; Davy, D. T.

    1993-01-01

    NASA technology and optimal design methodologies originally developed for the optimization of composite structures (engine blades) are adapted and applied to the optimization of orthopaedic knee implants. A method is developed enabling the shape tailoring of the tibial components of a total knee replacement implant for optimal interaction within the environment of the tibia. The shape of the implant components are optimized such that the stresses in the bone are favorably controlled to minimize bone degradation, to improve the mechanical integrity of the implant/interface/bone system, and to prevent failures of the implant components. A pilot tailoring system is developed and the feasibility of the concept is demonstrated and evaluated. The methodology and evolution of the existing aerospace technology from which this pilot optimization code was developed is also presented and discussed. Both symmetric and unsymmetric in-plane loading conditions are investigated. The results of the optimization process indicate a trend toward wider and tapered posts as well as thicker backing trays. Unique component geometries were obtained for the different load cases.

  16. Constrained Multiobjective Optimization Algorithm Based on Immune System Model.

    PubMed

    Qian, Shuqu; Ye, Yongqiang; Jiang, Bin; Wang, Jianhong

    2016-09-01

    An immune optimization algorithm, based on the model of biological immune system, is proposed to solve multiobjective optimization problems with multimodal nonlinear constraints. First, the initial population is divided into feasible nondominated population and infeasible/dominated population. The feasible nondominated individuals focus on exploring the nondominated front through clone and hypermutation based on a proposed affinity design approach, while the infeasible/dominated individuals are exploited and improved via the simulated binary crossover and polynomial mutation operations. And then, to accelerate the convergence of the proposed algorithm, a transformation technique is applied to the combined population of the above two offspring populations. Finally, a crowded-comparison strategy is used to create the next generation population. In numerical experiments, a series of benchmark constrained multiobjective optimization problems are considered to evaluate the performance of the proposed algorithm and it is also compared to several state-of-art algorithms in terms of the inverted generational distance and hypervolume indicators. The results indicate that the new method achieves competitive performance and even statistically significant better results than previous algorithms do on most of the benchmark suite. PMID:26285230

  17. Solving nonlinear equality constrained multiobjective optimization problems using neural networks.

    PubMed

    Mestari, Mohammed; Benzirar, Mohammed; Saber, Nadia; Khouil, Meryem

    2015-10-01

    This paper develops a neural network architecture and a new processing method for solving in real time, the nonlinear equality constrained multiobjective optimization problem (NECMOP), where several nonlinear objective functions must be optimized in a conflicting situation. In this processing method, the NECMOP is converted to an equivalent scalar optimization problem (SOP). The SOP is then decomposed into several-separable subproblems processable in parallel and in a reasonable time by multiplexing switched capacitor circuits. The approach which we propose makes use of a decomposition-coordination principle that allows nonlinearity to be treated at a local level and where coordination is achieved through the use of Lagrange multipliers. The modularity and the regularity of the neural networks architecture herein proposed make it suitable for very large scale integration implementation. An application to the resolution of a physical problem is given to show that the approach used here possesses some advantages of the point of algorithmic view, and provides processes of resolution often simpler than the usual techniques. PMID:25647664

  18. Constrained optimization for green engineering decision-making.

    PubMed

    Thurston, Deborah L; Srinivasan, Suresh

    2003-12-01

    Green engineering requires the designer to consider a very extensive set of environmental impacts. To minimize these impacts, the designer must significantly expand his or her "toolset" of product design concepts, alternative materials, manufacturing systems, and analytic methods for addressing life cycle impacts. This can overwhelm a designer, who then resorts to overly simplistic rules or checklists out of necessity. The central issue is how to identify all "pollution prevention pays" opportunities and then how to deal with the unavoidable tradeoffs that arise after all these opportunities have been exhausted. This paper presents a framework for employing mathematical decision modeling toward this end. A domain-independent constrained optimization formulation is presented. A multiattribute utility function reflects the willingness to pay for environmental improvement and is the basis of the objective function. The feasibility constraints reflect the unavoidable tradeoffs. Several case studies are presented, including power systems, floor tile manufacturing, and computer systems. PMID:14700324

  19. Aerodynamic shape optimization using control theory

    NASA Technical Reports Server (NTRS)

    Reuther, James

    1996-01-01

    Aerodynamic shape design has long persisted as a difficult scientific challenge due its highly nonlinear flow physics and daunting geometric complexity. However, with the emergence of Computational Fluid Dynamics (CFD) it has become possible to make accurate predictions of flows which are not dominated by viscous effects. It is thus worthwhile to explore the extension of CFD methods for flow analysis to the treatment of aerodynamic shape design. Two new aerodynamic shape design methods are developed which combine existing CFD technology, optimal control theory, and numerical optimization techniques. Flow analysis methods for the potential flow equation and the Euler equations form the basis of the two respective design methods. In each case, optimal control theory is used to derive the adjoint differential equations, the solution of which provides the necessary gradient information to a numerical optimization method much more efficiently then by conventional finite differencing. Each technique uses a quasi-Newton numerical optimization algorithm to drive an aerodynamic objective function toward a minimum. An analytic grid perturbation method is developed to modify body fitted meshes to accommodate shape changes during the design process. Both Hicks-Henne perturbation functions and B-spline control points are explored as suitable design variables. The new methods prove to be computationally efficient and robust, and can be used for practical airfoil design including geometric and aerodynamic constraints. Objective functions are chosen to allow both inverse design to a target pressure distribution and wave drag minimization. Several design cases are presented for each method illustrating its practicality and efficiency. These include non-lifting and lifting airfoils operating at both subsonic and transonic conditions.

  20. Aerodynamic Shape Optimization Using Hybridized Differential Evolution

    NASA Technical Reports Server (NTRS)

    Madavan, Nateri K.

    2003-01-01

    An aerodynamic shape optimization method that uses an evolutionary algorithm known at Differential Evolution (DE) in conjunction with various hybridization strategies is described. DE is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Various hybridization strategies for DE are explored, including the use of neural networks as well as traditional local search methods. A Navier-Stokes solver is used to evaluate the various intermediate designs and provide inputs to the hybrid DE optimizer. The method is implemented on distributed parallel computers so that new designs can be obtained within reasonable turnaround times. Results are presented for the inverse design of a turbine airfoil from a modern jet engine. (The final paper will include at least one other aerodynamic design application). The capability of the method to search large design spaces and obtain the optimal airfoils in an automatic fashion is demonstrated.

  1. Robust integrated autopilot/autothrottle design using constrained parameter optimization

    NASA Technical Reports Server (NTRS)

    Ly, Uy-Loi; Voth, Christopher; Sanjay, Swamy

    1990-01-01

    A multivariable control design method based on constrained parameter optimization was applied to the design of a multiloop aircraft flight control system. Specifically, the design method is applied to the following: (1) direct synthesis of a multivariable 'inner-loop' feedback control system based on total energy control principles; (2) synthesis of speed/altitude-hold designs as 'outer-loop' feedback/feedforward control systems around the above inner loop; and (3) direct synthesis of a combined 'inner-loop' and 'outer-loop' multivariable control system. The design procedure offers a direct and structured approach for the determination of a set of controller gains that meet design specifications in closed-loop stability, command tracking performance, disturbance rejection, and limits on control activities. The presented approach may be applied to a broader class of multiloop flight control systems. Direct tradeoffs between many real design goals are rendered systematic by this method following careful problem formulation of the design objectives and constraints. Performance characteristics of the optimization design were improved over the current autopilot design on the B737-100 Transport Research Vehicle (TSRV) at the landing approach and cruise flight conditions; particularly in the areas of closed-loop damping, command responses, and control activity in the presence of turbulence.

  2. An approximation function for frequency constrained structural optimization

    NASA Technical Reports Server (NTRS)

    Canfield, R. A.

    1989-01-01

    The purpose is to examine a function for approximating natural frequency constraints during structural optimization. The nonlinearity of frequencies has posed a barrier to constructing approximations for frequency constraints of high enough quality to facilitate efficient solutions. A new function to represent frequency constraints, called the Rayleigh Quotient Approximation (RQA), is presented. Its ability to represent the actual frequency constraint results in stable convergence with effectively no move limits. The objective of the optimization problem is to minimize structural weight subject to some minimum (or maximum) allowable frequency and perhaps subject to other constraints such as stress, displacement, and gage size, as well. A reason for constraining natural frequencies during design might be to avoid potential resonant frequencies due to machinery or actuators on the structure. Another reason might be to satisy requirements of an aircraft or spacecraft's control law. Whatever the structure supports may be sensitive to a frequency band that must be avoided. Any of these situations or others may require the designer to insure the satisfaction of frequency constraints. A further motivation for considering accurate approximations of natural frequencies is that they are fundamental to dynamic response constraints.

  3. Application of constrained optimization to active control of aeroelastic response

    NASA Technical Reports Server (NTRS)

    Newsom, J. R.; Mukhopadhyay, V.

    1981-01-01

    Active control of aeroelastic response is a complex in which the designer usually tries to satisfy many criteria which are often conflicting. To further complicate the design problem, the state space equations describing this type of control problem are usually of high order, involving a large number of states to represent the flexible structure and unsteady aerodynamics. Control laws based on the standard Linear-Quadratic-Gaussian (LQG) method are of the same high order as the aeroelastic plant. To overcome this disadvantage of the LQG mode, an approach developed for designing low order optimal control laws which uses a nonlinear programming algorithm to search for the values of the control law variables that minimize a composite performance index, was extended to the constrained optimization problem. The method involves searching for the values of the control law variables that minimize a basic performance index while satisfying several inequality constraints that describe the design criteria. The method is applied to gust load alleviation of a drone aircraft.

  4. Implant shape optimization using reverse FEA

    NASA Astrophysics Data System (ADS)

    Gladilin, Evgeny; Ivanov, A.; Roginsky, V.

    2005-04-01

    This work presents a novel approach for the physically-based optimization of individual implants in cranio-maxillofacial surgery. The proposed method is based on solving an inverse boundary value problem of the cranio-maxillofacial surgery planning, i.e. finding an optimal implant shape for a desired correction of soft tissues. The paper describes the methodology for the generation of individual geometrical models of human head, the reverse finite element approach for solving biomechanical boundary value problems and two clinical studies dealing with the computer aided design of individual craniofacial implants.

  5. Constrained simultaneous multi-state reconfigurable wing structure configuration optimization

    NASA Astrophysics Data System (ADS)

    Snyder, Matthew

    A reconfigurable aircraft is capable of in-flight shape change to increase mission performance or provide multi-mission capability. Reconfigurability has always been a consideration in aircraft design, from the Wright Flyer, to the F-14, and most recently the Lockheed-Martin folding wing concept. The Wright Flyer used wing-warping for roll control, the F-14 had a variable-sweep wing to improve supersonic flight capabilities, and the Lockheed-Martin folding wing demonstrated radical in-flight shape change. This dissertation will examine two questions that aircraft reconfigurability raises, especially as reconfiguration increases in complexity. First, is there an efficient method to develop a light weight structure which supports all the loads generated by each configuration? Second, can this method include the capability to propose a sub-structure topology that weighs less than other considered designs? The first question requires a method that will design and optimize multiple configurations of a reconfigurable aerostructure. Three options exist, this dissertation will show one is better than the others. Simultaneous optimization considers all configurations and their respective load cases and constraints at the same time. Another method is sequential optimization which considers each configuration of the vehicle one after the other - with the optimum design variable values from the first configuration becoming the lower bounds for subsequent configurations. This process repeats for each considered configuration and the lower bounds update as necessary. The third approach is aggregate combination — this method keeps the thickness or area of each member for the most critical configuration, the configuration that requires the largest cross-section. This research will show that simultaneous optimization produces a lower weight and different topology for the considered structures when compared to the sequential and aggregate techniques. To answer the second question

  6. Rapid Parameterization Schemes for Aircraft Shape Optimization

    NASA Technical Reports Server (NTRS)

    Li, Wu

    2012-01-01

    A rapid shape parameterization tool called PROTEUS is developed for aircraft shape optimization. This tool can be applied directly to any aircraft geometry that has been defined in PLOT3D format, with the restriction that each aircraft component must be defined by only one data block. PROTEUS has eight types of parameterization schemes: planform, wing surface, twist, body surface, body scaling, body camber line, shifting/scaling, and linear morphing. These parametric schemes can be applied to two types of components: wing-type surfaces (e.g., wing, canard, horizontal tail, vertical tail, and pylon) and body-type surfaces (e.g., fuselage, pod, and nacelle). These schemes permit the easy setup of commonly used shape modification methods, and each customized parametric scheme can be applied to the same type of component for any configuration. This paper explains the mathematics for these parametric schemes and uses two supersonic configurations to demonstrate the application of these schemes.

  7. A collective neurodynamic optimization approach to bound-constrained nonconvex optimization.

    PubMed

    Yan, Zheng; Wang, Jun; Li, Guocheng

    2014-07-01

    This paper presents a novel collective neurodynamic optimization method for solving nonconvex optimization problems with bound constraints. First, it is proved that a one-layer projection neural network has a property that its equilibria are in one-to-one correspondence with the Karush-Kuhn-Tucker points of the constrained optimization problem. Next, a collective neurodynamic optimization approach is developed by utilizing a group of recurrent neural networks in framework of particle swarm optimization by emulating the paradigm of brainstorming. Each recurrent neural network carries out precise constrained local search according to its own neurodynamic equations. By iteratively improving the solution quality of each recurrent neural network using the information of locally best known solution and globally best known solution, the group can obtain the global optimal solution to a nonconvex optimization problem. The advantages of the proposed collective neurodynamic optimization approach over evolutionary approaches lie in its constraint handling ability and real-time computational efficiency. The effectiveness and characteristics of the proposed approach are illustrated by using many multimodal benchmark functions. PMID:24705545

  8. Shape Optimization for Trailing Edge Noise Control

    NASA Astrophysics Data System (ADS)

    Marsden, Alison; Wang, Meng; Mohammadi, Bijan; Moin, Parviz

    2001-11-01

    Noise generated by turbulent boundary layers near the trailing edge of lifting surfaces continues to pose a challenge for many applications. In this study, we explore noise reduction strategies through shape optimization. A gradient based shape design method is formulated and implemented for use with large eddy simulation of the flow over an airfoil. The cost function gradient is calculated using the method of incomplete sensitivities (Mohammadi and Pironneau 2001 ph Applied shape Optimization for Fluids, Oxford Univ. Press). This method has the advantage that effects of geometry changes on the flow field can be neglected when computing the gradient of the cost function, making it far more cost effective than solving the full adjoint problem. Validation studies are presented for a model problem of the unsteady laminar flow over an acoustically compact airfoil. A section of the surface is allowed to deform and the cost function is derived based on aeroacoustic theroy. Rapid convergence of the trailing-edge shape and significant reduction of the noise due to vortex shedding and wake instability have been achieved. The addition of constraints and issues of extension to fully turbulent flows past an acoustically noncompact airfoil are also discussed.

  9. Optimal Performance of Buildings Isolated By Shape-Memory-Alloy-Rubber-Bearing (SMARB) Under Random Earthquakes

    NASA Astrophysics Data System (ADS)

    Das, Sumanta; Mishra, Sudib K.

    2014-05-01

    Shape Memory Alloy (SMA)-based bearing has been proposed recently for improved base isolation by optimal choice of its transformation strength. Presently, superior performances of the Shape-Memory-Alloy-Rubber-Bearing (SMARB) over the elastomeric bearing are established in mitigating seismic vibration under constraint on maximum isolator displacement. The optimal transformation strengths are proposed through constrained optimization based on stochastic responses. Numerical simulation reveals that Lead Rubber Bearings (LRB) either fails to provide feasible parameters or leads to large floor acceleration, compromising the isolation efficiency. Contrarily, optimal SMARB can efficiently enforce such constraint without greatly affecting the isolation efficiency. Evidence of robustness of SMARB over LRB is also established.

  10. An optimal constrained linear inverse method for magnetic source imaging

    SciTech Connect

    Hughett, P.

    1993-09-01

    Magnetic source imaging is the reconstruction of the current distribution inside an inaccessible volume from magnetic field measurements made outside the volume. If the unknown current distribution is expressed as a linear combination of elementary current distributions in fixed positions, then the magnetic field measurements are linear in the unknown source amplitudes and both the least square and minimum mean square reconstructions are linear problems. This offers several advantages: The problem is well understood theoretically and there is only a single, global minimum. Efficient and reliable software for numerical linear algebra is readily available. If the sources are localized and statistically uncorrelated, then a map of expected power dissipation is equivalent to the source covariance matrix. Prior geological or physiological knowledge can be used to determine such an expected power map and thus the source covariance matrix. The optimal constrained linear inverse method (OCLIM) derived in this paper uses this prior knowledge to obtain a minimum mean square error estimate of the current distribution. OCLIM can be efficiently computed using the Cholesky decomposition, taking about a second on a workstation-class computer for a problem with 64 sources and 144 detectors. Any source and detector configuration is allowed as long as their positions are fixed a priori. Correlations among source and noise amplitudes are permitted. OCLIM reduces to the optimally weighted pseudoinverse method of Shim and Cho if the source amplitudes are independent and identically distributed and to the minimum-norm least squares estimate in the limit of no measurement noise or no prior knowledge of the source amplitudes. In the general case, OCLIM has better mean square error than either previous method. OCLIM appears well suited to magnetic imaging, since it exploits prior information, provides the minimum reconstruction error, and is inexpensive to compute.

  11. On Optimizing Joint Inversion of Constrained Geophysical Data Sets

    NASA Astrophysics Data System (ADS)

    Sosa Aguirre, U. A.; Velazquez, L.; Argaez, M.; Velasco, A. A.; Romero, R.

    2010-12-01

    We implemented a joint inversion least-squares (LSQ) algorithm to characterize 1-D crustal velocity Earth structure using geophysical data sets with two different optimization methods: truncated singular value decomposition (TSVD), and primal-dual interior-point (PDIP). We used receiver function and surface wave dispersion velocity observations, and created a framework to incorporate other data sets. An improvement in the final outcome (model) is expected by providing better physical constraints than using just one single data set. The TSVD and PDIP methods solve a regularized unconstrained and an inherent regularized constrained minimization problems, respectively. Both techniques implement the inclusion of bounds into the layered shear velocities in a different fashion. We conduct a numerical experimentation with synthetic data, and find that the PDID method’s solution was more robust in terms of satisfying geophysical constraints, accuracy, and efficiency than the TSVD approach. Finally, we apply the PDIP method for characterizing material properties of the Rio Grande Rift region using real recorded seismic data with promising numerical results.

  12. A Parametrically Constrained Optimization Method for Fitting Sedimentation Velocity Experiments

    PubMed Central

    Gorbet, Gary; Devlin, Taylor; Hernandez Uribe, Blanca I.; Demeler, Aysha K.; Lindsey, Zachary L.; Ganji, Suma; Breton, Sabrah; Weise-Cross, Laura; Lafer, Eileen M.; Brookes, Emre H.; Demeler, Borries

    2014-01-01

    A method for fitting sedimentation velocity experiments using whole boundary Lamm equation solutions is presented. The method, termed parametrically constrained spectrum analysis (PCSA), provides an optimized approach for simultaneously modeling heterogeneity in size and anisotropy of macromolecular mixtures. The solutions produced by PCSA are particularly useful for modeling polymerizing systems, where a single-valued relationship exists between the molar mass of the growing polymer chain and its corresponding anisotropy. The PCSA uses functional constraints to identify this relationship, and unlike other multidimensional grid methods, assures that only a single molar mass can be associated with a given anisotropy measurement. A description of the PCSA algorithm is presented, as well as several experimental and simulated examples that illustrate its utility and capabilities. The performance advantages of the PCSA method in comparison to other methods are documented. The method has been added to the UltraScan-III software suite, which is available for free download from http://www.ultrascan.uthscsa.edu. PMID:24739173

  13. Newton's method for large bound-constrained optimization problems.

    SciTech Connect

    Lin, C.-J.; More, J. J.; Mathematics and Computer Science

    1999-01-01

    We analyze a trust region version of Newton's method for bound-constrained problems. Our approach relies on the geometry of the feasible set, not on the particular representation in terms of constraints. The convergence theory holds for linearly constrained problems and yields global and superlinear convergence without assuming either strict complementarity or linear independence of the active constraints. We also show that the convergence theory leads to an efficient implementation for large bound-constrained problems.

  14. Momentum Diffusivity Estimation via PDE-Constrained Optimization

    NASA Astrophysics Data System (ADS)

    Xu, C.; Ou, Y.; Schuster, E.; Humphreys, D. A.; Walker, M. L.; Casper, T. A.; Meyer, W. H.

    2008-11-01

    Several experiments around the world have demonstrated that plasma rotation can improve plasma stability and enhance confinement. It has been shown [1] that the critical rotation speed for stabilization is a function of the rotation profile shape, implying a radially distributed stabilizing mechanism. Modeling of the rotational profile dynamics is limited by poor knowledge of the momentum diffusivity coefficient. In this work we use toroidal angular velocity data from experiments where the torque is modulated using neutral beams, and we employ optimization techniques to estimate the momentum diffusivity coefficient for the angular momentum partial differential equation (PDE) that best fits the experimental data. To further investigate the nonlinear dependence of the momentum diffusivity on other physical variables such as temperatures and densities, we introduce techniques from nonlinear regression and machine learning. 6pt [1] A.C. Sontag, et al., Nucl. Fusion 47, 1005 (2007).

  15. Constrained Ordination Analysis with Enrichment of Bell-Shaped Response Functions.

    PubMed

    Zhang, Yingjie; Thas, Olivier

    2016-01-01

    Constrained ordination methods aims at finding an environmental gradient along which the species abundances are maximally separated. The species response functions, which describe the expected abundance as a function of the environmental score, are according to the ecological fundamental niche theory only meaningful if they are bell-shaped. Many classical model-based ordination methods, however, use quadratic regression models without imposing the bell-shape and thus allowing for meaningless U-shaped response functions. The analysis output (e.g. a biplot) may therefore be potentially misleading and the conclusions are prone to errors. In this paper we present a log-likelihood ratio criterion with a penalisation term to enforce more bell-shaped response shapes. We report the results of a simulation study and apply our method to metagenomics data from microbial ecology. PMID:27100464

  16. Constrained Ordination Analysis with Enrichment of Bell-Shaped Response Functions

    PubMed Central

    Zhang, Yingjie; Thas, Olivier

    2016-01-01

    Constrained ordination methods aims at finding an environmental gradient along which the species abundances are maximally separated. The species response functions, which describe the expected abundance as a function of the environmental score, are according to the ecological fundamental niche theory only meaningful if they are bell-shaped. Many classical model-based ordination methods, however, use quadratic regression models without imposing the bell-shape and thus allowing for meaningless U-shaped response functions. The analysis output (e.g. a biplot) may therefore be potentially misleading and the conclusions are prone to errors. In this paper we present a log-likelihood ratio criterion with a penalisation term to enforce more bell-shaped response shapes. We report the results of a simulation study and apply our method to metagenomics data from microbial ecology. PMID:27100464

  17. Shape optimization of pressure gradient microphones

    NASA Technical Reports Server (NTRS)

    Norum, T. D.; Seiner, J. M.

    1977-01-01

    Recently developed finite element computer programs were utilized to investigate the influence of the shape of a body on its scattering field with the aim of determining the optimal shape for a Pressure Gradient Microphone (PGM). Circular cylinders of various aspect ratios were evaluated to choose the length to diameter ratio best suited for a dual element PGM application. Alterations of the basic cylindrical shape by rounding the edges and recessing at the centerline were also studied. It was found that for a + or - 1 db deviation from a linear pressure gradient response, a circular cylinder of aspect ratio near 0.5 was most suitable, yielding a useful upper frequency corresponding to ka = 1.8. The maximum increase in this upper frequency limit obtained through a number of shape alterations was only about 20 percent. An initial experimental evaluation of a single element cylindrical PGM of aspect ratio 0.18 utilizing a piezoresistive type sensor was also performed and is compared to the analytical results.

  18. Aperture shape optimization for IMRT treatment planning

    NASA Astrophysics Data System (ADS)

    Cassioli, A.; Unkelbach, J.

    2013-01-01

    We propose an algorithm for aperture shape optimization (ASO) for step and shoot delivery of intensity-modulated radiotherapy. The method is an approach to direct aperture optimization (DAO) that exploits gradient information to locally optimize the positions of the leafs of a multileaf collimator. Based on the dose-influence matrix, the dose distribution is locally approximated as a linear function of the leaf positions. Since this approximation is valid only in a small interval around the current leaf positions, we use a trust-region-like method to optimize the leaf positions: in one iteration, the leaf motion is confined to the beamlets where the leaf edges are currently positioned. This yields a well-behaved optimization problem for the leaf positions and the aperture weights, which can be solved efficiently. If, in one iteration, a leaf is moved to the edge of a beamlet, the leaf motion can be confined to the neighboring beamlet in the next iteration. This allows for large leaf position changes over the course of the algorithm. In this paper, the ASO algorithm is embedded into a column-generation approach to DAO. After a new aperture is added to the treatment plan, we use the ASO algorithm to simultaneously optimize aperture weights and leaf positions for the new set of apertures. We present results for a paraspinal tumor case, a prostate case and a head and neck case. The computational results indicate that, using this approach, treatment plans close to the ideal fluence map optimization solution can be obtained.

  19. Multidimensionally constrained covariant density functional theories—nuclear shapes and potential energy surfaces

    NASA Astrophysics Data System (ADS)

    Zhou, Shan-Gui

    2016-06-01

    The intrinsic nuclear shapes deviating from a sphere not only manifest themselves in nuclear collective states but also play important roles in determining nuclear potential energy surfaces (PES’s) and fission barriers. In order to describe microscopically and self-consistently nuclear shapes and PES’s with as many shape degrees of freedom as possible included, we developed multidimensionally constrained covariant density functional theories (MDC-CDFTs). In MDC-CDFTs, the axial symmetry and the reflection symmetry are both broken and all deformations characterized by {β }λ μ with even μ are considered. We have used the MDC-CDFTs to study PES’s and fission barriers of actinides, the non-axial octupole Y 32 correlations in N = 150 isotones and shapes of hypernuclei. In this Review we will give briefly the formalism of MDC-CDFTs and present the applications to normal nuclei.

  20. Shape-constrained multi-atlas segmentation of spleen in CT

    NASA Astrophysics Data System (ADS)

    Xu, Zhoubing; Li, Bo; Panda, Swetasudha; Asman, Andrew J.; Merkle, Kristen L.; Shanahan, Peter L.; Abramson, Richard G.; Landman, Bennett A.

    2014-03-01

    Spleen segmentation on clinically acquired CT data is a challenging problem given the complicity and variability of abdominal anatomy. Multi-atlas segmentation is a potential method for robust estimation of spleen segmentations, but can be negatively impacted by registration errors. Although labeled atlases explicitly capture information related to feasible organ shapes, multi-atlas methods have largely used this information implicitly through registration. We propose to integrate a level set shape model into the traditional label fusion framework to create a shape-constrained multi-atlas segmentation framework. Briefly, we (1) adapt two alternative atlas-to-target registrations to obtain the loose bounds on the inner and outer boundaries of the spleen shape, (2) project the fusion estimate to registered shape models, and (3) convert the projected shape into shape priors. With the constraint of the shape prior, our proposed method offers a statistically significant improvement in spleen labeling accuracy with an increase in DSC by 0.06, a decrease in symmetric mean surface distance by 4.01 mm, and a decrease in symmetric Hausdorff surface distance by 23.21 mm when compared to a locally weighted vote (LWV) method.

  1. Security-constrained optimization. Added dimension in utility systems optimal power flow

    SciTech Connect

    Degeneff, R.C.; Neugebauer, W. ); Saylor, C.H.; Corey, S.L.

    1988-10-01

    Compared to the tempered environment of the late 1960s and early 1970s, the 1980s have been, and will continue to be, a time of challenge for utilities. Today's utility executive most confront a spectrum of technical issues, ranging from wheeling and transmission line access to loop flow. There are other challenges to face. The traditional utility corporate structure is being reorganized, with utility staffs shrinking in size. And public scrutiny has become more intense as public bodies question the technical and environmental impact, as well as the financial and legal prudence of a utility's activities. Utilities are successfully meeting these challenges and becoming more productive, due, in part to their use of innovative computer programs and tools. One of these tools is an optimal power flow (OPF). The following describes a new dimension in the optimal power flow technology known as the security-constrained optimization (SCO) program.

  2. An effective hybrid cuckoo search and genetic algorithm for constrained engineering design optimization

    NASA Astrophysics Data System (ADS)

    Kanagaraj, G.; Ponnambalam, S. G.; Jawahar, N.; Mukund Nilakantan, J.

    2014-10-01

    This article presents an effective hybrid cuckoo search and genetic algorithm (HCSGA) for solving engineering design optimization problems involving problem-specific constraints and mixed variables such as integer, discrete and continuous variables. The proposed algorithm, HCSGA, is first applied to 13 standard benchmark constrained optimization functions and subsequently used to solve three well-known design problems reported in the literature. The numerical results obtained by HCSGA show competitive performance with respect to recent algorithms for constrained design optimization problems.

  3. Shape Optimization for Aerodynamic Noise Control

    NASA Astrophysics Data System (ADS)

    Marsden, Alison; Wang, Meng; Mohammadi, Bijan; Moin, Parviz

    2002-11-01

    The objective of this work is to develop optimal shape design methods for reducing airfoil trailing-edge noise. Accurate evaluation of the cost function gradient via classical methods is expensive in unsteady turbulent flow simulations. We have evaluated the method of incomplete sensitivities (Mohammadi and Pironneau), which is inexpensive, and has been successful in previous applications. Gradients are approximated by neglecting changes in the flow field relative to geometrical contributions at each time step. Initial tests applied to a model problem seemed promising, however, in some cases the method was found to break down. A systematic evaluation of the incomplete sensitivities method as applied to the present problem has been carried out by comparison with the full gradient. The contribution to the gradient from changes in the flow field were found to be important. The underlying physical reasoning will be discussed and alternative methods including adjoint approaches and evolutionary algorithms will be explored.

  4. Modeling the transformation stress of constrained shape memory alloy single crystals

    SciTech Connect

    Comstock, R.J. Jr.; Buchheit, T.E.; Somerday, M.; Wert, J.A.

    1996-09-01

    Shape memory alloys (SMA) are a unique class of engineering materials that can be further exploited with accurate polycrystal constitutive models. Previous investigators have modeled stress-induced martensite formation in unconstrained single crystals. Understanding stress-induced martensite formation in constrained single crystals is the next step towards the development of a constitutive model for textured polycrystalline SMA. Such models have been previously developed for imposition of axisymmetric strain on a polycrystal with random crystal orientation; the present paper expands the constrained single crystal SMA model to encompass arbitrary imposed strains. To evaluate the model, axisymmetric tension and compression strains and pure shear strain are imposed on three SMA: NiTi, Cu-Al-Ni ({beta}{sub 1}{yields}{gamma}{prime}{sub 1}) and Ni-Al. Model results are then used to understand the anisotropy and asymmetry of transformation stress in the three SMA considered. Finally, the impact of the present results on polycrystal behavior is addressed.

  5. Analytical optimal pulse shapes obtained with the aid of genetic algorithms

    NASA Astrophysics Data System (ADS)

    Guerrero, Rubén D.; Arango, Carlos A.; Reyes, Andrés

    2015-09-01

    We propose a methodology to design optimal pulses for achieving quantum optimal control on molecular systems. Our approach constrains pulse shapes to linear combinations of a fixed number of experimentally relevant pulse functions. Quantum optimal control is obtained by maximizing a multi-target fitness function using genetic algorithms. As a first application of the methodology, we generated an optimal pulse that successfully maximized the yield on a selected dissociation channel of a diatomic molecule. Our pulse is obtained as a linear combination of linearly chirped pulse functions. Data recorded along the evolution of the genetic algorithm contained important information regarding the interplay between radiative and diabatic processes. We performed a principal component analysis on these data to retrieve the most relevant processes along the optimal path. Our proposed methodology could be useful for performing quantum optimal control on more complex systems by employing a wider variety of pulse shape functions.

  6. Analytical optimal pulse shapes obtained with the aid of genetic algorithms

    SciTech Connect

    Guerrero, Rubén D.; Arango, Carlos A.; Reyes, Andrés

    2015-09-28

    We propose a methodology to design optimal pulses for achieving quantum optimal control on molecular systems. Our approach constrains pulse shapes to linear combinations of a fixed number of experimentally relevant pulse functions. Quantum optimal control is obtained by maximizing a multi-target fitness function using genetic algorithms. As a first application of the methodology, we generated an optimal pulse that successfully maximized the yield on a selected dissociation channel of a diatomic molecule. Our pulse is obtained as a linear combination of linearly chirped pulse functions. Data recorded along the evolution of the genetic algorithm contained important information regarding the interplay between radiative and diabatic processes. We performed a principal component analysis on these data to retrieve the most relevant processes along the optimal path. Our proposed methodology could be useful for performing quantum optimal control on more complex systems by employing a wider variety of pulse shape functions.

  7. Shape transition of endotaxial islands growth from kinetically constrained to equilibrium regimes

    SciTech Connect

    Li, Zhi-Peng; Tok, Engsoon; Foo, Yonglim

    2013-09-01

    Graphical abstract: - Highlights: • All Fe{sub 13}Ge{sub 8} islands will grow into Ge(0 0 1) substrate at temperatures from 350 to 675 °C. • Shape transition occurred from kinetically constrained to equilibrium regime. • All endotaxial islands can be clarified into two types. • The mechanisms of endotaxial growth and shape transition have been rationalized. - Abstract: A comprehensive study of Fe grown on Ge(0 0 1) substrates has been conducted at elevated temperatures, ranging from 350 to 675 °C. All iron germinide islands, with the same Fe{sub 13}Ge{sub 8} phase, grow into the Ge substrate with the same epitaxial relationship. Shape transition occurs from small square islands (low temperatures), to elongated orthogonal islands or orthogonal nanowires (intermediate temperatures), and then finally to large square orthogonal islands (high temperatures). According to both transmission electron microscopy (TEM) and atomic force microscopy (AFM) investigations, all islands can be defined as either type-I or type-II. Type-I islands usually form at kinetically constrained growth regimes, like truncated pyramids. Type-II islands usually appear at equilibrium growth regimes forming a dome-like shape. Based on a simple semi-quantitative model, type-II islands have a lower total energy per volume than type-I, which is considered as the dominant mechanism for this type of shape transition. Moreover, this study not only elucidates details of endotaxial growth in the Fe–Ge system, but also suggests the possibility of controlled fabrication of temperature-dependent nanostructures, especially in materials with dissimilar crystal structures.

  8. Numerical study of a matrix-free trust-region SQP method for equality constrained optimization.

    SciTech Connect

    Heinkenschloss, Matthias; Ridzal, Denis; Aguilo, Miguel Antonio

    2011-12-01

    This is a companion publication to the paper 'A Matrix-Free Trust-Region SQP Algorithm for Equality Constrained Optimization' [11]. In [11], we develop and analyze a trust-region sequential quadratic programming (SQP) method that supports the matrix-free (iterative, in-exact) solution of linear systems. In this report, we document the numerical behavior of the algorithm applied to a variety of equality constrained optimization problems, with constraints given by partial differential equations (PDEs).

  9. Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem

    NASA Astrophysics Data System (ADS)

    Chen, Wei

    2015-07-01

    In this paper, we discuss the portfolio optimization problem with real-world constraints under the assumption that the returns of risky assets are fuzzy numbers. A new possibilistic mean-semiabsolute deviation model is proposed, in which transaction costs, cardinality and quantity constraints are considered. Due to such constraints the proposed model becomes a mixed integer nonlinear programming problem and traditional optimization methods fail to find the optimal solution efficiently. Thus, a modified artificial bee colony (MABC) algorithm is developed to solve the corresponding optimization problem. Finally, a numerical example is given to illustrate the effectiveness of the proposed model and the corresponding algorithm.

  10. Characterizing and modeling the free recovery and constrained recovery behavior of a polyurethane shape memory polymer

    PubMed Central

    Volk, Brent L; Lagoudas, Dimitris C; Maitland, Duncan J

    2011-01-01

    In this work, tensile tests and one-dimensional constitutive modeling are performed on a high recovery force polyurethane shape memory polymer that is being considered for biomedical applications. The tensile tests investigate the free recovery (zero load) response as well as the constrained displacement recovery (stress recovery) response at extension values up to 25%, and two consecutive cycles are performed during each test. The material is observed to recover 100% of the applied deformation when heated at zero load in the second thermomechanical cycle, and a stress recovery of 1.5 MPa to 4.2 MPa is observed for the constrained displacement recovery experiments. After performing the experiments, the Chen and Lagoudas model is used to simulate and predict the experimental results. The material properties used in the constitutive model – namely the coefficients of thermal expansion, shear moduli, and frozen volume fraction – are calibrated from a single 10% extension free recovery experiment. The model is then used to predict the material response for the remaining free recovery and constrained displacement recovery experiments. The model predictions match well with the experimental data. PMID:22003272

  11. The expanded LaGrangian system for constrained optimization problems

    NASA Technical Reports Server (NTRS)

    Poore, A. B.

    1986-01-01

    Smooth penalty functions can be combined with numerical continuation/bifurcation techniques to produce a class of robust and fast algorithms for constrainted optimization problems. The key to the development of these algorithms is the Expanded Lagrangian System which is derived and analyzed in this work. This parameterized system of nonlinear equations contains the penalty path as a solution, provides a smooth homotopy into the first-order necessary conditions, and yields a global optimization technique. Furthermore, the inevitable ill-conditioning present in a sequential optimization algorithm is removed for three penalty methods: the quadratic penalty function for equality constraints, and the logarithmic barrier function (an interior method) and the quadratic loss function (an interior method) for inequality constraints. Although these techniques apply to optimization in general and to linear and nonlinear programming, calculus of variations, optimal control and parameter identification in particular, the development is primarily within the context of nonlinear programming.

  12. Constraining neutron guide optimizations with phase-space considerations

    NASA Astrophysics Data System (ADS)

    Bertelsen, Mads; Lefmann, Kim

    2016-09-01

    We introduce a method named the Minimalist Principle that serves to reduce the parameter space for neutron guide optimization when the required beam divergence is limited. The reduced parameter space will restrict the optimization to guides with a minimal neutron intake that are still theoretically able to deliver the maximal possible performance. The geometrical constraints are derived using phase-space propagation from moderator to guide and from guide to sample, while assuming that the optimized guides will achieve perfect transport of the limited neutron intake. Guide systems optimized using these constraints are shown to provide performance close to guides optimized without any constraints, however the divergence received at the sample is limited to the desired interval, even when the neutron transport is not limited by the supermirrors used in the guide. As the constraints strongly limit the parameter space for the optimizer, two control parameters are introduced that can be used to adjust the selected subspace, effectively balancing between maximizing neutron transport and avoiding background from unnecessary neutrons. One parameter is needed to describe the expected focusing abilities of the guide to be optimized, going from perfectly focusing to no correlation between position and velocity. The second parameter controls neutron intake into the guide, so that one can select exactly how aggressively the background should be limited. We show examples of guides optimized using these constraints which demonstrates the higher signal to noise than conventional optimizations. Furthermore the parameter controlling neutron intake is explored which shows that the simulated optimal neutron intake is close to the analytically predicted, when assuming that the guide is dominated by multiple scattering events.

  13. Optimal charging profiles for mechanically constrained lithium-ion batteries

    SciTech Connect

    Suthar, B; Ramadesigan, V; De, S; Braatz, RD; Subramanian, VR

    2014-01-01

    The cost and safety related issues of lithium-ion batteries require intelligent charging profiles that can efficiently utilize the battery. This paper illustrates the application of dynamic optimization in obtaining the optimal current profile for charging a lithium-ion battery using a single-particle model while incorporating intercalation-induced stress generation. In this paper, we focus on the problem of maximizing the charge stored in a given time while restricting the development of stresses inside the particle. Conventional charging profiles for lithium-ion batteries (e.g., constant current followed by constant voltage) were not derived by considering capacity fade mechanisms. These charging profiles are not only inefficient in terms of lifetime usage of the batteries but are also slower since they do not exploit the changing dynamics of the system. Dynamic optimization based approaches have been used to derive optimal charging and discharging profiles with different objective functions. The progress made in understanding the capacity fade mechanisms has paved the way for inclusion of that knowledge in deriving optimal controls. While past efforts included thermal constraints, this paper for the first time presents strategies for optimally charging batteries by guaranteeing minimal mechanical damage to the electrode particles during intercalation. In addition, an executable form of the code has been developed and provided. This code can be used to identify optimal charging profiles for any material and design parameters.

  14. Dose-shaping using targeted sparse optimization

    SciTech Connect

    Sayre, George A.; Ruan, Dan

    2013-07-15

    distribution than conventional objective functions. In particular, E{sub tot}{sup sparse}-optimized plans for the pancreas case and head-and-neck case exhibited substantially improved sparing of the spinal cord and parotid glands, respectively, while maintaining or improving sparing for other OARs and markedly improving PTV homogeneity. Plan deliverability for E{sub tot}{sup sparse}-optimized plans was shown to be better than their associated clinical plans, according to the two-dimensional modulation index.Conclusions: These results suggest that our formulation may be used to improve dose-shaping and OAR-sparing for complicated disease sites, such as the pancreas or head and neck. Furthermore, our objective function and constraints are linear and constitute a linear program, which converges to the global minimum quickly, and can be easily implemented in treatment planning software. Thus, the authors expect fast translation of our method to the clinic where it may have a positive impact on plan quality for challenging disease sites.

  15. Energy-Constrained Optimal Quantization for Wireless Sensor Networks

    NASA Astrophysics Data System (ADS)

    Luo, Xiliang; Giannakis, Georgios B.

    2007-12-01

    As low power, low cost, and longevity of transceivers are major requirements in wireless sensor networks, optimizing their design under energy constraints is of paramount importance. To this end, we develop quantizers under strict energy constraints to effect optimal reconstruction at the fusion center. Propagation, modulation, as well as transmitter and receiver structures are jointly accounted for using a binary symmetric channel model. We first optimize quantization for reconstructing a single sensor's measurement, and deriving the optimal number of quantization levels as well as the optimal energy allocation across bits. The constraints take into account not only the transmission energy but also the energy consumed by the transceiver's circuitry. Furthermore, we consider multiple sensors collaborating to estimate a deterministic parameter in noise. Similarly, optimum energy allocation and optimum number of quantization bits are derived and tested with simulated examples. Finally, we study the effect of channel coding on the reconstruction performance under strict energy constraints and jointly optimize the number of quantization levels as well as the number of channel uses.

  16. Topics in constrained optimal control: Spacecraft formation flying, constrained attitude control, and rank minimization problems

    NASA Astrophysics Data System (ADS)

    Kim, Yoonsoo

    This dissertation focuses on cooperative control between multiple agents (e.g., spacecraft, UAVs). In particular, motivated by future NASA's multiple spacecraft missions, we have been guided to consider fundamental aspects of spacecraft formation flying, including collision avoidance issues; constraints on the relative position and attitude. In this venue, we have realized that one of the main challenges is dealing with nonconvex state constraints. In this dissertation, we will address such complications using classical control theory, heuristic techniques, and more recent semidefinite programming-based approaches. We then proceed to consider communication and interspacecraft sensing issues in multiple agent dynamic system setting. In this direction, we will study (1) how conventional control techniques should be augmented to meet our design objectives when the information flow between multiple agents is taken into account; (2) which information structures (e.g., information graphs) yield best performance guarantees in terms of stability, robustness, or fast agreement. In this work, we provide theoretical answers to these problems. Moreover, as many design problems involving information networks and graphs lead to combinatorial problems, which can be formulated as rank optimization problems over matrices, we consider these class of problems in this dissertation. Rank optimization problems also arise in system theory and are considered to be of paramount importance in modern control synthesis problems.

  17. Order-Constrained Solutions in K-Means Clustering: Even Better than Being Globally Optimal

    ERIC Educational Resources Information Center

    Steinley, Douglas; Hubert, Lawrence

    2008-01-01

    This paper proposes an order-constrained K-means cluster analysis strategy, and implements that strategy through an auxiliary quadratic assignment optimization heuristic that identifies an initial object order. A subsequent dynamic programming recursion is applied to optimally subdivide the object set subject to the order constraint. We show that…

  18. A Constrained Optimization Algorithm for Total Energy Minimizationin Electronic Structure Calculation

    SciTech Connect

    Yang, Chao; Meza, Juan C.; Wang, Lin-Wang

    2005-07-26

    A new direct constrained optimization algorithm forminimizing the Kohn-Sham (KS) total energy functional is presented inthis paper. The key ingredients of this algorithm involve projecting thetotal energy functional into a sequences of subspaces of small dimensionsand seeking the minimizer of total energy functional within eachsubspace. The minimizer of a subspace energy functional not only providesa search direction along which the KS total energy functional decreasesbut also gives an optimal "step-length" to move along this searchdirection. A numerical example is provided to demonstrate that this newdirect constrained optimization algorithm can be more efficient than theself-consistent field (SCF) iteration.

  19. State-Constrained Optimal Control Problems of Impulsive Differential Equations

    SciTech Connect

    Forcadel, Nicolas; Rao Zhiping Zidani, Hasnaa

    2013-08-01

    The present paper studies an optimal control problem governed by measure driven differential systems and in presence of state constraints. The first result shows that using the graph completion of the measure, the optimal solutions can be obtained by solving a reparametrized control problem of absolutely continuous trajectories but with time-dependent state-constraints. The second result shows that it is possible to characterize the epigraph of the reparametrized value function by a Hamilton-Jacobi equation without assuming any controllability assumption.

  20. Two Error Bounds for Constrained Optimization Problems and Their Applications

    SciTech Connect

    Wang Changyu Zhang Jianzhong; Zhao Wenling

    2008-06-15

    This paper presents a global error bound for the projected gradient and a local error bound for the distance from a feasible solution to the optimal solution set of a nonlinear programming problem by using some characteristic quantities such as value function, trust region radius etc., which are appeared in the trust region method. As applications of these error bounds, we obtain sufficient conditions under which a sequence of feasible solutions converges to a stationary point or to an optimal solution, respectively, and a necessary and sufficient condition under which a sequence of feasible solutions converges to a Kuhn-Tucker point. Other applications involve finite termination of a sequence of feasible solutions. For general optimization problems, when the optimal solution set is generalized non-degenerate or gives generalized weak sharp minima, we give a necessary and sufficient condition for a sequence of feasible solutions to terminate finitely at a Kuhn-Tucker point, and a sufficient condition which guarantees that a sequence of feasible solutions terminates finitely at a stationary point.

  1. On optimal strategies in event-constrained differential games

    NASA Technical Reports Server (NTRS)

    Heymann, M.; Rajan, N.; Ardema, M.

    1985-01-01

    Combat games are formulated as zero-sum differential games with unilateral event constraints. An interior penalty function approach is employed to approximate optimal strategies for the players. The method is very attractive computationally and possesses suitable approximation and convergence properties.

  2. Dome Shape Optimization of Composite Pressure Vessels Based on Rational B-Spline Curve and Genetic Algorithm

    NASA Astrophysics Data System (ADS)

    Vafaeesefat, Abbas

    2009-10-01

    This paper presents an algorithm for shape optimization of composite pressure vessels head. The shape factor which is defined as the ratio of internal volume to weight of the vessel is used as an objective function. Design constrains consist of the geometrical limitations, winding conditions, and Tsai-Wu failure criterion. The geometry of dome shape is defined by a B-spline rational curve. By altering the weights of control points, depth of dome, and winding angle, the dome shape is changed. The proposed algorithm uses genetic algorithm and finite element analysis to optimize the design parameters. The algorithm is applied on a CNG pressure vessel and the results show that the proposed algorithm can efficiently define the optimal dome shape. This algorithm is general and can be used for general shape optimization.

  3. Improved Sensitivity Relations in State Constrained Optimal Control

    SciTech Connect

    Bettiol, Piernicola; Frankowska, Hélène; Vinter, Richard B.

    2015-04-15

    Sensitivity relations in optimal control provide an interpretation of the costate trajectory and the Hamiltonian, evaluated along an optimal trajectory, in terms of gradients of the value function. While sensitivity relations are a straightforward consequence of standard transversality conditions for state constraint free optimal control problems formulated in terms of control-dependent differential equations with smooth data, their verification for problems with either pathwise state constraints, nonsmooth data, or for problems where the dynamic constraint takes the form of a differential inclusion, requires careful analysis. In this paper we establish validity of both ‘full’ and ‘partial’ sensitivity relations for an adjoint state of the maximum principle, for optimal control problems with pathwise state constraints, where the underlying control system is described by a differential inclusion. The partial sensitivity relation interprets the costate in terms of partial Clarke subgradients of the value function with respect to the state variable, while the full sensitivity relation interprets the couple, comprising the costate and Hamiltonian, as the Clarke subgradient of the value function with respect to both time and state variables. These relations are distinct because, for nonsmooth data, the partial Clarke subdifferential does not coincide with the projection of the (full) Clarke subdifferential on the relevant coordinate space. We show for the first time (even for problems without state constraints) that a costate trajectory can be chosen to satisfy the partial and full sensitivity relations simultaneously. The partial sensitivity relation in this paper is new for state constraint problems, while the full sensitivity relation improves on earlier results in the literature (for optimal control problems formulated in terms of Lipschitz continuous multifunctions), because a less restrictive inward pointing hypothesis is invoked in the proof, and because

  4. A limited-memory algorithm for bound-constrained optimization

    SciTech Connect

    Byrd, R.H.; Peihuang, L.; Nocedal, J. |

    1996-03-01

    An algorithm for solving large nonlinear optimization problems with simple bounds is described. It is based on the gradient projection method and uses a limited-memory BFGS matrix to approximate the Hessian of the objective function. We show how to take advantage of the form of the limited-memory approximation to implement the algorithm efficiently. The results of numerical tests on a set of large problems are reported.

  5. Shape-Constrained Segmentation Approach for Arctic Multiyear Sea Ice Floe Analysis

    NASA Technical Reports Server (NTRS)

    Tarabalka, Yuliya; Brucker, Ludovic; Ivanoff, Alvaro; Tilton, James C.

    2013-01-01

    The melting of sea ice is correlated to increases in sea surface temperature and associated climatic changes. Therefore, it is important to investigate how rapidly sea ice floes melt. For this purpose, a new Tempo Seg method for multi temporal segmentation of multi year ice floes is proposed. The microwave radiometer is used to track the position of an ice floe. Then,a time series of MODIS images are created with the ice floe in the image center. A Tempo Seg method is performed to segment these images into two regions: Floe and Background.First, morphological feature extraction is applied. Then, the central image pixel is marked as Floe, and shape-constrained best merge region growing is performed. The resulting tworegionmap is post-filtered by applying morphological operators.We have successfully tested our method on a set of MODIS images and estimated the area of a sea ice floe as afunction of time.

  6. Directional control of lamellipodia extension by constraining cell shape and orienting cell tractional forces

    NASA Technical Reports Server (NTRS)

    Parker, Kevin Kit; Brock, Amy Lepre; Brangwynne, Cliff; Mannix, Robert J.; Wang, Ning; Ostuni, Emanuele; Geisse, Nicholas A.; Adams, Josephine C.; Whitesides, George M.; Ingber, Donald E.

    2002-01-01

    Directed cell migration is critical for tissue morphogenesis and wound healing, but the mechanism of directional control is poorly understood. Here we show that the direction in which cells extend their leading edge can be controlled by constraining cell shape using micrometer-sized extracellular matrix (ECM) islands. When cultured on square ECM islands in the presence of motility factors, cells preferentially extended lamellipodia, filopodia, and microspikes from their corners. Square cells reoriented their stress fibers and focal adhesions so that tractional forces were concentrated in these corner regions. When cell tension was dissipated, lamellipodia extension ceased. Mechanical interactions between cells and ECM that modulate cytoskeletal tension may therefore play a key role in the control of directional cell motility.

  7. Thermodynamics Constrains Allometric Scaling of Optimal Development Time in Insects

    PubMed Central

    Dillon, Michael E.; Frazier, Melanie R.

    2013-01-01

    Development time is a critical life-history trait that has profound effects on organism fitness and on population growth rates. For ectotherms, development time is strongly influenced by temperature and is predicted to scale with body mass to the quarter power based on 1) the ontogenetic growth model of the metabolic theory of ecology which describes a bioenergetic balance between tissue maintenance and growth given the scaling relationship between metabolism and body size, and 2) numerous studies, primarily of vertebrate endotherms, that largely support this prediction. However, few studies have investigated the allometry of development time among invertebrates, including insects. Abundant data on development of diverse insects provides an ideal opportunity to better understand the scaling of development time in this ecologically and economically important group. Insects develop more quickly at warmer temperatures until reaching a minimum development time at some optimal temperature, after which development slows. We evaluated the allometry of insect development time by compiling estimates of minimum development time and optimal developmental temperature for 361 insect species from 16 orders with body mass varying over nearly 6 orders of magnitude. Allometric scaling exponents varied with the statistical approach: standardized major axis regression supported the predicted quarter-power scaling relationship, but ordinary and phylogenetic generalized least squares did not. Regardless of the statistical approach, body size alone explained less than 28% of the variation in development time. Models that also included optimal temperature explained over 50% of the variation in development time. Warm-adapted insects developed more quickly, regardless of body size, supporting the “hotter is better” hypothesis that posits that ectotherms have a limited ability to evolutionarily compensate for the depressing effects of low temperatures on rates of biological processes

  8. Kinetic constrained optimization of the golf swing hub path.

    PubMed

    Nesbit, Steven M; McGinnis, Ryan S

    2014-12-01

    This study details an optimization of the golf swing, where the hand path and club angular trajectories are manipulated. The optimization goal was to maximize club head velocity at impact within the interaction kinetic limitations (force, torque, work, and power) of the golfer as determined through the analysis of a typical swing using a two-dimensional dynamic model. The study was applied to four subjects with diverse swing capabilities and styles. It was determined that it is possible for all subjects to increase their club head velocity at impact within their respective kinetic limitations through combined modifications to their respective hand path and club angular trajectories. The manner of the modifications, the degree of velocity improvement, the amount of kinetic reduction, and the associated kinetic limitation quantities were subject dependent. By artificially minimizing selected kinetic inputs within the optimization algorithm, it was possible to identify swing trajectory characteristics that indicated relative kinetic weaknesses of a subject. Practical implications are offered based upon the findings of the study. Key PointsThe hand path trajectory is an important characteristic of the golf swing and greatly affects club head velocity and golfer/club energy transfer.It is possible to increase the energy transfer from the golfer to the club by modifying the hand path and swing trajectories without increasing the kinetic output demands on the golfer.It is possible to identify relative kinetic output strengths and weakness of a golfer through assessment of the hand path and swing trajectories.Increasing any one of the kinetic outputs of the golfer can potentially increase the club head velocity at impact.The hand path trajectory has important influences over the club swing trajectory. PMID:25435779

  9. Kinetic Constrained Optimization of the Golf Swing Hub Path

    PubMed Central

    Nesbit, Steven M.; McGinnis, Ryan S.

    2014-01-01

    This study details an optimization of the golf swing, where the hand path and club angular trajectories are manipulated. The optimization goal was to maximize club head velocity at impact within the interaction kinetic limitations (force, torque, work, and power) of the golfer as determined through the analysis of a typical swing using a two-dimensional dynamic model. The study was applied to four subjects with diverse swing capabilities and styles. It was determined that it is possible for all subjects to increase their club head velocity at impact within their respective kinetic limitations through combined modifications to their respective hand path and club angular trajectories. The manner of the modifications, the degree of velocity improvement, the amount of kinetic reduction, and the associated kinetic limitation quantities were subject dependent. By artificially minimizing selected kinetic inputs within the optimization algorithm, it was possible to identify swing trajectory characteristics that indicated relative kinetic weaknesses of a subject. Practical implications are offered based upon the findings of the study. Key Points The hand path trajectory is an important characteristic of the golf swing and greatly affects club head velocity and golfer/club energy transfer. It is possible to increase the energy transfer from the golfer to the club by modifying the hand path and swing trajectories without increasing the kinetic output demands on the golfer. It is possible to identify relative kinetic output strengths and weakness of a golfer through assessment of the hand path and swing trajectories. Increasing any one of the kinetic outputs of the golfer can potentially increase the club head velocity at impact. The hand path trajectory has important influences over the club swing trajectory. PMID:25435779

  10. Aerodynamic Shape Optimization Based on Free-form Deformation

    NASA Technical Reports Server (NTRS)

    Samareh, Jamshid A.

    2004-01-01

    This paper presents a free-form deformation technique suitable for aerodynamic shape optimization. Because the proposed technique is independent of grid topology, we can treat structured and unstructured computational fluid dynamics grids in the same manner. The proposed technique is an alternative shape parameterization technique to a trivariate volume technique. It retains the flexibility and freedom of trivariate volumes for CFD shape optimization, but it uses a bivariate surface representation. This reduces the number of design variables by an order of magnitude, and it provides much better control for surface shape changes. The proposed technique is simple, compact, and efficient. The analytical sensitivity derivatives are independent of the design variables and are easily computed for use in a gradient-based optimization. The paper includes the complete formulation and aerodynamics shape optimization results.

  11. A constrained optimization algorithm based on the simplex search method

    NASA Astrophysics Data System (ADS)

    Mehta, Vivek Kumar; Dasgupta, Bhaskar

    2012-05-01

    In this article, a robust method is presented for handling constraints with the Nelder and Mead simplex search method, which is a direct search algorithm for multidimensional unconstrained optimization. The proposed method is free from the limitations of previous attempts that demand the initial simplex to be feasible or a projection of infeasible points to the nonlinear constraint boundaries. The method is tested on several benchmark problems and the results are compared with various evolutionary algorithms available in the literature. The proposed method is found to be competitive with respect to the existing algorithms in terms of effectiveness and efficiency.

  12. The International Solar Polar Mission - A problem in constrained optimization

    NASA Technical Reports Server (NTRS)

    Sweetser, T. H., III; Parmenter, M. E.; Pojman, J. L.

    1981-01-01

    The International Solar Polar Mission is sponsored jointly by NASA and the European Space Agency to study the sun and the solar environment from a new vantage point. Trajectories far out of the ecliptic plane are achieved by a gravity assist from Jupiter which sends the spacecraft back over the poles of the sun. The process for optimizing these trajectories is described. From the point of view of trajectory design, performance is measured by the time spent at high heliographic latitudes, but many trajectory constraints must be met to ensure spacecraft integrity and good scientific return. The design problem is tractable by closely approximating integrated trajectories with specially calibrated conics. Then the optimum trajectory is found primarily by graphical methods, which were easy to develop and use and are highly adaptable to changes in the plan of the mission.

  13. Human energy - optimal control of disturbance rejection during constrained standing.

    PubMed

    Mihelj, M; Munih, M; Ponikvar, M

    2003-01-01

    An optimal control system that enables a subject to stand without hand support in the sagittal plane was designed. The subject was considered as a double inverted pendulum structure with a voluntarily controlled degree of freedom in the upper trunk and artificially controlled degree of freedom in the ankle joints. The control system design was based on a minimization of cost function that estimated the effort of the ankle joint muscles through observation of the ground reaction force position relative to the ankle joint axis. By maintaining the centre of pressure close to the ankle joint axis the objective of the upright stance is fulfilled with minimal ankle muscle energy cost. The performance of the developed controller was evaluated in a simulation-based study. The results were compared with the responses of an unimpaired subject to different disturbances in the sagittal plane. The proposed cost function was shown to produce a reasonable approximation of human natural behaviour. PMID:12936049

  14. Experiences with optimizing airfoil shapes for maximum lift over drag

    NASA Technical Reports Server (NTRS)

    Doria, Michael L.

    1991-01-01

    The goal was to find airfoil shapes which maximize the ratio of lift over drag for given flow conditions. For a fixed Mach number, Reynolds number, and angle of attack, the lift and drag depend only on the airfoil shape. This then becomes a problem in optimization: find the shape which leads to a maximum value of lift over drag. The optimization was carried out using a self contained computer code for finding the minimum of a function subject to constraints. To find the lift and drag for each airfoil shape, a flow solution has to be obtained. This was done using a two dimensional Navier-Stokes code.

  15. Partial differential equations constrained combinatorial optimization on an adiabatic quantum computer

    NASA Astrophysics Data System (ADS)

    Chandra, Rishabh

    Partial differential equation-constrained combinatorial optimization (PDECCO) problems are a mixture of continuous and discrete optimization problems. PDECCO problems have discrete controls, but since the partial differential equations (PDE) are continuous, the optimization space is continuous as well. Such problems have several applications, such as gas/water network optimization, traffic optimization, micro-chip cooling optimization, etc. Currently, no efficient classical algorithm which guarantees a global minimum for PDECCO problems exists. A new mapping has been developed that transforms PDECCO problem, which only have linear PDEs as constraints, into quadratic unconstrained binary optimization (QUBO) problems that can be solved using an adiabatic quantum optimizer (AQO). The mapping is efficient, it scales polynomially with the size of the PDECCO problem, requires only one PDE solve to form the QUBO problem, and if the QUBO problem is solved correctly and efficiently on an AQO, guarantees a global optimal solution for the original PDECCO problem.

  16. Shape-Constrained Sparse and Low-Rank Decomposition for Auroral Substorm Detection.

    PubMed

    Yang, Xi; Gao, Xinbo; Tao, Dacheng; Li, Xuelong; Han, Bing; Li, Jie

    2016-01-01

    An auroral substorm is an important geophysical phenomenon that reflects the interaction between the solar wind and the Earth's magnetosphere. Detecting substorms is of practical significance in order to prevent disruption to communication and global positioning systems. However, existing detection methods can be inaccurate or require time-consuming manual analysis and are therefore impractical for large-scale data sets. In this paper, we propose an automatic auroral substorm detection method based on a shape-constrained sparse and low-rank decomposition (SCSLD) framework. Our method automatically detects real substorm onsets in large-scale aurora sequences, which overcomes the limitations of manual detection. To reduce noise interference inherent in current SLD methods, we introduce a shape constraint to force the noise to be assigned to the low-rank part (stationary background), thus ensuring the accuracy of the sparse part (moving object) and improving the performance. Experiments conducted on aurora sequences in solar cycle 23 (1996-2008) show that the proposed SCSLD method achieves good performance for motion analysis of aurora sequences. Moreover, the obtained results are highly consistent with manual analysis, suggesting that the proposed automatic method is useful and effective in practice. PMID:25826810

  17. Driver Hamiltonians for constrained optimization in quantum annealing

    NASA Astrophysics Data System (ADS)

    Hen, Itay; Sarandy, Marcelo S.

    2016-06-01

    One of the current major challenges surrounding the use of quantum annealers for solving practical optimization problems is their inability to encode even moderately sized problems, the main reason for this being the rigid layout of their quantum bits as well as their sparse connectivity. In particular, the implementation of constraints has become a major bottleneck in the embedding of practical problems, because the latter is typically achieved by adding harmful penalty terms to the problem Hamiltonian, a technique that often requires an all-to-all connectivity between the qubits. Recently, a novel technique designed to obviate the need for penalty terms was suggested; it is based on the construction of driver Hamiltonians that commute with the constraints of the problem, rendering the latter constants of motion. In this work we propose general guidelines for the construction of such driver Hamiltonians given an arbitrary set of constraints. We illustrate the broad applicability of our method by analyzing several diverse examples, namely, graph isomorphism, not-all-equal three-satisfiability, and the so-called Lechner-Hauke-Zoller constraints. We also discuss the significance of our approach in the context of current and future experimental quantum annealers.

  18. Topology and boundary shape optimization as an integrated design tool

    NASA Technical Reports Server (NTRS)

    Bendsoe, Martin Philip; Rodrigues, Helder Carrico

    1990-01-01

    The optimal topology of a two dimensional linear elastic body can be computed by regarding the body as a domain of the plane with a high density of material. Such an optimal topology can then be used as the basis for a shape optimization method that computes the optimal form of the boundary curves of the body. This results in an efficient and reliable design tool, which can be implemented via common FEM mesh generator and CAD type input-output facilities.

  19. Integrated topology and shape optimization in structural design

    NASA Technical Reports Server (NTRS)

    Bremicker, M.; Chirehdast, M.; Kikuchi, N.; Papalambros, P. Y.

    1990-01-01

    Structural optimization procedures usually start from a given design topology and vary its proportions or boundary shapes to achieve optimality under various constraints. Two different categories of structural optimization are distinguished in the literature, namely sizing and shape optimization. A major restriction in both cases is that the design topology is considered fixed and given. Questions concerning the general layout of a design (such as whether a truss or a solid structure should be used) as well as more detailed topology features (e.g., the number and connectivities of bars in a truss or the number of holes in a solid) have to be resolved by design experience before formulating the structural optimization model. Design quality of an optimized structure still depends strongly on engineering intuition. This article presents a novel approach for initiating formal structural optimization at an earlier stage, where the design topology is rigorously generated in addition to selecting shape and size dimensions. A three-phase design process is discussed: an optimal initial topology is created by a homogenization method as a gray level image, which is then transformed to a realizable design using computer vision techniques; this design is then parameterized and treated in detail by sizing and shape optimization. A fully automated process is described for trusses. Optimization of two dimensional solid structures is also discussed. Several application-oriented examples illustrate the usefulness of the proposed methodology.

  20. Designing nanomaterials with desired mechanical properties by constraining the evolution of their grain shapes.

    PubMed

    Tengen, Thomas Bobga

    2011-01-01

    growth mechanisms. It is observed that materials whose grains deviate further away from the spherical ones have more enhanced properties, while materials with spherical grains have lesser properties. It is observed that there exist critical states beyond which Hall-Petch Relationship changes to Reversed Hall-Petch Relationship. It can be concluded that if grain shapes in nanomaterials are constrained in the way they evolve, then nanomaterials with desired properties can be designed. PMID:22067060

  1. Designing nanomaterials with desired mechanical properties by constraining the evolution of their grain shapes

    PubMed Central

    2011-01-01

    growth mechanisms. It is observed that materials whose grains deviate further away from the spherical ones have more enhanced properties, while materials with spherical grains have lesser properties. It is observed that there exist critical states beyond which Hall-Petch Relationship changes to Reversed Hall-Petch Relationship. It can be concluded that if grain shapes in nanomaterials are constrained in the way they evolve, then nanomaterials with desired properties can be designed. PMID:22067060

  2. Domestic cat walking parallels human constrained optimization: optimization strategies and the comparison of normal and sensory deficient individuals.

    PubMed

    Bertram, John E A; Gutmann, Anne; Randev, Jabina; Hulliger, Manuel

    2014-08-01

    To evaluate how fundamental gait parameters used in walking (stride length, frequency, speed) are selected by cats we compared stride characteristics selected when walking on a solid surface to those selected when they were constrained to specific stride lengths using a pedestal walkway. Humans spontaneously select substantially different stride length-stride frequency-speed relationships in walking when each of these parameters is constrained, as in walking to a metronome beat (frequency constrained), evenly spaced floor markers (stride length constrained) or on a treadmill (speed constrained). In humans such adjustments largely provide energetic economy under the prescribed walking conditions. Cats show a similar shift in gait parameter selection between conditions as observed in humans. This suggests that cats (and by extension, quadrupedal mammals) also select gait parameters to optimize walking cost-effectiveness. Cats with a profound peripheral sensory deficit (from pyridoxine overdose) appeared to parallel the optimization seen in healthy cats, but without the same level of precision. Recent studies in humans suggest that gait optimization may proceed in two stages - a fast perception-based stage that provides the initial gait selection strategy which is then fine-tuned by feedback. The sensory deficit cats appeared unable to accomplish the feedback-dependent aspect of this process. PMID:24974156

  3. Constrained growth flips the direction of optimal phenological responses among annual plants.

    PubMed

    Lindh, Magnus; Johansson, Jacob; Bolmgren, Kjell; Lundström, Niklas L P; Brännström, Åke; Jonzén, Niclas

    2016-03-01

    Phenological changes among plants due to climate change are well documented, but often hard to interpret. In order to assess the adaptive value of observed changes, we study how annual plants with and without growth constraints should optimize their flowering time when productivity and season length changes. We consider growth constraints that depend on the plant's vegetative mass: self-shading, costs for nonphotosynthetic structural tissue and sibling competition. We derive the optimal flowering time from a dynamic energy allocation model using optimal control theory. We prove that an immediate switch (bang-bang control) from vegetative to reproductive growth is optimal with constrained growth and constant mortality. Increasing mean productivity, while keeping season length constant and growth unconstrained, delayed the optimal flowering time. When growth was constrained and productivity was relatively high, the optimal flowering time advanced instead. When the growth season was extended equally at both ends, the optimal flowering time was advanced under constrained growth and delayed under unconstrained growth. Our results suggests that growth constraints are key factors to consider when interpreting phenological flowering responses. It can help to explain phenological patterns along productivity gradients, and links empirical observations made on calendar scales with life-history theory. PMID:26548947

  4. Use of constrained optimization in the conceptual design of a medium-range subsonic transport

    NASA Technical Reports Server (NTRS)

    Sliwa, S. M.

    1980-01-01

    Constrained parameter optimization was used to perform the optimal conceptual design of a medium range transport configuration. The impact of choosing a given performance index was studied, and the required income for a 15 percent return on investment was proposed as a figure of merit. A number of design constants and constraint functions were systematically varied to document the sensitivities of the optimal design to a variety of economic and technological assumptions. A comparison was made for each of the parameter variations between the baseline configuration and the optimally redesigned configuration.

  5. Some shape optimization problems for eigenvalues

    NASA Astrophysics Data System (ADS)

    Gasimov, Yusif S.

    2008-02-01

    In this work we consider some inverse problems with respect to domain for the Laplace operator. The considered problems are reduced to the variational formulation. The equivalency of these problems is obtained under some conditions. The formula is obtained for the eigenvalue in the optimal domain.

  6. Optimal Shape Design of a Plane Diffuser in Turbulent Flow

    NASA Astrophysics Data System (ADS)

    Lim, Seokhyun; Choi, Haecheon

    2000-11-01

    Stratford (1959) experimentally designed an optimal shape of plane diffuser for maximum pressure recovery by having zero skin friction throughout the region of pressure rise. In the present study, we apply an algorithm of optimal shape design developed by Pironneau (1973, 1974) and Cabuk & Modi (1992) to a diffuser in turbulent flow, and show that maintaining zero skin friction in the pressure-rise region is an optimal condition for maximum pressure recovery at the diffuser exit. For turbulence model, we use the k-ɛ-v^2-f model by Durbin (1995) which is known to accurately predict flow with separation. Our results with this model agree well with the previous experimental and LES results for a diffuser shape tested by Obi et al. (1993). From this initial shape, an optimal diffuser shape for maximum pressure recovery is obtained through an iterative procedure. The optimal diffuser has indeed zero skin friction throughout the pressure-rise region, and thus there is no separation in the flow. For the optimal diffuser shape obtained, an LES is being conducted to investigate the turbulence characteristics near the zero-skin-friction wall. A preliminary result of LES will also be presented.

  7. Constraining the shape distribution and binary fractions of asteroids observed by NEOWISE

    NASA Astrophysics Data System (ADS)

    Sonnett, Sarah M.; Mainzer, Amy; Grav, Tommy; Masiero, Joseph; Bauer, James; Vernazza, Pierre; Ries, Judit Gyorgyey; Kramer, Emily

    2015-11-01

    Knowing the shape distribution of an asteroid population gives clues to its collisional and dynamical history. Constraining light curve amplitudes (brightness variations) offers a first-order approximation to the shape distribution, provided all asteroids in the distribution were subject to the same observing biases. Asteroids observed by the NEOWISE space mission at roughly the same heliocentric distances have essentially the same observing biases and can therefore be inter-compared. We used the archival NEOWISE photometry of a statistically significant sample of Jovian Trojans, Hildas, and Main belt asteroids to compare the amplitude (and by proxy, shape) distributions of L4 vs. L5 Trojans, Trojans vs. Hildas of the same size range, and several subpopulations of Main belt asteroids.For asteroids with near-fluid rubble pile structures, very large light curve amplitudes can only be explained by close or contact binary systems, offering the potential to catalog and characterize binaries within a population and gleaning more information on its dynamical evolution. Because the structure of most asteroids is not known to a high confidence level, objects with very high light curve amplitudes can only be considered candidate binaries. In Sonnett et al. (2015), we identified several binary candidates in the Jovian Trojan and Hilda populations. We have since been conducting a follow-up campaign to obtain densely sampled light curves of the binary candidates to allow detailed shape and binary modeling, helping identify true binaries. Here, we present preliminary results from the follow-up campaign, including rotation properties.This research was carried out at the Jet Propulsion Laboratory (JPL), California Institute of Technology (CalTech) under a contract with the National Aeronautics and Space Administration (NASA) and was supported by the NASA Postdoctoral Program at JPL. We make use of data products from the Wide-field Infrared Survey Explorer, which is a joint project

  8. Aerothermodynamic shape optimization of hypersonic blunt bodies

    NASA Astrophysics Data System (ADS)

    Eyi, Sinan; Yumuşak, Mine

    2015-07-01

    The aim of this study is to develop a reliable and efficient design tool that can be used in hypersonic flows. The flow analysis is based on the axisymmetric Euler/Navier-Stokes and finite-rate chemical reaction equations. The equations are coupled simultaneously and solved implicitly using Newton's method. The Jacobian matrix is evaluated analytically. A gradient-based numerical optimization is used. The adjoint method is utilized for sensitivity calculations. The objective of the design is to generate a hypersonic blunt geometry that produces the minimum drag with low aerodynamic heating. Bezier curves are used for geometry parameterization. The performances of the design optimization method are demonstrated for different hypersonic flow conditions.

  9. Mixed finite element formulation applied to shape optimization

    NASA Technical Reports Server (NTRS)

    Rodrigues, Helder; Taylor, John E.; Kikuchi, Noboru

    1988-01-01

    The development presented introduces a general form of mixed formulation for the optimal shape design problem. The associated optimality conditions are easily obtained without resorting to highly elaborate mathematical developments. Also, the physical significance of the adjoint problem is clearly defined with this formulation.

  10. Buckling, driven by constrained phase separation, of toroid-shaped hydrogels

    NASA Astrophysics Data System (ADS)

    Dimitriyev, Michael S.; Chang, Ya-Wen; Souslov, Anton; Fernandez-Nieves, Alberto; Goldbart, Paul M.

    We investigate the buckling process observed in connection with the temperature-induced shrinking of an elastic toroid composed of hydrogel. Hydrogels are polymeric network media that become swollen when mixed with water, provided the temperature is low enough. As the temperature is increased beyond a certain point, such gels undergo a first-order de-swelling transition to a de-mixed state, in which the network segregates from the water, resulting in a shrunken phase. It is known that the rapid heating of swollen hydrogels beyond the de-swelling transition results in the formation of a shrunken-phase boundary region, or shell. This shell hinders the expulsion of fluid associated with the equilibration of the sample interior, and gives rise to a prolonged period of coexistence between shrunken and swollen domains in the interior of the sample. In contrast with the spherical case, toroidal samples have been observed to undergo a constrained phase separation that is accompanied by a global buckling (or ``Pringling'') deformation of the sample shape. We present a model of hydrogel toroid Pringling in which such deformations are driven by this phase separation process.

  11. Low Complexity Models to improve Incomplete Sensitivities for Shape Optimization

    NASA Astrophysics Data System (ADS)

    Stanciu, Mugurel; Mohammadi, Bijan; Moreau, Stéphane

    2003-01-01

    The present global platform for simulation and design of multi-model configurations treat shape optimization problems in aerodynamics. Flow solvers are coupled with optimization algorithms based on CAD-free and CAD-connected frameworks. Newton methods together with incomplete expressions of gradients are used. Such incomplete sensitivities are improved using reduced models based on physical assumptions. The validity and the application of this approach in real-life problems are presented. The numerical examples concern shape optimization for an airfoil, a business jet and a car engine cooling axial fan.

  12. Shape optimization of high-speed penetrators: a review

    NASA Astrophysics Data System (ADS)

    Ben-Dor, Gabi; Dubinsky, Anatoly; Elperin, Tov

    2012-12-01

    In spite of a large number of publications on shape optimization of penetrating projectiles there are no dedicated surveys of these studies. The goal of the present review is to close this gap. The review includes more than 50 studies published since 1980 and devoted to solving particular problems of shape optimization of high-speed penetrators. We analyze publications which employed analytical and numerical method for shape optimization of high-speed penetrators against concrete, metal, fiber-reinforced plastic laminate and soil shields. We present classification of the mathematical models used for describing interaction between a penetrator and a shield. The reviewed studies are summarized in the table where we display the following information: the model; indicate whether the model accounts for or neglects friction at the surface of penetrator; criterion for optimization (depth of penetration into a semi-infinite shield, ballistic limit velocity for a shield having a finite thickness, several criteria); class of considered shapes of penetrators (bodies of revolution, different classes of 3-D bodies, etc.); method of solution (analytical or numerical); in comments we present additional information on formulation of the optimization problem. The survey also includes discussion on certain methodological facets in formulating shape optimization problems for high-speed penetrators.

  13. Optimal mass transport for shape matching and comparison.

    PubMed

    Su, Zhengyu; Wang, Yalin; Shi, Rui; Zeng, Wei; Sun, Jian; Luo, Feng; Gu, Xianfeng

    2015-11-01

    Surface based 3D shape analysis plays a fundamental role in computer vision and medical imaging. This work proposes to use optimal mass transport map for shape matching and comparison, focusing on two important applications including surface registration and shape space. The computation of the optimal mass transport map is based on Monge-Brenier theory, in comparison to the conventional method based on Monge-Kantorovich theory, this method significantly improves the efficiency by reducing computational complexity from O(n(2)) to O(n) . For surface registration problem, one commonly used approach is to use conformal map to convert the shapes into some canonical space. Although conformal mappings have small angle distortions, they may introduce large area distortions which are likely to cause numerical instability thus resulting failures of shape analysis. This work proposes to compose the conformal map with the optimal mass transport map to get the unique area-preserving map, which is intrinsic to the Riemannian metric, unique, and diffeomorphic. For shape space study, this work introduces a novel Riemannian framework, Conformal Wasserstein Shape Space, by combing conformal geometry and optimal mass transport theory. In our work, all metric surfaces with the disk topology are mapped to the unit planar disk by a conformal mapping, which pushes the area element on the surface to a probability measure on the disk. The optimal mass transport provides a map from the shape space of all topological disks with metrics to the Wasserstein space of the disk and the pullback Wasserstein metric equips the shape space with a Riemannian metric. We validate our work by numerous experiments and comparisons with prior approaches and the experimental results demonstrate the efficiency and efficacy of our proposed approach. PMID:26440265

  14. Three-dimensional shape optimization using boundary element method

    NASA Astrophysics Data System (ADS)

    Yamazaki, Koetsu; Sakamoto, Jiro; Kitano, Masami

    1993-04-01

    A practical design sensitivity calculation technique of displacements and stresses for three-dimensional bodies based on the direct differentiation method of discrete boundary integral equations is formulated in detail. Then, the sensitivity calculation technique is applied to determine optimum shapes of minimum weight subjected to stress constraints, where an approximated subproblem is constructed repeatedly and solved sequentially by the mathematical programming method. The shape optimization technique suggested here is applied to determine optimum shapes of a cavity shape in a cube and a connecting rod.

  15. A tractable approximation of non-convex chance constrained optimization with non-Gaussian uncertainties

    NASA Astrophysics Data System (ADS)

    Geletu, Abebe; Klöppel, Michael; Hoffmann, Armin; Li, Pu

    2015-04-01

    Chance constrained optimization problems in engineering applications possess highly nonlinear process models and non-convex structures. As a result, solving a nonlinear non-convex chance constrained optimization (CCOPT) problem remains as a challenging task. The major difficulty lies in the evaluation of probability values and gradients of inequality constraints which are nonlinear functions of stochastic variables. This article proposes a novel analytic approximation to improve the tractability of smooth non-convex chance constraints. The approximation uses a smooth parametric function to define a sequence of smooth nonlinear programs (NLPs). The sequence of optimal solutions of these NLPs remains always feasible and converges to the solution set of the CCOPT problem. Furthermore, Karush-Kuhn-Tucker (KKT) points of the approximating problems converge to a subset of KKT points of the CCOPT problem. Another feature of this approach is that it can handle uncertainties with both Gaussian and/or non-Gaussian distributions.

  16. An Intelligence Model with Max-Min Strategy for Constrained Evolutionary Optimization

    NASA Astrophysics Data System (ADS)

    Li, Xueqiang; Hao, Zhifeng; Huang, Han

    An intelligence model (IM) is proposed for constrained optimization in this paper. In this model, two main issues are considered: first, handling feasible and infeasible individuals in population, and second, recognizing the piecewise continuous Pareto front to avoid unnecessary search, it could reduce the amount of calculation and improve the efficiency of search. In addition, max-min strategy is used in selecting optimization. By integrating IM with evolutionary algorithm (EA), a generic constrained optimization evolutionary (IMEA) is derived. The new algorithm is applied to tackle 7 test instances on the CEC2009 MOEA competition, and the performance is assessed by IGD metric, the results suggest that it outperforms or performs similarly to other algorithms in CEC2009 competition.

  17. Shape optimization of a sodium cooled fast reactor

    NASA Astrophysics Data System (ADS)

    Schmitt, Damien; Allaire, Grégoire; Pantz, Olivier; Pozin, Nicolas

    2014-06-01

    Traditional designs of sodium cooled fast reactors have a positive sodium expansion feedback. During a loss of flow transient without scram, sodium heating and boiling thus insert a positive reactivity and prevents the power from decreasing. Recent studies led at CEA, AREVA and EDF show that cores with complex geometries can feature a very low or even a negative sodium void worth.(1, 2) Usual optimization methods for core conception are based on a parametric description of a given core design(3).(4) New core concepts and shapes can then only be found by hand. Shape optimization methods have proven very efficient in the conception of optimal structures under thermal or mechanical constraints.(5, 6) First studies show that these methods could be applied to sodium cooled core conception.(7) In this paper, a shape optimization method is applied to the conception of a sodium cooled fast reactor core with low sodium void worth. An objective function to be minimized is defined. It includes the reactivity change induced by a 1% sodium density decrease. The optimization variable is a displacement field changing the core geometry from one shape to another. Additionally, a parametric optimization of the plutonium content distribution of the core is made, so as to ensure that the core is kept critical, and that the power shape is flat enough. The final shape obtained must then be adjusted to a get realistic core layout. Its caracteristics can be checked with reference neutronic codes such as ERANOS. Thanks to this method, new shapes of reactor cores could be inferred, and lead to new design ideas.

  18. Improving the Hydrodynamic Performance of Diffuser Vanes via Shape Optimization

    NASA Technical Reports Server (NTRS)

    Goel, Tushar; Dorney, Daniel J.; Haftka, Raphael T.; Shyy, Wei

    2007-01-01

    The performance of a diffuser in a pump stage depends on its configuration and placement within the stage. The influence of vane shape on the hydrodynamic performance of a diffuser has been studied. The goal of this effort has been to improve the performance of a pump stage by optimizing the shape of the diffuser vanes. The shape of the vanes was defined using Bezier curves and circular arcs. Surrogate model based tools were used to identify regions of the vane that have a strong influence on its performance. Optimization of the vane shape, in the absence of manufacturing, and stress constraints, led to a nearly nine percent reduction in the total pressure losses compared to the baseline design by reducing the extent of the base separation.

  19. On Shape Optimization for an Evolution Coupled System

    SciTech Connect

    Leugering, G.; Novotny, A. A. Perla Menzala, G.

    2011-12-15

    A shape optimization problem in three spatial dimensions for an elasto-dynamic piezoelectric body coupled to an acoustic chamber is introduced. Well-posedness of the problem is established and first order necessary optimality conditions are derived in the framework of the boundary variation technique. In particular, the existence of the shape gradient for an integral shape functional is obtained, as well as its regularity, sufficient for applications e.g. in modern loudspeaker technologies. The shape gradients are given by functions supported on the moving boundaries. The paper extends results obtained by the authors in (Math. Methods Appl. Sci. 33(17):2118-2131, 2010) where a similar problem was treated without acoustic coupling.

  20. Optimizing Data Locality for Fork/Join Programs Using Constrained Work Stealing

    SciTech Connect

    Lifflander, Jonathan; Krishnamoorthy, Sriram; Kale, Laxmikant

    2014-11-16

    We present an approach to improving data locality across different phases of fork/join programs scheduled using work stealing. The approach consists of: (1) user-specified and automated approaches to constructing a steal tree, the schedule of steal operations and (2) constrained work stealing algorithms that constrain the actions of the scheduler to mirror a given steal tree. These are combined to construct work stealing schedules that maximize data locality across computation phases while ensuring load balance within each phase. These algorithms are also used to demonstrate dynamic coarsening, an optimization to improve spatial locality and sequential overheads by combining many finer-grained tasks into coarser tasks while ensuring sufficient concurrency for locality-optimized load balance. Implementation and evaluation in Cilk demonstrate performance improvements of up to 2.5x on 80 cores. We also demonstrate that dynamic coarsening can combine the performance benefits of coarse task specification with the adaptability of finer tasks.

  1. On meeting capital requirements with a chance-constrained optimization model.

    PubMed

    Atta Mills, Ebenezer Fiifi Emire; Yu, Bo; Gu, Lanlan

    2016-01-01

    This paper deals with a capital to risk asset ratio chance-constrained optimization model in the presence of loans, treasury bill, fixed assets and non-interest earning assets. To model the dynamics of loans, we introduce a modified CreditMetrics approach. This leads to development of a deterministic convex counterpart of capital to risk asset ratio chance constraint. We pursue the scope of analyzing our model under the worst-case scenario i.e. loan default. The theoretical model is analyzed by applying numerical procedures, in order to administer valuable insights from a financial outlook. Our results suggest that, our capital to risk asset ratio chance-constrained optimization model guarantees banks of meeting capital requirements of Basel III with a likelihood of 95 % irrespective of changes in future market value of assets. PMID:27186464

  2. Design of SLM-constrained MACE filters using simulated annealing optimization

    NASA Astrophysics Data System (ADS)

    Khan, Ajmal; Rajan, P. Karivaratha

    1993-10-01

    Among the available filters for pattern recognition, the MACE filter produces the sharpest peak with very small sidelobes. However, when these filters are implemented using practical spatial light modulators (SLMs), because of the constrained nature of the amplitude and phase modulation characteristics of the SLM, the implementation is no longer optimal. The resulting filter response does not produce high accuracy in the recognition of the test images. In this paper, this deterioration in response is overcome by designing constrained MACE filters such that the filter is allowed to have only those values of phase-amplitude combination that can be implemented on a specified SLM. The design is carried out using simulated annealing optimization technique. The algorithm developed and the results obtained on computer simulations of the designed filters are presented.

  3. Optimization of entry-vehicle shapes during conceptual design

    NASA Astrophysics Data System (ADS)

    Dirkx, D.; Mooij, E.

    2014-01-01

    During the conceptual design of a re-entry vehicle, the vehicle shape and geometry can be varied and its impact on performance can be evaluated. In this study, the shape optimization of two classes of vehicles has been studied: a capsule and a winged vehicle. Their aerodynamic characteristics were analyzed using local-inclination methods, automatically selected per vehicle segment. Entry trajectories down to Mach 3 were calculated assuming trimmed conditions. For the winged vehicle, which has both a body flap and elevons, a guidance algorithm to track a reference heat-rate was used. Multi-objective particle swarm optimization was used to optimize the shape using objectives related to mass, volume and range. The optimizations show a large variation in vehicle performance over the explored parameter space. Areas of very strong non-linearity are observed in the direct neighborhood of the two-dimensional Pareto fronts. This indicates the need for robust exploration of the influence of vehicle shapes on system performance during engineering trade-offs, which are performed during conceptual design. A number of important aspects of the influence of vehicle behavior on the Pareto fronts are observed and discussed. There is a nearly complete convergence to narrow-wing solutions for the winged vehicle. Also, it is found that imposing pitch-stability for the winged vehicle at all angles of attack results in vehicle shapes which require upward control surface deflections during the majority of the entry.

  4. Shape optimization of rigid inclusions for elastic plates with cracks

    NASA Astrophysics Data System (ADS)

    Shcherbakov, Viktor

    2016-06-01

    In the paper, we consider an optimal control problem of finding the most safe rigid inclusion shapes in elastic plates with cracks from the viewpoint of the Griffith rupture criterion. We make use of a general Kirchhoff-Love plate model with both vertical and horizontal displacements, and nonpenetration conditions are fulfilled on the crack faces. The dependence of the first derivative of the energy functional with respect to the crack length on regular shape perturbations of the rigid inclusion is analyzed. It is shown that there exists a solution of the optimal control problem.

  5. Shape Optimization of Rubber Bushing Using Differential Evolution Algorithm

    PubMed Central

    2014-01-01

    The objective of this study is to design rubber bushing at desired level of stiffness characteristics in order to achieve the ride quality of the vehicle. A differential evolution algorithm based approach is developed to optimize the rubber bushing through integrating a finite element code running in batch mode to compute the objective function values for each generation. Two case studies were given to illustrate the application of proposed approach. Optimum shape parameters of 2D bushing model were determined by shape optimization using differential evolution algorithm. PMID:25276848

  6. A geometric representation scheme suitable for shape optimization

    NASA Technical Reports Server (NTRS)

    Tortorelli, Daniel A.

    1990-01-01

    A geometric representation scheme is outlined which utilizes the natural design variable concept. A base configuration with distinct topological features is created. This configuration is then deformed to define components with similar topology but different geometry. The values of the deforming loads are the geometric entities used in the shape representation. The representation can be used for all geometric design studies; it is demonstrated here for structural optimization. This technique can be used in parametric design studies, where the system response is defined as functions of geometric entities. It can also be used in shape optimization, where the geometric entities of an original design are modified to maximize performance and satisfy constraints. Two example problems are provided. A cantilever beam is elongated to meet new design specifications and then optimized to reduce volume and satisfy stress constraints. A similar optimization problem is presented for an automobile crankshaft section. The finite element method is used to perform the analyses.

  7. Three-dimensional shape optimization using the boundary element method

    NASA Astrophysics Data System (ADS)

    Yamazaki, Koetsu; Sakamoto, Jiro; Kitano, Masami

    1994-06-01

    A practical design sensitivity calculation technique of displacements and stresses for three-dimensional bodies based on the direct differentiation method of discrete boundary integral equations is formulated in detail. Then the sensitivity calculation technique is applied to determine optimum shapes of minimum weight subjected to stress constraints, where an approximated subproblem is constructed repeatedly and solved sequentially by the mathematical programming method. The shape optimization technique suggested here is applied to determine optimum shapes of a cavity in a cube and a connecting rod.

  8. Profile Optimization Method for Robust Airfoil Shape Optimization in Viscous Flow

    NASA Technical Reports Server (NTRS)

    Li, Wu

    2003-01-01

    Simulation results obtained by using FUN2D for robust airfoil shape optimization in transonic viscous flow are included to show the potential of the profile optimization method for generating fairly smooth optimal airfoils with no off-design performance degradation.

  9. Adjoint-based airfoil shape optimization in transonic flow

    NASA Astrophysics Data System (ADS)

    Gramanzini, Joe-Ray

    The primary focus of this work is efficient aerodynamic shape optimization in transonic flow. Adjoint-based optimization techniques are employed on airfoil sections and evaluated in terms of computational accuracy as well as efficiency. This study examines two test cases proposed by the AIAA Aerodynamic Design Optimization Discussion Group. The first is a two-dimensional, transonic, inviscid, non-lifting optimization of a Modified-NACA 0012 airfoil. The second is a two-dimensional, transonic, viscous optimization problem using a RAE 2822 airfoil. The FUN3D CFD code of NASA Langley Research Center is used as the ow solver for the gradient-based optimization cases. Two shape parameterization techniques are employed to study their effect and the number of design variables on the final optimized shape: Multidisciplinary Aerodynamic-Structural Shape Optimization Using Deformation (MASSOUD) and the BandAids free-form deformation technique. For the two airfoil cases, angle of attack is treated as a global design variable. The thickness and camber distributions are the local design variables for MASSOUD, and selected airfoil surface grid points are the local design variables for BandAids. Using the MASSOUD technique, a drag reduction of 72.14% is achieved for the NACA 0012 case, reducing the total number of drag counts from 473.91 to 130.59. Employing the BandAids technique yields a 78.67% drag reduction, from 473.91 to 99.98. The RAE 2822 case exhibited a drag reduction from 217.79 to 132.79 counts, a 39.05% decrease using BandAids.

  10. Transonic Wing Shape Optimization Using a Genetic Algorithm

    NASA Technical Reports Server (NTRS)

    Holst, Terry L.; Pulliam, Thomas H.; Kwak, Dochan (Technical Monitor)

    2002-01-01

    A method for aerodynamic shape optimization based on a genetic algorithm approach is demonstrated. The algorithm is coupled with a transonic full potential flow solver and is used to optimize the flow about transonic wings including multi-objective solutions that lead to the generation of pareto fronts. The results indicate that the genetic algorithm is easy to implement, flexible in application and extremely reliable.

  11. Optimal Heat Collection Element Shapes for Parabolic Trough Concentrators

    SciTech Connect

    Bennett, C

    2007-11-15

    For nearly 150 years, the cross section of the heat collection tubes used at the focus of parabolic trough solar concentrators has been circular. This type of tube is obviously simple and easily fabricated, but it is not optimal. It is shown in this article that the optimal shape, assuming a perfect parabolic figure for the concentrating mirror, is instead oblong, and is approximately given by a pair of facing parabolic segments.

  12. Configuration-shape-size optimization of space structures by material redistribution

    NASA Technical Reports Server (NTRS)

    Vandenbelt, D. N.; Crivelli, L. A.; Felippa, C. A.

    1993-01-01

    This project investigates the configuration-shape-size optimization (CSSO) of orbiting and planetary space structures. The project embodies three phases. In the first one the material-removal CSSO method introduced by Kikuchi and Bendsoe (KB) is further developed to gain understanding of finite element homogenization techniques as well as associated constrained optimization algorithms that must carry along a very large number (thousands) of design variables. In the CSSO-KB method an optimal structure is 'carved out' of a design domain initially filled with finite elements, by allowing perforations (microholes) to develop, grow and merge. The second phase involves 'materialization' of space structures from the void, thus reversing the carving process. The third phase involves analysis of these structures for construction and operational constraints, with emphasis in packaging and deployment. The present paper describes progress in selected areas of the first project phase and the start of the second one.

  13. Optimal shape and motion of undulatory swimming organisms

    PubMed Central

    Tokić, Grgur; Yue, Dick K. P.

    2012-01-01

    Undulatory swimming animals exhibit diverse ranges of body shapes and motion patterns and are often considered as having superior locomotory performance. The extent to which morphological traits of swimming animals have evolved owing to primarily locomotion considerations is, however, not clear. To shed some light on that question, we present here the optimal shape and motion of undulatory swimming organisms obtained by optimizing locomotive performance measures within the framework of a combined hydrodynamical, structural and novel muscular model. We develop a muscular model for periodic muscle contraction which provides relevant kinematic and energetic quantities required to describe swimming. Using an evolutionary algorithm, we performed a multi-objective optimization for achieving maximum sustained swimming speed U and minimum cost of transport (COT)—two conflicting locomotive performance measures that have been conjectured as likely to increase fitness for survival. Starting from an initial population of random characteristics, our results show that, for a range of size scales, fish-like body shapes and motion indeed emerge when U and COT are optimized. Inherent boundary-layer-dependent allometric scaling between body mass and kinematic and energetic quantities of the optimal populations is observed. The trade-off between U and COT affects the geometry, kinematics and energetics of swimming organisms. Our results are corroborated by empirical data from swimming animals over nine orders of magnitude in size, supporting the notion that optimizing U and COT could be the driving force of evolution in many species. PMID:22456876

  14. Procedures for shape optimization of gas turbine disks

    NASA Technical Reports Server (NTRS)

    Cheu, Tsu-Chien

    1989-01-01

    Two procedures, the feasible direction method and sequential linear programming, for shape optimization of gas turbine disks are presented. The objective of these procedures is to obtain optimal designs of turbine disks with geometric and stress constraints. The coordinates of the selected points on the disk contours are used as the design variables. Structural weight, stress and their derivatives with respect to the design variables are calculated by an efficient finite element method for design senitivity analysis. Numerical examples of the optimal designs of a disk subjected to thermo-mechanical loadings are presented to illustrate and compare the effectiveness of these two procedures.

  15. Optimal Shapes of Surface Slip Driven Self-Propelled Microswimmers

    NASA Astrophysics Data System (ADS)

    Vilfan, Andrej

    2012-09-01

    We study the efficiency of self-propelled swimmers at low Reynolds numbers, assuming that the local energetic cost of maintaining a propulsive surface slip velocity is proportional to the square of that velocity. We determine numerically the optimal shape of a swimmer such that the total power is minimal while maintaining the volume and the swimming speed. The resulting shape depends strongly on the allowed maximum curvature. When sufficient curvature is allowed the optimal swimmer exhibits two protrusions along the symmetry axis. The results show that prolate swimmers such as Paramecium have an efficiency that is ˜20% higher than that of a spherical body, whereas some microorganisms have shapes that allow even higher efficiency.

  16. A free boundary approach to shape optimization problems

    PubMed Central

    Bucur, D.; Velichkov, B.

    2015-01-01

    The analysis of shape optimization problems involving the spectrum of the Laplace operator, such as isoperimetric inequalities, has known in recent years a series of interesting developments essentially as a consequence of the infusion of free boundary techniques. The main focus of this paper is to show how the analysis of a general shape optimization problem of spectral type can be reduced to the analysis of particular free boundary problems. In this survey article, we give an overview of some very recent technical tools, the so-called shape sub- and supersolutions, and show how to use them for the minimization of spectral functionals involving the eigenvalues of the Dirichlet Laplacian, under a volume constraint. PMID:26261362

  17. Elliptical Cavity Shape Optimization for Acceleration and HOM Damping

    SciTech Connect

    Haipeng Wang; Robert Rimmer; Genfa Wu

    2005-05-01

    We report a survey of center cell shapes developed for Superconducting Radio Frequency (SRF) multi-cell cavities for different projects. Using a set of normalized parameters, we compare the designs for different frequencies and particle velocities for the fundamental mode. Using dispersion curves of High Order Modes (HOM) (frequency verse phase advance) calculated by MAFIA for a single cell, we further optimize the cavity shape to avoid a light cone line crossing at the dangerous resonance frequencies determined by the beam bunch structure and eliminate the trapped (or high R/Q) modes with a low group velocity. We developed this formulation to optimize a 5-cell, 750MHz cavity shape, with good real-estate accelerating gradient and a strong HOM damping waveguide structure for the JLab 1MW ERL-FEL project.

  18. Automatic 3D kidney segmentation based on shape constrained GC-OAAM

    NASA Astrophysics Data System (ADS)

    Chen, Xinjian; Summers, Ronald M.; Yao, Jianhua

    2011-03-01

    The kidney can be classified into three main tissue types: renal cortex, renal medulla and renal pelvis (or collecting system). Dysfunction of different renal tissue types may cause different kidney diseases. Therefore, accurate and efficient segmentation of kidney into different tissue types plays a very important role in clinical research. In this paper, we propose an automatic 3D kidney segmentation method which segments the kidney into the three different tissue types: renal cortex, medulla and pelvis. The proposed method synergistically combines active appearance model (AAM), live wire (LW) and graph cut (GC) methods, GC-OAAM for short. Our method consists of two main steps. First, a pseudo 3D segmentation method is employed for kidney initialization in which the segmentation is performed slice-by-slice via a multi-object oriented active appearance model (OAAM) method. An improved iterative model refinement algorithm is proposed for the AAM optimization, which synergistically combines the AAM and LW method. Multi-object strategy is applied to help the object initialization. The 3D model constraints are applied to the initialization result. Second, the object shape information generated from the initialization step is integrated into the GC cost computation. A multi-label GC method is used to segment the kidney into cortex, medulla and pelvis. The proposed method was tested on 19 clinical arterial phase CT data sets. The preliminary results showed the feasibility and efficiency of the proposed method.

  19. Determination of poroelastic properties of cartilage using constrained optimization coupled with finite element analysis

    PubMed Central

    Chung, Chen-Yuan; Mansour, Joseph M.

    2014-01-01

    The feasibility of determining biphasic material properties using a finite element model of stress relaxation coupled with two types of constrained optimization to match measured data was investigated. Comparison of these two approaches, a zero-order method and a gradient-based algorithm, validated the predicted material properties. Optimizations were started from multiple different initial guesses of material properties (design variables) to establish the robustness of the optimization. Overall, the optimal values are close to those found by Cohen et al., (1998), but these small differences produced a marked improvement in the fit to the measured stress relaxation. Despite the greater deviation in the optimized values obtained from the zero-order method, both optimization procedures produced material properties that gave equally good overall fits to the measured data. Furthermore, optimized values were all within the expected range of material properties. Modeling stress relaxation using the optimized material properties showed an excellent fit to the entire time history of the measured data. PMID:25460921

  20. Determination of poroelastic properties of cartilage using constrained optimization coupled with finite element analysis.

    PubMed

    Chung, Chen-Yuan; Mansour, Joseph M

    2015-02-01

    The feasibility of determining biphasic material properties using a finite element model of stress relaxation coupled with two types of constrained optimization to match measured data was investigated. Comparison of these two approaches, a zero-order method and a gradient-based algorithm, validated the predicted material properties. Optimizations were started from multiple different initial guesses of material properties (design variables) to establish the robustness of the optimization. Overall, the optimal values are close to those found by Cohen et al. (1998) but these small differences produced a marked improvement in the fit to the measured stress relaxation. Despite the greater deviation in the optimized values obtained from the zero-order method, both optimization procedures produced material properties that gave equally good overall fits to the measured data. Furthermore, optimized values were all within the expected range of material properties. Modeling stress relaxation using the optimized material properties showed an excellent fit to the entire time history of the measured data. PMID:25460921

  1. Genetic Algorithms Applied to Multi-Objective Aerodynamic Shape Optimization

    NASA Technical Reports Server (NTRS)

    Holst, Terry L.

    2004-01-01

    A genetic algorithm approach suitable for solving multi-objective optimization problems is described and evaluated using a series of aerodynamic shape optimization problems. Several new features including two variations of a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. A new masking array capability is included allowing any gene or gene subset to be eliminated as decision variables from the design space. This allows determination of the effect of a single gene or gene subset on the pareto optimal solution. Results indicate that the genetic algorithm optimization approach is flexible in application and reliable. The binning selection algorithms generally provide pareto front quality enhancements and moderate convergence efficiency improvements for most of the problems solved.

  2. A class of collinear scaling algorithms for bound-constrained optimization

    NASA Astrophysics Data System (ADS)

    Ariyawansa, K. A.; Tabor, Wayne L.

    2007-10-01

    A family of algorithms for approximate solution of the bound-constrained minimization problem was introduced in [K.A. Ariyawansa, W.L. Tabor, A class of collinear scaling algorithms for bound-constrained optimization: Derivation and computational results, Technical Report 2003-1, Department of Mathematics, Washington State University, Pullman, WA, 2003, submitted for publication. Available at http://www.math.wsu.edu/math/TRS/2003-1.pdf]. These algorithms employ the standard barrier method, with the inner iteration based on trust region methods. Local models are conic functions rather than the usual quadratic functions, and are required to match first and second derivatives of the barrier function at the current iterate. The various members of the family are distinguished by the choice of a vector-valued parameter, which is the zero vector in the degenerate case that quadratic local models are used. This paper presents a convergence analysis of the family of algorithms presented in [K.A. Ariyawansa, W.L. Tabor, A class of collinear scaling algorithms for bound-constrained optimization: Derivation and computational results, Technical Report 2003-1, Department of Mathematics, Washington State University, Pullman, WA, 2003, submitted for publication. Available at http://www.math.wsu.edu/math/TRS/2003-1.pdf]. Specifically, convergence properties similar to those of barrier methods using quadratic local models are established.

  3. Optimization of bow shape for a non ballast water ship

    NASA Astrophysics Data System (ADS)

    Van He, Ngo; Ikeda, Yoshiho

    2013-09-01

    In this research, a commercial CFD code "Fluent" was applied to optimization of bulbous bow shape for a non ballast water ships (NBS). The ship was developed at the Laboratory of the authors in Osaka Prefecture University, Japan. At first, accuracy of the CFD code was validated by comparing the CFD results with experimental results at towing tank of Osaka Prefecture University. In the optimizing process, the resistances acting on ships in calm water and in regular head waves were defined as the object function. Following features of bulbous bow shapes were considered as design parameters: volume of bulbous bow, height of its volume center, angle of bow bottom, and length of bulbous bow. When referring to the computed results given by the CFD like resistance, pressure and wave pattern made by ships in calm water and in waves, an optimal bow shape for ships was discovered by comparing the results in the series of bow shapes. In the computation on waves, the ship is in fully captured condition because shorter waves, λ/ L pp <0.6, are assumed.

  4. Shape Optimization and Supremal Minimization Approaches in Landslides Modeling

    SciTech Connect

    Hassani, Riad Ionescu, Ioan R. Lachand-Robert, Thomas

    2005-10-15

    The steady-state unidirectional (anti-plane) flow for a Bingham fluid is considered. We take into account the inhomogeneous yield limit of the fluid, which is well adjusted to the description of landslides. The blocking property is analyzed and we introduce the safety factor which is connected to two optimization problems in terms of velocities and stresses. Concerning the velocity analysis the minimum problem in Bv({omega}) is equivalent to a shape-optimization problem. The optimal set is the part of the land which slides whenever the loading parameter becomes greater than the safety factor. This is proved in the one-dimensional case and conjectured for the two-dimensional flow. For the stress-optimization problem we give a stream function formulation in order to deduce a minimum problem in W{sup 1,{infinity}}({omega}) and we prove the existence of a minimizer. The L{sup p}({omega}) approximation technique is used to get a sequence of minimum problems for smooth functionals. We propose two numerical approaches following the two analysis presented before.First, we describe a numerical method to compute the safety factor through equivalence with the shape-optimization problem.Then the finite-element approach and a Newton method is used to obtain a numerical scheme for the stress formulation. Some numerical results are given in order to compare the two methods. The shape-optimization method is sharp in detecting the sliding zones but the convergence is very sensitive to the choice of the parameters. The stress-optimization method is more robust, gives precise safety factors but the results cannot be easily compiled to obtain the sliding zone.

  5. A Near-Optimal Distributed QoS Constrained Routing Algorithm for Multichannel Wireless Sensor Networks

    PubMed Central

    Lin, Frank Yeong-Sung; Hsiao, Chiu-Han; Yen, Hong-Hsu; Hsieh, Yu-Jen

    2013-01-01

    One of the important applications in Wireless Sensor Networks (WSNs) is video surveillance that includes the tasks of video data processing and transmission. Processing and transmission of image and video data in WSNs has attracted a lot of attention in recent years. This is known as Wireless Visual Sensor Networks (WVSNs). WVSNs are distributed intelligent systems for collecting image or video data with unique performance, complexity, and quality of service challenges. WVSNs consist of a large number of battery-powered and resource constrained camera nodes. End-to-end delay is a very important Quality of Service (QoS) metric for video surveillance application in WVSNs. How to meet the stringent delay QoS in resource constrained WVSNs is a challenging issue that requires novel distributed and collaborative routing strategies. This paper proposes a Near-Optimal Distributed QoS Constrained (NODQC) routing algorithm to achieve an end-to-end route with lower delay and higher throughput. A Lagrangian Relaxation (LR)-based routing metric that considers the “system perspective” and “user perspective” is proposed to determine the near-optimal routing paths that satisfy end-to-end delay constraints with high system throughput. The empirical results show that the NODQC routing algorithm outperforms others in terms of higher system throughput with lower average end-to-end delay and delay jitter. In this paper, for the first time, the algorithm shows how to meet the delay QoS and at the same time how to achieve higher system throughput in stringently resource constrained WVSNs.

  6. A New Continuous-Time Equality-Constrained Optimization to Avoid Singularity.

    PubMed

    Quan, Quan; Cai, Kai-Yuan

    2016-02-01

    In equality-constrained optimization, a standard regularity assumption is often associated with feasible point methods, namely, that the gradients of constraints are linearly independent. In practice, the regularity assumption may be violated. In order to avoid such a singularity, a new projection matrix is proposed based on which a feasible point method to continuous-time, equality-constrained optimization is developed. First, the equality constraint is transformed into a continuous-time dynamical system with solutions that always satisfy the equality constraint. Second, a new projection matrix without singularity is proposed to realize the transformation. An update (or say a controller) is subsequently designed to decrease the objective function along the solutions of the transformed continuous-time dynamical system. The invariance principle is then applied to analyze the behavior of the solution. Furthermore, the proposed method is modified to address cases in which solutions do not satisfy the equality constraint. Finally, the proposed optimization approach is applied to three examples to demonstrate its effectiveness. PMID:26415188

  7. Firefly Algorithm for Cardinality Constrained Mean-Variance Portfolio Optimization Problem with Entropy Diversity Constraint

    PubMed Central

    2014-01-01

    Portfolio optimization (selection) problem is an important and hard optimization problem that, with the addition of necessary realistic constraints, becomes computationally intractable. Nature-inspired metaheuristics are appropriate for solving such problems; however, literature review shows that there are very few applications of nature-inspired metaheuristics to portfolio optimization problem. This is especially true for swarm intelligence algorithms which represent the newer branch of nature-inspired algorithms. No application of any swarm intelligence metaheuristics to cardinality constrained mean-variance (CCMV) portfolio problem with entropy constraint was found in the literature. This paper introduces modified firefly algorithm (FA) for the CCMV portfolio model with entropy constraint. Firefly algorithm is one of the latest, very successful swarm intelligence algorithm; however, it exhibits some deficiencies when applied to constrained problems. To overcome lack of exploration power during early iterations, we modified the algorithm and tested it on standard portfolio benchmark data sets used in the literature. Our proposed modified firefly algorithm proved to be better than other state-of-the-art algorithms, while introduction of entropy diversity constraint further improved results. PMID:24991645

  8. A Resource Constrained Distributed Constraint Optimization Method using Resource Constraint Free Pseudo-tree

    NASA Astrophysics Data System (ADS)

    Matsui, Toshihiro; Silaghi, Marius C.; Hirayama, Katsutoshi; Yokoo, Makoto; Matsuo, Hiroshi

    Cooperative problem solving with shared resources is important in practical multi-agent systems. Resource constraints are necessary to handle practical problems such as distributed task scheduling with limited resource availability. As a fundamental formalism for multi-agent cooperation, the Distributed Constraint Optimization Problem (DCOP) has been investigated. With DCOPs, the agent states and the relationships between agents are formalized into a constraint optimization problem. However, in the original DCOP framework, constraints for resources that are consumed by teams of agents are not well supported. A framework called Resource Constrained Distributed Constraint Optimization Problem (RCDCOP) has recently been proposed. In RCDCOPs, a limit on resource usage is represented as an n-ary constraint. Previous research addressing RCDCOPs employ a pseudo-tree based solver. The pseudo-tree is an important graph structure for constraint networks. A pseudo-tree implies a partial ordering of variables. However, n-ary constrained variables, which are placed on a single path of the pseudo-tree, decrease efficiency of the solver. We propose another method using (i) a pseudo-tree that is generated ignoring resource constraints and (ii) virtual variables representing the usage of resources. However the virtual variables increase search space. To improve pruning efficiency of search, (iii) we apply a set of upper/lower bounds that are inferred from resource constraints. The efficiency of the proposed method is evaluated by experiment.

  9. PAPR-Constrained Pareto-Optimal Waveform Design for OFDM-STAP Radar

    SciTech Connect

    Sen, Satyabrata

    2014-01-01

    We propose a peak-to-average power ratio (PAPR) constrained Pareto-optimal waveform design approach for an orthogonal frequency division multiplexing (OFDM) radar signal to detect a target using the space-time adaptive processing (STAP) technique. The use of an OFDM signal does not only increase the frequency diversity of our system, but also enables us to adaptively design the OFDM coefficients in order to further improve the system performance. First, we develop a parametric OFDM-STAP measurement model by considering the effects of signaldependent clutter and colored noise. Then, we observe that the resulting STAP-performance can be improved by maximizing the output signal-to-interference-plus-noise ratio (SINR) with respect to the signal parameters. However, in practical scenarios, the computation of output SINR depends on the estimated values of the spatial and temporal frequencies and target scattering responses. Therefore, we formulate a PAPR-constrained multi-objective optimization (MOO) problem to design the OFDM spectral parameters by simultaneously optimizing four objective functions: maximizing the output SINR, minimizing two separate Cramer-Rao bounds (CRBs) on the normalized spatial and temporal frequencies, and minimizing the trace of CRB matrix on the target scattering coefficients estimations. We present several numerical examples to demonstrate the achieved performance improvement due to the adaptive waveform design.

  10. Genetic Algorithms Applied to Multi-Objective Aerodynamic Shape Optimization

    NASA Technical Reports Server (NTRS)

    Holst, Terry L.

    2005-01-01

    A genetic algorithm approach suitable for solving multi-objective problems is described and evaluated using a series of aerodynamic shape optimization problems. Several new features including two variations of a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding Pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. A new masking array capability is included allowing any gene or gene subset to be eliminated as decision variables from the design space. This allows determination of the effect of a single gene or gene subset on the Pareto optimal solution. Results indicate that the genetic algorithm optimization approach is flexible in application and reliable. The binning selection algorithms generally provide Pareto front quality enhancements and moderate convergence efficiency improvements for most of the problems solved.

  11. Optimal Multiple Surface Segmentation With Shape and Context Priors

    PubMed Central

    Bai, Junjie; Garvin, Mona K.; Sonka, Milan; Buatti, John M.; Wu, Xiaodong

    2014-01-01

    Segmentation of multiple surfaces in medical images is a challenging problem, further complicated by the frequent presence of weak boundary evidence, large object deformations, and mutual influence between adjacent objects. This paper reports a novel approach to multi-object segmentation that incorporates both shape and context prior knowledge in a 3-D graph-theoretic framework to help overcome the stated challenges. We employ an arc-based graph representation to incorporate a wide spectrum of prior information through pair-wise energy terms. In particular, a shape-prior term is used to penalize local shape changes and a context-prior term is used to penalize local surface-distance changes from a model of the expected shape and surface distances, respectively. The globally optimal solution for multiple surfaces is obtained by computing a maximum flow in a low-order polynomial time. The proposed method was validated on intraretinal layer segmentation of optical coherence tomography images and demonstrated statistically significant improvement of segmentation accuracy compared to our earlier graph-search method that was not utilizing shape and context priors. The mean unsigned surface positioning errors obtained by the conventional graph-search approach (6.30 ± 1.58 μm) was improved to 5.14 ± 0.99 μm when employing our new method with shape and context priors. PMID:23193309

  12. Application of genetic algorithm on optimization of laser beam shaping.

    PubMed

    Tsai, Cheng-Mu; Fang, Yi-Chin; Lin, Chia-Te

    2015-06-15

    This study proposes a newly developed optimization method for an aspherical lens system employed in a refractive laser beam shaping system, which performs transformations on laser spots such that they are transformed into flat-tops of any size. In this paper, a genetic algorithm (GA) with multipoint search is proposed as the optimization method, together with macro language in optical simulation software, in order to search for ideal and optimized parameters. In comparison to a traditional two-dimensional (2D) computational method, using the one-dimensional (1D) computation for laser beam shaping can search for the optimal solution approximately twice as fast (after experiments). The optimal results show that when the laser spot shrinks from 3 mm to 1.07 mm, 88% uniformity is achieved, and when the laser spot increases from 3 mm to 5.273 mm, 90% uniformity is achieved. The distances between the lenses for both systems described above are even smaller than the thickness for the first lens, enabling us to conclude that our design objectives of extra light and slimness in the system are achieved. PMID:26193566

  13. Estimating contrast transfer function and associated parameters by constrained non-linear optimization

    PubMed Central

    YANG, C.; JIANG, W.; CHEN, D. -H.; ADIGA, U.; NG, E. G.; CHIU, W.

    2009-01-01

    Summary The three-dimensional reconstruction of macromolecules from two-dimensional single-particle electron images requires determination and correction of the contrast transfer function (CTF) and envelope function. A computational algorithm based on constrained non-linear optimization is developed to estimate the essential parameters in the CTF and envelope function model simultaneously and automatically. The application of this estimation method is demonstrated with focal series images of amorphous carbon film as well as images of ice-embedded icosahedral virus particles suspended across holes. PMID:19250460

  14. Estimating Contrast Transfer Function and Associated Parameters by Constrained Nonlinear Optimization

    SciTech Connect

    Yang, Chao; Jiang, Wen; Chen, Dong-Hua; Adiga, Umesh; Ng, Esmond G.; Chiu, Wah

    2008-07-28

    The three-dimensional reconstruction of macromolecules from two-dimensional single-particle electron images requires determination and correction of the contrast transfer function (CTF) and envelope function. A computational algorithm based on constrained non-linear optimization is developed to estimate the essential parameters in the CTF and envelope function model simultaneously and automatically. The application of this estimation method is demonstrated with focal series images of amorphous carbon film as well as images of ice-embedded icosahedral virus particles suspended across holes.

  15. Optimization strategy to find shapes of soliton molecules

    NASA Astrophysics Data System (ADS)

    Gholami, S.; Rohrmann, Ph.; Hause, A.; Mitschke, F.

    2014-07-01

    Frequently, a certain solution of a nonlinear wave equation is of interest, but no analytic form is known, and one must work with approximations. We introduce a search strategy to find solutions of the propagation of soliton molecules in a dispersion-managed optical fiber and to determine their shape with some precision. The strategy compares shapes before and after propagation and invokes an optimization routine to minimize the difference. The scheme is designed to be implemented in an experiment so that all fiber parameters are taken into account. Here, we present a full numerical study and a verification of convergence; we validate the method with cases of known solutions. We also compare the performance of two optimization procedures, the Nelder-Mead simplex method and a genetic algorithm.

  16. SU-E-I-23: A General KV Constrained Optimization of CNR for CT Abdominal Imaging

    SciTech Connect

    Weir, V; Zhang, J

    2015-06-15

    Purpose: While Tube current modulation has been well accepted for CT dose reduction, kV adjusting in clinical settings is still at its early stage. This is mainly due to the limited kV options of most current CT scanners. kV adjusting can potentially reduce radiation dose and optimize image quality. This study is to optimize CT abdomen imaging acquisition based on the assumption of a continuous kV, with the goal to provide the best contrast to noise ratio (CNR). Methods: For a given dose (CTDIvol) level, the CNRs at different kV and pitches were measured with an ACR GAMMEX phantom. The phantom was scanned in a Siemens Sensation 64 scanner and a GE VCT 64 scanner. A constrained mathematical optimization was used to find the kV which led to the highest CNR for the anatomy and pitch setting. Parametric equations were obtained from polynomial fitting of plots of kVs vs CNRs. A suitable constraint region for optimization was chosen. Subsequent optimization yielded a peak CNR at a particular kV for different collimations and pitch setting. Results: The constrained mathematical optimization approach yields kV of 114.83 and 113.46, with CNRs of 1.27 and 1.11 at the pitch of 1.2 and 1.4, respectively, for the Siemens Sensation 64 scanner with the collimation of 32 x 0.625mm. An optimized kV of 134.25 and 1.51 CNR is obtained for a GE VCT 64 slice scanner with a collimation of 32 x 0.625mm and a pitch of 0.969. At 0.516 pitch and 32 x 0.625 mm an optimized kV of 133.75 and a CNR of 1.14 was found for the GE VCT 64 slice scanner. Conclusion: CNR in CT image acquisition can be further optimized with a continuous kV option instead of current discrete or fixed kV settings. A continuous kV option is a key for individualized CT protocols.

  17. Focusing time harmonic scalar fields in non-homogenous lossy media: Inverse filter vs. constrained power focusing optimization

    NASA Astrophysics Data System (ADS)

    Iero, D. A. M.; Isernia, T.; Crocco, L.

    2013-08-01

    Two strategies to focus time harmonic scalar fields in known inhomogeneous lossy media are compared. The first one is the Inverse Filter (IF) method, which faces the focusing task as the synthesis of a nominal field. The second one is the Constrained Power Focusing Optimization (CPFO) method, which tackles the problem in terms of constrained mask constrained power optimization. Numerical examples representative of focusing in noninvasive microwave hyperthermia are provided to show that CPFO is able to outperform IF, thanks to the additional degrees of freedom arising from the adopted power synthesis formulation.

  18. BEM4I applied to shape optimization problems

    NASA Astrophysics Data System (ADS)

    Zapletal, Jan; Merta, Michal; Čermák, Martin

    2016-06-01

    Shape optimization problems are one of the areas where the boundary element method can be applied efficiently. We present the application of the BEM4I library developed at IT4Innovations to a class of free surface Bernoulli problems in 3D. Apart from the boundary integral formulation of the related state and adjoint boundary value problems we present an implementation of a general scheme for the treatment of similar problems.

  19. Optimization of negative central shear discharges in shaped cross sections

    SciTech Connect

    Turnbull, A.D., Chu, M.S., Taylor, T.S., Casper, T.A., Rice, B.W.; Greene, J.M., Greenfield, C.M., La Haye, R.J., Lao, L.L., Lee, B.J.; Miller, R.L., Ren, C., Strait, E.J., Tritz, K.; Rettig, C.L., Rhodes, T.L.; Sauter, O.

    1996-10-01

    Magnetohydrodynamic (MHD) stability analyses of Negative Central Shear (NCS) equilibria have revealed a new understanding of the limiting MHD instabilities in NCS experiments. Ideal stability calculations show a synergistic effect between cross section shape and pressure profile optimization; strong shaping and broader pressure independently lead to moderately higher {Beta} limits, but broadening of the pressure profile in a strongly dee-shaped cross- section leads to a dramatic increase in the ideal {Beta} limit. Localized resistive interchange (RI) modes can be unstable in the negative shear region and are most restrictive for peaked pressure profiles. Resistive global modes can also be destabilized significantly below the ideal P limit. Experiments largely confirm the general trends, and diagnostic measurements and numerical stability calculations are found to be in good qualitative agreement. Observed disruptions in NCS discharges with L-mode edge and strongly peaked pressure, appear to be initiated by interactions between the RI, and the global ideal and resistive modes.

  20. Optimized pulse shapes for a resonator-induced phase gate

    NASA Astrophysics Data System (ADS)

    Cross, Andrew W.; Gambetta, Jay M.

    2015-03-01

    The resonator-induced phase gate is a multiqubit controlled-phase gate for fixed-frequency superconducting qubits. Through off-resonant driving of a bus resonator, statically coupled qubits acquire a state-dependent phase. However, photon loss leads to dephasing during the gate, and any residual entanglement between the resonator and qubits after the gate leads to decoherence. Here we consider how to shape the drive pulse to minimize these unwanted effects. First, we review how the gate's entangling and dephasing rates depend on the system parameters and validate closed-form solutions against direct numerical solution of a master equation. Next, we propose spline pulse shapes that reduce residual qubit-bus entanglement, are robust to imprecise knowledge of the resonator shift, and can be shortened by using higher-degree polynomials. Finally, we present a procedure that optimizes over the subspace of pulses that leave the resonator unpopulated. This finds shaped drive pulses that further reduce the gate duration. Assuming realistic parameters, we exhibit shaped pulses that have the potential to realize ˜212 ns spline pulse gates and ˜120 ns optimized gates with ˜6 ×10-4 average gate infidelity. These examples do not represent fundamental limits of the gate and, in principle, even shorter gates may be achievable.

  1. Interpretable exemplar-based shape classification using constrained sparse linear models

    NASA Astrophysics Data System (ADS)

    Sigurdsson, Gunnar A.; Yang, Zhen; Tran, Trac D.; Prince, Jerry L.

    2015-03-01

    Many types of diseases manifest themselves as observable changes in the shape of the affected organs. Using shape classification, we can look for signs of disease and discover relationships between diseases. We formulate the problem of shape classification in a holistic framework that utilizes a lossless scalar field representation and a non-parametric classification based on sparse recovery. This framework generalizes over certain classes of unseen shapes while using the full information of the shape, bypassing feature extraction. The output of the method is the class whose combination of exemplars most closely approximates the shape, and furthermore, the algorithm returns the most similar exemplars along with their similarity to the shape, which makes the result simple to interpret. Our results show that the method offers accurate classification between three cerebellar diseases and controls in a database of cerebellar ataxia patients. For reproducible comparison, promising results are presented on publicly available 2D datasets, including the ETH-80 dataset where the method achieves 88.4% classification accuracy.

  2. Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing

    NASA Technical Reports Server (NTRS)

    Ono, Masahiro; Kuwata, Yoshiaki

    2013-01-01

    A chance-constrained dynamic programming algorithm was developed that is capable of making optimal sequential decisions within a user-specified risk bound. This work handles stochastic uncertainties over multiple stages in the CEMAT (Combined EDL-Mobility Analyses Tool) framework. It was demonstrated by a simulation of Mars entry, descent, and landing (EDL) using real landscape data obtained from the Mars Reconnaissance Orbiter. Although standard dynamic programming (DP) provides a general framework for optimal sequential decisionmaking under uncertainty, it typically achieves risk aversion by imposing an arbitrary penalty on failure states. Such a penalty-based approach cannot explicitly bound the probability of mission failure. A key idea behind the new approach is called risk allocation, which decomposes a joint chance constraint into a set of individual chance constraints and distributes risk over them. The joint chance constraint was reformulated into a constraint on an expectation over a sum of an indicator function, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the chance-constraint optimization problem can be turned into an unconstrained optimization over a Lagrangian, which can be solved efficiently using a standard DP approach.

  3. Experiments on power optimization for displacement-constrained operation of a vibration energy harvester

    NASA Astrophysics Data System (ADS)

    Truong, Binh Duc; Phu Le, Cuong; Halvorsen, Einar

    2015-12-01

    This paper presents experiments on how to approach the physical limits on power from vibration energy harvesting under displacement-constrained operation. A MEMS electrostatic vibration energy harvester with voltage-control of the system stiffness is used for this purpose. The power saturation problem, when the proof mass displacement reaches maximum amplitude for sufficient acceleration amplitude, is shifted to higher accelerations by use of load optimization and tunable electromechanical coupling k2. Measurement results show that harvested power can be made to follow the optimal velocity-damped generator also for a range of accelerations that implies displacement constraints. Comparing to the saturated power, the power increases 1.5 times with the optimal load and an electromechanical coupling k2=8.7%. This value is 2.3 times for a higher coupling k2=17.9%. The obtained system effectiveness is beyond 60% under the optimization. This work also shows a first demonstration of reaching optimal power in the intermediate acceleration-range between the two extremes of maximum efficiency and maximum power transfer.

  4. A simple two stage optimization algorithm for constrained power economic dispatch

    SciTech Connect

    Huang, G.; Song, K. . Dept. of Electrical Engineering)

    1994-11-01

    A simple two stage optimization algorithm is proposed and investigated for fast computation of constrained power economic dispatch control problems. The method is a simple demonstration of the hierarchical aggregation-disaggregation (HAD) concept. The algorithm first solves an aggregated problem to obtain an initial solution. This aggregated problem turns out to be classical economic dispatch formulation, and it can be solved in 1% of overall computation time. In the second stage, linear programming method finds optimal solution which satisfies power balance constraints, generation and transmission inequality constraints and security constraints. Implementation of the algorithm for IEEE systems and EPRI Scenario systems shows that the two stage method obtains average speedup ratio 10.64 as compared to classical LP-based method.

  5. Reinforcement learning solution for HJB equation arising in constrained optimal control problem.

    PubMed

    Luo, Biao; Wu, Huai-Ning; Huang, Tingwen; Liu, Derong

    2015-11-01

    The constrained optimal control problem depends on the solution of the complicated Hamilton-Jacobi-Bellman equation (HJBE). In this paper, a data-based off-policy reinforcement learning (RL) method is proposed, which learns the solution of the HJBE and the optimal control policy from real system data. One important feature of the off-policy RL is that its policy evaluation can be realized with data generated by other behavior policies, not necessarily the target policy, which solves the insufficient exploration problem. The convergence of the off-policy RL is proved by demonstrating its equivalence to the successive approximation approach. Its implementation procedure is based on the actor-critic neural networks structure, where the function approximation is conducted with linearly independent basis functions. Subsequently, the convergence of the implementation procedure with function approximation is also proved. Finally, its effectiveness is verified through computer simulations. PMID:26356598

  6. Shape Memory as a Process: Optimizing Polymer Design for Shape Recovery

    NASA Astrophysics Data System (ADS)

    Vaia, Richard; Koerner, Hilmar; Lee, Kyungmin; Strong, Robert; Smith, Mattew; Wang, Huabin; White, Tim; Tan, Loon-Seng

    2012-02-01

    Shape memory is a process that enables the reversible storage and recovery of mechanical energy through a change in shape. Polymers provide a unique alternative to kinematic designs and other materials (e.g. metallic alloys) for applications requiring large deformation and novel control options. The effect control of storage and relaxation of strain energy associated with chain deformation depends on the nonlinear visco-elasitc behavior and glassy dynamics of the polymer network. Considering the molecular understanding of rubbery elasticity, chain entanglements in concentrated polymer liquids, affine deformation of networks, and glass fragility, heuristic guidelines can be formulated to optimize the molecular design of a polymer for shape memory. These are applied to the development of a polymer system for shape memory processes at high-temperature (200^oC). The low-crosslink density polyimide exhibits very rapid shape recovery, excellent fixity, high creep resistance, and good cyclability. Furthermore, the molecular design affords a very narrow temperature range for programming and triggering shape change that can also be accessed by photo-isomerization of the cross-link nodes.

  7. Simultaneous beam sampling and aperture shape optimization for SPORT

    SciTech Connect

    Zarepisheh, Masoud; Li, Ruijiang; Xing, Lei; Ye, Yinyu

    2015-02-15

    Purpose: Station parameter optimized radiation therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital linear accelerators, in which the station parameters of a delivery system, such as aperture shape and weight, couch position/angle, gantry/collimator angle, can be optimized simultaneously. SPORT promises to deliver remarkable radiation dose distributions in an efficient manner, yet there exists no optimization algorithm for its implementation. The purpose of this work is to develop an algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: The authors build a mathematical model with the fundamental station point parameters as the decision variables. To solve the resulting large-scale optimization problem, the authors devise an effective algorithm by integrating three advanced optimization techniques: column generation, subgradient method, and pattern search. Column generation adds the most beneficial stations sequentially until the plan quality improvement saturates and provides a good starting point for the subsequent optimization. It also adds the new stations during the algorithm if beneficial. For each update resulted from column generation, the subgradient method improves the selected stations locally by reshaping the apertures and updating the beam angles toward a descent subgradient direction. The algorithm continues to improve the selected stations locally and globally by a pattern search algorithm to explore the part of search space not reachable by the subgradient method. By combining these three techniques together, all plausible combinations of station parameters are searched efficiently to yield the optimal solution. Results: A SPORT optimization framework with seamlessly integration of three complementary algorithms, column generation, subgradient method, and pattern search, was established. The proposed technique was applied to two previously treated clinical cases: a head and

  8. In-Space Radiator Shape Optimization using Genetic Algorithms

    NASA Technical Reports Server (NTRS)

    Hull, Patrick V.; Kittredge, Ken; Tinker, Michael; SanSoucie, Michael

    2006-01-01

    Future space exploration missions will require the development of more advanced in-space radiators. These radiators should be highly efficient and lightweight, deployable heat rejection systems. Typical radiators for in-space heat mitigation commonly comprise a substantial portion of the total vehicle mass. A small mass savings of even 5-10% can greatly improve vehicle performance. The objective of this paper is to present the development of detailed tools for the analysis and design of in-space radiators using evolutionary computation techniques. The optimality criterion is defined as a two-dimensional radiator with a shape demonstrating the smallest mass for the greatest overall heat transfer, thus the end result is a set of highly functional radiator designs. This cross-disciplinary work combines topology optimization and thermal analysis design by means of a genetic algorithm The proposed design tool consists of the following steps; design parameterization based on the exterior boundary of the radiator, objective function definition (mass minimization and heat loss maximization), objective function evaluation via finite element analysis (thermal radiation analysis) and optimization based on evolutionary algorithms. The radiator design problem is defined as follows: the input force is a driving temperature and the output reaction is heat loss. Appropriate modeling of the space environment is added to capture its effect on the radiator. The design parameters chosen for this radiator shape optimization problem fall into two classes, variable height along the width of the radiator and a spline curve defining the -material boundary of the radiator. The implementation of multiple design parameter schemes allows the user to have more confidence in the radiator optimization tool upon demonstration of convergence between the two design parameter schemes. This tool easily allows the user to manipulate the driving temperature regions thus permitting detailed design of in

  9. Finite-horizon control-constrained nonlinear optimal control using single network adaptive critics.

    PubMed

    Heydari, Ali; Balakrishnan, Sivasubramanya N

    2013-01-01

    To synthesize fixed-final-time control-constrained optimal controllers for discrete-time nonlinear control-affine systems, a single neural network (NN)-based controller called the Finite-horizon Single Network Adaptive Critic is developed in this paper. Inputs to the NN are the current system states and the time-to-go, and the network outputs are the costates that are used to compute optimal feedback control. Control constraints are handled through a nonquadratic cost function. Convergence proofs of: 1) the reinforcement learning-based training method to the optimal solution; 2) the training error; and 3) the network weights are provided. The resulting controller is shown to solve the associated time-varying Hamilton-Jacobi-Bellman equation and provide the fixed-final-time optimal solution. Performance of the new synthesis technique is demonstrated through different examples including an attitude control problem wherein a rigid spacecraft performs a finite-time attitude maneuver subject to control bounds. The new formulation has great potential for implementation since it consists of only one NN with single set of weights and it provides comprehensive feedback solutions online, though it is trained offline. PMID:24808214

  10. Constrained body shape among highly genetically divergent allopatric lineages of the supralittoral isopod Ligia occidentalis (Oniscidea).

    PubMed

    Santamaria, Carlos A; Mateos, Mariana; DeWitt, Thomas J; Hurtado, Luis A

    2016-03-01

    Multiple highly divergent lineages have been identified within Ligia occidentalis sensu lato, a rocky supralittoral isopod distributed along a ~3000 km latitudinal gradient that encompasses several proposed marine biogeographic provinces and ecoregions in the eastern Pacific. Highly divergent lineages have nonoverlapping geographic distributions, with distributional limits that generally correspond with sharp environmental changes. Crossbreeding experiments suggest postmating reproductive barriers exist among some of them, and surveys of mitochondrial and nuclear gene markers do not show evidence of hybridization. Populations are highly isolated, some of which appear to be very small; thus, the effects of drift are expected to reduce the efficiency of selection. Large genetic divergences among lineages, marked environmental differences in their ranges, reproductive isolation, and/or high isolation of populations may have resulted in morphological differences in L. occidentalis, not detected yet by traditional taxonomy. We used landmark-based geometric morphometric analyses to test for differences in body shape among highly divergent lineages of L. occidentalis, and among populations within these lineages. We analyzed a total of 492 individuals from 53 coastal localities from the southern California Bight to Central Mexico, including the Gulf of California. We conducted discriminant function analyses (DFAs) on body shape morphometrics to assess morphological variation among genetically differentiated lineages and their populations. We also tested for associations between phylogeny and morphological variation, and whether genetic divergence is correlated to multivariate morphological divergence. We detected significant differences in body shape among highly divergent lineages, and among populations within these lineages. Nonetheless, neither lineages nor populations can be discriminated on the basis of body shape, because correct classification rates of cross

  11. Optimization of an idealized Y-Shaped Extracardiac Fontan Baffle

    NASA Astrophysics Data System (ADS)

    Yang, Weiguang; Feinstein, Jeffrey; Mohan Reddy, V.; Marsden, Alison

    2008-11-01

    Research has showed that vascular geometries can significantly impact hemodynamic performance, particularly in pediatric cardiology, where anatomy varies from one patient to another. In this study we optimize a newly proposed design for the Fontan procedure, a surgery used to treat single ventricle heart patients. The current Fontan procedure connects the inferior vena cava (IVC) to the pulmonary arteries (PA's) via a straight Gore-Tex tube, forming a T-shaped junction. In the Y-graft design, the IVC is connected to the left and right PAs by two branches. Initial studies on the Y-graft design showed an increase in efficiency and improvement in flow distribution compared to traditional designs in a single patient-specific model. We now optimize an idealized Y-graft model to refine the design prior to patient testing. A derivate-free optimization algorithm using Kriging surrogate functions and mesh adaptive direct search is coupled to a 3-D finite element Navier-Stokes solver. We will present optimization results for rest and exercise conditions and examine the influence of energy efficiency, wall shear stress, pulsatile flow, and flow distribution on the optimal design.

  12. Optimal aeroacoustic shape design using the surrogate management framework

    NASA Astrophysics Data System (ADS)

    Marsden, Alison; Wang, Meng; Dennis, John E., Jr.; Moin, Parviz

    2003-11-01

    Shape optimization is applied in conjunction with time-dependent Navier-Stokes simulations to minimize airfoil trailing-edge noise. Optimization is performed using the surrogate management framework (SMF) (Booker phet al., J. Struct. Opt. 1999), a non-gradient based pattern search method chosen for its efficiency and rigorous convergence properties. Using SMF, optimization is performed not on the expensive actual function but on an inexpensive surrogate function. The use of a polling step in the SMF guarantees convergence to a local minimum of the cost function on a mesh. Results are presented for cases with several shape parameters, using a model problem with unsteady laminar flow past an acoustically compact airfoil. Constraints on lift and drag are applied using a penalty function within the framework of the filtering method of Audet and Dennis (Rice Univ. TR 00-09), an extension of the SMF method. Significant reduction (as much as much as 80%) in acoustic power has been demonstrated in all cases with reasonable computational cost.

  13. Optimizing water permeability through the hourglass shape of aquaporins

    PubMed Central

    Gravelle, Simon; Joly, Laurent; Detcheverry, François; Ybert, Christophe; Cottin-Bizonne, Cécile; Bocquet, Lydéric

    2013-01-01

    The ubiquitous aquaporin channels are able to conduct water across cell membranes, combining the seemingly antagonist functions of a very high selectivity with a remarkable permeability. Whereas molecular details are obvious keys to perform these tasks, the overall efficiency of transport in such nanopores is also strongly limited by viscous dissipation arising at the connection between the nanoconstriction and the nearby bulk reservoirs. In this contribution, we focus on these so-called entrance effects and specifically examine whether the characteristic hourglass shape of aquaporins may arise from a geometrical optimum for such hydrodynamic dissipation. Using a combination of finite-element calculations and analytical modeling, we show that conical entrances with suitable opening angle can indeed provide a large increase of the overall channel permeability. Moreover, the optimal opening angles that maximize the permeability are found to compare well with the angles measured in a large variety of aquaporins. This suggests that the hourglass shape of aquaporins could be the result of a natural selection process toward optimal hydrodynamic transport. Finally, in a biomimetic perspective, these results provide guidelines to design artificial nanopores with optimal performances. PMID:24067650

  14. Optimizing water permeability through the hourglass shape of aquaporins.

    PubMed

    Gravelle, Simon; Joly, Laurent; Detcheverry, François; Ybert, Christophe; Cottin-Bizonne, Cécile; Bocquet, Lydéric

    2013-10-01

    The ubiquitous aquaporin channels are able to conduct water across cell membranes, combining the seemingly antagonist functions of a very high selectivity with a remarkable permeability. Whereas molecular details are obvious keys to perform these tasks, the overall efficiency of transport in such nanopores is also strongly limited by viscous dissipation arising at the connection between the nanoconstriction and the nearby bulk reservoirs. In this contribution, we focus on these so-called entrance effects and specifically examine whether the characteristic hourglass shape of aquaporins may arise from a geometrical optimum for such hydrodynamic dissipation. Using a combination of finite-element calculations and analytical modeling, we show that conical entrances with suitable opening angle can indeed provide a large increase of the overall channel permeability. Moreover, the optimal opening angles that maximize the permeability are found to compare well with the angles measured in a large variety of aquaporins. This suggests that the hourglass shape of aquaporins could be the result of a natural selection process toward optimal hydrodynamic transport. Finally, in a biomimetic perspective, these results provide guidelines to design artificial nanopores with optimal performances. PMID:24067650

  15. Optimization of Pulse Shape Discrimination of PROSPECT Liquid Scintillator Signals

    NASA Astrophysics Data System (ADS)

    Han, Ke; Prospect Collaboration

    2015-04-01

    PROSPECT, A Precision Oscillation and Spectrum Experiment, will use a segmented Li-6 doped liquid scintillator detector for precision measurement of the reactor anti-neutrino spectrum at the High Flux Isotope Reactor at Oak Ridge National Laboratory. PROSPECT also searches for very short baseline neutrino oscillation, an indication of the existence of eV-scale sterile neutrinos. Pulse shape analysis of the prompt anti-neutino signal and delayed neutron capture on Li-6 signal will greatly suppress background sources such as fast neutrons and accidental coincidence of gammas. In this talk, I will discuss different pulse shape parameters used in PROSPECT prototype detectors and multivariate optimization of event selection cuts based on those parameters.

  16. On orthogonality constrained multiple core-hole states and optimized effective potential method.

    PubMed

    Glushkov, V N; Assfeld, X

    2012-10-01

    An attempt to construct a multiple core-hole state within the optimized effective potential (OEP) methodology is presented. In contrast to the conventional Δ-self-consistent field method for hole states, the effects of removing an electron is achieved using some orthogonality constraints imposed on the orbitals so that a Slater determinant describing a hole state is constrained to be orthogonal to that of a neutral system. It is shown that single, double, and multiple core-hole states can be treated within a unified framework and can be easily implemented for atoms and molecules. For this purpose, a constrained OEP method proposed earlier for excited states (Glushkov and Levy, J. Chem. Phys. 2007, 126, 174106) is further developed to calculate single and double core ionization energies using a local effective potential expressed as a direct mapping of the external potential. The corresponding equations, determining core-hole orbitals from a one-particle Schrödinger equation with a local potential as well as correlation corrections derived from the second-order many-body perturbation theory are given. One of the advantages of the present direct mapping formulation is that the effective potential, which plays the role of the Kohn-Sham potential, has the symmetry of the external potential. Single and double core ionization potentials computed with the presented scheme were found to be in agreement with data available from experiment and other calculations. We also discuss core-hole state local potentials for the systems studied. PMID:22696265

  17. Optimal Forebody Shape for Minimum Drag in Supersonic Flow

    NASA Astrophysics Data System (ADS)

    Natarajan, G.; Sahoo, N.; Kulkarni, V.

    2015-01-01

    In this work, a simple and efficient numerical approach to determine the shape of the minimum-drag axisymmetric forebody in inviscid supersonic flow with an attached shock constraint has been described. Taylor-Maccoll equation in conjunction with the tangent cone method is employed to estimate the pressure drag coefficient which is also chosen as the cost function. The forebody geometry is parameterized using a Non-Uniform Rational B-Splines (NURBS) curve whose control points are the design variables for optimisation using the steepest descent algorithm. Numerical studies demonstrate that the optimal forebody geometry for a given length and base radius has as much as 15 % lesser drag, depending on the Mach number than a cone of the same fineness ratio and that the convergence to the optimal solution exhibits a relatively weak Mach-number dependence.

  18. Pseudo-time methods for constrained optimization problems governed by PDE

    NASA Technical Reports Server (NTRS)

    Taasan, Shlomo

    1995-01-01

    In this paper we present a novel method for solving optimization problems governed by partial differential equations. Existing methods are gradient information in marching toward the minimum, where the constrained PDE is solved once (sometimes only approximately) per each optimization step. Such methods can be viewed as a marching techniques on the intersection of the state and costate hypersurfaces while improving the residuals of the design equations per each iteration. In contrast, the method presented here march on the design hypersurface and at each iteration improve the residuals of the state and costate equations. The new method is usually much less expensive per iteration step since, in most problems of practical interest, the design equation involves much less unknowns that that of either the state or costate equations. Convergence is shown using energy estimates for the evolution equations governing the iterative process. Numerical tests show that the new method allows the solution of the optimization problem in a cost of solving the analysis problems just a few times, independent of the number of design parameters. The method can be applied using single grid iterations as well as with multigrid solvers.

  19. Optimization and static output-feedback control for half-car active suspensions with constrained information

    NASA Astrophysics Data System (ADS)

    Wang, Gang; Chen, Changzheng; Yu, Shenbo

    2016-09-01

    In this paper, the static output-feedback control problem of active suspension systems with information structure constraints is investigated. In order to simultaneously improve the ride comfort and stability, a half car model is used. Other constraints such as suspension deflection, actuator saturation, and controller constrained information are also considered. A novel static output-feedback design method based on the variable substitution is employed in the controller design. A single-step linear matrix inequality (LMI) optimization problem is solved to derive the initial feasible solution with a sparsity constraint. The initial infeasibility issue of the static output-feedback is resolved by using state-feedback information. Specifically, an optimization algorithm is proposed to search for less conservative results based on the feasible controller gain matrix. Finally, the validity of the designed controller for different road profiles is illustrated through numerical examples. The simulation results indicate that the optimized static output-feedback controller can achieve better suspension performances when compared with the feasible static output-feedback controller.

  20. Constrained Optimization of Average Arrival Time via a Probabilistic Approach to Transport Reliability.

    PubMed

    Namazi-Rad, Mohammad-Reza; Dunbar, Michelle; Ghaderi, Hadi; Mokhtarian, Payam

    2015-01-01

    To achieve greater transit-time reduction and improvement in reliability of transport services, there is an increasing need to assist transport planners in understanding the value of punctuality; i.e. the potential improvements, not only to service quality and the consumer but also to the actual profitability of the service. In order for this to be achieved, it is important to understand the network-specific aspects that affect both the ability to decrease transit-time, and the associated cost-benefit of doing so. In this paper, we outline a framework for evaluating the effectiveness of proposed changes to average transit-time, so as to determine the optimal choice of average arrival time subject to desired punctuality levels whilst simultaneously minimizing operational costs. We model the service transit-time variability using a truncated probability density function, and simultaneously compare the trade-off between potential gains and increased service costs, for several commonly employed cost-benefit functions of general form. We formulate this problem as a constrained optimization problem to determine the optimal choice of average transit time, so as to increase the level of service punctuality, whilst simultaneously ensuring a minimum level of cost-benefit to the service operator. PMID:25992902

  1. Adaptive optimal control of unknown constrained-input systems using policy iteration and neural networks.

    PubMed

    Modares, Hamidreza; Lewis, Frank L; Naghibi-Sistani, Mohammad-Bagher

    2013-10-01

    This paper presents an online policy iteration (PI) algorithm to learn the continuous-time optimal control solution for unknown constrained-input systems. The proposed PI algorithm is implemented on an actor-critic structure where two neural networks (NNs) are tuned online and simultaneously to generate the optimal bounded control policy. The requirement of complete knowledge of the system dynamics is obviated by employing a novel NN identifier in conjunction with the actor and critic NNs. It is shown how the identifier weights estimation error affects the convergence of the critic NN. A novel learning rule is developed to guarantee that the identifier weights converge to small neighborhoods of their ideal values exponentially fast. To provide an easy-to-check persistence of excitation condition, the experience replay technique is used. That is, recorded past experiences are used simultaneously with current data for the adaptation of the identifier weights. Stability of the whole system consisting of the actor, critic, system state, and system identifier is guaranteed while all three networks undergo adaptation. Convergence to a near-optimal control law is also shown. The effectiveness of the proposed method is illustrated with a simulation example. PMID:24808590

  2. Constrained Optimization of Average Arrival Time via a Probabilistic Approach to Transport Reliability

    PubMed Central

    Namazi-Rad, Mohammad-Reza; Dunbar, Michelle; Ghaderi, Hadi; Mokhtarian, Payam

    2015-01-01

    To achieve greater transit-time reduction and improvement in reliability of transport services, there is an increasing need to assist transport planners in understanding the value of punctuality; i.e. the potential improvements, not only to service quality and the consumer but also to the actual profitability of the service. In order for this to be achieved, it is important to understand the network-specific aspects that affect both the ability to decrease transit-time, and the associated cost-benefit of doing so. In this paper, we outline a framework for evaluating the effectiveness of proposed changes to average transit-time, so as to determine the optimal choice of average arrival time subject to desired punctuality levels whilst simultaneously minimizing operational costs. We model the service transit-time variability using a truncated probability density function, and simultaneously compare the trade-off between potential gains and increased service costs, for several commonly employed cost-benefit functions of general form. We formulate this problem as a constrained optimization problem to determine the optimal choice of average transit time, so as to increase the level of service punctuality, whilst simultaneously ensuring a minimum level of cost-benefit to the service operator. PMID:25992902

  3. Thermodynamic optimization of mixed refrigerant Joule- Thomson systems constrained by heat transfer considerations

    NASA Astrophysics Data System (ADS)

    Hinze, J. F.; Klein, S. A.; Nellis, G. F.

    2015-12-01

    Mixed refrigerant (MR) working fluids can significantly increase the cooling capacity of a Joule-Thomson (JT) cycle. The optimization of MRJT systems has been the subject of substantial research. However, most optimization techniques do not model the recuperator in sufficient detail. For example, the recuperator is usually assumed to have a heat transfer coefficient that does not vary with the mixture. Ongoing work at the University of Wisconsin-Madison has shown that the heat transfer coefficients for two-phase flow are approximately three times greater than for a single phase mixture when the mixture quality is between 15% and 85%. As a result, a system that optimizes a MR without also requiring that the flow be in this quality range may require an extremely large recuperator or not achieve the performance predicted by the model. To ensure optimal performance of the JT cycle, the MR should be selected such that it is entirely two-phase within the recuperator. To determine the optimal MR composition, a parametric study was conducted assuming a thermodynamically ideal cycle. The results of the parametric study are graphically presented on a contour plot in the parameter space consisting of the extremes of the qualities that exist within the recuperator. The contours show constant values of the normalized refrigeration power. This ‘map’ shows the effect of MR composition on the cycle performance and it can be used to select the MR that provides a high cooling load while also constraining the recuperator to be two phase. The predicted best MR composition can be used as a starting point for experimentally determining the best MR.

  4. Enceladus's internal ocean and ice shell constrained from Cassini gravity, shape, and libration data

    NASA Astrophysics Data System (ADS)

    Čadek, Ondřej; Tobie, Gabriel; Van Hoolst, Tim; Massé, Marion; Choblet, Gaël.; Lefèvre, Axel; Mitri, Giuseppe; Baland, Rose-Marie; Běhounková, Marie; Bourgeois, Olivier; Trinh, Anthony

    2016-06-01

    The intense plume activity at the South Pole of Enceladus together with the recent detection of libration hints at an internal water ocean underneath the outer ice shell. However, the interpretation of gravity, shape, and libration data leads to contradicting results regarding the depth of ocean/ice interface and the total volume of the ocean. Here we develop an interior structure model consisting of a rocky core, an internal ocean, and an ice shell, which satisfies simultaneously the gravity, shape, and libration data. We show that the data can be reconciled by considering isostatic compensation including the effect of a few hundred meter thick elastic lithosphere. Our model predicts that the core radius is 180-185 km, the ocean density is at least 1030 kg/m3, and the ice shell is 18-22 km thick on average. The ice thicknesses are reduced at poles decreasing to less than 5 km in the south polar region.

  5. Analysis of Constrained Optimization Variants of the Map-Seeking Circuit Algorithm

    SciTech Connect

    S.R. Harker; C.R. Vogel; T. Gedeon

    2005-09-05

    The map-seeking circuit algorithm (MSC) was developed by Arathorn to efficiently solve the combinatorial problem of correspondence maximization, which arises in applications like computer vision, motion estimation, image matching, and automatic speech recognition [D. W. Arathorn, Map-Seeking Circuits in Visual Cognition: A Computational Mechanism for Biological and Machine Vision, Stanford University Press, 2002]. Given an input image, a template image, and a discrete set of transformations, the goal is to find a composition of transformations which gives the best fit between the transformed input and the template. We imbed the associated combinatorial search problem within a continuous framework by using superposition, and we analyze a resulting constrained optimization problem. We present several numerical schemes to compute local solutions, and we compare their performance on a pair of test problems: an image matching problem and the challenging problem of automatically solving a Rubik's cube.

  6. Seamless tube shape is constrained by endocytosis-dependent regulation of active Moesin.

    PubMed

    Schottenfeld-Roames, Jodi; Rosa, Jeffrey B; Ghabrial, Amin S

    2014-08-01

    Most tubes have seams (intercellular or autocellular junctions that seal membranes together into a tube), but "seamless" tubes also exist. In Drosophila, stellate-shaped tracheal terminal cells make seamless tubes, with single branches running through each of dozens of cellular extensions. We find that mutations in braided impair terminal cell branching and cause formation of seamless tube cysts. We show that braided encodes Syntaxin7 and that cysts also form in cells deficient for other genes required either for membrane scission (shibire) or for early endosome formation (Rab5, Vps45, and Rabenosyn-5). These data define a requirement for early endocytosis in shaping seamless tube lumens. Importantly, apical proteins Crumbs and phospho-Moesin accumulate to aberrantly high levels in braided terminal cells. Overexpression of either Crumbs or phosphomimetic Moesin induced lumenal cysts and decreased terminal branching. Conversely, the braided seamless tube cyst phenotype was suppressed by mutations in crumbs or Moesin. Indeed, mutations in Moesin dominantly suppressed seamless tube cyst formation and restored terminal branching. We propose that early endocytosis maintains normal steady-state levels of Crumbs, which recruits apical phosphorylated (active) Moe, which in turn regulates seamless tube shape through modulation of cortical actin filaments. PMID:25065756

  7. Finite element shape optimization for biodegradable magnesium alloy stents.

    PubMed

    Wu, W; Petrini, L; Gastaldi, D; Villa, T; Vedani, M; Lesma, E; Previtali, B; Migliavacca, F

    2010-09-01

    Biodegradable magnesium alloy stents (MAS) are a promising solution for long-term adverse events caused by interactions between vessels and permanent stent platforms of drug eluting stents. However, the existing MAS showed severe lumen loss after a few months: too short degradation time may be the main reason for this drawback. In this study, a new design concept of MAS was proposed and a shape optimization method with finite element analysis was applied on two-dimensional (2D) stent models considering four different magnesium alloys: AZ80, AZ31, ZM21, and WE43. A morphing procedure was utilized to facilitate the optimization. Two experiments were carried out for a preliminary validation of the 2D models with good results. The optimized designs were compared to an existing MAS by means of three-dimensional finite element analysis. The results showed that the final optimized design with alloy WE43, compared to the existing MAS, has an increased strut width by approximately 48%, improved safety properties (decreased the maximum principal stress after recoil with tissue by 29%, and decreased the maximum principal strain during expansion by 14%) and improved scaffolding ability (increased by 24%). Accordingly, the degradation time can be expected to extend. The used methodology provides a convenient and practical way to develop novel MAS designs. PMID:20446037

  8. SU-F-BRF-02: Automated Lung Segmentation Method Using Atlas-Based Sparse Shape Composition with a Shape Constrained Deformable Model

    SciTech Connect

    Zhou, J; Yan, Z; Zhang, S; Zhang, B; Lasio, G; Prado, K; D'Souza, W

    2014-06-15

    Purpose: To develop an automated lung segmentation method, which combines the atlas-based sparse shape composition with a shape constrained deformable model in thoracic CT for patients with compromised lung volumes. Methods: Ten thoracic computed tomography scans for patients with large lung tumors were collected and reference lung ROIs in each scan was manually segmented to assess the performance of the method. We propose an automated and robust framework for lung tissue segmentation by using single statistical atlas registration to initialize a robust deformable model in order to perform fine segmentation that includes compromised lung tissue. First, a statistical image atlas with sparse shape composition is constructed and employed to obtain an approximate estimation of lung volume. Next, a robust deformable model with shape prior is initialized from this estimation. Energy terms from ROI edge potential and interior ROI region based potential as well as the initial ROI are combined in this model for accurate and robust segmentation. Results: The proposed segmentation method is applied to segment right lung on three CT scans. The quantitative results of our segmentation method achieved mean dice score of (0.92–0.95), mean accuracy of (0.97,0.98), and mean relative error of (0.10,0.16) with 95% CI. The quantitative results of previously published RASM segmentation method achieved mean dice score of (0.74,0.96), mean accuracy of (0.66,0.98), and mean relative error of (0.04, 0.38) with 95% CI. The qualitative and quantitative comparisons show that our proposed method can achieve better segmentation accuracy with less variance compared with a robust active shape model method. Conclusion: The atlas-based segmentation approach achieved relatively high accuracy with less variance compared to RASM in the sample dataset and the proposed method will be useful in image analysis applications for lung nodule or lung cancer diagnosis and radiotherapy assessment in thoracic

  9. Ontogenetic allometry constrains cranial shape of the head-first burrowing worm lizard Cynisca leucura (Squamata: Amphisbaenidae).

    PubMed

    Hipsley, Christy A; Rentinck, Marc-Nicolas; Rödel, Mark-Oliver; Müller, Johannes

    2016-09-01

    Amphisbaenians are fossorial, predominantly limbless squamate reptiles with distinct cranial shapes corresponding to specific burrowing behaviors. Due to their cryptic lifestyles and the scarcity of museum specimens, little is known of their intraspecific variation, particularly regarding cranial osteology. This represents a critical lack of information, because the majority of morphological investigations of squamate relationships are based on cranial characters. We investigated cranial variation in the West African Coast Worm Lizard Cynisca leucura, a round-headed member of the Amphisbaenidae. Using geometric morphometric analyses of three-dimensional computed tomographic scans, we found that cranial osteology of C. leucura is highly conserved, with the majority of shape changes occurring during growth as the cranium becomes more slender and elongate, accompanied by increasing interdigitation among the dermal roofing bones. Elements of the ventral portion of the cranium remain loosely connected in adults, possibly as a protective mechanism against repeated compression and torsion during burrow excavation. Intraspecific variation was strongly correlated with size change from juveniles to adults, indicating a dominant role of ontogenetic allometry in determining cranial shape. We found no evidence of sexual dimorphism, either during growth or among adults. Given the fossorial habits of C. leucura, we hypothesize that cranial allometry is under strong stabilizing selection to maintain adequate proportions for head-first digging, thereby constraining the ability of individuals to respond to differing selection pressures, including sexual selection and variation in diet or microhabitat. For species in which digging imposes less mechanical stress (e.g., in softer sand), allometric associations during growth may be weakened, allowing changes to the ontogenetic trajectory and subsequent morphological traits. Such developmental dissociation between size and shape, known

  10. On choosing ?optimal? shape parameters for RBF approximation

    NASA Astrophysics Data System (ADS)

    Fasshauer, Gregory; Zhang, Jack

    2007-08-01

    Many radial basis function (RBF) methods contain a free shape parameter that plays an important role for the accuracy of the method. In most papers the authors end up choosing this shape parameter by trial and error or some other ad hoc means. The method of cross validation has long been used in the statistics literature, and the special case of leave-one-out cross validation forms the basis of the algorithm for choosing an optimal value of the shape parameter proposed by Rippa in the setting of scattered data interpolation with RBFs. We discuss extensions of this approach that can be applied in the setting of iterated approximate moving least squares approximation of function value data and for RBF pseudo-spectral methods for the solution of partial differential equations. The former method can be viewed as an efficient alternative to ridge regression or smoothing spline approximation, while the latter forms an extension of the classical polynomial pseudo-spectral approach. Numerical experiments illustrating the use of our algorithms are included.

  11. Multidisciplinary Aerodynamic-Structural Shape Optimization Using Deformation (MASSOUD)

    NASA Technical Reports Server (NTRS)

    Samareh, Jamshid A.

    2000-01-01

    This paper presents a multidisciplinary shape parameterization approach. The approach consists of two basic concepts: (1) parameterizing the shape perturbations rather than the geometry itself and (2) performing the shape deformation by means of the soft object animation algorithms used in computer graphics. Because the formulation presented in this paper is independent of grid topology, we can treat computational fluid dynamics and finite element grids in the same manner. The proposed approach is simple, compact, and efficient. Also, the analytical sensitivity derivatives are easily computed for use in a gradient-based optimization. This algorithm is suitable for low-fidelity (e.g., linear aerodynamics and equivalent laminate plate structures) and high-fidelity (e.g., nonlinear computational fluid dynamics and detailed finite element modeling) analysis tools. This paper contains the implementation details of parameterizing for planform, twist, dihedral, thickness, camber, and free-form surface. Results are presented for a multidisciplinary application consisting of nonlinear computational fluid dynamics, detailed computational structural mechanics, and a simple performance module.

  12. A GENERALIZED STOCHASTIC COLLOCATION APPROACH TO CONSTRAINED OPTIMIZATION FOR RANDOM DATA IDENTIFICATION PROBLEMS

    SciTech Connect

    Webster, Clayton G; Gunzburger, Max D

    2013-01-01

    We present a scalable, parallel mechanism for stochastic identification/control for problems constrained by partial differential equations with random input data. Several identification objectives will be discussed that either minimize the expectation of a tracking cost functional or minimize the difference of desired statistical quantities in the appropriate $L^p$ norm, and the distributed parameters/control can both deterministic or stochastic. Given an objective we prove the existence of an optimal solution, establish the validity of the Lagrange multiplier rule and obtain a stochastic optimality system of equations. The modeling process may describe the solution in terms of high dimensional spaces, particularly in the case when the input data (coefficients, forcing terms, boundary conditions, geometry, etc) are affected by a large amount of uncertainty. For higher accuracy, the computer simulation must increase the number of random variables (dimensions), and expend more effort approximating the quantity of interest in each individual dimension. Hence, we introduce a novel stochastic parameter identification algorithm that integrates an adjoint-based deterministic algorithm with the sparse grid stochastic collocation FEM approach. This allows for decoupled, moderately high dimensional, parameterized computations of the stochastic optimality system, where at each collocation point, deterministic analysis and techniques can be utilized. The advantage of our approach is that it allows for the optimal identification of statistical moments (mean value, variance, covariance, etc.) or even the whole probability distribution of the input random fields, given the probability distribution of some responses of the system (quantities of physical interest). Our rigorously derived error estimates, for the fully discrete problems, will be described and used to compare the efficiency of the method with several other techniques. Numerical examples illustrate the theoretical

  13. Computer aided segmentation of kidneys using locally shape constrained deformable models on CT images

    NASA Astrophysics Data System (ADS)

    Erdt, Marius; Sakas, Georgios

    2010-03-01

    This work presents a novel approach for model based segmentation of the kidney in images acquired by Computed Tomography (CT). The developed computer aided segmentation system is expected to support computer aided diagnosis and operation planning. We have developed a deformable model based approach based on local shape constraints that prevents the model from deforming into neighboring structures while allowing the global shape to adapt freely to the data. Those local constraints are derived from the anatomical structure of the kidney and the presence and appearance of neighboring organs. The adaptation process is guided by a rule-based deformation logic in order to improve the robustness of the segmentation in areas of diffuse organ boundaries. Our work flow consists of two steps: 1.) a user guided positioning and 2.) an automatic model adaptation using affine and free form deformation in order to robustly extract the kidney. In cases which show pronounced pathologies, the system also offers real time mesh editing tools for a quick refinement of the segmentation result. Evaluation results based on 30 clinical cases using CT data sets show an average dice correlation coefficient of 93% compared to the ground truth. The results are therefore in most cases comparable to manual delineation. Computation times of the automatic adaptation step are lower than 6 seconds which makes the proposed system suitable for an application in clinical practice.

  14. Design of a gradient-index beam shaping system via a genetic algorithm optimization method

    NASA Astrophysics Data System (ADS)

    Evans, Neal C.; Shealy, David L.

    2000-10-01

    Geometrical optics - the laws of reflection and refraction, ray tracing, conservation of energy within a bundle of rays, and the condition of constant optical path length - provides a foundation for design of laser beam shaping systems. This paper explores the use of machine learning techniques, concentrating on genetic algorithms, to design laser beam shaping systems using geometrical optics. Specifically, a three-element GRIN laser beam shaping system has been designed to expand and transform a Gaussian input beam profile into one with a uniform irradiance profile. Solution to this problem involves the constrained optimization of a merit function involving a mix of discrete and continuous parameters. The merit function involves terms that measure the deviation of the output beam diameter, divergence, and irradiance from target values. The continuous parameters include the distances between the lens elements, the thickness, and radii of the lens elements. The discrete parameters include the GRIN glass types from a manufacturer's database, the gradient direction of the GRIN elements (positive or negative), and the actual number of lens elements in the system (one to four).

  15. Blunt-body drag reduction through base cavity shape optimization

    NASA Astrophysics Data System (ADS)

    Lorite-Díez, Manuel; Jiménez-González, José Ignacio; Gutiérrez-Montes, Cándido; Martínez-Bazán, Carlos

    2015-11-01

    We present a numerical study on the drag reduction of a turbulent incompressible flow around two different blunt bodies, of height H and length L, at a Reynolds number Re = ρU∞ H / μ = 2000 , where U∞ is the turbulent incompressible free-stream velocity, ρ is their density and μ their viscosity. The study is based on the optimization of the geometry of a cavity placed at the rear part of the body with the aim of increasing the base pressure. Thus, we have used an optimization algorithm, which implements the adjoint method, to compute the two-dimensional incompressible turbulent steady flow sensitivity field of axial forces on both bodies, and consequently modify the shape of the cavity to reduce the induced drag force. In addition, we have performed three dimensional numerical simulations using an IDDES model in order to analyze the drag reduction effect of the optimized cavities at higher Reynolds numbers.The results show average drag reductions of 17 and 25 % for Re=2000, as well as more regularized and less chaotic wake flows in both bodies. Supported by the Spanish MINECO, Junta de Andalucía and EU Funds under projects DPI2014-59292-C3-3-P and P11-TEP7495.

  16. High resolution quantitative phase imaging of live cells with constrained optimization approach

    NASA Astrophysics Data System (ADS)

    Pandiyan, Vimal Prabhu; Khare, Kedar; John, Renu

    2016-03-01

    Quantitative phase imaging (QPI) aims at studying weakly scattering and absorbing biological specimens with subwavelength accuracy without any external staining mechanisms. Use of a reference beam at an angle is one of the necessary criteria for recording of high resolution holograms in most of the interferometric methods used for quantitative phase imaging. The spatial separation of the dc and twin images is decided by the reference beam angle and Fourier-filtered reconstructed image will have a very poor resolution if hologram is recorded below a minimum reference angle condition. However, it is always inconvenient to have a large reference beam angle while performing high resolution microscopy of live cells and biological specimens with nanometric features. In this paper, we treat reconstruction of digital holographic microscopy images as a constrained optimization problem with smoothness constraint in order to recover only complex object field in hologram plane even with overlapping dc and twin image terms. We solve this optimization problem by gradient descent approach iteratively and the smoothness constraint is implemented by spatial averaging with appropriate size. This approach will give excellent high resolution image recovery compared to Fourier filtering while keeping a very small reference angle. We demonstrate this approach on digital holographic microscopy of live cells by recovering the quantitative phase of live cells from a hologram recorded with nearly zero reference angle.

  17. Adaptive Evolutionary Programming Incorporating Neural Network for Transient Stability Constrained Optimal Power Flow

    NASA Astrophysics Data System (ADS)

    Tangpatiphan, Kritsana; Yokoyama, Akihiko

    This paper presents an adaptive evolutionary programming incorporating neural network for solving transient stability constrained optimal power flow (TSCOPF). The proposed AEP method is an evolutionary programming (EP)-based algorithm, which adjusts its population size automatically during an optimization process. The artificial neural network, which classifies the AEP individual based on its stability degrees, is embedded into the search template to reduce the computational load caused by transient stability constraints. The fuel cost minimization is selected as the objective function of TSCOPF. The proposed method is tested on the IEEE 30-bus system with two types of the fuel cost functions, i.e. the conventional quadratic function and the quadratic function superimposed by sine component to model the cost curves without and with valve-point loading effect respectively. The numerical examples show that AEP is more effective than conventional EP in terms of computational speed, and when the neural network is incorporated into AEP, it can significantly reduce the computational time of TSCOPF. A study of the architecture of the neural network is also conducted and discussed. In addition, the effectiveness of the proposed method for solving TSCOPF with the consideration of multiple contingencies is manifested.

  18. Improved helicopter aeromechanical stability analysis using segmented constrained layer damping and hybrid optimization

    NASA Astrophysics Data System (ADS)

    Liu, Qiang; Chattopadhyay, Aditi

    2000-06-01

    Aeromechanical stability plays a critical role in helicopter design and lead-lag damping is crucial to this design. In this paper, the use of segmented constrained damping layer (SCL) treatment and composite tailoring is investigated for improved rotor aeromechanical stability using formal optimization technique. The principal load-carrying member in the rotor blade is represented by a composite box beam, of arbitrary thickness, with surface bonded SCLs. A comprehensive theory is used to model the smart box beam. A ground resonance analysis model and an air resonance analysis model are implemented in the rotor blade built around the composite box beam with SCLs. The Pitt-Peters dynamic inflow model is used in air resonance analysis under hover condition. A hybrid optimization technique is used to investigate the optimum design of the composite box beam with surface bonded SCLs for improved damping characteristics. Parameters such as stacking sequence of the composite laminates and placement of SCLs are used as design variables. Detailed numerical studies are presented for aeromechanical stability analysis. It is shown that optimum blade design yields significant increase in rotor lead-lag regressive modal damping compared to the initial system.

  19. Optimized conical shaped charge design using the SCAP (Shaped Charge Analysis Program) code

    SciTech Connect

    Vigil, M.G.

    1988-09-01

    The Shaped Charge Analysis Program (SCAP) is used to analytically model and optimize the design of Conical Shaped Charges (CSC). A variety of existing CSCs are initially modeled with the SCAP code and the predicted jet tip velocities, jet penetrations, and optimum standoffs are compared to previously published experimental results. The CSCs vary in size from 0.69 inch (1.75 cm) to 9.125 inch (23.18 cm) conical liner inside diameter. Two liner materials (copper and steel) and several explosives (Octol, Comp B, PBX-9501) are included in the CSCs modeled. The target material was mild steel. A parametric study was conducted using the SCAP code to obtain the optimum design for a 3.86 inch (9.8 cm) CSC. The variables optimized in this study included the CSC apex angle, conical liner thickness, explosive height, optimum standoff, tamper/confinement thickness, and explosive width. The non-dimensionalized jet penetration to diameter ratio versus the above parameters are graphically presented. 12 refs., 10 figs., 7 tabs.

  20. The Constrained Maximal Expression Level Owing to Haploidy Shapes Gene Content on the Mammalian X Chromosome.

    PubMed

    Hurst, Laurence D; Ghanbarian, Avazeh T; Forrest, Alistair R R; Huminiecki, Lukasz

    2015-12-01

    X chromosomes are unusual in many regards, not least of which is their nonrandom gene content. The causes of this bias are commonly discussed in the context of sexual antagonism and the avoidance of activity in the male germline. Here, we examine the notion that, at least in some taxa, functionally biased gene content may more profoundly be shaped by limits imposed on gene expression owing to haploid expression of the X chromosome. Notably, if the X, as in primates, is transcribed at rates comparable to the ancestral rate (per promoter) prior to the X chromosome formation, then the X is not a tolerable environment for genes with very high maximal net levels of expression, owing to transcriptional traffic jams. We test this hypothesis using The Encyclopedia of DNA Elements (ENCODE) and data from the Functional Annotation of the Mammalian Genome (FANTOM5) project. As predicted, the maximal expression of human X-linked genes is much lower than that of genes on autosomes: on average, maximal expression is three times lower on the X chromosome than on autosomes. Similarly, autosome-to-X retroposition events are associated with lower maximal expression of retrogenes on the X than seen for X-to-autosome retrogenes on autosomes. Also as expected, X-linked genes have a lesser degree of increase in gene expression than autosomal ones (compared to the human/Chimpanzee common ancestor) if highly expressed, but not if lowly expressed. The traffic jam model also explains the known lower breadth of expression for genes on the X (and the Z of birds), as genes with broad expression are, on average, those with high maximal expression. As then further predicted, highly expressed tissue-specific genes are also rare on the X and broadly expressed genes on the X tend to be lowly expressed, both indicating that the trend is shaped by the maximal expression level not the breadth of expression per se. Importantly, a limit to the maximal expression level explains biased tissue of expression

  1. The Constrained Maximal Expression Level Owing to Haploidy Shapes Gene Content on the Mammalian X Chromosome

    PubMed Central

    Hurst, Laurence D.; Ghanbarian, Avazeh T.; Forrest, Alistair R. R.; Huminiecki, Lukasz

    2015-01-01

    X chromosomes are unusual in many regards, not least of which is their nonrandom gene content. The causes of this bias are commonly discussed in the context of sexual antagonism and the avoidance of activity in the male germline. Here, we examine the notion that, at least in some taxa, functionally biased gene content may more profoundly be shaped by limits imposed on gene expression owing to haploid expression of the X chromosome. Notably, if the X, as in primates, is transcribed at rates comparable to the ancestral rate (per promoter) prior to the X chromosome formation, then the X is not a tolerable environment for genes with very high maximal net levels of expression, owing to transcriptional traffic jams. We test this hypothesis using The Encyclopedia of DNA Elements (ENCODE) and data from the Functional Annotation of the Mammalian Genome (FANTOM5) project. As predicted, the maximal expression of human X-linked genes is much lower than that of genes on autosomes: on average, maximal expression is three times lower on the X chromosome than on autosomes. Similarly, autosome-to-X retroposition events are associated with lower maximal expression of retrogenes on the X than seen for X-to-autosome retrogenes on autosomes. Also as expected, X-linked genes have a lesser degree of increase in gene expression than autosomal ones (compared to the human/Chimpanzee common ancestor) if highly expressed, but not if lowly expressed. The traffic jam model also explains the known lower breadth of expression for genes on the X (and the Z of birds), as genes with broad expression are, on average, those with high maximal expression. As then further predicted, highly expressed tissue-specific genes are also rare on the X and broadly expressed genes on the X tend to be lowly expressed, both indicating that the trend is shaped by the maximal expression level not the breadth of expression per se. Importantly, a limit to the maximal expression level explains biased tissue of expression

  2. Constraining GRACE-derived cryosphere-attributed signal to irregularly shaped ice-covered areas

    NASA Astrophysics Data System (ADS)

    Colgan, W.; Luthcke, S.; Abdalati, W.; Citterio, M.

    2013-12-01

    We use a Monte Carlo approach to invert a spherical harmonic representation of cryosphere-attributed mass change in order to infer the most likely underlying mass changes within irregularly shaped ice-covered areas at nominal 26 km resolution. By inverting a spherical harmonic representation through the incorporation of additional fractional ice coverage information, this approach seeks to eliminate signal leakage between non-ice-covered and ice-covered areas. The spherical harmonic representation suggests a Greenland mass loss of 251 ± 25 Gt a-1 over the December 2003 to December 2010 period. The inversion suggests 218 ± 20 Gt a-1 was due to the ice sheet proper, and 34 ± 5 Gt a-1 (or ~14%) was due to Greenland peripheral glaciers and ice caps (GrPGICs). This mass loss from GrPGICs exceeds that inferred from all ice masses on both Ellesmere and Devon islands combined. This partition therefore highlights that GRACE-derived "Greenland" mass loss cannot be taken as synonymous with "Greenland ice sheet" mass loss when making comparisons with estimates of ice sheet mass balance derived from techniques that sample only the ice sheet proper.

  3. Shape optimization of an accommodative intra-ocular lens

    NASA Astrophysics Data System (ADS)

    Jouve, François; Hanna, Khalil

    2005-03-01

    Cataract surgery consists in replacing the clouded or opacified crystalline lens by an Intra-Ocular Lens (IOL) having the same mean dioptrical power. Clear vision is then achieved at a given distance and glasses are needed in many situations. A new kind of IOL, potentially accommodative, is proposed. Its design is based on the deep understanding of the accommodation mechanism and on the mathematical modeling and the numerical simulation of the IOL's comportment in vivo. A preliminary version of this IOL is now commercialized by the company HumanOptics under the name '1CU'. In a second phase, shape optimization techniques equipped with strong mechanical and physiological constraints, are used to enhance the IOL performance and build a new design. To cite this article: F. Jouve, K. Hanna, C. R. Mecanique 333 (2005).

  4. Shape optimized headers and methods of manufacture thereof

    SciTech Connect

    Perrin, Ian James

    2013-11-05

    Disclosed herein is a shape optimized header comprising a shell that is operative for collecting a fluid; wherein an internal diameter and/or a wall thickness of the shell vary with a change in pressure and/or a change in a fluid flow rate in the shell; and tubes; wherein the tubes are in communication with the shell and are operative to transfer fluid into the shell. Disclosed herein is a method comprising fixedly attaching tubes to a shell; wherein the shell is operative for collecting a fluid; wherein an internal diameter and/or a wall thickness of the shell vary with a change in pressure and/or a change in a fluid flow rate in the shell; and wherein the tubes are in communication with the shell and are operative to transfer fluid into the shell.

  5. Incorporating a Constrained Optimization Algorithm into Remote- Sensing/Precision Agriculture Methodology

    NASA Astrophysics Data System (ADS)

    Morgenthaler, George; Khatib, Nader; Kim, Byoungsoo

    with information to improve their crop's vigor has been a major topic of interest. With world population growing exponentially, arable land being consumed by urbanization, and an unfavorable farm economy, the efficiency of farming must increase to meet future food requirements and to make farming a sustainable occupation for the farmer. "Precision Agriculture" refers to a farming methodology that applies nutrients and moisture only where and when they are needed in the field. The goal is to increase farm revenue by increasing crop yield and decreasing applications of costly chemical and water treatments. In addition, this methodology will decrease the environmental costs of farming, i.e., reduce air, soil, and water pollution. Sensing/Precision Agriculture has not grown as rapidly as early advocates envisioned. Technology for a successful Remote Sensing/Precision Agriculture system is now available. Commercial satellite systems can image (multi-spectral) the Earth with a resolution of approximately 2.5 m. Variable precision dispensing systems using GPS are available and affordable. Crop models that predict yield as a function of soil, chemical, and irrigation parameter levels have been formulated. Personal computers and internet access are in place in most farm homes and can provide a mechanism to periodically disseminate, e.g. bi-weekly, advice on what quantities of water and chemicals are needed in individual regions of the field. What is missing is a model that fuses the disparate sources of information on the current states of the crop and soil, and the remaining resource levels available with the decisions farmers are required to make. This must be a product that is easy for the farmer to understand and to implement. A "Constrained Optimization Feed-back Control Model" to fill this void will be presented. The objective function of the model will be used to maximize the farmer's profit by increasing yields while decreasing environmental costs and decreasing

  6. Incorporating a constrained optimization algorithm into remote sensing/precision agriculture methodology

    NASA Astrophysics Data System (ADS)

    Moreenthaler, George W.; Khatib, Nader; Kim, Byoungsoo

    2003-08-01

    For two decades now, the use of Remote Sensing/Precision Agriculture to improve farm yields while reducing the use of polluting chemicals and the limited water supply has been a major goal. With world population growing exponentially, arable land being consumed by urbanization, and an unfavorable farm economy, farm efficiency must increase to meet future food requirements and to make farming a sustainable, profitable occupation. "Precision Agriculture" refers to a farming methodology that applies nutrients and moisture only where and when they are needed in the field. The real goal is to increase farm profitability by identifying the additional treatments of chemicals and water that increase revenues more than they increase costs and do no exceed pollution standards (constrained optimization). Even though the economic and environmental benefits appear to be great, Remote Sensing/Precision Agriculture has not grown as rapidly as early advocates envisioned. Technology for a successful Remote Sensing/Precision Agriculture system is now in place, but other needed factors have been missing. Commercial satellite systems can now image the Earth (multi-spectrally) with a resolution as fine as 2.5 m. Precision variable dispensing systems using GPS are now available and affordable. Crop models that predict yield as a function of soil, chemical, and irrigation parameter levels have been developed. Personal computers and internet access are now in place in most farm homes and can provide a mechanism for periodically disseminating advice on what quantities of water and chemicals are needed in specific regions of each field. Several processes have been selected that fuse the disparate sources of information on the current and historic states of the crop and soil, and the remaining resource levels available, with the critical decisions that farmers are required to make. These are done in a way that is easy for the farmer to understand and profitable to implement. A "Constrained

  7. Shape-constrained multi-atlas based segmentation with multichannel registration

    NASA Astrophysics Data System (ADS)

    Hao, Yongfu; Jiang, Tianzi; Fan, Yong

    2012-02-01

    Multi-atlas based segmentation methods have recently attracted much attention in medical image segmentation. The multi-atlas based segmentation methods typically consist of three steps, including image registration, label propagation, and label fusion. Most of the recent studies devote to improving the label fusion step and adopt a typical image registration method for registering atlases to the target image. However, the existing registration methods may become unstable when poor image quality or high anatomical variance between registered image pairs involved. In this paper, we propose an iterative image segmentation and registration procedure to simultaneously improve the registration and segmentation performance in the multi-atlas based segmentation framework. Particularly, a two-channel registration method is adopted with one channel driven by appearance similarity between the atlas image and the target image and the other channel optimized by similarity between atlas label and the segmentation of the target image. The image segmentation is performed by fusing labels of multiple atlases. The validation of our method on hippocampus segmentation of 30 subjects containing MR images with both 1.5T and 3.0T field strength has demonstrated that our method can significantly improve the segmentation performance with different fusion strategies and obtain segmentation results with Dice overlap of 0.892+/-0.024 for 1.5T images and 0.902+/-0.022 for 3.0T images to manual segmentations.

  8. Shaping Diffraction-Grating Grooves to Optimize Efficiency

    NASA Technical Reports Server (NTRS)

    Backlund, John; Wilson, Daniel; Mouroulis, Pantazis; Maker, Paul; Muller, Richard

    2008-01-01

    A method of shaping diffraction-grating grooves to optimize the spectral efficiency, spectral range, and image quality of a spectral imaging instrument is under development. The method is based on the use of an advanced design algorithm to determine the possibly complex shape of grooves needed to obtain a desired efficiency-versus-wavelength response (see figure). Then electron- beam fabrication techniques are used to realize the required groove shape. The method could be used, for example, to make the spectral efficiency of the grating in a given wavelength range proportional to the inverse of the spectral efficiency of a photodetector array so that the overall spectral efficiency of the combination of the grating and the photodetector array would be flat. The method has thus far been applied to one-dimensional gratings only, but in principle, it is also applicable to two-dimensional gratings. The algorithm involves calculations in the spatial-frequency domain. The spatial-frequency spectrum of a grating is represented as a diffraction-order spectral-peak-width function multiplied by an efficiency function for a single grating groove. This representation affords computational efficiency and accuracy by making it possible to consider only the response from one grating groove (one period of the grating), instead of from the whole grating area, in determining the response from the entire grating. This combination of efficiency and accuracy is crucial for future extensions of the algorithm to two-dimensional designs and to designs in which polarization must also be taken into account. The algorithm begins with the definition of target values of relative efficiency that represent the desired spectral response of the grating in certain spectral frequencies calculated from the diffraction order and wavelength. The grating period is divided into a number of cells - typically, 100. The phase contribution from each cell is determined from the phase of the incident

  9. Multidimensionally-constrained relativistic mean-field study of spontaneous fission: Coupling between shape and pairing degrees of freedom

    NASA Astrophysics Data System (ADS)

    Zhao, Jie; Lu, Bing-Nan; Nikšić, Tamara; Vretenar, Dario; Zhou, Shan-Gui

    2016-04-01

    Background: Studies of fission dynamics, based on nuclear energy density functionals, have shown that the coupling between shape and pairing degrees of freedom has a pronounced effect on the nonperturbative collective inertia and, therefore, on dynamic (least-action) spontaneous fission paths and half-lives. Purpose: The aim is to analyze the effects of particle-number fluctuation degrees of freedom on symmetric and asymmetric spontaneous fission (SF) dynamics, and to compare the findings with the results of recent studies based on the self-consistent Hartree-Fock-Bogoliubov (HFB) method. Methods: Collective potentials and nonperturbative cranking collective inertia tensors are calculated using the multidimensionally-constrained relativistic-mean-field (MDC-RMF) model. Pairing correlations are treated in the BCS approximation using a separable pairing force of finite range. Pairing fluctuations are included as a collective variable using a constraint on particle-number dispersion. Fission paths are determined with the dynamic programming method by minimizing the action in multidimensional collective spaces. Results: The dynamics of spontaneous fission of 264Fm and 250Fm are explored. Fission paths, action integrals, and corresponding half-lives computed in the three-dimensional collective space of shape and pairing coordinates, using the relativistic functional DD-PC1 and a separable pairing force of finite range, are compared with results obtained without pairing fluctuations. Results for 264Fm are also discussed in relation with those recently obtained using the HFB model. Conclusions: The inclusion of pairing correlations in the space of collective coordinates favors axially symmetric shapes along the dynamic path of the fissioning system, amplifies pairing as the path traverses the fission barriers, significantly reduces the action integral, and shortens the

  10. CONSTANd : A Normalization Method for Isobaric Labeled Spectra by Constrained Optimization.

    PubMed

    Maes, Evelyne; Hadiwikarta, Wahyu Wijaya; Mertens, Inge; Baggerman, Geert; Hooyberghs, Jef; Valkenborg, Dirk

    2016-08-01

    In quantitative proteomics applications, the use of isobaric labels is a very popular concept as they allow for multiplexing, such that peptides from multiple biological samples are quantified simultaneously in one mass spectrometry experiment. Although this multiplexing allows that peptide intensities are affected by the same amount of instrument variability, systematic effects during sample preparation can also introduce a bias in the quantitation measurements. Therefore, normalization methods are required to remove this systematic error. At present, a few dedicated normalization methods for isobaric labeled data are at hand. Most of these normalization methods include a framework for statistical data analysis and rely on ANOVA or linear mixed models. However, for swift quality control of the samples or data visualization a simple normalization technique is sufficient. To this aim, we present a new and easy-to-use data-driven normalization method, named CONSTANd. The CONSTANd method employs constrained optimization and prior information about the labeling strategy to normalize the peptide intensities. Further, it allows maintaining the connection to any biological effect while reducing the systematic and technical errors. As a result, peptides can not only be compared directly within a multiplexed experiment, but are also comparable between other isobaric labeled datasets from multiple experimental designs that are normalized by the CONSTANd method, without the need to include a reference sample in every experimental setup. The latter property is especially useful when more than six, eight or ten (TMT/iTRAQ) biological samples are required to detect differential peptides with sufficient statistical power and to optimally make use of the multiplexing capacity of isobaric labels. PMID:27302888

  11. On the Optimal Identification of Tag Sets in Time-Constrained RFID Configurations

    PubMed Central

    Vales-Alonso, Javier; Bueno-Delgado, María Victoria; Egea-López, Esteban; Alcaraz, Juan José; Pérez-Mañogil, Juan Manuel

    2011-01-01

    In Radio Frequency Identification facilities the identification delay of a set of tags is mainly caused by the random access nature of the reading protocol, yielding a random identification time of the set of tags. In this paper, the cumulative distribution function of the identification time is evaluated using a discrete time Markov chain for single-set time-constrained passive RFID systems, namely those ones where a single group of tags is assumed to be in the reading area and only for a bounded time (sojourn time) before leaving. In these scenarios some tags in a set may leave the reader coverage area unidentified. The probability of this event is obtained from the cumulative distribution function of the identification time as a function of the sojourn time. This result provides a suitable criterion to minimize the probability of losing tags. Besides, an identification strategy based on splitting the set of tags in smaller subsets is also considered. Results demonstrate that there are optimal splitting configurations that reduce the overall identification time while keeping the same probability of losing tags. PMID:22163777

  12. Optimal Index Policies for Anomaly Localization in Resource-Constrained Cyber Systems

    NASA Astrophysics Data System (ADS)

    Cohen, Kobi; Zhao, Qing; Swami, Ananthram

    2014-08-01

    The problem of anomaly localization in a resource-constrained cyber system is considered. Each anomalous component of the system incurs a cost per unit time until its anomaly is identified and fixed. Different anomalous components may incur different costs depending on their criticality to the system. Due to resource constraints, only one component can be probed at each given time. The observations from a probed component are realizations drawn from two different distributions depending on whether the component is normal or anomalous. The objective is a probing strategy that minimizes the total expected cost, incurred by all the components during the detection process, under reliability constraints. We consider both independent and exclusive models. In the former, each component can be abnormal with a certain probability independent of other components. In the latter, one and only one component is abnormal. We develop optimal simple index policies under both models. The proposed index policies apply to a more general case where a subset (more than one) of the components can be probed simultaneously and have strong performance as demonstrated by simulation examples. The problem under study also finds applications in spectrum scanning in cognitive radio networks and event detection in sensor networks.

  13. Shape and Albedo from Shading (SAfS) for Pixel-Level dem Generation from Monocular Images Constrained by Low-Resolution dem

    NASA Astrophysics Data System (ADS)

    Wu, Bo; Chung Liu, Wai; Grumpe, Arne; Wöhler, Christian

    2016-06-01

    Lunar topographic information, e.g., lunar DEM (Digital Elevation Model), is very important for lunar exploration missions and scientific research. Lunar DEMs are typically generated from photogrammetric image processing or laser altimetry, of which photogrammetric methods require multiple stereo images of an area. DEMs generated from these methods are usually achieved by various interpolation techniques, leading to interpolation artifacts in the resulting DEM. On the other hand, photometric shape reconstruction, e.g., SfS (Shape from Shading), extensively studied in the field of Computer Vision has been introduced to pixel-level resolution DEM refinement. SfS methods have the ability to reconstruct pixel-wise terrain details that explain a given image of the terrain. If the terrain and its corresponding pixel-wise albedo were to be estimated simultaneously, this is a SAfS (Shape and Albedo from Shading) problem and it will be under-determined without additional information. Previous works show strong statistical regularities in albedo of natural objects, and this is even more logically valid in the case of lunar surface due to its lower surface albedo complexity than the Earth. In this paper we suggest a method that refines a lower-resolution DEM to pixel-level resolution given a monocular image of the coverage with known light source, at the same time we also estimate the corresponding pixel-wise albedo map. We regulate the behaviour of albedo and shape such that the optimized terrain and albedo are the likely solutions that explain the corresponding image. The parameters in the approach are optimized through a kernel-based relaxation framework to gain computational advantages. In this research we experimentally employ the Lunar-Lambertian model for reflectance modelling; the framework of the algorithm is expected to be independent of a specific reflectance model. Experiments are carried out using the monocular images from Lunar Reconnaissance Orbiter (LRO

  14. Optimal quantum control via numerical pulse shape optimization for two exciton qubits confined to semiconductor quantum dots

    NASA Astrophysics Data System (ADS)

    Mathew, Reuble; Shi Yang, Hong Yi; Hall, Kimberley

    2015-03-01

    Optimal quantum control (OQC), which iteratively optimizes the control Hamiltonian to achieve a target quantum state, is a versatile approach for manipulating quantum systems. For optically-active transitions, OQC can be implemented using femtosecond pulse shaping which provides control over the amplitude and/or phase of the electric field. Optical pulse shaping has been employed to optimize physical processes such as nonlinear optical signals, photosynthesis, and has recently been applied to optimizing single-qubit gates in multiple semiconductor quantum dots. In this work, we examine the use of numerical pulse shape optimization for optimal quantum control of multiple qubits confined to quantum dots as a function of their electronic structure parameters. The numerically optimized pulse shapes were found to produce high fidelity quantum gates for a range of transition frequencies, dipole moments, and arbitrary initial and final states. This work enhances the potential for scalability by reducing the laser resources required to control multiple qubits.

  15. Shape Optimization by Bayesian-Validated Computer-Simulation Surrogates

    NASA Technical Reports Server (NTRS)

    Patera, Anthony T.

    1997-01-01

    A nonparametric-validated, surrogate approach to optimization has been applied to the computational optimization of eddy-promoter heat exchangers and to the experimental optimization of a multielement airfoil. In addition to the baseline surrogate framework, a surrogate-Pareto framework has been applied to the two-criteria, eddy-promoter design problem. The Pareto analysis improves the predictability of the surrogate results, preserves generality, and provides a means to rapidly determine design trade-offs. Significant contributions have been made in the geometric description used for the eddy-promoter inclusions as well as to the surrogate framework itself. A level-set based, geometric description has been developed to define the shape of the eddy-promoter inclusions. The level-set technique allows for topology changes (from single-body,eddy-promoter configurations to two-body configurations) without requiring any additional logic. The continuity of the output responses for input variations that cross the boundary between topologies has been demonstrated. Input-output continuity is required for the straightforward application of surrogate techniques in which simplified, interpolative models are fitted through a construction set of data. The surrogate framework developed previously has been extended in a number of ways. First, the formulation for a general, two-output, two-performance metric problem is presented. Surrogates are constructed and validated for the outputs. The performance metrics can be functions of both outputs, as well as explicitly of the inputs, and serve to characterize the design preferences. By segregating the outputs and the performance metrics, an additional level of flexibility is provided to the designer. The validated outputs can be used in future design studies and the error estimates provided by the output validation step still apply, and require no additional appeals to the expensive analysis. Second, a candidate-based a posteriori

  16. Multi-Objective Differential Evolution for Voltage Security Constrained Optimal Power Flow in Deregulated Power Systems

    NASA Astrophysics Data System (ADS)

    Roselyn, J. Preetha; Devaraj, D.; Dash, Subhransu Sekhar

    2013-11-01

    Voltage stability is an important issue in the planning and operation of deregulated power systems. The voltage stability problems is a most challenging one for the system operators in deregulated power systems because of the intense use of transmission line capabilities and poor regulation in market environment. This article addresses the congestion management problem avoiding offline transmission capacity limits related to voltage stability by considering Voltage Security Constrained Optimal Power Flow (VSCOPF) problem in deregulated environment. This article presents the application of Multi Objective Differential Evolution (MODE) algorithm to solve the VSCOPF problem in new competitive power systems. The maximum of L-index of the load buses is taken as the indicator of voltage stability and is incorporated in the Optimal Power Flow (OPF) problem. The proposed method in hybrid power market which also gives solutions to voltage stability problems by considering the generation rescheduling cost and load shedding cost which relieves the congestion problem in deregulated environment. The buses for load shedding are selected based on the minimum eigen value of Jacobian with respect to the load shed. In the proposed approach, real power settings of generators in base case and contingency cases, generator bus voltage magnitudes, real and reactive power demands of selected load buses using sensitivity analysis are taken as the control variables and are represented as the combination of floating point numbers and integers. DE/randSF/1/bin strategy scheme of differential evolution with self-tuned parameter which employs binomial crossover and difference vector based mutation is used for the VSCOPF problem. A fuzzy based mechanism is employed to get the best compromise solution from the pareto front to aid the decision maker. The proposed VSCOPF planning model is implemented on IEEE 30-bus system, IEEE 57 bus practical system and IEEE 118 bus system. The pareto optimal

  17. Elastic Model Transitions: a Hybrid Approach Utilizing Quadratic Inequality Constrained Least Squares (LSQI) and Direct Shape Mapping (DSM)

    NASA Technical Reports Server (NTRS)

    Jurenko, Robert J.; Bush, T. Jason; Ottander, John A.

    2014-01-01

    A method for transitioning linear time invariant (LTI) models in time varying simulation is proposed that utilizes both quadratically constrained least squares (LSQI) and Direct Shape Mapping (DSM) algorithms to determine physical displacements. This approach is applicable to the simulation of the elastic behavior of launch vehicles and other structures that utilize multiple LTI finite element model (FEM) derived mode sets that are propagated throughout time. The time invariant nature of the elastic data for discrete segments of the launch vehicle trajectory presents a problem of how to properly transition between models while preserving motion across the transition. In addition, energy may vary between flex models when using a truncated mode set. The LSQI-DSM algorithm can accommodate significant changes in energy between FEM models and carries elastic motion across FEM model transitions. Compared with previous approaches, the LSQI-DSM algorithm shows improvements ranging from a significant reduction to a complete removal of transients across FEM model transitions as well as maintaining elastic motion from the prior state.

  18. Optimal control of a universal rotating magnetic vector for petal-shaped capsule robot in curve environment

    NASA Astrophysics Data System (ADS)

    Zhang, Yongshun; Bai, Jianwei; Chi, Minglu; Cheng, Cunxin; Wang, Dianlong

    2014-09-01

    Steering control of a capsule robot in curve environment by magnetic navigation is not yet solved completely. A petal-shaped capsule robot with less steering resistance based on multiple wedge effects is presented, and an optimization method with two processes for determining the orientation of a pre-applied universal magnetic spin vector is proposed. To realize quick and non-contact steering swimming, a fuzzy comprehensive evaluation method for optimizing the steering driving angle is presented based on two evaluation indexes including the average steering speed and the average steering trajectory deviation, achieving the initial optimal orientation of a universal magnetic spin vector. To further reduce robotic magnetic vibration, a main target method for optimizing its final orientation, which is used for fine adjustment, is employed under the constrains of the magnetic moments. Swimming experimental results in curve pipe verified the effectiveness of the optimization method, which can be effectively used to realize non-contact steering swimming of the petal-shaped robot and reduce its vibration.

  19. Robust Constrained Optimization Approach to Control Design for International Space Station Centrifuge Rotor Auto Balancing Control System

    NASA Technical Reports Server (NTRS)

    Postma, Barry Dirk

    2005-01-01

    This thesis discusses application of a robust constrained optimization approach to control design to develop an Auto Balancing Controller (ABC) for a centrifuge rotor to be implemented on the International Space Station. The design goal is to minimize a performance objective of the system, while guaranteeing stability and proper performance for a range of uncertain plants. The Performance objective is to minimize the translational response of the centrifuge rotor due to a fixed worst-case rotor imbalance. The robustness constraints are posed with respect to parametric uncertainty in the plant. The proposed approach to control design allows for both of these objectives to be handled within the framework of constrained optimization. The resulting controller achieves acceptable performance and robustness characteristics.

  20. Shape optimization of road tunnel cross-section by simulated annealing

    NASA Astrophysics Data System (ADS)

    Sobótka, Maciej; Pachnicz, Michał

    2016-06-01

    The paper concerns shape optimization of a tunnel excavation cross-section. The study incorporates optimization procedure of the simulated annealing (SA). The form of a cost function derives from the energetic optimality condition, formulated in the authors' previous papers. The utilized algorithm takes advantage of the optimization procedure already published by the authors. Unlike other approaches presented in literature, the one introduced in this paper takes into consideration a practical requirement of preserving fixed clearance gauge. Itasca Flac software is utilized in numerical examples. The optimal excavation shapes are determined for five different in situ stress ratios. This factor significantly affects the optimal topology of excavation. The resulting shapes are elongated in the direction of a principal stress greater value. Moreover, the obtained optimal shapes have smooth contours circumscribing the gauge.

  1. Stable least-squares matching for oblique images using bound constrained optimization and a robust loss function

    NASA Astrophysics Data System (ADS)

    Hu, Han; Ding, Yulin; Zhu, Qing; Wu, Bo; Xie, Linfu; Chen, Min

    2016-08-01

    Least-squares matching is a standard procedure in photogrammetric applications for obtaining sub-pixel accuracies of image correspondences. However, least-squares matching has also been criticized for its instability, which is primarily reflected by the requests for the initial correspondence and favorable image quality. In image matching between oblique images, due to the blur, illumination differences and other effects, the image attributes of different views are notably different, which results in a more severe convergence problem. Aiming at improving the convergence rate and robustness of least-squares matching of oblique images, we incorporated prior geometric knowledge in the optimization process, which is reflected as the bounded constraints on the optimizing parameters that constrain the search for a solution to a reasonable region. Furthermore, to be resilient to outliers, we substituted the square loss with a robust loss function. To solve the composite problem, we reformulated the least-squares matching problem as a bound constrained optimization problem, which can be solved with bounds constrained Levenberg-Marquardt solver. Experimental results consisting of images from two different penta-view oblique camera systems confirmed that the proposed method shows guaranteed final convergences in various scenarios compared to the approximately 20-50% convergence rate of classical least-squares matching.

  2. Elastic Model Transitions: A Hybrid Approach Utilizing Quadratic Inequality Constrained Least Squares (LSQI) and Direct Shape Mapping (DSM)

    NASA Technical Reports Server (NTRS)

    Hannan, Mike R.; Jurenko, Robert J.; Bush, Jason; Ottander, John

    2014-01-01

    A method for transitioning linear time invariant (LTI) models in time varying simulation is proposed that utilizes a hybrid approach for determining physical displacements by augmenting the original quadratically constrained least squares (LSQI) algorithm with Direct Shape Mapping (DSM) and modifying the energy constraints. The approach presented is applicable to simulation of the elastic behavior of launch vehicles and other structures that utilize discrete LTI finite element model (FEM) derived mode sets (eigenvalues and eigenvectors) that are propagated throughout time. The time invariant nature of the elastic data presents a problem of how to properly transition elastic states from the prior to the new model while preserving motion across the transition and ensuring there is no truncation or excitation of the system. A previous approach utilizes a LSQI algorithm with an energy constraint to effect smooth transitions between eigenvector sets with no requirement that the models be of similar dimension or have any correlation. This approach assumes energy is conserved across the transition, which results in significant non-physical transients due to changing quasi-steady state energy between mode sets, a phenomenon seen when utilizing a truncated mode set. The computational burden of simulating a full mode set is significant so a subset of modes is often selected to reduce run time. As a result of this truncation, energy between mode sets may not be constant and solutions across transitions could produce non-physical transients. In an effort to abate these transients an improved methodology was developed based on the aforementioned approach, but this new approach can handle significant changes in energy across mode set transitions. It is proposed that physical velocities due to elastic behavior be solved for using the LSQI algorithm, but solve for displacements using a two-step process that independently addresses the quasi-steady-state and non

  3. Optimization of Lens Adjustment in Semiconductor Lithography Equipment Using Quadratically Constrained and Second-Order Cone Programming

    NASA Astrophysics Data System (ADS)

    Shinano, Yuji; Yoshihara, Toshiyuki; Miyashiro, Ryuhei; Fukagawa, Youzou

    The present paper considers optimization of lens adjustment in semiconductor lithography equipment. For improving productivity, the laser irradiation power of recent semiconductor lithography equipment has been boosted, which causes significant aberration due to heating during exposure. The aberration of the equipment must be measured or estimated in order to adjust the positions and orientations of the lenses. Since this adjustment is performed sequentially during exposure, the optimization problem to obtain optimal lens adjustment should be solved within a time as short as 100 ms. Although the problem of calculating the optimal lens adjustment can be naturally formulated as a convex minimization problem, in such a formulation the objective function is convex but includes several nondifferentiable points. Hence, optimization methods based on derivatives cannot be applied. Other approaches using derivative-free optimization or meta-heuristic methods cannot guarantee that the obtained solutions are truly optimal. Therefore, we formulate the optimization problem as quadratically constrained and second-order cone programming problems, which can be handled by solvers using an interior point method. Using the proposed formulations, computational experiments demonstrate that the optimal lens adjustment is obtained in a practical computational time, which is much less than 100 ms.

  4. Communication: Analytical optimal pulse shapes obtained with the aid of genetic algorithms: Controlling the photoisomerization yield of retinal

    NASA Astrophysics Data System (ADS)

    Guerrero, R. D.; Arango, C. A.; Reyes, A.

    2016-07-01

    We recently proposed a Quantum Optimal Control (QOC) method constrained to build pulses from analytical pulse shapes [R. D. Guerrero et al., J. Chem. Phys. 143(12), 124108 (2015)]. This approach was applied to control the dissociation channel yields of the diatomic molecule KH, considering three potential energy curves and one degree of freedom. In this work, we utilized this methodology to study the strong field control of the cis-trans photoisomerization of 11-cis retinal. This more complex system was modeled with a Hamiltonian comprising two potential energy surfaces and two degrees of freedom. The resulting optimal pulse, made of 6 linearly chirped pulses, was capable of controlling the population of the trans isomer on the ground electronic surface for nearly 200 fs. The simplicity of the pulse generated with our QOC approach offers two clear advantages: a direct analysis of the sequence of events occurring during the driven dynamics, and its reproducibility in the laboratory with current laser technologies.

  5. Optimizing coherent anti-Stokes Raman scattering by genetic algorithm controlled pulse shaping

    NASA Astrophysics Data System (ADS)

    Yang, Wenlong; Sokolov, Alexei

    2010-10-01

    The hybrid coherent anti-Stokes Raman scattering (CARS) has been successful applied to fast chemical sensitive detections. As the development of femto-second pulse shaping techniques, it is of great interest to find the optimum pulse shapes for CARS. The optimum pulse shapes should minimize the non-resonant four wave mixing (NRFWM) background and maximize the CARS signal. A genetic algorithm (GA) is developed to make a heuristic searching for optimized pulse shapes, which give the best signal the background ratio. The GA is shown to be able to rediscover the hybrid CARS scheme and find optimized pulse shapes for customized applications by itself.

  6. Memory and Energy Optimization Strategies for Multithreaded Operating System on the Resource-Constrained Wireless Sensor Node

    PubMed Central

    Liu, Xing; Hou, Kun Mean; de Vaulx, Christophe; Xu, Jun; Yang, Jianfeng; Zhou, Haiying; Shi, Hongling; Zhou, Peng

    2015-01-01

    Memory and energy optimization strategies are essential for the resource-constrained wireless sensor network (WSN) nodes. In this article, a new memory-optimized and energy-optimized multithreaded WSN operating system (OS) LiveOS is designed and implemented. Memory cost of LiveOS is optimized by using the stack-shifting hybrid scheduling approach. Different from the traditional multithreaded OS in which thread stacks are allocated statically by the pre-reservation, thread stacks in LiveOS are allocated dynamically by using the stack-shifting technique. As a result, memory waste problems caused by the static pre-reservation can be avoided. In addition to the stack-shifting dynamic allocation approach, the hybrid scheduling mechanism which can decrease both the thread scheduling overhead and the thread stack number is also implemented in LiveOS. With these mechanisms, the stack memory cost of LiveOS can be reduced more than 50% if compared to that of a traditional multithreaded OS. Not is memory cost optimized, but also the energy cost is optimized in LiveOS, and this is achieved by using the multi-core “context aware” and multi-core “power-off/wakeup” energy conservation approaches. By using these approaches, energy cost of LiveOS can be reduced more than 30% when compared to the single-core WSN system. Memory and energy optimization strategies in LiveOS not only prolong the lifetime of WSN nodes, but also make the multithreaded OS feasible to run on the memory-constrained WSN nodes. PMID:25545264

  7. Shape optimization for maximum stability and dynamic stiffness

    NASA Technical Reports Server (NTRS)

    Szyszkowski, W.

    1990-01-01

    Any optimization of structures for maximum stability or for maximum dynamic stiffness deals with an eigenvalue problem. The goal of this optimization is to raise the lowest eigenvalue (or eigenvalues) of the problem to its highest (optimal) level at a constant volume of the structure. Likely the lowest eigenvalue may be either inherently multi-modal or it can become multi-modal as a result of the optimization process. The multimodeness introduces some ambiguity to the eigenvalue problem and make the optimization difficult to handle. Thus far, only the simplest cases of multi-modal structures have been effectively optimized using rather elaborate analytical methods. Numerous publications report design of a minimum volume structure with different eigenvalues constraints, in which, however, the modality of the problem is assumed a priori. The method presented here utilizes a multi-modal optimality criteria and allows for inclusion of an arbitrary number of buckling or vibrations modes which might influence the optimization process. The real multi-modality of the problem, that is the number of modes participating in the final optimal design is determined iteratively. Because of a natural use of the FEM technique the method is easy to program and might be helpful in design of large flexible space structures.

  8. An adaptive multiquadric radial basis function method for expensive black-box mixed-integer nonlinear constrained optimization

    NASA Astrophysics Data System (ADS)

    Rashid, Kashif; Ambani, Saumil; Cetinkaya, Eren

    2013-02-01

    Many real-world optimization problems comprise objective functions that are based on the output of one or more simulation models. As these underlying processes can be time and computation intensive, the objective function is deemed expensive to evaluate. While methods to alleviate this cost in the optimization procedure have been explored previously, less attention has been given to the treatment of expensive constraints. This article presents a methodology for treating expensive simulation-based nonlinear constraints alongside an expensive simulation-based objective function using adaptive radial basis function techniques. Specifically, a multiquadric radial basis function approximation scheme is developed, together with a robust training method, to model not only the costly objective function, but also each expensive simulation-based constraint defined in the problem. The article presents the methodology developed for expensive nonlinear constrained optimization problems comprising both continuous and integer variables. Results from various test cases, both analytical and simulation-based, are presented.

  9. Optimization of Stability Constrained Geometrically Nonlinear Shallow Trusses Using an Arc Length Sparse Method with a Strain Energy Density Approach

    NASA Technical Reports Server (NTRS)

    Hrinda, Glenn A.; Nguyen, Duc T.

    2008-01-01

    A technique for the optimization of stability constrained geometrically nonlinear shallow trusses with snap through behavior is demonstrated using the arc length method and a strain energy density approach within a discrete finite element formulation. The optimization method uses an iterative scheme that evaluates the design variables' performance and then updates them according to a recursive formula controlled by the arc length method. A minimum weight design is achieved when a uniform nonlinear strain energy density is found in all members. This minimal condition places the design load just below the critical limit load causing snap through of the structure. The optimization scheme is programmed into a nonlinear finite element algorithm to find the large strain energy at critical limit loads. Examples of highly nonlinear trusses found in literature are presented to verify the method.

  10. Surface effects on shape and topology optimization of nanostructures

    NASA Astrophysics Data System (ADS)

    Nanthakumar, S. S.; Valizadeh, Navid; Park, Harold S.; Rabczuk, Timon

    2015-07-01

    We present a computational method for the optimization of nanostructures, where our specific interest is in capturing and elucidating surface stress and surface elastic effects on the optimal nanodesign. XFEM is used to solve the nanomechanical boundary value problem, which involves a discontinuity in the strain field and the presence of surface effects along the interface. The boundary of the nano-structure is implicitly represented by a level set function, which is considered as the design variable in the optimization process. Two objective functions, minimizing the total potential energy of a nanostructure subjected to a material volume constraint and minimizing the least square error compared to a target displacement, are chosen for the numerical examples. We present results of optimal topologies of a nanobeam subject to cantilever and fixed boundary conditions. The numerical examples demonstrate the importance of size and aspect ratio in determining how surface effects impact the optimized topology of nanobeams.