Constrained Aeroacoustic Shape Optimization Using the Surrogate Management Framework
2003-12-01
412 A. L. Marsden, M. Wang & J. E. Dennis, Jr. rum for collaboration, as well as Charles Audet and Petros Koumoutsakos for valuable discussions...2003 Optimal aeroa- coustic shape design using the surrogate management framework. Submitted for review. MARSDEN, A. L., WANG, M. & KOUMOUTSAKOS , P
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.
NASA Astrophysics Data System (ADS)
Lee, Dae Young
The design of a small satellite is challenging since they are constrained by mass, volume, and power. To mitigate these constraint effects, designers adopt deployable configurations on the spacecraft that result in an interesting and difficult optimization problem. The resulting optimization problem is challenging due to the computational complexity caused by the large number of design variables and the model complexity created by the deployables. Adding to these complexities, there is a lack of integration of the design optimization systems into operational optimization, and the utility maximization of spacecraft in orbit. The developed methodology enables satellite Multidisciplinary Design Optimization (MDO) that is extendable to on-orbit operation. Optimization of on-orbit operations is possible with MDO since the model predictive controller developed in this dissertation guarantees the achievement of the on-ground design behavior in orbit. To enable the design optimization of highly constrained and complex-shaped space systems, the spherical coordinate analysis technique, called the "Attitude Sphere", is extended and merged with an additional engineering tools like OpenGL. OpenGL's graphic acceleration facilitates the accurate estimation of the shadow-degraded photovoltaic cell area. This technique is applied to the design optimization of the satellite Electric Power System (EPS) and the design result shows that the amount of photovoltaic power generation can be increased more than 9%. Based on this initial methodology, the goal of this effort is extended from Single Discipline Optimization to Multidisciplinary Optimization, which includes the design and also operation of the EPS, Attitude Determination and Control System (ADCS), and communication system. The geometry optimization satisfies the conditions of the ground development phase; however, the operation optimization may not be as successful as expected in orbit due to disturbances. To address this issue
Stability-Constrained Aerodynamic Shape Optimization with Applications to Flying Wings
NASA Astrophysics Data System (ADS)
Mader, Charles Alexander
A set of techniques is developed that allows the incorporation of flight dynamics metrics as an additional discipline in a high-fidelity aerodynamic optimization. Specifically, techniques for including static stability constraints and handling qualities constraints in a high-fidelity aerodynamic optimization are demonstrated. These constraints are developed from stability derivative information calculated using high-fidelity computational fluid dynamics (CFD). Two techniques are explored for computing the stability derivatives from CFD. One technique uses an automatic differentiation adjoint technique (ADjoint) to efficiently and accurately compute a full set of static and dynamic stability derivatives from a single steady solution. The other technique uses a linear regression method to compute the stability derivatives from a quasi-unsteady time-spectral CFD solution, allowing for the computation of static, dynamic and transient stability derivatives. Based on the characteristics of the two methods, the time-spectral technique is selected for further development, incorporated into an optimization framework, and used to conduct stability-constrained aerodynamic optimization. This stability-constrained optimization framework is then used to conduct an optimization study of a flying wing configuration. This study shows that stability constraints have a significant impact on the optimal design of flying wings and that, while static stability constraints can often be satisfied by modifying the airfoil profiles of the wing, dynamic stability constraints can require a significant change in the planform of the aircraft in order for the constraints to be satisfied.
NASA Astrophysics Data System (ADS)
Hau, L. C.; Fung, E. H. K.
2004-08-01
This work presents the use of a multi-objective genetic algorithm (MOGA) to solve an integrated optimization problem for the shape control of flexible beams with an active constrained layer damping (ACLD) treatment. The design objectives are to minimize the total weight of the system, the input voltages and the steady-state error between the achieved and desired shapes. Design variables include the thickness of the constraining and viscoelastic layers, the arrangement of the ACLD patches, as well as the control gains. In order to set up an evaluator for the MOGA, the finite element method (FEM), in conjunction with the Golla-Hughes-McTavish (GHM) method, is employed to model a clamped-free beam with ACLD patches to predict the dynamic behaviour of the system. As a result of the optimization, reasonable Pareto solutions are successfully obtained. It is shown that ACLD treatment is suitable for shape control of flexible structures and that the MOGA is applicable to the present integrated optimization problem.
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
Constrained Multiobjective Biogeography Optimization Algorithm
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
Interactive graphics nonlinear constrained optimization
NASA Technical Reports Server (NTRS)
Saouma, V. E.; Sikiotis, E. S.
1984-01-01
An interactive computer graphics environment was used for nonlinear constrained optimization analysis. It is found that by combining the power of a digital computer with the subtlety of engineering judgment during program execution, final results can be substantially better than the ones achieved by the numerical algorithm by itself.
Method of constrained global optimization
NASA Astrophysics Data System (ADS)
Altschuler, Eric Lewin; Williams, Timothy J.; Ratner, Edward R.; Dowla, Farid; Wooten, Frederick
1994-04-01
We present a new method for optimization: constrained global optimization (CGO). CGO iteratively uses a Glauber spin flip probability and the Metropolis algorithm. The spin flip probability allows changing only the values of variables contributing excessively to the function to be minimized. We illustrate CGO with two problems-Thomson's problem of finding the minimum-energy configuration of unit charges on a spherical surface, and a problem of assigning offices-for which CGO finds better minima than other methods. We think CGO will apply to a wide class of optimization problems.
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.
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.
Shape optimization of damping layers
NASA Technical Reports Server (NTRS)
Lin, T.-C.; Scott, R. A.
1987-01-01
Shape optimization of unconstrained and constrained damping layers is completed. The specific problem analyzed is a cantilever beam loaded at its tip by a harmonic force. Finite element modeling and mathematical programming techniques are used to obtain the solution. Performance measures are taken to be reduction of maximum diplacement and increase in fatigue lifetime. Results include the improvement, over the uniform treatment case, of these measures when the profile of the damping layer is optimized.
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.
Order-constrained linear optimization.
Tidwell, Joe W; Dougherty, Michael R; Chrabaszcz, Jeffrey S; Thomas, Rick P
2017-02-27
Despite the fact that data and theories in the social, behavioural, and health sciences are often represented on an ordinal scale, there has been relatively little emphasis on modelling ordinal properties. The most common analytic framework used in psychological science is the general linear model, whose variants include ANOVA, MANOVA, and ordinary linear regression. While these methods are designed to provide the best fit to the metric properties of the data, they are not designed to maximally model ordinal properties. In this paper, we develop an order-constrained linear least-squares (OCLO) optimization algorithm that maximizes the linear least-squares fit to the data conditional on maximizing the ordinal fit based on Kendall's τ. The algorithm builds on the maximum rank correlation estimator (Han, 1987, Journal of Econometrics, 35, 303) and the general monotone model (Dougherty & Thomas, 2012, Psychological Review, 119, 321). Analyses of simulated data indicate that when modelling data that adhere to the assumptions of ordinary least squares, OCLO shows minimal bias, little increase in variance, and almost no loss in out-of-sample predictive accuracy. In contrast, under conditions in which data include a small number of extreme scores (fat-tailed distributions), OCLO shows less bias and variance, and substantially better out-of-sample predictive accuracy, even when the outliers are removed. We show that the advantages of OCLO over ordinary least squares in predicting new observations hold across a variety of scenarios in which researchers must decide to retain or eliminate extreme scores when fitting data.
Energetic Materials Optimization via Constrained Search
2015-06-01
ARL-TR-7304• JUN 2015 US Army Research Laboratory Energetic Materials Optimization via Constrained Search by Berend Christopher Rinderspacher...Army Research Laboratory Energetic Materials Optimization via Constrained Search by Berend Christopher Rinderspacher Weapons and Materials Research...burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching
Optimization of retinotopy constrained source estimation constrained by prior
Hagler, Donald J.
2015-01-01
Studying how the timing and amplitude of visual evoked responses (VERs) vary between visual areas is important for understanding visual processing but is complicated by difficulties in reliably estimating VERs in individual visual areas using non-invasive brain measurements. Retinotopy constrained source estimation (RCSE) addresses this challenge by using multiple, retinotopically-mapped stimulus locations to simultaneously constrain estimates of VERs in visual areas V1, V2, and V3, taking advantage of the spatial precision of fMRI retinotopy and the temporal resolution of magnetoencephalography (MEG) or electroencephalography (EEG). Nonlinear optimization of dipole locations, guided by a group-constrained RCSE solution as a prior, improved the robustness of RCSE. This approach facilitated the analysis of differences in timing and amplitude of VERs between V1, V2, and V3, elicited by stimuli with varying luminance contrast in a sample of eight adult humans. The V1 peak response was 37% larger than that of V2 and 74% larger than that of V3, and also ~10–20 msec earlier. Normalized contrast response functions were nearly identical for the three areas. Results without dipole optimization, or with other nonlinear methods not constrained by prior estimates were similar but suffered from greater between-subject variability. The increased reliability of estimates offered by this approach may be particularly valuable when using a smaller number of stimulus locations, enabling a greater variety of stimulus and task manipulations. PMID:23868690
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
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
Optimal constrained layer damping with partial coverage
NASA Astrophysics Data System (ADS)
Marcelin, J.-L.; Trompette, Ph.; Smati, A.
1992-12-01
This paper deals with the optimal damping of beams constrained by viscoelastic layers when only one or several portions of the beam are covered. An efficient finite element model for dynamic analysis of such beams is used. The design variables are the dimensions and prescribed locations of the viscoelastic layers and the objective is the maximum viscoelastic damping factor. The method for nonlinear programming in structural optimization is the so-called method of moving asymptotes.
Newton modified barrier method in constrained optimization
NASA Technical Reports Server (NTRS)
Polyak, R.
1990-01-01
In this paper, we develop and investigate the Newton method for solving constrained (non-smooth) optimization problems. This approach is based on the modified barrier functions (MBF) theory and on the global converging step-size version of the Newton method for smooth unconstrained optimization. Due to the excellent properties of the MBF near primal-dual solution, the Newton modified barrier method (NMBM) has a better rate of convergence, better complexity bound, and is much more stable in the final stage of the computational process than the methods which are based on the classical barrier functions (CBF).
New General Tools for Constrained Geometry Optimizations.
De Vico, Luca; Olivucci, Massimo; Lindh, Roland
2005-09-01
A modification of the constrained geometry optimization method by Anglada and Bofill (Anglada, J. M.; Bofill, J. M. J. Comput. Chem. 1997, 18, 992-1003) is designed and implemented. The changes include the choice of projection, quasi-line-search, and the use of a Rational Function optimization approach rather than a reduced-restricted-quasi-Newton-Raphson method in the optimization step. Furthermore, we show how geometrical constrains can be implemented in an approach based on nonredundant curvilinear coordinates avoiding the inclusion of the constraints in the set of redundant coordinates used to define the internal coordinates. The behavior of the new implementation is demonstrated in geometry optimizations featuring single or multiple geometrical constraints (bond lengths, angles, etc.), optimizations on hyperspherical cross sections (as in the computation of steepest descent paths), and location of energy minima on the intersection subspace of two potential energy surfaces (i.e. minimum energy crossing points). In addition, a novel scheme to determine the crossing point geometrically nearest to a given molecular structure is proposed.
Constrained Graph Optimization: Interdiction and Preservation Problems
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.
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.
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.
Shared developmental programme strongly constrains beak shape diversity in songbirds.
Fritz, Joerg A; Brancale, Joseph; Tokita, Masayoshi; Burns, Kevin J; Hawkins, M Brent; Abzhanov, Arhat; Brenner, Michael P
2014-04-16
The striking diversity of bird beak shapes is an outcome of natural selection, yet the relative importance of the limitations imposed by the process of beak development on generating such variation is unclear. Untangling these factors requires mapping developmental mechanisms over a phylogeny far exceeding model systems studied thus far. We address this issue with a comparative morphometric analysis of beak shape in a diverse group of songbirds. Here we show that the dynamics of the proliferative growth zone must follow restrictive rules to explain the observed variation, with beak diversity constrained to a three parameter family of shapes, parameterized by length, depth and the degree of shear. We experimentally verify these predictions by analysing cell proliferation in the developing embryonic beaks of the zebra finch. Our findings indicate that beak shape variability in many songbirds is strongly constrained by shared properties of the developmental programme controlling the growth zone.
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.
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.
Printer model inversion by constrained optimization
NASA Astrophysics Data System (ADS)
Cholewo, Tomasz J.
1999-12-01
This paper describes a novel method for finding colorant amounts for which a printer will produce a requested color appearance based on constrained optimization. An error function defines the gamut mapping method and black replacement method. The constraints limit the feasible solution region to the device gamut and prevent exceeding the maximum total area coverage. Colorant values corresponding to in-gamut colors are found with precision limited only by the accuracy of the device model. Out-of- gamut colors are mapped to colors within the boundary of the device gamut. This general approach, used in conjunction with different types of color difference equations, can perform a wide range of out-of-gamut mappings such as chroma clipping or for finding colors on gamut boundary having specified properties. We present an application of this method to the creation of PostScript color rendering dictionaries and ICC profiles.
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
Smooth Constrained Heuristic Optimization of a Combinatorial Chemical Space
2015-05-01
ARL-TR-7294•MAY 2015 US Army Research Laboratory Smooth ConstrainedHeuristic Optimization of a Combinatorial Chemical Space by Berend Christopher...7294•MAY 2015 US Army Research Laboratory Smooth ConstrainedHeuristic Optimization of a Combinatorial Chemical Space by Berend Christopher...
NASA Astrophysics Data System (ADS)
Nguyen, Q. H.; Choi, S. B.
2012-01-01
This research focuses on optimal design of different types of magnetorheological brakes (MRBs), from which an optimal selection of MRB types is identified. In the optimization, common types of MRB such as disc-type, drum-type, hybrid-types, and T-shaped type are considered. The optimization problem is to find the optimal value of significant geometric dimensions of the MRB that can produce a maximum braking torque. The MRB is constrained in a cylindrical volume of a specific radius and length. After a brief description of the configuration of MRB types, the braking torques of the MRBs are derived based on the Herschel-Bulkley model of the MR fluid. The optimal design of MRBs constrained in a specific cylindrical volume is then analysed. The objective of the optimization is to maximize the braking torque while the torque ratio (the ratio of maximum braking torque and the zero-field friction torque) is constrained to be greater than a certain value. A finite element analysis integrated with an optimization tool is employed to obtain optimal solutions of the MRBs. Optimal solutions of MRBs constrained in different volumes are obtained based on the proposed optimization procedure. From the results, discussions on the optimal selection of MRB types depending on constrained volumes are given.
Shape optimization of peristaltic pumping
NASA Astrophysics Data System (ADS)
Walker, Shawn W.; Shelley, Michael J.
2010-02-01
Transport is a fundamental aspect of biology and peristaltic pumping is a fundamental mechanism to accomplish this; it is also important to many industrial processes. We present a variational method for optimizing the wave shape of a peristaltic pump. Specifically, we optimize the wave profile of a two dimensional channel containing a Navier-Stokes fluid with no assumption on the wave profile other than it is a traveling wave (e.g. we do not assume it is the graph of a function). Hence, this is an infinite-dimensional optimization problem. The optimization criteria consists of minimizing the input fluid power (due to the peristaltic wave) subject to constraints on the average flux of fluid and area of the channel. Sensitivities of the cost and constraints are computed variationally via shape differential calculus and we use a sequential quadratic programming (SQP) method to find a solution of the first order KKT conditions. We also use a merit-function based line search in order to balance between decreasing the cost and keeping the constraints satisfied when updating the channel shape. Our numerical implementation uses a finite element method for computing a solution of the Navier-Stokes equations, adjoint equations, as well as for the SQP method when computing perturbations of the channel shape. The walls of the channel are deformed by an explicit front-tracking approach. In computing functional sensitivities with respect to shape, we use L2-type projections for computing boundary stresses and for geometric quantities such as the tangent field on the channel walls and the curvature; we show error estimates for the boundary stress and tangent field approximations. As a result, we find optimized shapes that are not obvious and have not been previously reported in the peristaltic pumping literature. Specifically, we see highly asymmetric wave shapes that are far from being sine waves. Many examples are shown for a range of fluxes and Reynolds numbers up to Re=500
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
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.
A Model for Optimal Constrained Adaptive Testing.
ERIC Educational Resources Information Center
van der Linden, Wim J.; Reese, Lynda M.
1998-01-01
Proposes a model for constrained computerized adaptive testing in which the information in the test at the trait level (theta) estimate is maximized subject to the number of possible constraints on the content of the test. Test assembly relies on a linear-programming approach. Illustrates the approach through simulation with items from the Law…
Asynchronous parallel generating set search for linearly-constrained optimization.
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.
NASA Astrophysics Data System (ADS)
Na, Seong-Won; Kallivokas, Loukas F.
2008-03-01
In this article we discuss a formal framework for casting the inverse problem of detecting the location and shape of an insonified scatterer embedded within a two-dimensional homogeneous acoustic host, in terms of a partial-differential-equation-constrained optimization approach. We seek to satisfy the ensuing Karush-Kuhn-Tucker first-order optimality conditions using boundary integral equations. The treatment of evolving boundary shapes, which arise naturally during the search for the true shape, resides on the use of total derivatives, borrowing from recent work by Bonnet and Guzina [1-4] in elastodynamics. We consider incomplete information collected at stations sparsely spaced at the assumed obstacle’s backscattered region. To improve on the ability of the optimizer to arrive at the global optimum we: (a) favor an amplitude-based misfit functional; and (b) iterate over both the frequency- and wave-direction spaces through a sequence of problems. We report numerical results for sound-hard objects with shapes ranging from circles, to penny- and kite-shaped, including obstacles with arbitrarily shaped non-convex boundaries.
Constrained Trajectory Optimization Using Pseudospectral Methods (Preprint)
2008-08-05
at itu de , d eg POST SPOCS Figure 5. Trajectory Comparison of Integration Method Comparison IV.B. Basic Optimization Comparison The second set of...1500 2000 2500 3000 20 30 40 50 60 70 80 90 100 110 120 Altitude Time, sec A lti tu de , k m POST SPOCS Figure 7. Altitude Comparison of the First...Coordinates Z , k m POST SPOCS Figure 8. Range Comparison of the First Optimization Comparison 13 of 33 American Institute of Aeronautics and
A spatial shape constrained clustering method for mammographic mass segmentation.
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.
Constrained optimization for image restoration using nonlinear programming
NASA Technical Reports Server (NTRS)
Yeh, C.-L.; Chin, R. T.
1985-01-01
The constrained optimization problem for image restoration, utilizing incomplete information and partial constraints, is formulated using nonlinear proramming techniques. This method restores a distorted image by optimizing a chosen object function subject to available constraints. The penalty function method of nonlinear programming is used. Both linear or nonlinear object function, and linear or nonlinear constraint functions can be incorporated in the formulation. This formulation provides a generalized approach to solve constrained optimization problems for image restoration. Experiments using this scheme have been performed. The results are compared with those obtained from other restoration methods and the comparative study is presented.
Constrained optimization for image restoration using nonlinear programming
NASA Technical Reports Server (NTRS)
Yeh, C.-L.; Chin, R. T.
1985-01-01
The constrained optimization problem for image restoration, utilizing incomplete information and partial constraints, is formulated using nonlinear proramming techniques. This method restores a distorted image by optimizing a chosen object function subject to available constraints. The penalty function method of nonlinear programming is used. Both linear or nonlinear object function, and linear or nonlinear constraint functions can be incorporated in the formulation. This formulation provides a generalized approach to solve constrained optimization problems for image restoration. Experiments using this scheme have been performed. The results are compared with those obtained from other restoration methods and the comparative study is presented.
Insights into capacity-constrained optimal transport.
Korman, Jonathan; McCann, Robert J
2013-06-18
A variant of the classical optimal transportation problem is the following: among all joint measures with fixed marginals and that are dominated by a given density, find the optimal one. Existence and uniqueness of solutions to this variant were established by Korman and McCann. In the present article, we expose an unexpected symmetry leading to explicit examples in two and more dimensions. These are inspired in part by simulations in one dimension that display singularities and topology and in part by two further developments: the identification of all extreme points in the feasible set and an approach to uniqueness based on constructing feasible perturbations.
Sequential unconstrained minimization algorithms for constrained optimization
NASA Astrophysics Data System (ADS)
Byrne, Charles
2008-02-01
The problem of minimizing a function f(x):RJ → R, subject to constraints on the vector variable x, occurs frequently in inverse problems. Even without constraints, finding a minimizer of f(x) may require iterative methods. We consider here a general class of iterative algorithms that find a solution to the constrained minimization problem as the limit of a sequence of vectors, each solving an unconstrained minimization problem. Our sequential unconstrained minimization algorithm (SUMMA) is an iterative procedure for constrained minimization. At the kth step we minimize the function G_k(x)=f(x)+g_k(x), to obtain xk. The auxiliary functions gk(x):D ⊆ RJ → R+ are nonnegative on the set D, each xk is assumed to lie within D, and the objective is to minimize the continuous function f:RJ → R over x in the set C=\\overline D , the closure of D. We assume that such minimizers exist, and denote one such by \\hat x . We assume that the functions gk(x) satisfy the inequalities 0\\leq g_k(x)\\leq G_{k-1}(x)-G_{k-1}(x^{k-1}), for k = 2, 3, .... Using this assumption, we show that the sequence {f(xk)} is decreasing and converges to f({\\hat x}) . If the restriction of f(x) to D has bounded level sets, which happens if \\hat x is unique and f(x) is closed, proper and convex, then the sequence {xk} is bounded, and f(x^*)=f({\\hat x}) , for any cluster point x*. Therefore, if \\hat x is unique, x^*={\\hat x} and \\{x^k\\}\\rightarrow {\\hat x} . When \\hat x is not unique, convergence can still be obtained, in particular cases. The SUMMA includes, as particular cases, the well-known barrier- and penalty-function methods, the simultaneous multiplicative algebraic reconstruction technique (SMART), the proximal minimization algorithm of Censor and Zenios, the entropic proximal methods of Teboulle, as well as certain cases of gradient descent and the Newton-Raphson method. The proof techniques used for SUMMA can be extended to obtain related results for the induced proximal
Optimization of input-constrained systems
NASA Astrophysics Data System (ADS)
Malki, Suleyman; Spaanenburg, Lambert
2009-05-01
The computational demands of algorithms are rapidly growing. The naive implementation uses extended doubleprecision floating-point numbers and has therefore extreme difficulties in maintaining real-time performance. For fixedpoint numbers, the value representation pushes in two directions (value range and step size) to set the applicationdependent word size. In the general case, checking all combinations of all different values on all system inputs will easily become computationally infeasible. Checking corner cases only helps to reduce the combinatorial explosion, as still checking for accuracy and precision to limit word size remains a considerable effort. A range of evolutionary techniques have been tried where the sheer size of the problem withstands an extensive search. When the value range can be limited, the problem becomes tractable and a constructive approach becomes feasible. We propose an approach that is reminiscent of the Quine-Mc.Cluskey logic minimization procedure. Next to the conjunctive search as popular in Boolean minimization, we investigate the disjunctive approach that starts from a presumed minimal word size. To eliminate the occurrence of anomalies, this still has to be checked for larger word sizes. The procedure has initially been implemented using Java and Matlab. We have applied the above procedure to feed-forward and to cellular neural networks (CNN) as typical examples of input-constrained systems. In the case of hole-filling by means of a CNN, we find that the 1461 different coefficient sets can be reduced to 360, each giving robust behaviour on 7-bits internal words.
Robust Constrained Blackbox Optimization with Surrogates
2015-05-21
hydroelectric generators: A case study. International Journal of Performability Engineering, 10(6):615–630, 2014. 7. M. Minville, D. Cartier, C. Guay...optimization, scheduling of a fleet of hydroelectric generators, and calibration of hydrological models. The PI and CoPi are currently supervising 1 MSc...approved for public release 6) M.S. Ouali, H. Aoudjit and C. Audet. Replacement Scheduling of a Fleet of Hydroelectric Generators: A Case Study
Posture strategies generated by constrained optimization.
Pettersson, Robert; Bartonek, Åsa; Gutierrez-Farewik, Elena M
2012-02-02
For people with motion disorders, posture can impact fatigue, discomfort or deformities in the long term. Orthopedic treatments such as orthoses or orthopedic surgeries which change geometric properties can improve posture in these individuals. In this study, a model has been created to study posture strategies in such situations. A 3D mechanical model consisting of eight rigid segments and 30 muscle groups is used in which varying moment arms along the ranges of motion and biarticular muscles are considered. The method is based on static optimization, both to solve the load sharing in the muscle system and to choose posture strategy. The optimization computes the specific posture with minimal required effort (level of muscle activations), while fulfilling constraints containing subject specific ranges of motion, muscle strength/weakness and external support if present. Anthropometry and strength were scaled to each individual, based on reported pediatric anthropometry and strength values, combined with each individual's physical assessment. A control group of 10 able-bodied subjects as well as three subjects with motion disorders were studied, and simulated posture was compared with experimental data. The simulation showed reasonable to good agreement and ability to predict the effect of motion disorders and of external support. An example of application in parameter studies was also presented wherein ankle orthosis angles were varied. The model allows the user to study muscle activity at the muscle group level, position of center of mass and moments at joints in various situations.
A Collective Neurodynamic Approach to Constrained Global Optimization.
Yan, Zheng; Fan, Jianchao; Wang, Jun
2016-04-01
Global optimization is a long-lasting research topic in the field of optimization, posting many challenging theoretic and computational issues. This paper presents a novel collective neurodynamic method for solving constrained global optimization problems. At first, a one-layer recurrent neural network (RNN) is presented for searching the Karush-Kuhn-Tucker points of the optimization problem under study. Next, a collective neuroydnamic optimization approach is developed by emulating the paradigm of brainstorming. Multiple RNNs are exploited cooperatively to search for the global optimal solutions in a framework of particle swarm optimization. Each RNN carries out a precise local search and converges to a candidate solution according to its own neurodynamics. The neuronal state of each neural network is repetitively reset by exchanging historical information of each individual network and the entire group. Wavelet mutation is performed to avoid prematurity, add diversity, and promote global convergence. It is proved in the framework of stochastic optimization that the proposed collective neurodynamic approach is capable of computing the global optimal solutions with probability one provided that a sufficiently large number of neural networks are utilized. The essence of the collective neurodynamic optimization approach lies in its potential to solve constrained global optimization problems in real time. The effectiveness and characteristics of the proposed approach are illustrated by using benchmark optimization problems.
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.
Constrained ripple optimization of Tokamak bundle divertors
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.
Improved Differential Evolution with Shrinking Space Technique for Constrained Optimization
NASA Astrophysics Data System (ADS)
Fu, Chunming; Xu, Yadong; Jiang, Chao; Han, Xu; Huang, Zhiliang
2017-05-01
Most of the current evolutionary algorithms for constrained optimization algorithm are low computational efficiency. In order to improve efficiency, an improved differential evolution with shrinking space technique and adaptive trade-off model, named ATMDE, is proposed to solve constrained optimization problems. The proposed ATMDE algorithm employs an improved differential evolution as the search optimizer to generate new offspring individuals into evolutionary population. For the constraints, the adaptive trade-off model as one of the most important constraint-handling techniques is employed to select better individuals to retain into the next population, which could effectively handle multiple constraints. Then the shrinking space technique is designed to shrink the search region according to feedback information in order to improve computational efficiency without losing accuracy. The improved DE algorithm introduces three different mutant strategies to generate different offspring into evolutionary population. Moreover, a new mutant strategy called "DE/rand/best/1" is constructed to generate new individuals according to the feasibility proportion of current population. Finally, the effectiveness of the proposed method is verified by a suite of benchmark functions and practical engineering problems. This research presents a constrained evolutionary algorithm with high efficiency and accuracy for constrained optimization problems.
Constrained optimization schemes for geophysical inversion of seismic data
NASA Astrophysics Data System (ADS)
Sosa Aguirre, Uram Anibal
Many experimental techniques in geophysics advance the understanding of Earth processes by estimating and interpreting Earth structure (e.g., velocity and/or density structure). These techniques use different types of geophysical data which can be collected and analyzed separately, sometimes resulting in inconsistent models of the Earth depending on data quality, methods and assumptions made. This dissertation presents two approaches for geophysical inversion of seismic data based on constrained optimization. In one approach we expand a one dimensional (1-D) joint inversion least-squares (LSQ) algorithm by introducing a constrained optimization methodology. Then we use the 1-D inversion results to produce 3-D Earth velocity structure models. In the second approach, we provide a unified constrained optimization framework for solving a 1-D inverse wave propagation problem. In Chapter 2 we present a constrained optimization framework for joint inversion. This framework characterizes 1-D Earth's structure by using seismic shear wave velocities as a model parameter. We create two geophysical synthetic data sets sensitive to shear velocities, namely receiver function and surface wave dispersion. We validate our approach by comparing our numerical results with a traditional unconstrained method, and also we test our approach robustness in the presence of noise. Chapter 3 extends this framework to include an interpolation technique for creating 3-D Earth velocity structure models of the Rio Grande Rift region. Chapter 5 introduces the joint inversion of multiple data sets by adding delay travel times information in a synthetic setup, and leave the posibility to include more data sets. Finally, in Chapter 4 we pose a 1-D inverse full-waveform propagation problem as a PDE-constrained optimization program, where we invert for the material properties in terms of shear wave velocities throughout the physical domain. We facilitate the implementation and comparison of different
A filter-based evolutionary algorithm for constrained optimization.
Clevenger, Lauren M.; Hart, William Eugene; Ferguson, Lauren Ann
2004-02-01
We introduce a filter-based evolutionary algorithm (FEA) for constrained optimization. The filter used by an FEA explicitly imposes the concept of dominance on a partially ordered solution set. We show that the algorithm is provably robust for both linear and nonlinear problems and constraints. FEAs use a finite pattern of mutation offsets, and our analysis is closely related to recent convergence results for pattern search methods. We discuss how properties of this pattern impact the ability of an FEA to converge to a constrained local optimum.
A Projection Neural Network for Constrained Quadratic Minimax Optimization.
Liu, Qingshan; Wang, Jun
2015-11-01
This paper presents a projection neural network described by a dynamic system for solving constrained quadratic minimax programming problems. Sufficient conditions based on a linear matrix inequality are provided for global convergence of the proposed neural network. Compared with some of the existing neural networks for quadratic minimax optimization, the proposed neural network in this paper is capable of solving more general constrained quadratic minimax optimization problems, and the designed neural network does not include any parameter. Moreover, the neural network has lower model complexities, the number of state variables of which is equal to that of the dimension of the optimization problems. The simulation results on numerical examples are discussed to demonstrate the effectiveness and characteristics of the proposed neural network.
Spectral finite-element methods for parametric constrained optimization problems.
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.
Zeng, Sanyou; Jiao, Ruwang; Li, Changhe; Li, Xi; Alkasassbeh, Jawdat S
2017-09-01
A novel multiobjective technique is proposed for solving constrained optimization problems (COPs) in this paper. The method highlights three different perspectives: 1) a COP is converted into an equivalent dynamic constrained multiobjective optimization problem (DCMOP) with three objectives: a) the original objective; b) a constraint-violation objective; and c) a niche-count objective; 2) a method of gradually reducing the constraint boundary aims to handle the constraint difficulty; and 3) a method of gradually reducing the niche size aims to handle the multimodal difficulty. A general framework of the design of dynamic constrained multiobjective evolutionary algorithms is proposed for solving DCMOPs. Three popular types of multiobjective evolutionary algorithms, i.e., Pareto ranking-based, decomposition-based, and hype-volume indicator-based, are employed to instantiate the framework. The three instantiations are tested on two benchmark suites. Experimental results show that they perform better than or competitive to a set of state-of-the-art constraint optimizers, especially on problems with a large number of dimensions.
Geometry parameterization and multidisciplinary constrained optimization of coronary stents.
Pant, Sanjay; Bressloff, Neil W; Limbert, Georges
2012-01-01
Coronary stents are tubular type scaffolds that are deployed, using an inflatable balloon on a catheter, most commonly to recover the lumen size of narrowed (diseased) arterial segments. A common differentiating factor between the numerous stents used in clinical practice today is their geometric design. An ideal stent should have high radial strength to provide good arterial support post-expansion, have high flexibility for easy manoeuvrability during deployment, cause minimal injury to the artery when being expanded and, for drug eluting stents, should provide adequate drug in the arterial tissue. Often, with any stent design, these objectives are in competition such that improvement in one objective is a result of trade-off in others. This study proposes a technique to parameterize stent geometry, by varying the shape of circumferential rings and the links, and assess performance by modelling the processes of balloon expansion and drug diffusion. Finite element analysis is used to expand each stent (through balloon inflation) into contact with a representative diseased coronary artery model, followed by a drug release simulation. Also, a separate model is constructed to measure stent flexibility. Since the computational simulation time for each design is very high (approximately 24 h), a Gaussian process modelling approach is used to analyse the design space corresponding to the proposed parameterization. Four objectives to assess recoil, stress distribution, drug distribution and flexibility are set up to perform optimization studies. In particular, single objective constrained optimization problems are set up to improve the design relative to the baseline geometry-i.e. to improve one objective without compromising the others. Improvements of 8, 6 and 15% are obtained individually for stress, drug and flexibility metrics, respectively. The relative influence of the design features on each objective is quantified in terms of main effects, thereby suggesting the
Metal artifact reduction in x-ray computed tomography (CT) by constrained optimization
Zhang, Xiaomeng; Wang, Jing; Xing, Lei
2011-01-01
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. PMID:21452707
Truss systems and shape optimization
NASA Astrophysics Data System (ADS)
Pricop, Mihai Victor; Bunea, Marian; Nedelcu, Roxana
2017-07-01
Structure optimization is an important topic because of its benefits and wide applicability range, from civil engineering to aerospace and automotive industries, contributing to a more green industry and life. Truss finite elements are still in use in many research/industrial codesfor their simple stiffness matrixand are naturally matching the requirements for cellular materials especially considering various 3D printing technologies. Optimality Criteria combined with Solid Isotropic Material with Penalization is the optimization method of choice, particularized for truss systems. Global locked structures areobtainedusinglocally locked lattice local organization, corresponding to structured or unstructured meshes. Post processing is important for downstream application of the method, to make a faster link to the CAD systems. To export the optimal structure in CATIA, a CATScript file is automatically generated. Results, findings and conclusions are given for two and three-dimensional cases.
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.
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.
Shape Optimization of Swimming Sheets
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.
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.
What constrains children's learning of novel shape terms?
O'Hanlon, Catherine G; Roberson, Debi
2007-06-01
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 child's label for the target) produced more learning than did either semantic or referential contrast. In addition, regardless of group, more was learned about those targets that were classified more variably at pretest. Avoidance of lexical overlap (i.e., using more than one term for the same dimension) might make it more difficult for children to learn new dimensional adjectives, and a "shape bias" might make learning shape terms easier. However, children's expectations about the speaker's communicative intent interacted with the potential benefits of contrast in the semantic condition, and children in that group learned no more than did controls.
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…
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.
Domain decomposition in time for PDE-constrained optimization
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.
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.
Population Induced Instabilities in Genetic Algorithms for Constrained Optimization
NASA Astrophysics Data System (ADS)
Vlachos, D. S.; Parousis-Orthodoxou, K. J.
2013-02-01
Evolutionary computation techniques, like genetic algorithms, have received a lot of attention as optimization techniques but, although they exhibit a very promising potential in curing the problem, they have not produced a significant breakthrough in the area of systematic treatment of constraints. There are two mainly ways of handling the constraints: the first is to produce an infeasibility measure and add it to the general cost function (the well known penalty methods) and the other is to modify the mutation and crossover operation in a way that they only produce feasible members. Both methods have their drawbacks and are strongly correlated to the problem that they are applied. In this work, we propose a different treatment of the constraints: we induce instabilities in the evolving population, in a way that infeasible solution cannot survive as they are. Preliminary results are presented in a set of well known from the literature constrained optimization problems.
A dynamic hybrid framework for constrained evolutionary optimization.
Wang, Yong; Cai, Zixing
2012-02-01
Based on our previous work, this paper presents a dynamic hybrid framework, called DyHF, for solving constrained optimization problems. This framework consists of two major steps: global search model and local search model. In the global and local search models, differential evolution serves as the search engine, and Pareto dominance used in multiobjective optimization is employed to compare the individuals in the population. Unlike other existing methods, the above two steps are executed dynamically according to the feasibility proportion of the current population in this paper, with the purpose of reasonably distributing the computational resource for the global and local search during the evolution. The performance of DyHF is tested on 22 benchmark test functions. The experimental results clearly show that the overall performance of DyHF is highly competitive with that of a number of state-of-the-art approaches from the literature.
Prediction-Correction Algorithms for Time-Varying Constrained Optimization
Dall-Anese, Emiliano; Simonetto, Andrea
2017-07-26
This paper develops online algorithms to track solutions of time-varying constrained optimization problems. Particularly, resembling workhorse Kalman filtering-based approaches for dynamical systems, the proposed methods involve prediction-correction steps to provably track the trajectory of the optimal solutions of time-varying convex problems. The merits of existing prediction-correction methods have been shown for unconstrained problems and for setups where computing the inverse of the Hessian of the cost function is computationally affordable. This paper addresses the limitations of existing methods by tackling constrained problems and by designing first-order prediction steps that rely on the Hessian of the cost function (and do notmore » require the computation of its inverse). In addition, the proposed methods are shown to improve the convergence speed of existing prediction-correction methods when applied to unconstrained problems. Numerical simulations corroborate the analytical results and showcase performance and benefits of the proposed algorithms. A realistic application of the proposed method to real-time control of energy resources is presented.« less
Optimal stimulus shapes for neuronal excitation.
Forger, Daniel B; Paydarfar, David; Clay, John R
2011-07-01
An important problem in neuronal computation is to discern how features of stimuli control the timing of action potentials. One aspect of this problem is to determine how an action potential, or spike, can be elicited with the least energy cost, e.g., a minimal amount of applied current. Here we show in the Hodgkin & Huxley model of the action potential and in experiments on squid giant axons that: 1) spike generation in a neuron can be highly discriminatory for stimulus shape and 2) the optimal stimulus shape is dependent upon inputs to the neuron. We show how polarity and time course of post-synaptic currents determine which of these optimal stimulus shapes best excites the neuron. These results are obtained mathematically using the calculus of variations and experimentally using a stochastic search methodology. Our findings reveal a surprising complexity of computation at the single cell level that may be relevant for understanding optimization of signaling in neurons and neuronal networks.
Error estimation and structural shape optimization
NASA Astrophysics Data System (ADS)
Song, Xiaoguang
This work is concerned with three topics: error estimation, data smoothing process and the structural shape optimization design and analysis. In particular, the superconvergent stress recovery technique, the dual kriging B-spline curve and surface fittings, the development and the implementation of a novel node-based numerical shape optimization package are addressed. Concept and new technique of accurate stress recovery are developed and applied in finding the lateral buckling parameters of plate structures. Some useful conclusions are made for the finite element Reissner-Mindlin plate solutions. The powerful dual kriging B-spline fitting technique is reviewed and a set of new compact formulations are developed. This data smoothing method is then applied in accurately recovering curves and surfaces. The new node-based shape optimization method is based on the consideration that the critical stress and displacement constraints are generally located along or near the structural boundary. The method puts the maximum weights on the selected boundary nodes, referred to as the design points, so that the time-consuming sensitivity analysis is related to the perturbation of only these nodes. The method also allows large shape changes to achieve the optimal shape. The design variables are specified as the moving magnitudes for the prescribed design points that are always located at the structural boundary. Theories, implementations and applications are presented for various modules by which the package is constructed. Especially, techniques involving finite element error estimation, adaptive mesh generation, design sensitivity analysis, and data smoothing are emphasized.
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
Improving the efficiency of aerodynamic shape optimization
NASA Technical Reports Server (NTRS)
Burgreen, Greg W.; Baysal, Oktay; Eleshaky, Mohamed E.
1994-01-01
The computational efficiency of an aerodynamic shape optimization procedure that is based on discrete sensitivity analysis is increased through the implementation of two improvements. The first improvement involves replacing a grid-point-based approach for surface representation with a Bezier-Bernstein polynomial parameterization of the surface. Explicit analytical expressions for the grid sensitivity terms are developed for both approaches. The second improvement proposes the use of Newton's method in lieu of an alternating direction implicit methodology to calculate the highly converged flow solutions that are required to compute the sensitivity coefficients. The modified design procedure is demonstrated by optimizing the shape of an internal-external nozzle configuration. Practically identical optimization results are obtained that are independent of the method used to represent the surface. A substantial factor of 8 decrease in computational time for the optimization process is achieved by implementing both of the design procedure improvements.
Three-dimensional trajectory optimization in constrained airspace
NASA Astrophysics Data System (ADS)
Dai, Ran
This dissertation deals with the generation of three-dimensional optimized trajectory in constrained airspace. It expands the previously used two-dimensional aircraft model to a three-dimensional model and includes the consideration of complex airspace constraints not included in previous trajectory optimization studies. Two major branches of optimization methods, indirect and direct methods, are introduced and compared. Both of the methods are applied to solve a two-dimensional minimum-time-to-climb (MTTC) problem. The solution procedure is described in detail. Two traditional problems, the Brachistochrone problem and Zermelo's problem, are solved using the direct collocation and nonlinear programming method. Because analytical solutions to these problems are known. These solutions provide verification of the numerical methods. Three discretization methods, trapezoidal, Hermite-Simpson and Chebyshev Pseudospectral (CP) are introduced and applied to solve the Brachistochrone problem. The solutions obtained using these discretization methods are compared with the analytical results. An 3-D aircraft model with six state variables and two control variables are presented. Two primary trajectory optimization problems are considered using this model in the dissertation. One is to assume that the aircraft climbs up from sea level to a desired altitude in a square cross section cylinder of arbitrary height. Another is to intercept a constant velocity, constant altitude target in minimum time starting from sea level. Results of the optimal trajectories are compared with the results from the proportional navigation guidance law. Field of View constraint is finally considered in this interception problem. The CP discretization and nonlinear programming method is shown to have advantages over indirect methods in solving three-dimensional (3-D) trajectory optimization problems with multiple controls and complex constraints. Conclusions from both problems are presented and
Shape optimization techniques for musical instrument design
NASA Astrophysics Data System (ADS)
Henrique, Luis; Antunes, Jose; Carvalho, Joao S.
2002-11-01
The design of musical instruments is still mostly based on empirical knowledge and costly experimentation. One interesting improvement is the shape optimization of resonating components, given a number of constraints (allowed parameter ranges, shape smoothness, etc.), so that vibrations occur at specified modal frequencies. Each admissible geometrical configuration generates an error between computed eigenfrequencies and the target set. Typically, error surfaces present many local minima, corresponding to suboptimal designs. This difficulty can be overcome using global optimization techniques, such as simulated annealing. However these methods are greedy, concerning the number of function evaluations required. Thus, the computational effort can be unacceptable if complex problems, such as bell optimization, are tackled. Those issues are addressed in this paper, and a method for improving optimization procedures is proposed. Instead of using the local geometric parameters as searched variables, the system geometry is modeled in terms of truncated series of orthogonal space-funcitons, and optimization is performed on their amplitude coefficients. Fourier series and orthogonal polynomials are typical such functions. This technique reduces considerably the number of searched variables, and has a potential for significant computational savings in complex problems. It is illustrated by optimizing the shapes of both current and uncommon marimba bars.
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.
Constrained Multiobjective Optimization Algorithm Based on Immune System Model.
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.
Digital robust control law synthesis using constrained optimization
NASA Technical Reports Server (NTRS)
Mukhopadhyay, Vivekananda
1989-01-01
Development of digital robust control laws for active control of high performance flexible aircraft and large space structures is a research area of significant practical importance. The flexible system is typically modeled by a large order state space system of equations in order to accurately represent the dynamics. The active control law must satisy multiple conflicting design requirements and maintain certain stability margins, yet should be simple enough to be implementable on an onboard digital computer. Described here is an application of a generic digital control law synthesis procedure for such a system, using optimal control theory and constrained optimization technique. A linear quadratic Gaussian type cost function is minimized by updating the free parameters of the digital control law, while trying to satisfy a set of constraints on the design loads, responses and stability margins. Analytical expressions for the gradients of the cost function and the constraints with respect to the control law design variables are used to facilitate rapid numerical convergence. These gradients can be used for sensitivity study and may be integrated into a simultaneous structure and control optimization scheme.
Microgrid Optimal Scheduling With Chance-Constrained Islanding Capability
Liu, Guodong; Starke, Michael R.; Xiao, B.; ...
2017-01-13
To facilitate the integration of variable renewable generation and improve the resilience of electricity sup-ply in a microgrid, this paper proposes an optimal scheduling strategy for microgrid operation considering constraints of islanding capability. A new concept, probability of successful islanding (PSI), indicating the probability that a microgrid maintains enough spinning reserve (both up and down) to meet local demand and accommodate local renewable generation after instantaneously islanding from the main grid, is developed. The PSI is formulated as mixed-integer linear program using multi-interval approximation taking into account the probability distributions of forecast errors of wind, PV and load. With themore » goal of minimizing the total operating cost while preserving user specified PSI, a chance-constrained optimization problem is formulated for the optimal scheduling of mirogrids and solved by mixed integer linear programming (MILP). Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, a micro-turbine, a diesel generator and a battery demonstrate the effectiveness of the proposed scheduling strategy. Lastly, we verify the relationship between PSI and various factors.« less
Solving nonlinear equality constrained multiobjective optimization problems using neural networks.
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.
A parametrically constrained optimization method for fitting sedimentation velocity experiments.
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
2014-04-15
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.
Constrained optimization for green engineering decision-making.
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.
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.
NASA Astrophysics Data System (ADS)
Silva, Guilherme Augusto Lopes da; Nicoletti, Rodrigo
2017-06-01
This work focuses on the placement of natural frequencies of beams to desired frequency regions. More specifically, we investigate the effects of combining mode shapes to shape a beam to change its natural frequencies, both numerically and experimentally. First, we present a parametric analysis of a shaped beam and we analyze the resultant effects for different boundary conditions and mode shapes. Second, we present an optimization procedure to find the optimum shape of the beam for desired natural frequencies. In this case, we adopt the Nelder-Mead simplex search method, which allows a broad search of the optimum shape in the solution domain. Finally, the obtained results are verified experimentally for a clamped-clamped beam in three different optimization runs. Results show that the method is effective in placing natural frequencies at desired values (experimental results lie within a 10% error to the expected theoretical ones). However, the beam must be axially constrained to have the natural frequencies changed.
NASA Astrophysics Data System (ADS)
Afshar, M. H.
2007-04-01
This paper exploits the unique feature of the Ant Colony Optimization Algorithm (ACOA), namely incremental solution building mechanism, to develop partially constraint ACO algorithms for the solution of optimization problems with explicit constraints. The method is based on the provision of a tabu list for each ant at each decision point of the problem so that some constraints of the problem are satisfied. The application of the method to the problem of storm water network design is formulated and presented. The network nodes are considered as the decision points and the nodal elevations of the network are used as the decision variables of the optimization problem. Two partially constrained ACO algorithms are formulated and applied to a benchmark example of storm water network design and the results are compared with those of the original unconstrained algorithm and existing methods. In the first algorithm the positive slope constraints are satisfied explicitly and the rest are satisfied by using the penalty method while in the second one the satisfaction of constraints regarding the maximum ratio of flow depth to the diameter are also achieved explicitly via the tabu list. The method is shown to be very effective and efficient in locating the optimal solutions and in terms of the convergence characteristics of the resulting ACO algorithms. The proposed algorithms are also shown to be relatively insensitive to the initial colony used compared to the original algorithm. Furthermore, the method proves itself capable of finding an optimal or near-optimal solution, independent of the discretisation level and the size of the colony used.
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.
Multiplicative noise removal using variable splitting and constrained optimization.
Bioucas-Dias, José M; Figueiredo, Mário A T
2010-07-01
Multiplicative noise (also known as speckle noise) models are central to the study of coherent imaging systems, such as synthetic aperture radar and sonar, and ultrasound and laser imaging. These models introduce two additional layers of difficulties with respect to the standard Gaussian additive noise scenario: (1) the noise is multiplied by (rather than added to) the original image; (2) the noise is not Gaussian, with Rayleigh and Gamma being commonly used densities. These two features of multiplicative noise models preclude the direct application of most state-of-the-art algorithms, which are designed for solving unconstrained optimization problems where the objective has two terms: a quadratic data term (log-likelihood), reflecting the additive and Gaussian nature of the noise, plus a convex (possibly nonsmooth) regularizer (e.g., a total variation or wavelet-based regularizer/prior). In this paper, we address these difficulties by: (1) converting the multiplicative model into an additive one by taking logarithms, as proposed by some other authors; (2) using variable splitting to obtain an equivalent constrained problem; and (3) dealing with this optimization problem using the augmented Lagrangian framework. A set of experiments shows that the proposed method, which we name MIDAL (multiplicative image denoising by augmented Lagrangian), yields state-of-the-art results both in terms of speed and denoising performance.
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.
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.
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.
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.
Aerodynamic Shape Optimization using an Evolutionary Algorithm
NASA Technical Reports Server (NTRS)
Hoist, Terry L.; Pulliam, Thomas H.
2003-01-01
A method for aerodynamic shape optimization based on an evolutionary algorithm approach is presented and demonstrated. Results are presented for a number of model problems to access the effect of algorithm parameters on convergence efficiency and reliability. A transonic viscous airfoil optimization problem-both single and two-objective variations is used as the basis for a preliminary comparison with an adjoint-gradient optimizer. The evolutionary algorithm is coupled with a transonic full potential flow solver and is used to optimize the inviscid flow about transonic wings including multi-objective and multi-discipline solutions that lead to the generation of pareto fronts. The results indicate that the evolutionary algorithm approach is easy to implement, flexible in application and extremely reliable.
Aerodynamic Shape Optimization using an Evolutionary Algorithm
NASA Technical Reports Server (NTRS)
Holst, Terry L.; Pulliam, Thomas H.; Kwak, Dochan (Technical Monitor)
2003-01-01
A method for aerodynamic shape optimization based on an evolutionary algorithm approach is presented and demonstrated. Results are presented for a number of model problems to access the effect of algorithm parameters on convergence efficiency and reliability. A transonic viscous airfoil optimization problem, both single and two-objective variations, is used as the basis for a preliminary comparison with an adjoint-gradient optimizer. The evolutionary algorithm is coupled with a transonic full potential flow solver and is used to optimize the inviscid flow about transonic wings including multi-objective and multi-discipline solutions that lead to the generation of pareto fronts. The results indicate that the evolutionary algorithm approach is easy to implement, flexible in application and extremely reliable.
Aerodynamic Shape Optimization using an Evolutionary Algorithm
NASA Technical Reports Server (NTRS)
Holst, Terry L.; Pulliam, Thomas H.; Kwak, Dochan (Technical Monitor)
2003-01-01
A method for aerodynamic shape optimization based on an evolutionary algorithm approach is presented and demonstrated. Results are presented for a number of model problems to access the effect of algorithm parameters on convergence efficiency and reliability. A transonic viscous airfoil optimization problem, both single and two-objective variations, is used as the basis for a preliminary comparison with an adjoint-gradient optimizer. The evolutionary algorithm is coupled with a transonic full potential flow solver and is used to optimize the inviscid flow about transonic wings including multi-objective and multi-discipline solutions that lead to the generation of pareto fronts. The results indicate that the evolutionary algorithm approach is easy to implement, flexible in application and extremely reliable.
Aerodynamic Shape Optimization using an Evolutionary Algorithm
NASA Technical Reports Server (NTRS)
Hoist, Terry L.; Pulliam, Thomas H.
2003-01-01
A method for aerodynamic shape optimization based on an evolutionary algorithm approach is presented and demonstrated. Results are presented for a number of model problems to access the effect of algorithm parameters on convergence efficiency and reliability. A transonic viscous airfoil optimization problem-both single and two-objective variations is used as the basis for a preliminary comparison with an adjoint-gradient optimizer. The evolutionary algorithm is coupled with a transonic full potential flow solver and is used to optimize the inviscid flow about transonic wings including multi-objective and multi-discipline solutions that lead to the generation of pareto fronts. The results indicate that the evolutionary algorithm approach is easy to implement, flexible in application and extremely reliable.
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
A collective neurodynamic optimization approach to bound-constrained nonconvex optimization.
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.
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.
Optimal Stimulus Shapes for Neuronal Excitation
Forger, Daniel B.; Paydarfar, David; Clay, John R.
2011-01-01
An important problem in neuronal computation is to discern how features of stimuli control the timing of action potentials. One aspect of this problem is to determine how an action potential, or spike, can be elicited with the least energy cost, e.g., a minimal amount of applied current. Here we show in the Hodgkin & Huxley model of the action potential and in experiments on squid giant axons that: 1) spike generation in a neuron can be highly discriminatory for stimulus shape and 2) the optimal stimulus shape is dependent upon inputs to the neuron. We show how polarity and time course of post-synaptic currents determine which of these optimal stimulus shapes best excites the neuron. These results are obtained mathematically using the calculus of variations and experimentally using a stochastic search methodology. Our findings reveal a surprising complexity of computation at the single cell level that may be relevant for understanding optimization of signaling in neurons and neuronal networks. PMID:21760759
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.
Aerodynamic shape optimization of arbitrary hypersonic vehicles
NASA Technical Reports Server (NTRS)
Dulikravich, George S.; Sheffer, Scott G.
1991-01-01
A new method was developed to optimize, in terms of aerodynamic wave drag minimization, arbitrary (nonaxisymmetric) hypersonic vehicles in modified Newtonian flow, while maintaining the initial volume and length of the vehicle. This new method uses either a surface fitted Fourier series to represent the vehicle's geometry or an independent point motion algorithm. In either case, the coefficients of the Fourier series or the spatial locations of the points defining each cross section were varied and a numerical optimization algorithm based on a quasi-Newton gradient search concept was used to determine the new optimal configuration. Results indicate a significant decrease in aerodynamic wave drag for simple and complex geometries at relatively low CPU costs. In the case of a cone, the results agreed well with known analytical optimum ogive shapes. The procedure is capable of accepting more complex flow field analysis codes.
An optimal constrained linear inverse method for magnetic source imaging
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.
A Parametrically Constrained Optimization Method for Fitting Sedimentation Velocity Experiments
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
Newton's method for large bound-constrained optimization problems.
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.
Constrained Ordination Analysis with Enrichment of Bell-Shaped Response Functions.
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.
Shape optimization of multi-chamber cross-flow mufflers by SA optimization
NASA Astrophysics Data System (ADS)
Chiu, Min-Chie; Chang, Ying-Chun
2008-05-01
It is essential when searching for an efficient acoustical mechanism to have an optimally shaped muffler designed specially for the constrained space found in today's plants. Because the research work of optimally shaped straight silencers in conjunction with multi-chamber cross-flow perforated ducts is rarely addressed, this paper will not only analyze the sound transmission loss (STL) of three kinds of cross-flow perforated mufflers but also will analyze the optimal design shape within a limited space. In this paper, the four-pole system matrix used in evaluating acoustic performance is derived by using the decoupled numerical method. Moreover, a simulated annealing (SA) algorithm, a robust scheme in searching for the global optimum by imitating the softening process of metal, has been adopted during shape optimization. To reassure SA's correctness, the STL's maximization of three kinds of muffles with respect to one-tone and dual-tone noise is exemplified. Furthermore, the optimization of mufflers with respect to an octave-band fan noise by the simulated algorithm has been introduced and fully discussed. Before the SA operation can be carried out, an accuracy check of the mathematical model with respect to cross-flow perforated mufflers has to be performed by Munjal's analytical data and experimental data. The optimal result in eliminating broadband noise reveals that the cross-flow perforated muffler with more chambers is far superior at noise reduction than a muffler with fewer chambers. Consequently, the approach used for the optimal design of noise elimination proposed in this study is certainly easy and efficient.
Depletion Mapping and Constrained Optimization to Support Managing Groundwater Extraction.
Fienen, Michael N; Bradbury, Kenneth R; Kniffin, Maribeth; Barlow, Paul M
2017-06-06
Groundwater models often serve as management tools to evaluate competing water uses including ecosystems, irrigated agriculture, industry, municipal supply, and others. Depletion potential mapping-showing the model-calculated potential impacts that wells have on stream baseflow-can form the basis for multiple potential management approaches in an oversubscribed basin. Specific management approaches can include scenarios proposed by stakeholders, systematic changes in well pumping based on depletion potential, and formal constrained optimization, which can be used to quantify the tradeoff between water use and stream baseflow. Variables such as the maximum amount of reduction allowed in each well and various groupings of wells using, for example, K-means clustering considering spatial proximity and depletion potential are considered. These approaches provide a potential starting point and guidance for resource managers and stakeholders to make decisions about groundwater management in a basin, spreading responsibility in different ways. We illustrate these approaches in the Little Plover River basin in central Wisconsin, United States-home to a rich agricultural tradition, with farmland and urban areas both in close proximity to a groundwater-dependent trout stream. Groundwater withdrawals have reduced baseflow supplying the Little Plover River below a legally established minimum. The techniques in this work were developed in response to engaged stakeholders with various interests and goals for the basin. They sought to develop a collaborative management plan at a watershed scale that restores the flow rate in the river in a manner that incorporates principles of shared governance and results in effective and minimally disruptive changes in groundwater extraction practices. © 2017, National Ground Water Association.
Depletion mapping and constrained optimization to support managing groundwater extraction
Fienen, Michael N.; Bradbury, Kenneth R.; Kniffin, Maribeth; Barlow, Paul M.
2017-01-01
Groundwater models often serve as management tools to evaluate competing water uses including ecosystems, irrigated agriculture, industry, municipal supply, and others. Depletion potential mapping—showing the model-calculated potential impacts that wells have on stream baseflow - can form the basis for multiple potential management approaches in an oversubscribed basin. Specific management approaches can include scenarios proposed by stakeholders, systematic changes in well pumping based on depletion potential, and formal constrained optimization, which can be used to quantify the tradeoff between water use and stream baseflow. Variables such as the maximum amount of reduction allowed in each well and various groupings of wells using, for example, K-means clustering considering spatial proximity and depletion potential are considered. These approaches provide a potential starting point and guidance for resource managers and stakeholders to make decisions about groundwater management in a basin, spreading responsibility in different ways. We illustrate these approaches in the Little Plover River basin in central Wisconsin, United States—home to a rich agricultural tradition, with farmland and urban areas both in close proximity to a groundwater-dependent trout stream. Groundwater withdrawals have reduced baseflow supplying the Little Plover River below a legally established minimum. The techniques in this work were developed in response to engaged stakeholders with various interests and goals for the basin. They sought to develop a collaborative management plan at a watershed scale that restores the flow rate in the river in a manner that incorporates principles of shared governance and results in effective and minimally disruptive changes in groundwater extraction practices.
Optimizing performance of nonparametric species richness estimators under constrained sampling.
Rajakaruna, Harshana; Drake, D Andrew R; T Chan, Farrah; Bailey, Sarah A
2016-10-01
Understanding the functional relationship between the sample size and the performance of species richness estimators is necessary to optimize limited sampling resources against estimation error. Nonparametric estimators such as Chao and Jackknife demonstrate strong performances, but consensus is lacking as to which estimator performs better under constrained sampling. We explore a method to improve the estimators under such scenario. The method we propose involves randomly splitting species-abundance data from a single sample into two equally sized samples, and using an appropriate incidence-based estimator to estimate richness. To test this method, we assume a lognormal species-abundance distribution (SAD) with varying coefficients of variation (CV), generate samples using MCMC simulations, and use the expected mean-squared error as the performance criterion of the estimators. We test this method for Chao, Jackknife, ICE, and ACE estimators. Between abundance-based estimators with the single sample, and incidence-based estimators with the split-in-two samples, Chao2 performed the best when CV < 0.65, and incidence-based Jackknife performed the best when CV > 0.65, given that the ratio of sample size to observed species richness is greater than a critical value given by a power function of CV with respect to abundance of the sampled population. The proposed method increases the performance of the estimators substantially and is more effective when more rare species are in an assemblage. We also show that the splitting method works qualitatively similarly well when the SADs are log series, geometric series, and negative binomial. We demonstrate an application of the proposed method by estimating richness of zooplankton communities in samples of ballast water. The proposed splitting method is an alternative to sampling a large number of individuals to increase the accuracy of richness estimations; therefore, it is appropriate for a wide range of resource
Shape optimization: Good looks and acoustics too!
NASA Astrophysics Data System (ADS)
D'Antonio, Peter; Cox, Trevor J.; Haas, Steve
2003-04-01
One of the challenges in the architectural acoustic design of museums and other public spaces is to develop contemporary scattering surfaces that complement contemporary architecture in the way that statuary, coffered ceilings, columns, and relief ornamentation complemented classic architecture. Often acoustic surfaces satisfy the acoustics, but may or may not satisfy the aesthetics. One approach that has been successful employs a combination of boundary element and multidimensional optimization techniques. The architect supplies the desired shape motif and the acoustician supplies the acoustical performance requirements. The optimization program then provides an Arcousthetic surface, which simultaneously satisfies the architecture, the acoustics, and the aesthetics. The program can be used with diffusive or diffsorptive surfaces. Photos of installations using these acoustic tools and a description of the design of the National Museum of the American Indian will also be presented to illustrate the usefulness of these devices and their impact on architectural acoustics.
Prospects for constraining the shape of non-Gaussianity with the scale-dependent bias
Noreña, Jorge; Verde, Licia; Barenboim, Gabriela; Bosch, Cristian E-mail: liciaverde@icc.ub.edu E-mail: Cristian.Bosch@uv.es
2012-08-01
We consider whether the non-Gaussian scale-dependent halo bias can be used not only to constrain the local form of non-Gaussianity but also to distinguish among different shapes. In particular, we ask whether it can constrain the behavior of the primordial three-point function in the squeezed limit where one of the momenta is much smaller than the other two. This is potentially interesting since the observation of a three-point function with a squeezed limit that does not go like the local nor equilateral templates would be a signal of non-trivial dynamics during inflation. To this end we use the quasi-single field inflation model of Chen and Wang [1, 2] as a representative two-parameter model, where one parameter governs the amplitude of non-Gaussianity and the other the shape. We also perform a model-independent analysis by parametrizing the scale-dependent bias as a power-law on large scales, where the power is to be constrained from observations. We find that proposed large-scale structure surveys (with characteristics similar to the dark energy task force stage IV surveys) have the potential to distinguish among the squeezed limit behavior of different bispectrum shapes for a wide range of fiducial model parameters. Thus the halo bias can help discriminate between different models of inflation.
2008-01-01
Constrained optimization problems arise in a wide variety of scientific and engineering applications. Since several single recurrent neural networks when applied to solve constrained optimization problems for real-time engineering applications have shown some limitations, cooperative recurrent neural network approaches have been developed to overcome drawbacks of these single recurrent neural networks. This paper surveys in details work on cooperative recurrent neural networks for solving constrained optimization problems and their engineering applications, and points out their standing models from viewpoint of both convergence to the optimal solution and model complexity. We provide examples and comparisons to shown advantages of these models in the given applications. PMID:19003467
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.
Hydrodynamic optimality of ribbon fin shapes
NASA Astrophysics Data System (ADS)
Bale, Rahul; Maciver, Malcolm; Patankar, Neelesh
2011-11-01
The primary mode of propulsion in gymnotiform and balistiform swimmers is via the undulation of anal and/or dorsal fins, commonly referred to as ribbon fins, attached to a more or less rigid body. Ribbon fins usually have a convex shape as opposed to a rectangular or concave profile. In this work we investigate if there is a hydrodynamic basis underlying this observation. Fully resolved fluid dynamics computations are performed to calculate the mechanical cost of transport (COT) as a measure of swimming efficiency of the fin. We find that the ribbon fin of a black ghost knifefish has lower COT compared to a hypothetical rectangular ribbon fin. In order to quantify this difference in COT between the two fin shapes, we obtain scaling for COT in terms of various parameters which affect the swimming performance of the fin. Using scaling arguments we address the question of how a convex profile, commonly observed in gymnotiform and balistiform swimmers, is optimal compared to rectangular or concave shapes. NSF support is gratefully acknowledged.
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.
Wang, Yin; Jiang, Han
2014-01-01
We present a nonparametric shape constrained algorithm for segmentation of coronary arteries in computed tomography images within the framework of active contours. An adaptive scale selection scheme, based on the global histogram information of the image data, is employed to determine the appropriate window size for each point on the active contour, which improves the performance of the active contour model in the low contrast local image regions. The possible leakage, which cannot be identified by using intensity features alone, is reduced through the application of the proposed shape constraint, where the shape of circular sampled intensity profile is used to evaluate the likelihood of current segmentation being considered vascular structures. Experiments on both synthetic and clinical datasets have demonstrated the efficiency and robustness of the proposed method. The results on clinical datasets have shown that the proposed approach is capable of extracting more detailed coronary vessels with subvoxel accuracy. PMID:24803950
Fast Energy Minimization of large Polymers Using Constrained Optimization
Todd D. Plantenga
1998-10-01
A new computational technique is described that uses distance constraints to calculate empirical potential energy minima of partially rigid molecules. A constrained minimuzation algorithm that works entirely in Cartesian coordinates is used. The algorithm does not obey the constraints until convergence, a feature that reduces ill-conditioning and allows constrained local minima to be computed more quickly than unconstrained minima. Computational speedup exceeds the 3-fold factor commonly obtained in constained molecular dynamics simulations, where the constraints must be strictly obeyed at all times.
Optimization of lens shape for autostereoscopic display
NASA Astrophysics Data System (ADS)
Su, Ping; An, Shu; Ma, Jianshe
2016-10-01
The three-dimensional(3D) displays based on binocular parallax have drawn increasingly interests. The light splitting element, which presents separate images to the viewer's left and right eyes, plays an important part in the auto-stereoscopic display. Lenticular lenses are widely used as the light splitting elements. However, the crosstalk resulted from the unsatisfied splitting may reduce the 3D experience. It was determined that the most suitable cross sectional shape for lenticular lenses is elliptical. Firstly, the formula of the surface is derived based on the ellipse expression and the requirement of the 3D display system, that is y2+0.5651x2 - 303.4768=0. Secondly, one axial source and 4 off-axial sources placed at the heights of 2.5mm, 5mm, 7.5mm and 8mm are used to analyze the beam splitting quality of the cylindrical and elliptical lens element, respectively. The spot of elliptical lens is smaller which means a better beam splitting quality. Thirdly, Monte Carlo Non-Sequential Ray tracing algorithm is used to simulate the luminance distribution on the viewing plane, the narrower width of vertical stripes means that the aberration is suppressed. Finally, the shape of elliptical can reduce the processing difficulty with the 10μm minimum step width. In a word, the optimization of the surface has a significant effect on the improvement of stereoscopic depth and the reduction of ghost images.
NASA Astrophysics Data System (ADS)
Somasundaram, P.; Muthuselvan, N. B.
This paper presents new computationally efficient improved Particle Swarm algorithms for solving Security Constrained Optimal Power Flow (SCOPF) in power systems with the inclusion of FACTS devices. The proposed algorithms are developed based on the combined application of Gaussian and Cauchy Probability distribution functions incorporated in Particle Swarm Optimization (PSO). The power flow algorithm with the presence of Static Var Compensator (SVC) Thyristor Controlled Series Capacitor (TCSC) and Unified Power Flow Controller (UPFC), has been formulated and solved. The proposed algorithms are tested on standard IEEE 30-bus system. The analysis using PSO and modified PSO reveals that the proposed algorithms are relatively simple, efficient, reliable and suitable for real-time applications. And these algorithms can provide accurate solution with fast convergence and have the potential to be applied to other power engineering problems.
Shape transition of endotaxial islands growth from kinetically constrained to equilibrium regimes
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.
Mesh Adaptive Direct Search Methods for Constrained Nonsmooth Optimization
2012-02-24
L.A. Leclaire. Snow water equivalent estimation using blackbox optimization. Technical report, Les Cahiers du GERAD G-2011-09, 2011. To appear in...Technical report, Les Cahiers du GERAD G-2011-03, 2011. To appear in Optimization Letters. 3. C. Audet, J.E. Dennis and S. Le Digabel. Trade-off...studies in blackbox optimization. Technical report, Les Cahiers du GERAD G-2010-49, 2010. To appear in Optimization Methods and Software. 4. C. Audet, and
Constrained optimization using a multipoint type chaotic Lagrangian method with a coupling structure
NASA Astrophysics Data System (ADS)
Okamoto, Takashi; Hirata, Hironori
2013-03-01
This article proposes a new constrained optimization method using a multipoint type chaotic Lagrangian method that utilizes chaotic search trajectories generated by Lagrangian gradient dynamics with a coupling structure. In the proposed method, multiple search points autonomously implement global search using the chaotic search trajectory generated by the coupled Lagrangian gradient dynamics. These points are advected to elite points (which are chosen by considering their objective function values and their feasibility) by the coupling in order to explore promising regions intensively. In this way, the proposed method successfully provides diversification and intensification for constrained optimization problems. The effectiveness of the proposed method is confirmed through application to various types of benchmark problem, including the coil spring design problem, the benchmark problems used in the special session on constrained real parameter optimization in CEC2006, and a high-dimensional and multi-peaked constrained optimization problem.
Analytical optimal pulse shapes obtained with the aid of genetic algorithms
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.
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.
Numerical study of a matrix-free trust-region SQP method for equality constrained optimization.
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).
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
Neural network for constrained nonsmooth optimization using Tikhonov regularization.
Qin, Sitian; Fan, Dejun; Wu, Guangxi; Zhao, Lijun
2015-03-01
This paper presents a one-layer neural network to solve nonsmooth convex optimization problems based on the Tikhonov regularization method. Firstly, it is shown that the optimal solution of the original problem can be approximated by the optimal solution of a strongly convex optimization problems. Then, it is proved that for any initial point, the state of the proposed neural network enters the equality feasible region in finite time, and is globally convergent to the unique optimal solution of the related strongly convex optimization problems. Compared with the existing neural networks, the proposed neural network has lower model complexity and does not need penalty parameters. In the end, some numerical examples and application are given to illustrate the effectiveness and improvement of the proposed neural network.
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.
A One-Layer Recurrent Neural Network for Constrained Complex-Variable Convex Optimization.
Qin, Sitian; Feng, Jiqiang; Song, Jiahui; Wen, Xingnan; Xu, Chen
2016-12-22
In this paper, based on CR calculus and penalty method, a one-layer recurrent neural network is proposed for solving constrained complex-variable convex optimization. It is proved that for any initial point from a given domain, the state of the proposed neural network reaches the feasible region in finite time and converges to an optimal solution of the constrained complex-variable convex optimization finally. In contrast to existing neural networks for complex-variable convex optimization, the proposed neural network has a lower model complexity and better convergence. Some numerical examples and application are presented to substantiate the effectiveness of the proposed neural network.
Modelling, Transformations, and Scaling Decisions in Constrained Optimization Problems
1976-03-01
goal programming, linear fractional programming, mathematical programming, nonlinear programming, nonlinear optimization , transformations, scaling... nonlinear optimization problems. A discussion is given of separable programming, goal programming, and linear fractional DD i j°N 73 1473 EDITION OF 1... nonlinear programming codes. The sensitivity of the GRG code to scaling, rotation of coordinates, and translation of variables is examined. Trans
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.
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.
Optimal charging profiles for mechanically constrained lithium-ion batteries
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.
On optimal solutions of the constrained ℓ 0 regularization and its penalty problem
NASA Astrophysics Data System (ADS)
Zhang, Na; Li, Qia
2017-02-01
The constrained {{\\ell}0} regularization plays an important role in sparse reconstruction. A widely used approach for solving this problem is the penalty method, of which the least square penalty problem is a special case. However, the connections between global minimizers of the constrained {{\\ell}0} problem and its penalty problem have never been studied in a systematic way. This work provides a comprehensive investigation on optimal solutions of these two problems and their connections. We give detailed descriptions of optimal solutions of the two problems, including existence, stability with respect to the parameter, cardinality and strictness. In particular, we find that the optimal solution set of the penalty problem is piecewise constant with respect to the penalty parameter. Then we analyze in-depth the relationship between optimal solutions of the two problems. It is shown that, in the noisy case the least square penalty problem probably has no common optimal solutions with the constrained {{\\ell}0} problem for any penalty parameter. Under a mild condition on the penalty function, we establish that the penalty problem has the same optimal solution set as the constrained {{\\ell}0} problem when the penalty parameter is sufficiently large. Based on the conditions, we further propose exact penalty problems for the constrained {{\\ell}0} problem. Finally, we present a numerical example to illustrate our main theoretical results.
Dose-shaping using targeted sparse optimization
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.
Dose-shaping using targeted sparse optimization.
Sayre, George A; Ruan, Dan
2013-07-01
(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 tot (sparse)-optimized plans was shown to be better than their associated clinical plans, according to the two-dimensional modulation index. 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.
Closed form solutions of constrained trajectories - Application in optimal ascent of aerospace plane
NASA Technical Reports Server (NTRS)
Lu, Ping; Samsundar, John
1992-01-01
The present consideration of the flight trajectory of hypersonic aerospace vehicles subject to a class of path constraints notes the constrained dynamics to constitute a natural two-timescale system, so that problems of trajectory optimization and guidance can be dramatically simplified by means of the asymptotic analytical solutions thus obtained. An illustrative application in ascent trajectory optimization for an aerospace vehicle is presented.
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…
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…
NASA Astrophysics Data System (ADS)
Iwan Solihin, Mahmud; Fauzi Zanil, Mohd
2016-11-01
Cuckoo Search (CS) and Differential Evolution (DE) algorithms are considerably robust meta-heuristic algorithms to solve constrained optimization problems. In this study, the performance of CS and DE are compared in solving the constrained optimization problem from selected benchmark functions. Selection of the benchmark functions are based on active or inactive constraints and dimensionality of variables (i.e. number of solution variable). In addition, a specific constraint handling and stopping criterion technique are adopted in the optimization algorithm. The results show, CS approach outperforms DE in term of repeatability and the quality of the optimum solutions.
Nery, Gesner A; Martins, Márcio A F; Kalid, Ricardo
2014-03-01
This paper describes the development of a method to optimally tune constrained MPC algorithms with model uncertainty. The proposed method is formulated by using the worst-case control scenario, which is characterized by the Morari resiliency index and the condition number, and a given nonlinear multi-objective performance criterion. The resulting constrained mixed-integer nonlinear optimization problem is solved on the basis of a modified version of the particle swarm optimization technique, because of its effectiveness in dealing with this kind of problem. The performance of this PSO-based tuning method is evaluated through its application to the well-known Shell heavy oil fractionator process.
State-Constrained Optimal Control Problems of Impulsive Differential Equations
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.
Constrained Burn Optimization for the International Space Station
NASA Technical Reports Server (NTRS)
Brown, Aaron J.; Jones, Brandon A.
2017-01-01
In long-term trajectory planning for the International Space Station (ISS), translational burns are currently targeted sequentially to meet the immediate trajectory constraints, rather than simultaneously to meet all constraints, do not employ gradient-based search techniques, and are not optimized for a minimum total deltav (v) solution. An analytic formulation of the constraint gradients is developed and used in an optimization solver to overcome these obstacles. Two trajectory examples are explored, highlighting the advantage of the proposed method over the current approach, as well as the potential v and propellant savings in the event of propellant shortages.
Singular perturbations in shape optimization for the Dirichlet Laplacian
NASA Astrophysics Data System (ADS)
Nazarov, Serguei A.; Sokolowski, Jan
2005-04-01
A shape optimization problem is considered for the Dirichlet Laplacian. Asymptotic analysis is used in order to characterise the optimal shapes which are finally given by a singular perturbation of the smooth initial domain. To cite this article: S.A. Nazarov, J. Sokolowski, C. R. Mecanique 333 (2005).
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.
Improved Sensitivity Relations in State Constrained Optimal Control
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
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.
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.
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.
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.
A limited-memory algorithm for bound-constrained optimization
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.
Thermodynamics Constrains Allometric Scaling of Optimal Development Time in Insects
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
Kinetic Constrained Optimization of the Golf Swing Hub Path
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
Thermodynamics constrains allometric scaling of optimal development time in insects.
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. The
Optimized, Budget-constrained Monitoring Well Placement Using DREAM
Yonkofski, Catherine M. R.; Davidson, Casie L.; Rodriguez, Luke R.; ...
2017-08-18
Defining the ideal suite of monitoring technologies to be deployed at a carbon capture and storage (CCS) site presents a challenge to project developers, financers, insurers, regulators and other stakeholders. The monitoring, verification, and accounting (MVA) toolkit offers a suite of technologies to monitor an extensive range of parameters across a wide span of spatial and temporal resolutions, each with their own degree of sensitivity to changes in the parameter being monitored. Understanding how best to optimize MVA budgets to minimize the time to leak detection could help to address issues around project risks, and in turn help support broadmore » CCS deployment. This paper presents a case study demonstrating an application of the Designs for Risk Evaluation and Management (DREAM) tool using an ensemble of CO2 leakage scenarios taken from a previous study on leakage impacts to groundwater. Impacts were assessed and monitored as a function of pH, total dissolved solids (TDS), and trace metal concentrations of arsenic (As), cadmium (Cd), chromium (Cr), and lead (Pb). Using output from the previous study, DREAM was used to optimize monitoring system designs based on variable sampling locations and parameters. The algorithm requires the user to define a finite budget to limit the number of monitoring wells and technologies deployed, and then iterates well placement and sensor type and location until it converges on the configuration with the lowest time to first detection of the leak averaged across all scenarios. To facilitate an understanding of the optimal number of sampling wells, DREAM was used to assess the marginal utility of additional sampling locations. Based on assumptions about monitoring costs and replacement costs of degraded water, the incremental cost of each additional sampling well can be compared against its marginal value in terms of avoided aquifer degradation. Applying this method, DREAM identified the most cost-effective ensemble with 14
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.
A Simply Constrained Optimization Reformulation of KKT Systems Arising from Variational Inequalities
Facchinei, F. Fischer, A. Kanzow, C. Peng, J.-M.
1999-01-15
The Karush-Kuhn-Tucker (KKT) conditions can be regarded as optimality conditions for both variational inequalities and constrained optimization problems. In order to overcome some drawbacks of recently proposed reformulations of KKT systems, we propose casting KKT systems as a minimization problem with nonnegativity constraints on some of the variables. We prove that, under fairly mild assumptions, every stationary point of this constrained minimization problem is a solution of the KKT conditions. Based on this reformulation, a new algorithm for the solution of the KKT conditions is suggested and shown to have some strong global and local convergence properties.
Aerodynamic shape optimization using preconditioned conjugate gradient methods
NASA Technical Reports Server (NTRS)
Burgreen, Greg W.; Baysal, Oktay
1993-01-01
In an effort to further improve upon the latest advancements made in aerodynamic shape optimization procedures, a systematic study is performed to examine several current solution methodologies as applied to various aspects of the optimization procedure. It is demonstrated that preconditioned conjugate gradient-like methodologies dramatically decrease the computational efforts required for such procedures. The design problem investigated is the shape optimization of the upper and lower surfaces of an initially symmetric (NACA-012) airfoil in inviscid transonic flow and at zero degree angle-of-attack. The complete surface shape is represented using a Bezier-Bernstein polynomial. The present optimization method then automatically obtains supercritical airfoil shapes over a variety of freestream Mach numbers. Furthermore, the best optimization strategy examined resulted in a factor of 8 decrease in computational time as well as a factor of 4 decrease in memory over the most efficient strategies in current use.
Shape optimization of the modular press body
NASA Astrophysics Data System (ADS)
Pabiszczak, Stanisław
2016-12-01
A paper contains an optimization algorithm of cross-sectional dimensions of a modular press body for the minimum mass criterion. Parameters of the wall thickness and the angle of their inclination relative to the base of section are assumed as the decision variables. The overall dimensions are treated as a constant. The optimal values of parameters were calculated using numerical method of the tool Solver in the program Microsoft Excel. The results of the optimization procedure helped reduce body weight by 27% while maintaining the required rigidity of the body.
NASA Astrophysics Data System (ADS)
Tengen, Thomas Bobga
2011-11-01
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.
Tengen, Thomas Bobga
2011-11-08
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.
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.
Integrated Multidisciplinary Constrained Optimization of Offshore Support Structures
NASA Astrophysics Data System (ADS)
Haghi, Rad; Ashuri, Turaj; van der Valk, Paul L. C.; Molenaar, David P.
2014-12-01
In the current offshore wind turbine support structure design method, the tower and foundation, which form the support structure are designed separately by the turbine and foundation designer. This method yields a suboptimal design and it results in a heavy, overdesigned and expensive support structure. This paper presents an integrated multidisciplinary approach to design the tower and foundation simultaneously. Aerodynamics, hydrodynamics, structure and soil mechanics are the modeled disciplines to capture the full dynamic behavior of the foundation and tower under different environmental conditions. The objective function to be minimized is the mass of the support structure. The model includes various design constraints: local and global buckling, modal frequencies, and fatigue damage along different stations of the structure. To show the usefulness of the method, an existing SWT-3.6-107 offshore wind turbine where its tower and foundation are designed separately is used as a case study. The result of the integrated multidisciplinary design optimization shows 12.1% reduction in the mass of the support structure, while satisfying all the design constraints.
Constrained optimization techniques for active control of aeroelastic response
NASA Technical Reports Server (NTRS)
Mukhopadhyay, Vivekananda
1987-01-01
Active control of aeroelastic response is a complex problem in which the designer usually tries to satisfy many design criteria which are often conflicting in nature. 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 method are of the same high order as the aeroelastic plant and may be difficult to implement in the flight computer. To overcome this disadvantage a new approach was developed for designing low-order optimized robust control laws. In this approach, a nonlinear programming algorithm is used to search for the values of control law design variables that minimize a performance index while satisfying several inequality constraints that describe the design criteria on the stability robustness and responses. The method is applied to a gust load alleviation problem and a stability robustness improvement problem of a drone aircraft.
Constrained nonlinear optimization approaches to color-signal separation.
Chang, P R; Hsieh, T H
1995-01-01
Separating a color signal into illumination and surface reflectance components is a fundamental issue in color reproduction and constancy. This can be carried out by minimizing the error in the least squares (LS) fit of the product of the illumination and the surface spectral reflectance to the actual color signal. When taking in account the physical realizability constraints on the surface reflectance and illumination, the feasible solutions to the nonlinear LS problem should satisfy a number of linear inequalities. Four distinct novel optimization algorithms are presented to employ these constraints to minimize the nonlinear LS fitting error. The first approach, which is based on Ritter's superlinear convergent method (Luengerger, 1980), provides a computationally superior algorithm to find the minimum solution to the nonlinear LS error problem subject to linear inequality constraints. Unfortunately, this gradient-like algorithm may sometimes be trapped at a local minimum or become unstable when the parameters involved in the algorithm are not tuned properly. The remaining three methods are based on the stable and promising global minimizer called simulated annealing. The annealing algorithm can always find the global minimum solution with probability one, but its convergence is slow. To tackle this, a cost-effective variable-separable formulation based on the concept of Golub and Pereyra (1973) is adopted to reduce the nonlinear LS problem to be a small-scale nonlinear LS problem. The computational efficiency can be further improved when the original Boltzman generating distribution of the classical annealing is replaced by the Cauchy distribution.
Application of a particle swarm optimization for shape optimization in hydraulic machinery
NASA Astrophysics Data System (ADS)
Moravec, Prokop; Rudolf, Pavel
A study of shape optimization has become increasingly popular in academia and industry. A typical problem is to find an optimal shape, which minimizes (or maximizes) a certain cost function and satisfies given constraints. Particle Swarm Optimization (PSO) has received a lot of attention in past years and is inspired by social behaviour of some animals such as flocking behaviour of birds. This paper focuses on a possibility of a diffuser shape optimization using particle swarm optimization (PSO), which is coupled with CFD simulation. Influence of main parameters of PSO-algorithm and later diffuser shapes obtained with this method are discussed and advantages/disadvantages summarized.
Center for Shape Optimization and Material Layout
1992-01-01
that eventually participate in the optimal layout for non -self-adjoint problems . Currently, these microstructures are worked out numerically [6...the fourth order problem arising in the theory of plates. 1.2 The Fourth Order Problems Direct Approach in the Optimal Design of Plates. The state of... constraint set. In fact, the constraint set is not only nonlinear, its also non -smooth, and even non - convex . Worst of all, we do not even have an analytic
Constrained growth flips the direction of optimal phenological responses among annual plants.
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.
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.
Morphing-Based Shape Optimization in Computational Fluid Dynamics
NASA Astrophysics Data System (ADS)
Rousseau, Yannick; Men'Shov, Igor; Nakamura, Yoshiaki
In this paper, a Morphing-based Shape Optimization (MbSO) technique is presented for solving Optimum-Shape Design (OSD) problems in Computational Fluid Dynamics (CFD). The proposed method couples Free-Form Deformation (FFD) and Evolutionary Computation, and, as its name suggests, relies on the morphing of shape and computational domain, rather than direct shape parameterization. Advantages of the FFD approach compared to traditional parameterization are first discussed. Then, examples of shape and grid deformations by FFD are presented. Finally, the MbSO approach is illustrated and applied through an example: the design of an airfoil for a future Mars exploration airplane.
Characterizations of PAPR-Constrained Radar Waveforms for Optimal Target Detection
Sen, Satyabrata
2014-01-01
We propose to design a peak-to-average power ratio (PAPR) constrained transmit waveform that achieves the optimal performance (following the Neyman Pearson lemma) in detecting a target in the presence of signal-dependent interference. The direct time-domain approach allows straightforward characterizations of the correlation and PAPR properties of the designed signals, which are critically important to analyze the system performance in the presence of multiple targets and to assess the transmitter power-utilization, respectively. Therefore, instead of designing a transmit signal only for the optimal detection performance, we solve a biobjective Pareto-optimization problem, subjecting to the PAPR and total energy constraints, in order to simultaneously optimize the detection and cross-correlation performances. With extensive numerical examples, we demonstrate that PAPR-constrained signals produce nearly optimum detection performance even with a strict PAPR requirement, and also highlight the conflicting behavior of the detection and correlation performances.
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.
Shape Optimization of Cochlear Implant Electrode Array Using Genetic Algorithms
2007-11-02
Shape Optimization of Cochlear Implant Electrode Array using Genetic Algorithms Charles T.M. Choi, Ph.D., senior member, IEEE Department of...c.t.choi@ieee.org Abstract−Finite element analysis is used to compute the current distribution of the human cochlea during cochlear implant electrical...stimulation. Genetic algorithms are then applied in conjunction with the finite element analysis to optimize the shape of cochlear implant electrode array
Shape-Measure Method for Introducing the Nearly Optimal Domain
2001-07-01
elements. The problem is to find the optimal domain approximately for a given functional that is involved with the solution of a linear or nonlinear...elliptic equation with a boundary condition over a domain. The Shape-Measure method, in Cartesian coordinates will be used to find the nearly optimal...domain by using the embedding method. Then the Shape-Measure method will be applied to find the best domain approximately. An example will be given.
Shape optimization for contact problems based on isogeometric analysis
NASA Astrophysics Data System (ADS)
Horn, Benjamin; Ulbrich, Stefan
2016-08-01
We consider the shape optimization for mechanical connectors. To avoid the gap between the representation in CAD systems and the finite element simulation used by mathematical optimization, we choose an isogeometric approach for the solution of the contact problem within the optimization method. This leads to a shape optimization problem governed by an elastic contact problem. We handle the contact conditions using the mortar method and solve the resulting contact problem with a semismooth Newton method. The optimization problem is nonconvex and nonsmooth due to the contact conditions. To reduce the number of simulations, we use a derivative based optimization method. With the adjoint approach the design derivatives can be calculated efficiently. The resulting optimization problem is solved with a modified Bundle Trust Region algorithm.
Design optimization of rod shaped IPMC actuator
NASA Astrophysics Data System (ADS)
Ruiz, S. A.; Mead, B.; Yun, H.; Yim, W.; Kim, K. J.
2013-04-01
Ionic polymer-metal composites (IPMCs) are some of the most well-known electro-active polymers. This is due to their large deformation provided a relatively low voltage source. IPMCs have been acknowledged as a potential candidate for biomedical applications such as cardiac catheters and surgical probes; however, there is still no existing mass manufacturing of IPMCs. This study intends to provide a theoretical framework which could be used to design practical purpose IPMCs depending on the end users interest. By explicitly coupling electrostatics, transport phenomenon, and solid mechanics, design optimization is conducted on a simulation in order to provide conceptual motivation for future designs. Utilizing a multi-physics analysis approach on a three dimensional cylinder and tube type IPMC provides physically accurate results for time dependent end effector displacement given a voltage source. Simulations are conducted with the finite element method and are also validated with empirical evidences. Having an in-depth understanding of the physical coupling provides optimal design parameters that cannot be altered from a standard electro-mechanical coupling. These parameters are altered in order to determine optimal designs for end-effector displacement, maximum force, and improved mobility with limited voltage magnitude. Design alterations are conducted on the electrode patterns in order to provide greater mobility, electrode size for efficient bending, and Nafion diameter for improved force. The results of this study will provide optimal design parameters of the IPMC for different applications.
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.
Shape insensitive optimal adhesion of nanoscale fibrillar structures
Gao, Huajian; Yao, Haimin
2004-01-01
Gecko and many insects have adopted nanoscale fibrillar structures on their feet as adhesion devices. Here, we consider adhesion between a single fiber and a substrate by van der Waals or electrostatic interactions. For a given contact area A, the theoretical pull-off force of the fiber is σthA where σth is the theoretical strength of adhesion. We show that it is possible to design an optimal shape of the tip of the fiber to achieve the theoretical pull-off force. However, such design tends to be unreliable at the macroscopic scale because the pull-off force is sensitive to small variations in the tip shape. We find that a robust design of shape-insensitive optimal adhesion becomes possible only when the diameter of the fiber is reduced to length scales on the order of 100 nm. In general, optimal adhesion could be achieved by a combination of size reduction and shape optimization. The smaller the size, the less important the shape. At large contact sizes, optimal adhesion could still be achieved if the shape can be manufactured to a sufficiently high precision. The robust design of optimal adhesion at nanoscale provides a plausible explanation for the convergent evolution of hairy attachment systems in biology. PMID:15148400
Optimal control design of pulse shapes as analytic functions.
Skinner, Thomas E; Gershenzon, Naum I
2010-06-01
Representing NMR pulse shapes by analytic functions is widely employed in procedures for optimizing performance. Insights concerning pulse dynamics can be applied to the choice of appropriate functions that target specific performance criteria, focusing the solution search and reducing the space of possible pulse shapes that must be considered to a manageable level. Optimal control theory can accommodate significantly larger parameter spaces and has been able to tackle problems of much larger scope than more traditional optimization methods. However, its numerically generated pulses, as currently constructed, do not readily incorporate the capabilities of particular functional forms, and the pulses are not guaranteed to vary smoothly in time, which can be a problem for faithful implementation on older hardware. An optimal control methodology is derived for generating pulse shapes as simple parameterized functions. It combines the benefits of analytic and numerical protocols in a single powerful algorithm that both complements and enhances existing optimization strategies.
Determination of Optimal Blank Shape by Radius Vector Method
NASA Astrophysics Data System (ADS)
Shim, Hyun Bo; Park, Jong Kyu; Kim, Yang Soo
2004-06-01
A new method of optimal blank shape design for stampings of arbitrary shapes has been proposed. Similar to the sensitivity method, a past work of the present author, the basic nature of this method is iterative modification of an undeformed blank shape by adjusting the nodal positions at the boundary of the blank, until the final shape satisfies a target shape. The main difference from the sensitivity method is that both shape error measure and blank shape modification is done along the normal to a boundary direction in the current method instead of nodal moving direction as in the sensitivity method. Even though the sensitivity method has been proven to be excellent through experiment, huge computational effort is still a problem since the method requires a couple of deformation process analyses per each design stage. Differently from the sensitivity method, the present radius vector method requires only a single deformation analysis per each design step and it can handle an extraordinary motion due to a rigid-body rotation during forming. Drawings of L-shaped cup and wheel housing have been chosen as the examples to verify the present method. In every cases the optimal blank shapes have been obtained after a few times of modification. Through the investigation, the present method, which incorporates normal to boundary is found to be an excellent, or better than the sensitivity method, which incorporates moving direction, for the optimal blank design.
Optimal embedding for shape indexing in medical image databases.
Qian, Xiaoning; Tagare, Hemant D; Fulbright, Robert K; Long, Rodney; Antani, Sameer
2010-06-01
This paper addresses the problem of indexing shapes in medical image databases. Shapes of organs are often indicative of disease, making shape similarity queries important in medical image databases. Mathematically, shapes with landmarks belong to shape spaces which are curved manifolds with a well defined metric. The challenge in shape indexing is to index data in such curved spaces. One natural indexing scheme is to use metric trees, but metric trees are prone to inefficiency. This paper proposes a more efficient alternative. We show that it is possible to optimally embed finite sets of shapes in shape space into a Euclidean space. After embedding, classical coordinate-based trees can be used for efficient shape retrieval. The embedding proposed in the paper is optimal in the sense that it least distorts the partial Procrustes shape distance. The proposed indexing technique is used to retrieve images by vertebral shape from the NHANES II database of cervical and lumbar spine X-ray images maintained at the National Library of Medicine. Vertebral shape strongly correlates with the presence of osteophytes, and shape similarity retrieval is proposed as a tool for retrieval by osteophyte presence and severity. Experimental results included in the paper evaluate (1) the usefulness of shape similarity as a proxy for osteophytes, (2) the computational and disk access efficiency of the new indexing scheme, (3) the relative performance of indexing with embedding to the performance of indexing without embedding, and (4) the computational cost of indexing using the proposed embedding versus the cost of an alternate embedding. The experimental results clearly show the relevance of shape indexing and the advantage of using the proposed embedding. Copyright (c) 2010 Elsevier B.V. All rights reserved.
Optimal Embedding for Shape Indexing in Medical Image Databases
Qian, Xiaoning; Tagare, Hemant D.; Fulbright, Robert K.; Long, Rodney; Antani, Sameer
2010-01-01
This paper addresses the problem of indexing shapes in medical image databases. Shapes of organs are often indicative of disease, making shape similarity queries important in medical image databases. Mathematically, shapes with landmarks belong to shape spaces which are curved manifolds with a well defined metric. The challenge in shape indexing is to index data in such curved spaces. One natural indexing scheme is to use metric trees, but metric trees are prone to inefficiency. This paper proposes a more efficient alternative. We show that it is possible to optimally embed finite sets of shapes in shape space into a Euclidean space. After embedding, classical coordinate-based trees can be used for efficient shape retrieval. The embedding proposed in the paper is optimal in the sense that it least distorts the partial Procrustes shape distance. The proposed indexing technique is used to retrieve images by vertebral shape from the NHANES II database of cervical and lumbar spine x-ray images maintained at the National Library of Medicine. Vertebral shape strongly correlates with the presence of osteophytes, and shape similarity retrieval is proposed as a tool for retrieval by osteophyte presence and severity. Experimental results included in the paper evaluate (1) the usefulness of shape-similarity as a proxy for osteophytes, (2) the computational and disk access efficiency of the new indexing scheme, (3) the relative performance of indexing with embedding to the performance of indexing without embedding, and (4) the computational cost of indexing using the proposed embedding versus the cost of an alternate embedding. The experimental results clearly show the relevance of shape indexing and the advantage of using the proposed embedding. PMID:20163981
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.
Multi-objective optimization shapes ecological variation.
Kaitaniemi, Pekka; Scheiner, Annette; Klemola, Tero; Ruohomäki, Kai
2012-02-22
Ecological systems contain a huge amount of quantitative variation between and within species and locations, which makes it difficult to obtain unambiguous verification of theoretical predictions. Ordinary experiments consider just a few explanatory factors and are prone to providing oversimplified answers because they ignore the complexity of the factors that underlie variation. We used multi-objective optimization (MO) for a mechanistic analysis of the potential ecological and evolutionary causes and consequences of variation in the life-history traits of a species of moth. Optimal life-history solutions were sought for environmental conditions where different life stages of the moth were subject to predation and other known fitness-reducing factors in a manner that was dependent on the duration of these life stages and on variable mortality rates. We found that multi-objective optimal solutions to these conditions that the moths regularly experience explained most of the life-history variation within this species. Our results demonstrate that variation can have a causal interpretation even for organisms under steady conditions. The results suggest that weather and species interactions can act as underlying causes of variation, and MO acts as a corresponding adaptive mechanism that maintains variation in the traits of organisms.
NASA Astrophysics Data System (ADS)
Ueno, Atsushi; Suzuki, Kojiro
For the success of hypersonic vehicles, their shape must be optimized to achieve a high lift-to-drag ratio as well as a low aerodynamic heating rate in the hypersonic regime. In addition, the transonic lift-to-drag ratio must also be optimized to realize quick acceleration to the hypersonic cruise speed. The three-dimensional lift-to-drag ratio can be improved even by the two-dimensional section shape (i.e., airfoil) optimization in the region where the sweep back angle is small. Here, prior to three-dimensional shape optimization, a study is done to optimize airfoils of hypersonic vehicles based on these three parameters. At optimization, the hypersonic lift-to-drag ratio is maximized while the transonic lift-to-drag ratio and the aerodynamic heating rate are constrained. The optimum lift coefficient for hypersonic cruise at the maximum lift-to-drag ratio is investigated. The relation between the leading edge radius, which determines the aerodynamic heating rate, and the hypersonic lift-to-drag ratio is also investigated. Results show that to improve the hypersonic lift-to-drag ratio, the airfoil thickness around the leading edge should be small as long as an appropriate compromise with the transonic lift-to-drag ratio is achieved. Results also show that the optimum lift coefficient for hypersonic cruise is much lower than that for typical supersonic vehicles. Small cruise lift coefficient suggests that the wing loading of a hypersonic vehicle should be small. The leading edge radius should be determined by a compromise between the hypersonic lift-to-drag ratio and leading edge heating. Airfoil optimization can provide an appropriate initial guess of the three-dimensional optimum shape. By using an appropriate initial guess, the computation time of the three-dimensional shape optimization is expected to be reduced.
Optimal shapes of axisymmetric bodies penetrating into soil
NASA Astrophysics Data System (ADS)
Kotov, V. L.; Linnik, E. Yu.; Tarasova, A. A.
2016-09-01
This paper presents the results of a study of the shapes of axisymmetric bodies with minimum drag and maximum depth of penetration into the plastic soils. Optimal shapes of bodies of revolution of given length and cross-sectional radius with generatrices represented by line segments are obtained by a modified method of local variations. The problem is solved using a binomial quadratic model of local interaction, including inertial and strength terms containing constant and Coulomb frictions. The drag forces and the penetration depth of cones and the obtained bodies of optimal shape are determined at different penetration velocities.
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.
A penalty method for PDE-constrained optimization in inverse problems
NASA Astrophysics Data System (ADS)
van Leeuwen, T.; Herrmann, F. J.
2016-01-01
Many inverse and parameter estimation problems can be written as PDE-constrained optimization problems. The goal is to infer the parameters, typically coefficients of the PDE, from partial measurements of the solutions of the PDE for several right-hand sides. Such PDE-constrained problems can be solved by finding a stationary point of the Lagrangian, which entails simultaneously updating the parameters and the (adjoint) state variables. For large-scale problems, such an all-at-once approach is not feasible as it requires storing all the state variables. In this case one usually resorts to a reduced approach where the constraints are explicitly eliminated (at each iteration) by solving the PDEs. These two approaches, and variations thereof, are the main workhorses for solving PDE-constrained optimization problems arising from inverse problems. In this paper, we present an alternative method that aims to combine the advantages of both approaches. Our method is based on a quadratic penalty formulation of the constrained optimization problem. By eliminating the state variable, we develop an efficient algorithm that has roughly the same computational complexity as the conventional reduced approach while exploiting a larger search space. Numerical results show that this method indeed reduces some of the nonlinearity of the problem and is less sensitive to the initial iterate.
Induced charge electro osmotic mixer: Obstacle shape optimization
Jain, Mranal; Yeung, Anthony; Nandakumar, K.
2009-01-01
Efficient mixing is difficult to achieve in miniaturized devices due to the nature of low Reynolds number flow. Mixing can be intentionally induced, however, if conducting or nonconducting obstacles are embedded within the microchannel. In the case of conducting obstacles, vortices can be generated in the vicinity of the obstacle due to induced charge electro-osmosis (ICEO) which enhances mixing of different streams: the obstacle shape affects the induced zeta potential on the conducting surface, which in turn influences the flow profile near the obstacle. This study deals with optimization of the geometric shape of a conducting obstacle for the purpose of micromixing. The obstacle boundary is parametrically represented by nonuniform rational B-spline curves. The optimal obstacle shape, which maximizes the mixing for given operating conditions, is found using genetic algorithms. Various case studies at different operating conditions demonstrated that the near right triangle shape provides optimal mixing in the ICEO flow dominant regime, whereas rectangular shape is the optimal shape in diffusion dominant regime. The tradeoff between mixing and transport is examined for symmetric and nonsymmetric obstacle shapes. PMID:19693348
CONORBIT: constrained optimization by radial basis function interpolation in trust regions
Regis, Rommel G.; Wild, Stefan M.
2016-09-26
Here, this paper presents CONORBIT (CONstrained Optimization by Radial Basis function Interpolation in Trust regions), a derivative-free algorithm for constrained black-box optimization where the objective and constraint functions are computationally expensive. CONORBIT employs a trust-region framework that uses interpolating radial basis function (RBF) models for the objective and constraint functions, and is an extension of the ORBIT algorithm. It uses a small margin for the RBF constraint models to facilitate the generation of feasible iterates, and extensive numerical tests confirm that such a margin is helpful in improving performance. CONORBIT is compared with other algorithms on 27 test problems, a chemical process optimization problem, and an automotive application. Numerical results show that CONORBIT performs better than COBYLA, a sequential penalty derivative-free method, an augmented Lagrangian method, a direct search method, and another RBF-based algorithm on the test problems and on the automotive application.
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.
CONORBIT: constrained optimization by radial basis function interpolation in trust regions
Regis, Rommel G.; Wild, Stefan M.
2016-09-26
Here, this paper presents CONORBIT (CONstrained Optimization by Radial Basis function Interpolation in Trust regions), a derivative-free algorithm for constrained black-box optimization where the objective and constraint functions are computationally expensive. CONORBIT employs a trust-region framework that uses interpolating radial basis function (RBF) models for the objective and constraint functions, and is an extension of the ORBIT algorithm. It uses a small margin for the RBF constraint models to facilitate the generation of feasible iterates, and extensive numerical tests confirm that such a margin is helpful in improving performance. CONORBIT is compared with other algorithms on 27 test problems, amore » chemical process optimization problem, and an automotive application. Numerical results show that CONORBIT performs better than COBYLA, a sequential penalty derivative-free method, an augmented Lagrangian method, a direct search method, and another RBF-based algorithm on the test problems and on the automotive application.« less
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.
Genetic algorithms for multicriteria shape optimization of induction furnace
NASA Astrophysics Data System (ADS)
Kůs, Pavel; Mach, František; Karban, Pavel; Doležel, Ivo
2012-09-01
In this contribution we deal with a multi-criteria shape optimization of an induction furnace. We want to find shape parameters of the furnace in such a way, that two different criteria are optimized. Since they cannot be optimized simultaneously, instead of one optimum we find set of partially optimal designs, so called Pareto front. We compare two different approaches to the optimization, one using nonlinear conjugate gradient method and second using variation of genetic algorithm. As can be seen from the numerical results, genetic algorithm seems to be the right choice for this problem. Solution of direct problem (coupled problem consisting of magnetic and heat field) is done using our own code Agros2D. It uses finite elements of higher order leading to fast and accurate solution of relatively complicated coupled problem. It also provides advanced scripting support, allowing us to prepare parametric model of the furnace and simply incorporate various types of optimization algorithms.
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.
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.
A sensitivity equation approach to shape optimization in fluid flows
NASA Technical Reports Server (NTRS)
Borggaard, Jeff; Burns, John
1994-01-01
A sensitivity equation method to shape optimization problems is applied. An algorithm is developed and tested on a problem of designing optimal forebody simulators for a 2D, inviscid supersonic flow. The algorithm uses a BFGS/Trust Region optimization scheme with sensitivities computed by numerically approximating the linear partial differential equations that determine the flow sensitivities. Numerical examples are presented to illustrate the method.
Optimal mass transport for shape matching and comparison.
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.
Optimal Mass Transport for Shape Matching and Comparison
Su, Zhengyu; Wang, Yalin; Shi, Rui; Zeng, Wei; Sun, Jian; Luo, Feng; Gu, Xianfeng
2015-01-01
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(n2) 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
Zhang, Songchuan; Xia, Youshen; Wang, Jun
2015-12-01
In this paper, we present a complex-valued projection neural network for solving constrained convex optimization problems of real functions with complex variables, as an extension of real-valued projection neural networks. Theoretically, by developing results on complex-valued optimization techniques, we prove that the complex-valued projection neural network is globally stable and convergent to the optimal solution. Obtained results are completely established in the complex domain and thus significantly generalize existing results of the real-valued projection neural networks. Numerical simulations are presented to confirm the obtained results and effectiveness of the proposed complex-valued projection neural network.
A Newton-Krylov Approach to Aerodynamic Shape Optimization in Three Dimensions
NASA Astrophysics Data System (ADS)
Leung, Timothy Man-Ming
A Newton-Krylov algorithm is presented for aerodynamic shape optimization in three dimensions using the Euler equations. An inexact-Newton method is used in the flow solver, a discrete-adjoint method to compute the gradient, and the quasi-Newton optimizer to find the optimum. A Krylov subspace method with approximate-Schur preconditioning is used to solve both the flow equation and the adjoint equation. Basis spline surfaces are used to parameterize the geometry, and a fast algebraic algorithm is used for grid movement. Accurate discrete- adjoint gradients can be obtained in approximately one-fourth the time required for a converged flow solution. Single- and multi-point lift-constrained drag minimization optimization cases are presented for wing design at transonic speeds. In all cases, the optimizer is able to efficiently decrease the objective function and gradient for problems with hundreds of design variables.
Application of Chance-Constrained Stochastic Optimization for Mitigating Downstream Flood Risks
NASA Astrophysics Data System (ADS)
Alvarado Montero, Rodolfo; Schwanenberg, Dirk; Mainardi Fan, Fernando; Assis dos Reis, Alberto
2015-04-01
Ensemble forecasting is a growing field in the operation of multi-purpose reservoirs and mitigation of flood risks in downstream river reaches. The assessment of uncertainty over the prediction horizon provides added value to the operational flow forecasting system. It provides probabilistic inflow forecasts which, combined with decision support systems, determine optimum release strategies. One way of doing this is through scenario tree-based stochastic optimization. The representation of the ensemble forecasted is converted into a scenario-tree and optimized based on an adaptive multi-stage stochastic optimization. Typical inequality constraints applied over this problem require a full compliance of each ensemble's trajectory and neglect the uncertainty distribution. We propose the application of chance constrained optimization to overcome such problem, allowing a more flexible approach that does not depend on the number of ensembles but rather on the distribution of uncertainty. This technique is used to compute release trajectories of the reservoirs over a finite forecast horizon of up to 14 days by integrating a nonlinear gradient-based optimization algorithm and a model of the water system. The latter consists of simulation components for pool routing and kinematic or diffusive wave models for the downstream river reaches including a simulation mode and a reverse adjoint mode for the efficient computation of first-order derivatives. This framework has been implemented for a reservoir system operated by the Brazilian Companhia Energética de Minas Gerais S.A. (CEMIG). We present results obtained for the operation of the Tres Marias reservoir in the Brazilian state of Minas Gerais with a catchment area of near 55,000 km2. The focus of our discussion is the impact of chance constrains on the optimization procedure and its flexibility for extending the number of ensemble forecasts thus providing a more accurate representation of uncertainty. We compare the
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.
On the optimal shape of magnetic swimmers
NASA Astrophysics Data System (ADS)
Gadêlha, Hermes
2013-01-01
Magnetic actuation of elasto-magnetic devices has long been proposed as a simple way to propel fluid and achieve locomotion in environments dominated by viscous forces. Under the action of an oscillating magnetic field, a permanent magnet, when attached to an elastic tail, is able to generate bending waves and sufficient thrust for propulsion. We study the hydrodynamical effects of the magnetic head geometry using a geometrically exact formulation for the elastic tail elastohydrodynamics.We show that the spherical head geometry fails to take full advantage of the propulsive potential from the flexible tail. Nevertheless, while elongated prolate spheroids demonstrate a superior swimming performance, this is still regulated by the nature of the imposed magnetic field. Interestingly, the highest swimming speed is observed when the magnitude of the magnetic field is weak due to delays between the orientation of the magnetic moment and the oscillating magnetic field. This allows the stored elastic energy from the deformed tail to relax during the phase lag between the imposed magnetic field and the swimmer's magnetic moment, favouring in this way the net propulsion. In particular, this result suggests the existence of optimal magnetic actuations that are non-smooth, and even discontinuous in time, in order to fully explore the propulsive potential associated with the relaxation dynamics of periodically deformed elastic filaments.
Shape Optimization of Vehicle Radiator Using Computational Fluid Dynamics (cfd)
NASA Astrophysics Data System (ADS)
Maddipatla, Sridhar; Guessous, Laila
2002-11-01
Automotive manufacturers need to improve the efficiency and lifetime of all engine components. In the case of radiators, performance depends significantly on coolant flow homogeneity across the tubes and overall pressure drop between the inlet and outlet. Design improvements are especially needed in tube-flow uniformity to prevent premature fouling and failure of heat exchangers. Rather than relying on ad-hoc geometry changes, the current study combines Computational Fluid Dynamics with shape optimization methods to improve radiator performance. The goal is to develop an automated suite of virtual tools to assist in radiator design. Two objective functions are considered: a flow non-uniformity coefficient,Cf, and the overall pressure drop, dP*. The methodology used to automate the CFD and shape optimization procedures is discussed. In the first phase, single and multi-variable optimization methods, coupled with CFD, are applied to simplified 2-D radiator models to investigate effects of inlet and outlet positions on the above functions. The second phase concentrates on CFD simulations of a simplified 3-D radiator model. The results, which show possible improvements in both pressure and flow uniformity, validate the optimization criteria that were developed, as well as the potential of shape optimization methods with CFD to improve heat exchanger design. * Improving Radiator Design Through Shape Optimization, L. Guessous and S. Maddipatla, Paper # IMECE2002-33888, Proceedings of the 2002 ASME International Mechanical Engineering Congress and Exposition, November 2002
NASA Astrophysics Data System (ADS)
Beri, Rajan; Chattopadhyay, Aditi; Nam, Changho
2000-06-01
A rigorous multi-objective optimization procedure, is developed to address the integrated structures/control design of composite plates with surface bonded segmented active constrained layer (ACL) damping treatment. The Kresselmeier- Steinhauser function approach is used to formulate this multidisciplinary problem. The goal is to control vibration without incorporating a weight penalty. Objective functions and constraints include damping ratios, structural weight and natural frequencies. Design variables include the ply stacking sequence, dimensions and placement of segmented ACL. The optimal designs show improved plate vibratory characteristics and reduced structural weight. The results of the multi- objective optimization problem are compared to those of a single objective optimization with vibration control as the objective. Results establish the necessity for developing the integrated structures/controls optimization procedure.
Optimizing Data Locality for Fork/Join Programs Using Constrained Work Stealing
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.
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.
On Shape Optimization for an Evolution Coupled System
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.
CSOLNP: Numerical Optimization Engine for Solving Non-linearly Constrained Problems.
Zahery, Mahsa; Maes, Hermine H; Neale, Michael C
2017-08-01
We introduce the optimizer CSOLNP, which is a C++ implementation of the R package RSOLNP (Ghalanos & Theussl, 2012, Rsolnp: General non-linear optimization using augmented Lagrange multiplier method. R package version, 1) alongside some improvements. CSOLNP solves non-linearly constrained optimization problems using a Sequential Quadratic Programming (SQP) algorithm. CSOLNP, NPSOL (a very popular implementation of SQP method in FORTRAN (Gill et al., 1986, User's guide for NPSOL (version 4.0): A Fortran package for nonlinear programming (No. SOL-86-2). Stanford, CA: Stanford University Systems Optimization Laboratory), and SLSQP (another SQP implementation available as part of the NLOPT collection (Johnson, 2014, The NLopt nonlinear-optimization package. Retrieved from http://ab-initio.mit.edu/nlopt)) are three optimizers available in OpenMx package. These optimizers are compared in terms of runtimes, final objective values, and memory consumption. A Monte Carlo analysis of the performance of the optimizers was performed on ordinal and continuous models with five variables and one or two factors. While the relative difference between the objective values is less than 0.5%, CSOLNP is in general faster than NPSOL and SLSQP for ordinal analysis. As for continuous data, none of the optimizers performs consistently faster than the others. In terms of memory usage, we used Valgrind's heap profiler tool, called Massif, on one-factor threshold models. CSOLNP and NPSOL consume the same amount of memory, while SLSQP uses 71 MB more memory than the other two optimizers.
Shape optimization for a composite crack-length sensor
NASA Technical Reports Server (NTRS)
Prabhakaran, R.; Ramasamy, M.
1992-01-01
Techniques for improving the sensitivity of a carbon powder-polymer composite continuous crack-length sensor are examined. These conductive polymeric sensors can be used as crack-length gages, the shape of which can be varied in certain ways to improve their sensitivity. It is concluded that the gages with optimized or tapered shape are capable of overcoming the principal disadvantage of rectangular gages, i.e., poor sensitivity at small crack length.
Shape optimization of rubber bushing using differential evolution algorithm.
Kaya, Necmettin
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.
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.
Shape Optimization of Rubber Bushing Using Differential Evolution Algorithm
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
A Bi-Projection Neural Network for Solving Constrained Quadratic Optimization Problems.
Xia, Youshen; Wang, Jun
2016-02-01
In this paper, a bi-projection neural network for solving a class of constrained quadratic optimization problems is proposed. It is proved that the proposed neural network is globally stable in the sense of Lyapunov, and the output trajectory of the proposed neural network will converge globally to an optimal solution. Compared with existing projection neural networks (PNNs), the proposed neural network has a very small model size owing to its bi-projection structure. Furthermore, an application to data fusion shows that the proposed neural network is very effective. Numerical results demonstrate that the proposed neural network is much faster than the existing PNNs.
NASA Astrophysics Data System (ADS)
Andretta, Marina; Birgin, Ernesto; Martínez, J.
2010-01-01
A method for linearly constrained optimization which modifies and generalizes recent box-constraint optimization algorithms is introduced. The new algorithm is based on a relaxed form of Spectral Projected Gradient iterations. Intercalated with these projected steps, internal iterations restricted to faces of the polytope are performed, which enhance the efficiency of the algorithm. Convergence proofs are given and numerical experiments are included and commented. Software supporting this paper is available through the Tango Project web page: http://www.ime.usp.br/˜egbirgin/tango/.
Shape design sensitivity analysis and optimal design of structural systems
NASA Technical Reports Server (NTRS)
Choi, Kyung K.
1987-01-01
The material derivative concept of continuum mechanics and an adjoint variable method of design sensitivity analysis are used to relate variations in structural shape to measures of structural performance. A domain method of shape design sensitivity analysis is used to best utilize the basic character of the finite element method that gives accurate information not on the boundary but in the domain. Implementation of shape design sensitivty analysis using finite element computer codes is discussed. Recent numerical results are used to demonstrate the accuracy obtainable using the method. Result of design sensitivity analysis is used to carry out design optimization of a built-up structure.
Optimized input shaping for a single flexible robot link
Wilson, D.G.; Stokes, D.; Starr, G.; Robinett, R.D.
1996-03-01
This paper will discuss the design of an input shaped open-loop control for a single flexible robot link. The authors develop the equations of motion, including the first flexible mode shape and the actuator dynamics. Additional content includes the hardware system identification iterative runs used to update the model. Optimized input shaped commands for the flexible robot link to produce a rest-to-rest, residual vibration-free, 90 degree maneuver are developed. Correlation between both experimental and analytical results of the 90{degree} slew, using two different identification models, are reviewed.
Optimal Heat Collection Element Shapes for Parabolic Trough Concentrators
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.
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.
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.
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.
Optimal shape and motion of undulatory swimming organisms.
Tokić, Grgur; Yue, Dick K P
2012-08-07
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.
Optimal shape and motion of undulatory swimming organisms
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
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.
Optimal vibration control of a rotating plate with self-sensing active constrained layer damping
NASA Astrophysics Data System (ADS)
Xie, Zhengchao; Wong, Pak Kin; Lo, Kin Heng
2012-04-01
This paper proposes a finite element model for optimally controlled constrained layer damped (CLD) rotating plate with self-sensing technique and frequency-dependent material property in both the time and frequency domain. Constrained layer damping with viscoelastic material can effectively reduce the vibration in rotating structures. However, most existing research models use complex modulus approach to model viscoelastic material, and an additional iterative approach which is only available in frequency domain has to be used to include the material's frequency dependency. It is meaningful to model the viscoelastic damping layer in rotating part by using the anelastic displacement fields (ADF) in order to include the frequency dependency in both the time and frequency domain. Also, unlike previous ones, this finite element model treats all three layers as having the both shear and extension strains, so all types of damping are taken into account. Thus, in this work, a single layer finite element is adopted to model a three-layer active constrained layer damped rotating plate in which the constraining layer is made of piezoelectric material to work as both the self-sensing sensor and actuator under an linear quadratic regulation (LQR) controller. After being compared with verified data, this newly proposed finite element model is validated and could be used for future research.
Three-dimensional aerodynamic shape optimization using discrete sensitivity analysis
NASA Technical Reports Server (NTRS)
Burgreen, Gregory W.
1995-01-01
An aerodynamic shape optimization procedure based on discrete sensitivity analysis is extended to treat three-dimensional geometries. The function of sensitivity analysis is to directly couple computational fluid dynamics (CFD) with numerical optimization techniques, which facilitates the construction of efficient direct-design methods. The development of a practical three-dimensional design procedures entails many challenges, such as: (1) the demand for significant efficiency improvements over current design methods; (2) a general and flexible three-dimensional surface representation; and (3) the efficient solution of very large systems of linear algebraic equations. It is demonstrated that each of these challenges is overcome by: (1) employing fully implicit (Newton) methods for the CFD analyses; (2) adopting a Bezier-Bernstein polynomial parameterization of two- and three-dimensional surfaces; and (3) using preconditioned conjugate gradient-like linear system solvers. Whereas each of these extensions independently yields an improvement in computational efficiency, the combined effect of implementing all the extensions simultaneously results in a significant factor of 50 decrease in computational time and a factor of eight reduction in memory over the most efficient design strategies in current use. The new aerodynamic shape optimization procedure is demonstrated in the design of both two- and three-dimensional inviscid aerodynamic problems including a two-dimensional supersonic internal/external nozzle, two-dimensional transonic airfoils (resulting in supercritical shapes), three-dimensional transport wings, and three-dimensional supersonic delta wings. Each design application results in realistic and useful optimized shapes.
Optimal Aeroacoustic Shape Design Using the Surrogate Management Framework
2004-02-09
wish to thank the IMA for providing a forum for collaboration, as well as Charles Audet and Petros Koumoutsakos for valuable discussions. The authors...17] N. Hansen, D. Mller, and P. Koumoutsakos . Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation...P. Koumoutsakos . Optimal aeroacoustic shape design using approximation modeling. Annual Research Briefs, Center for Turbulence Research, Stanford
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
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.
Elliptical Cavity Shape Optimization for Acceleration and HOM Damping
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.
A free boundary approach to shape optimization problems
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
A free boundary approach to shape optimization problems.
Bucur, D; Velichkov, B
2015-09-13
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.
NASA Astrophysics Data System (ADS)
Ciaramello, Frank M.; Hemami, Sheila S.
2008-01-01
Sign language users are eager for the freedom and convenience of video communication over cellular devices. Compression of sign language video in this setting offers unique challenges. The low bitrates available make encoding decisions extremely important, while the power constraints of the device limit the encoder complexity. The ultimate goal is to maximize the intelligibility of the conversation given the rate-constrained cellular channel and power constrained encoding device. This paper uses an objective measure of intelligibility, based on subjective testing with members of the Deaf community, for rate-distortion optimization of sign language video within the H.264 framework. Performance bounds are established by using the intelligibility metric in a Lagrangian cost function along with a trellis search to make optimal mode and quantizer decisions for each macroblock. The optimal QP values are analyzed and the unique structure of sign language is exploited in order to reduce complexity by three orders of magnitude relative to the trellis search technique with no loss in rate-distortion performance. Further reductions in complexity are made by eliminating rarely occuring modes in the encoding process. The low complexity SL optimization technique increases the measured intelligibility up to 3.5 dB, at fixed rates, and reduces rate by as much as 60% at fixed levels of intelligibility with respect to a rate control algorithm designed for aesthetic distortion as measured by MSE.
Stenrup, Michael; Lindh, Roland; Fdez Galván, Ignacio
2015-08-15
A method is proposed to easily reduce the number of energy evaluations required to compute numerical gradients when constraints are imposed on the system, especially in connection with rigid fragment optimization. The method is based on the separation of the coordinate space into a constrained and an unconstrained space, and the numerical differentiation is done exclusively in the unconstrained space. The decrease in the number of energy calculations can be very important if the system is significantly constrained. The performance of the method is tested on systems that can be considered as composed of several rigid groups or molecules, and the results show that the error with respect to conventional optimizations is of the order of the convergence criteria. Comparison with another method designed for rigid fragment optimization proves the present method to be competitive. The proposed method can also be applied to combine numerical and analytical gradients computed at different theory levels, allowing an unconstrained optimization with numerical differentiation restricted to the most significant degrees of freedom. This approach can be a practical alternative when analytical gradients are not available at the desired computational level and full numerical differentiation is not affordable. © 2015 Wiley Periodicals, Inc.
CLFs-based optimization control for a class of constrained visual servoing systems.
Song, Xiulan; Miaomiao, Fu
2017-03-01
In this paper, we use the control Lyapunov function (CLF) technique to present an optimized visual servo control method for constrained eye-in-hand robot visual servoing systems. With the knowledge of camera intrinsic parameters and depth of target changes, visual servo control laws (i.e. translation speed) with adjustable parameters are derived by image point features and some known CLF of the visual servoing system. The Fibonacci method is employed to online compute the optimal value of those adjustable parameters, which yields an optimized control law to satisfy constraints of the visual servoing system. The Lyapunov's theorem and the properties of CLF are used to establish stability of the constrained visual servoing system in the closed-loop with the optimized control law. One merit of the presented method is that there is no requirement of online calculating the pseudo-inverse of the image Jacobian's matrix and the homography matrix. Simulation and experimental results illustrated the effectiveness of the method proposed here.
Dynamic optimization and its relation to classical and quantum constrained systems
NASA Astrophysics Data System (ADS)
Contreras, Mauricio; Pellicer, Rely; Villena, Marcelo
2017-08-01
We study the structure of a simple dynamic optimization problem consisting of one state and one control variable, from a physicist's point of view. By using an analogy to a physical model, we study this system in the classical and quantum frameworks. Classically, the dynamic optimization problem is equivalent to a classical mechanics constrained system, so we must use the Dirac method to analyze it in a correct way. We find that there are two second-class constraints in the model: one fix the momenta associated with the control variables, and the other is a reminder of the optimal control law. The dynamic evolution of this constrained system is given by the Dirac's bracket of the canonical variables with the Hamiltonian. This dynamic results to be identical to the unconstrained one given by the Pontryagin equations, which are the correct classical equations of motion for our physical optimization problem. In the same Pontryagin scheme, by imposing a closed-loop λ-strategy, the optimality condition for the action gives a consistency relation, which is associated to the Hamilton-Jacobi-Bellman equation of the dynamic programming method. A similar result is achieved by quantizing the classical model. By setting the wave function Ψ(x , t) =e iS(x , t) in the quantum Schrödinger equation, a non-linear partial equation is obtained for the S function. For the right-hand side quantization, this is the Hamilton-Jacobi-Bellman equation, when S(x , t) is identified with the optimal value function. Thus, the Hamilton-Jacobi-Bellman equation in Bellman's maximum principle, can be interpreted as the quantum approach of the optimization problem.
An explicit shape-constrained MRF-based contour evolution method for 2-D medical image segmentation.
Chittajallu, Deepak R; Paragios, Nikos; Kakadiaris, Ioannis A
2014-01-01
Image segmentation is, in general, an ill-posed problem and additional constraints need to be imposed in order to achieve the desired segmentation result. While segmenting organs in medical images, which is the topic of this paper, a significant amount of prior knowledge about the shape, appearance, and location of the organs is available that can be used to constrain the solution space of the segmentation problem. Among the various types of prior information, the incorporation of prior information about shape, in particular, is very challenging. In this paper, we present an explicit shape-constrained MAP-MRF-based contour evolution method for the segmentation of organs in 2-D medical images. Specifically, we represent the segmentation contour explicitly as a chain of control points. We then cast the segmentation problem as a contour evolution problem, wherein the evolution of the contour is performed by iteratively solving a MAP-MRF labeling problem. The evolution of the contour is governed by three types of prior information, namely: (i) appearance prior, (ii) boundary-edgeness prior, and (iii) shape prior, each of which is incorporated as clique potentials into the MAP-MRF problem. We use the master-slave dual decomposition framework to solve the MAP-MRF labeling problem in each iteration. In our experiments, we demonstrate the application of the proposed method to the challenging problem of heart segmentation in non-contrast computed tomography data.
Improving the efficiency of aerodynamic shape optimization procedures
NASA Technical Reports Server (NTRS)
Burgreen, Greg W.; Baysal, Oktay; Eleshaky, Mohamed E.
1992-01-01
The computational efficiency of an aerodynamic shape optimization procedure which is based on discrete sensitivity analysis is increased through the implementation of two improvements. The first improvement involves replacing a grid point-based approach for surface representation with a Bezier-Bernstein polynomial parameterization of the surface. Explicit analytical expressions for the grid sensitivity terms are developed for both approaches. The second improvement proposes the use of Newton's method in lieu of an alternating direction implicit (ADI) methodology to calculate the highly converged flow solutions which are required to compute the sensitivity coefficients. The modified design procedure is demonstrated by optimizing the shape of an internal-external nozzle configuration. A substantial factor of 8 decrease in computational time for the optimization process was achieved by implementing both of the design improvements.
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.
NASA Astrophysics Data System (ADS)
Zhang, Weiyu; Vorobyov, Sergiy A.
2016-01-01
A joint robust transmit/receive adaptive beamforming for multiple-input multipleoutput (MIMO) radar based on probability-constrained optimization approach is developed in the case of Gaussian and arbitrary distributed mismatch present in both the transmit and receive signal steering vectors. A tight lower bound of the probability constraint is also derived by using duality theory. The formulated probability-constrained robust beamforming problem is nonconvex and NP-hard. However, we reformulate its cost function into a bi-quadratic function while the probability constraint splits into transmit and receive parts. Then, a block coordinate descent method based on second-order cone programming is developed to address the biconvex problem. Simulation results show an improved robustness of the proposed beamforming method as compared to the worst-case and other existing state-of-the-art joint transmit/receive robust adaptive beamforming methods for MIMO radar.
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.
NASA Astrophysics Data System (ADS)
Shieh, Niahn-Chung; Lin, Chun-Liang; Lin, Yu-Chen; Liang, Kuo-Zoo
2005-07-01
This research proposes a systematic and effective optimization process for the design of vertical passive suspension of light rail vehicles (LRVs) using new constrained multiobjective evolution algorithms. A multibody dynamic model of the three-car train set is presented and the suspension spring and damping parameters are optimally designed. A new design of the passive suspension is aided by the use of evolution algorithms to attain the best compromise between ride quality and suspension deflections due to irregular gradient tracks. Extensive simulations are performed to verify the proposed design scheme. The preliminary results show that, when the passive suspension is optimized via the proposed approach, a substantial improvement in the vertical ride quality is obtained while keeping the suspension deflections within their allowable clearance when the light rail vehicle runs onto the worst track condition.
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.
Laboratory transferability of optimally shaped laser pulses for quantum control
Moore Tibbetts, Katharine; Xing, Xi; Rabitz, Herschel
2014-02-21
Optimal control experiments can readily identify effective shaped laser pulses, or “photonic reagents,” that achieve a wide variety of objectives. An important additional practical desire is for photonic reagent prescriptions to produce good, if not optimal, objective yields when transferred to a different system or laboratory. Building on general experience in chemistry, the hope is that transferred photonic reagent prescriptions may remain functional even though all features of a shaped pulse profile at the sample typically cannot be reproduced exactly. As a specific example, we assess the potential for transferring optimal photonic reagents for the objective of optimizing a ratio of photoproduct ions from a family of halomethanes through three related experiments. First, applying the same set of photonic reagents with systematically varying second- and third-order chirp on both laser systems generated similar shapes of the associated control landscape (i.e., relation between the objective yield and the variables describing the photonic reagents). Second, optimal photonic reagents obtained from the first laser system were found to still produce near optimal yields on the second laser system. Third, transferring a collection of photonic reagents optimized on the first laser system to the second laser system reproduced systematic trends in photoproduct yields upon interaction with the homologous chemical family. These three transfers of photonic reagents are demonstrated to be successful upon paying reasonable attention to overall laser system characteristics. The ability to transfer photonic reagents from one laser system to another is analogous to well-established utilitarian operating procedures with traditional chemical reagents. The practical implications of the present results for experimental quantum control are discussed.
Shape optimization methods locating layer interfaces in geothermal reservoirs
NASA Astrophysics Data System (ADS)
Huang, Simin; Wellmann, Florian; Marquart, Gabriele; Clauser, Christoph; Herty, Michael
2015-04-01
Subsurface structures have a strong influence on fluid flow and heat transport in geothermal systems. We examine whether the position of an interface between two units within a geothermal system with different petrophysical properties can be detected based on measured temperature-depth profiles. We use a shape optimization method for a level set function and combine it with the calculation of an adjoint variable on basis of the heat transport equation. The level set follows a Hamilton-Jacobi equation where the zero level set represents the position of the boundary. Starting from an initial guess, the position is iteratively adjusted during model optimization. Instead of directly computing the gradient of an objective function, we compute an adjoint temperature. The method is very efficient and requires only one forward simulation. The adjoint variable is then used in combination with the simulated temperature field to iteratively update the level set function to a new position until a shape convergence is obtained. The method was tested to determine the interface position in a set of two-layer models with differently shaped interfaces. Specifically, we investigated how advective heat transport affects the identification of the boundary. We generated synthetic observation data of temperatures in two boreholes in the model and used this data for shape optimization. First results are encouraging as we could identify the location of simple interfaces. Furthermore, our simulations suggest that advective heat transport often helps to detect the interface better. However, challenges remain, particularly if the shape of the interface becomes too complex or the dip of a layer is very steep. Currently, we are investigating these issues in more detail, for example addressing questions of number and position of boreholes with temperature measurements required for optimal interface identification.
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
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.
A New Continuous-Time Equality-Constrained Optimization to Avoid Singularity.
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.
PAPR-Constrained Pareto-Optimal Waveform Design for OFDM-STAP Radar
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.
Bacanin, Nebojsa; Tuba, Milan
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.
Solution techniques for transient stability-constrained optimal power flow – Part II
Geng, Guangchao; Abhyankar, Shrirang; Wang, Xiaoyu; ...
2017-06-28
Transient stability-constrained optimal power flow is an important emerging problem with power systems pushed to the limits for economic benefits, dense and larger interconnected systems, and reduced inertia due to expected proliferation of renewable energy resources. In this study, two more approaches: single machine equivalent and computational intelligence are presented. Also discussed are various application areas, and future directions in this research area. In conclusion, a comprehensive resource for the available literature, publicly available test systems, and relevant numerical libraries is also provided.
Constrained time-optimal control of double-integrator system and its application in MPC
NASA Astrophysics Data System (ADS)
Fehér, Marek; Straka, Ondřej; Šmídl, Václav
2017-01-01
The paper deals with the design of a time-optimal controller for systems subject to both state and control constraints. The focus is laid on a double-integrator system, for which the time-to-go function is calculated. The function is then used as a part of a model predictive control criterion where it represents the long-horizon part. The designed model predictive control algorithm is then used in a constrained control problem of permanent magnet synchronous motor model, which behavior can be approximated by a double integrator model. Accomplishments of the control goals are illustrated in a numerical example.
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.
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.
SU-E-I-23: A General KV Constrained Optimization of CNR for CT Abdominal Imaging
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.
Aerostructural Shape and Topology Optimization of Aircraft Wings
NASA Astrophysics Data System (ADS)
James, Kai
A series of novel algorithms for performing aerostructural shape and topology optimization are introduced and applied to the design of aircraft wings. An isoparametric level set method is developed for performing topology optimization of wings and other non-rectangular structures that must be modeled using a non-uniform, body-fitted mesh. The shape sensitivities are mapped to computational space using the transformation defined by the Jacobian of the isoparametric finite elements. The mapped sensitivities are then passed to the Hamilton-Jacobi equation, which is solved on a uniform Cartesian grid. The method is derived for several objective functions including mass, compliance, and global von Mises stress. The results are compared with SIMP results for several two-dimensional benchmark problems. The method is also demonstrated on a three-dimensional wingbox structure subject to fixed loading. It is shown that the isoparametric level set method is competitive with the SIMP method in terms of the final objective value as well as computation time. In a separate problem, the SIMP formulation is used to optimize the structural topology of a wingbox as part of a larger MDO framework. Here, topology optimization is combined with aerodynamic shape optimization, using a monolithic MDO architecture that includes aerostructural coupling. The aerodynamic loads are modeled using a three-dimensional panel method, and the structural analysis makes use of linear, isoparametric, hexahedral elements. The aerodynamic shape is parameterized via a set of twist variables representing the jig twist angle at equally spaced locations along the span of the wing. The sensitivities are determined analytically using a coupled adjoint method. The wing is optimized for minimum drag subject to a compliance constraint taken from a 2 g maneuver condition. The results from the MDO algorithm are compared with those of a sequential optimization procedure in order to quantify the benefits of the MDO
Flow simulation and shape optimization for aircraft design
NASA Astrophysics Data System (ADS)
Kroll, Norbert; Gauger, Nicolas R.; Brezillon, Joel; Dwight, Richard; Fazzolari, Antonio; Vollmer, Daniel; Becker, Klaus; Barnewitz, Holger; Schulz, Volker; Hazra, Subhendu
2007-06-01
Within the framework of the German aerospace research program, the CFD project MEGADESIGN was initiated. The main goal of the project is the development of efficient numerical methods for shape design and optimization. In order to meet the requirements of industrial implementations a co-operative effort has been set up which involves the German aircraft industry, the DLR, several universities and some small enterprises specialized in numerical optimization. This paper outlines the planned activities within MEGADESIGN, the status at the beginning of the project and it presents some early results achieved in the project.
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.
Geometric constraints for shape and topology optimization in architectural design
NASA Astrophysics Data System (ADS)
Dapogny, Charles; Faure, Alexis; Michailidis, Georgios; Allaire, Grégoire; Couvelas, Agnes; Estevez, Rafael
2017-02-01
This work proposes a shape and topology optimization framework oriented towards conceptual architectural design. A particular emphasis is put on the possibility for the user to interfere on the optimization process by supplying information about his personal taste. More precisely, we formulate three novel constraints on the geometry of shapes; while the first two are mainly related to aesthetics, the third one may also be used to handle several fabrication issues that are of special interest in the device of civil structures. The common mathematical ingredient to all three models is the signed distance function to a domain, and its sensitivity analysis with respect to perturbations of this domain; in the present work, this material is extended to the case where the ambient space is equipped with an anisotropic metric tensor. Numerical examples are discussed in two and three space dimensions.
Geometric constraints for shape and topology optimization in architectural design
NASA Astrophysics Data System (ADS)
Dapogny, Charles; Faure, Alexis; Michailidis, Georgios; Allaire, Grégoire; Couvelas, Agnes; Estevez, Rafael
2017-06-01
This work proposes a shape and topology optimization framework oriented towards conceptual architectural design. A particular emphasis is put on the possibility for the user to interfere on the optimization process by supplying information about his personal taste. More precisely, we formulate three novel constraints on the geometry of shapes; while the first two are mainly related to aesthetics, the third one may also be used to handle several fabrication issues that are of special interest in the device of civil structures. The common mathematical ingredient to all three models is the signed distance function to a domain, and its sensitivity analysis with respect to perturbations of this domain; in the present work, this material is extended to the case where the ambient space is equipped with an anisotropic metric tensor. Numerical examples are discussed in two and three space dimensions.
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.
Optimizing implosion yields using rugby-shaped hohlraums
NASA Astrophysics Data System (ADS)
Park, Hye-Sook; Robey, H.; Amendt, P.; Philippe, F.; Casner, A.; Caillaud, T.; Bourgade, J.-L.; Landoas, O.; Li, C. K.; Petrasso, R.; Seguin, F.; Rosenberg, M.; Glebov, V. Yu.
2009-11-01
We present the first experimental results on optimizing capsule implosion experiments by using rugby-shaped hohlraums [1] on the Omega laser, University of Rochester. This campaign compared D2-filled capsule performance between standard cylindrical Au hohlraums and rugby-shaped hohlraums for demonstrating the energetics advantages of the rugby geometry. Not only did the rugby-shaped hohlraums show nearly 20% more x-ray drive energy over the cylindrical hohlraums, but also the high-performance design of the capsules provided nearly 20 times more DD neutrons than in any previous Omega hohlraum campaigns, thereby enabling use of neutron temporal diagnostics. Comparison with simulations on neutron burn histories, x-ray core imaging, backscattered laser light and radiation temperature are presented. [1] P. Amendt et al., Phys. Plasmas 15, 012702 (2008)
Recent developments in equivalent plate modeling for wing shape optimization
NASA Technical Reports Server (NTRS)
Livne, Eli
1993-01-01
A new technique for structural modeling of airplane wings is presented taking transverse shear effects into account. The kinematic assumptions of first order shear deformation plate theory in combination with numerical analysis based on simple polynomials which define geometry, construction and displacement approximations lead to analytical expressions for elements of the stiffness and mass matrices and load vector. Contributions from the cover skins, spar and rib caps and spar and rib webs are included as well as concentrated springs and concentrated masses. Limitations of current equivalent plate wing modeling techniques based on classical plate theory are discussed, and the improved accuracy of the new equivalent plate technique is demonstrated through comparison to finite element analysis and test results. Analytical derivatives of stiffness, mass and load terms with respect to wing shape lead to analytic sensitivities of displacements, stresses and natural modes with respect to planform shape and depth distribution. This makes the new capability an effective structural tool for wing shape optimization.
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.
Reinforcement learning solution for HJB equation arising in constrained optimal control problem.
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.
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.
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.
A Predictive Framework to Elucidate Venous Stenosis: CFD & Shape Optimization.
Javid Mahmoudzadeh Akherat, S M; Cassel, Kevin; Boghosian, Michael; Hammes, Mary; Coe, Fredric
2017-07-01
The surgical creation of vascular accesses for renal failure patients provides an abnormally high flow rate conduit in the patient's upper arm vasculature that facilitates the hemodialysis treatment. These vascular accesses, however, are very often associated with complications that lead to access failure and thrombotic incidents, mainly due to excessive neointimal hyperplasia (NH) and subsequently stenosis. Development of a framework to monitor and predict the evolution of the venous system post access creation can greatly contribute to maintaining access patency. Computational fluid dynamics (CFD) has been exploited to inspect the non-homeostatic wall shear stress (WSS) distribution that is speculated to trigger NH in the patient cohort under investigation. Thereafter, CFD in liaison with a gradient-free shape optimization method has been employed to analyze the deformation modes of the venous system enduring non-physiological hemodynamics. It is observed that the optimally evolved shapes and their corresponding hemodynamics strive to restore the homeostatic state of the venous system to a normal, pre-surgery condition. It is concluded that a CFD-shape optimization coupling that seeks to regulate the WSS back to a well-defined physiological WSS target range can accurately predict the mode of patient-specific access failure.
NASA Astrophysics Data System (ADS)
Zhao, Jie; Lu, Bing-Nan; Zhao, En-Guang; Zhou, Shan-Gui
2017-01-01
We develop a multidimensionally constrained relativistic Hartree-Bogoliubov (MDC-RHB) model in which the pairing correlations are taken into account by making the Bogoliubov transformation. In this model, the nuclear shape is assumed to be invariant under the reversion of x and y axes; i.e., the intrinsic symmetry group is V4 and all shape degrees of freedom βλ μ with even μ are included self-consistently. The RHB equation is solved in an axially deformed harmonic oscillator basis. A separable pairing force of finite range is adopted in the MDC-RHB model. The potential energy curves of neutron-rich even-even Zr isotopes are calculated with relativistic functionals DD-PC1 and PC-PK1 and possible tetrahedral shapes in the ground and isomeric states are investigated. The ground state shape of 110Zr is predicted to be tetrahedral with both functionals and so is that of 112Zr with the functional DD-PC1. The tetrahedral ground states are caused by large energy gaps around Z =40 and N =70 when β32 deformation is included. Although the inclusion of the β30 deformation can also reduce the energy around β20=0 and lead to minima with pear-like shapes for nuclei around 110Zr, these minima are unstable due to their shallowness.
Wing Rib Stress Analysis and Design Optimization Using Constrained Natural Element Method
NASA Astrophysics Data System (ADS)
Amine Bennaceur, Mohamed; Xu, Yuan-ming; Layachi, Hemza
2017-09-01
This paper demonstrates the applicability of a novel meshless method in solving problems related to aeronautical engineering, the constraint-natural element method is used to optimize a wing rib where it present several shape of cut-outs deals with the results findings we select the optimum design, we focus on the description and analysis of the constraint-natural element method and its application for simulating mechanical problems, the constraint natural element method is the alternative method for the finite element method where the shape functions is constructed on an extension of Voronoi diagram dual of Delaunay tessellation for non-convex domains.
NASA Astrophysics Data System (ADS)
Su, Yonggang; Tang, Chen; Chen, Xia; Li, Biyuan; Xu, Wenjun; Lei, Zhenkun
2017-01-01
We propose an image encryption scheme using chaotic phase masks and cascaded Fresnel transform holography based on a constrained optimization algorithm. In the proposed encryption scheme, the chaotic phase masks are generated by Henon map, and the initial conditions and parameters of Henon map serve as the main secret keys during the encryption and decryption process. With the help of multiple chaotic phase masks, the original image can be encrypted into the form of a hologram. The constrained optimization algorithm makes it possible to retrieve the original image from only single frame hologram. The use of chaotic phase masks makes the key management and transmission become very convenient. In addition, the geometric parameters of optical system serve as the additional keys, which can improve the security level of the proposed scheme. Comprehensive security analysis performed on the proposed encryption scheme demonstrates that the scheme has high resistance against various potential attacks. Moreover, the proposed encryption scheme can be used to encrypt video information. And simulations performed on a video in AVI format have also verified the feasibility of the scheme for video encryption.
NASA Astrophysics Data System (ADS)
Park, Chuljin; Telci, Ilker T.; Kim, Seong-Hee; Aral, Mustafa M.
2014-01-01
The problem of designing a water quality monitoring network for river systems is to find the optimal location of a finite number of monitoring devices that minimizes the expected detection time of a contaminant spill event while guaranteeing good detection reliability. When uncertainties in spill and rain events are considered, both the expected detection time and detection reliability need to be estimated by stochastic simulation. This problem is formulated as a stochastic discrete optimization via simulation (OvS) problem on the expected detection time with a stochastic constraint on detection reliability; and it is solved with an OvS algorithm combined with a recently proposed method called penalty function with memory (PFM). The performance of the algorithm is tested on the Altamaha River and compared with that of a genetic algorithm due to Telci, Nam, Guan and Aral (2009).
NASA Astrophysics Data System (ADS)
Martínez González, M. J.; Asensio Ramos, A.; Manso Sainz, R.; Corradi, R. L. M.; Leone, F.
2015-02-01
We carried out high-sensitivity spectro-polarimetric observations of the central star of the Red Rectangle protoplanetary nebula with the aim of constraining the mechanism that gives its biconical shape. The stellar light of the central binary system is linearly polarised since it is scattered on the dust particles of the nebula. Surprisingly, the linear polarisation in the continuum is aligned with one of the spikes of the biconical outflow. Also, the observed Balmer lines, as well as the Ca ii K lines, are polarised. These observational constraints are used to confirm or reject current theoretical models for the shaping mechanism of the Red Rectangle. We propose that the observed polarisation is not very likely to be generated by a uniform biconical stellar wind. Also, the hypothesis of a precessing jet does not completely match observations since it requires a larger aperture jet than for the nebula.
Viscous Aerodynamic Shape Optimization with Installed Propulsion Effects
NASA Technical Reports Server (NTRS)
Heath, Christopher M.; Seidel, Jonathan A.; Rallabhandi, Sriram K.
2017-01-01
Aerodynamic shape optimization is demonstrated to tailor the under-track pressure signature of a conceptual low-boom supersonic aircraft. Primarily, the optimization reduces nearfield pressure waveforms induced by propulsion integration effects. For computational efficiency, gradient-based optimization is used and coupled to the discrete adjoint formulation of the Reynolds-averaged Navier Stokes equations. The engine outer nacelle, nozzle, and vertical tail fairing are axi-symmetrically parameterized, while the horizontal tail is shaped using a wing-based parameterization. Overall, 48 design variables are coupled to the geometry and used to deform the outer mold line. During the design process, an inequality drag constraint is enforced to avoid major compromise in aerodynamic performance. Linear elastic mesh morphing is used to deform volume grids between design iterations. The optimization is performed at Mach 1.6 cruise, assuming standard day altitude conditions at 51,707-ft. To reduce uncertainty, a coupled thermodynamic engine cycle model is employed that captures installed inlet performance effects on engine operation.
Optimal shape of entrances for a frictionless nanochannel
NASA Astrophysics Data System (ADS)
Belin, Christophe; Joly, Laurent; Detcheverry, François
2016-09-01
The nearly frictionless flow of water in narrow carbon nanotubes is a genuine nanofluidic phenomenon with many prospects of applications in membrane technology. When inner dissipation is vanishing, the limiting factor to high flux lies in the viscous dissipation occurring at the tube mouth. As shown by Gravelle et al. [Gravelle, Joly, Detcheverry, Ybert, Cottin-Bizonne, and Bocquet, Proc. Natl. Acad. Sci. USA 110, 16367 (2013), 10.1073/pnas.1306447110], these so-called end effects can be reduced by adding a conical entrance. In this work, we take a step further and search for the optimal entrance shape. We use finite element calculations to compute the hydrodynamic resistance of a frictionless tube with superellipse-shaped entrances and propose an approximate analytical model. If perfect slip applies on its wall, an optimal entrance which is only 10 tube radii in length is sufficient to reduce end effects by an order of magnitude, a performance almost three times better than the optimal cone. In the case of partial slip, the resistance decreases with the entrance length before reaching a plateau at an optimal length controlled by liquid-solid slip. Our results are discussed in connection with biological and artificial systems.
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
Simultaneous beam sampling and aperture shape optimization for SPORT
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
Maximum-likelihood estimation optimizer for constrained, time-optimal satellite reorientation
NASA Astrophysics Data System (ADS)
Melton, Robert G.
2014-10-01
The Covariance Matrix Adaptation-Evolutionary Strategy (CMA-ES) method provides a high-quality estimate of the control solution for an unconstrained satellite reorientation problem, and rapid, useful guesses needed for high-fidelity methods that can solve time-optimal reorientation problems with multiple path constraints. The CMA-ES algorithm offers two significant advantages over heuristic methods such as Particle Swarm or Bacteria Foraging Optimisation: it builds an approximation to the covariance matrix for the cost function, and uses that to determine a direction of maximum likelihood for the search, reducing the chance of stagnation; and it achieves second-order, quasi-Newton convergence behaviour.
NASA Astrophysics Data System (ADS)
He, L.; Huang, G. H.; Lu, H. W.
2008-12-01
In this study a simulation-based fuzzy chance-constrained programming (SFCCP) model is developed based on possibility theory. The model is solved through an indirect search approach which integrates fuzzy simulation, artificial neural network and simulated annealing techniques. This approach has the advantages of: (1) handling simulation and optimization problems under uncertainty associated with fuzzy parameters, (2) providing additional information (i.e. possibility of constraint satisfaction) indicating that how likely one can believe the decision results, (3) alleviating computational burdens in the optimization process, and (4) reducing the chances of being trapped in local optima. The model is applied to a petroleum-contaminated aquifer located in western Canada for supporting the optimal design of groundwater remediation systems. The model solutions provide optimal groundwater pumping rates for the 3, 5 and 10 years of pumping schemes. It is observed that the uncertainty significantly affects the remediation strategies. To mitigate such impacts, additional cost is required either for increased pumping rate or for reinforced site characterization.
Multi-Constrained Optimal Control of 3D Robotic Arm Manipulators
NASA Astrophysics Data System (ADS)
Trivailo, Pavel M.; Fujii, Hironori A.; Kojima, Hirohisa; Watanabe, Takeo
This paper presents a generic method for optimal motion planning for three-dimensional 3-DOF multi-link robotic manipulators. We consider the operation of the manipulator systems, which involve constrained payload transportation/ capture/release, which is a subject to the minimization of the user-defined objective function, enabling for example minimization of the time of the transfer and/or actuation efforts. It should be stressed out that the task is solved in the presence of arbitrary multiple additional constraints. The solutions of the associated nonlinear differential equations of motion are obtained numerically using the direct transcription method. The direct method seeks to transform the continuous optimal control problem into a discrete mathematical programming problem, which in turn is solved using a non-linear programming algorithm. By discretizing the state and control variables at a series of nodes, the integration of the dynamical equations of motion is not required. The Chebyshev pseudospectral method, due to its high accuracy and fast computation times, was chosen as the direct optimization method to be employed to solve the problem. To illustrate the capabilities of the methodology, maneuvering of RRR 3D robot manipulators were considered in detail. Their optimal operations were simulated for the manipulators, binded to move their effectors along the specified 2D plane and 3D spherical and cylindrical surfaces (imitating for example, welding, tooling or scanning robots).
Study of hot tearing of A206 aluminum alloy using Instrumented Constrained T-shaped Casting method
Esfahani, M.R. Nasr; Niroumand, B.
2010-03-15
The hot tearing susceptibility of A206 aluminum alloy was investigated using Instrumented Constrained T-shaped Casting method and the effect of the casting temperature on hot tearing was studied. The Instrumented Constrained T-shaped Casting apparatus enabled real-time measurements of the contraction load developed in the casting and the temperature variations during solidification as a function of time. Critical temperatures and points during solidification of the castings were extracted from these data. The contraction load developed at the coalescence point of the castings was identified as a comparative criterion for predicting the hot tearing susceptibility of the alloys which could be utilized even when no visual tearing had occurred. The results showed that hot tearing susceptibility increased with the casting temperature. This was associated with reduced cooling rate, increased solute segregation and more localized hot spot formation at the T-junction area. Increase in the casting temperature also increased the grain size which may in turn have affected the initiation of the hot tears. The visual observations were further validated with radiographic tests.
NASA Astrophysics Data System (ADS)
Lester, Christopher G.
2007-10-01
Considering the cascade decay D → cC → cbB → cbaA in which D, C, B, A are massive particles and c, b, a are massless particles, we determine for the shape of the distribution of the invariant mass of the three massless particles mabc for the sub-set of decays in which the invariant mass mab of the last two particles in the chain is (optionally) constrained to lie inside an arbitrary interval, mab ∈ [mabcut min, mabcut max]. An example of an experimentally important distribution of this kind is the “mqll threshold”—which is the distribution of the combined invariant mass of the visible Standard Model particles radiated from the hypothesised decay of a squark to the lightest neutralino via successive two body decay: q˜ → qχ˜20 → qll˜ → qllχ˜10, in which the experimenter requires additionally that mll be greater than mllmax /√{ 2}. The location of the “foot” of this distribution is often used to constrain sparticle mass scales. The new results presented here permit the location of this foot to be better understood as the shape of the distribution is derived. The effects of varying the position of the mll cut(s) may now be seen more easily.
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 a similar 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 laminated 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 design optimization application consisting of nonlinear computational fluid dynamics, detailed computational structural mechanics, and a simple performance module.
Optimizing water permeability through the hourglass shape of aquaporins
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
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.
Multiobjective muffler shape optimization with hybrid acoustics modeling.
Airaksinen, Tuomas; Heikkola, Erkki
2011-09-01
This paper considers the combined use of a hybrid numerical method for the modeling of acoustic mufflers and a genetic algorithm for multiobjective optimization. The hybrid numerical method provides accurate modeling of sound propagation in uniform waveguides with non-uniform obstructions. It is based on coupling a wave based modal solution in the uniform sections of the waveguide to a finite element solution in the non-uniform component. Finite element method provides flexible modeling of complicated geometries, varying material parameters, and boundary conditions, while the wave based solution leads to accurate treatment of non-reflecting boundaries and straightforward computation of the transmission loss (TL) of the muffler. The goal of optimization is to maximize TL at multiple frequency ranges simultaneously by adjusting chosen shape parameters of the muffler. This task is formulated as a multiobjective optimization problem with the objectives depending on the solution of the simulation model. NSGA-II genetic algorithm is used for solving the multiobjective optimization problem. Genetic algorithms can be easily combined with different simulation methods, and they are not sensitive to the smoothness properties of the objective functions. Numerical experiments demonstrate the accuracy and feasibility of the model-based optimization method in muffler design.
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.
Saad, Sameh M I; Policova, Zdenka; Acosta, Edgar J; Neumann, A Wilhelm
2008-10-07
Collapse pressure of insoluble monolayers is a property determined from surface pressure/area isotherms. Such isotherms are commonly measured by a Langmuir film balance or a drop shape technique using a pendant drop constellation (ADSA-PD). Here, a different embodiment of a drop shape analysis, called axisymmetric drop shape analysis-constrained sessile drop (ADSA-CSD) is used as a film balance. It is shown that ADSA-CSD has certain advantages over conventional methods. The ability to measure very low surface tension values (e.g., <2 mJ/m2), an easier deposition procedure than in a pendant drop setup, and leak-proof design make the constrained sessile drop constellation a better choice than the pendant drop constellation in many situations. Results of compression isotherms are obtained on three different monolayers: octadecanol, dipalmitoyl-phosphatidyl-choline (DPPC), and dipalmitoyl-phosphatidyl-glycerol (DPPG). The collapse pressures are found to be reproducible and in agreement with previous methods. For example, the collapse pressure of DPPC is found to be 70.2 mJ/m2. Such values are not achievable with a pendant drop. The collapse pressure of octadecanol is found to be 61.3 mJ/m2, while that of DPPG is 59.0 mJ/m2. The physical reasons for these differences are discussed. The results also show a distinctive difference between the onset of collapse and the ultimate collapse pressure (ultimate strength) of these films. ADSA-CSD allows detailed study of this collapse region.
A robust approach to chance constrained optimal power flow with renewable generation
Lubin, Miles; Dvorkin, Yury; Backhaus, Scott N.
2016-09-01
Optimal Power Flow (OPF) dispatches controllable generation at minimum cost subject to operational constraints on generation and transmission assets. The uncertainty and variability of intermittent renewable generation is challenging current deterministic OPF approaches. Recent formulations of OPF use chance constraints to limit the risk from renewable generation uncertainty, however, these new approaches typically assume the probability distributions which characterize the uncertainty and variability are known exactly. We formulate a robust chance constrained (RCC) OPF that accounts for uncertainty in the parameters of these probability distributions by allowing them to be within an uncertainty set. The RCC OPF is solved using a cutting-plane algorithm that scales to large power systems. We demonstrate the RRC OPF on a modified model of the Bonneville Power Administration network, which includes 2209 buses and 176 controllable generators. In conclusion, deterministic, chance constrained (CC), and RCC OPF formulations are compared using several metrics including cost of generation, area control error, ramping of controllable generators, and occurrence of transmission line overloads as well as the respective computational performance.
A robust approach to chance constrained optimal power flow with renewable generation
Lubin, Miles; Dvorkin, Yury; Backhaus, Scott N.
2016-09-01
Optimal Power Flow (OPF) dispatches controllable generation at minimum cost subject to operational constraints on generation and transmission assets. The uncertainty and variability of intermittent renewable generation is challenging current deterministic OPF approaches. Recent formulations of OPF use chance constraints to limit the risk from renewable generation uncertainty, however, these new approaches typically assume the probability distributions which characterize the uncertainty and variability are known exactly. We formulate a robust chance constrained (RCC) OPF that accounts for uncertainty in the parameters of these probability distributions by allowing them to be within an uncertainty set. The RCC OPF is solved usingmore » a cutting-plane algorithm that scales to large power systems. We demonstrate the RRC OPF on a modified model of the Bonneville Power Administration network, which includes 2209 buses and 176 controllable generators. In conclusion, deterministic, chance constrained (CC), and RCC OPF formulations are compared using several metrics including cost of generation, area control error, ramping of controllable generators, and occurrence of transmission line overloads as well as the respective computational performance.« less
A robust approach to chance constrained optimal power flow with renewable generation
Lubin, Miles; Dvorkin, Yury; Backhaus, Scott N.
2016-09-01
Optimal Power Flow (OPF) dispatches controllable generation at minimum cost subject to operational constraints on generation and transmission assets. The uncertainty and variability of intermittent renewable generation is challenging current deterministic OPF approaches. Recent formulations of OPF use chance constraints to limit the risk from renewable generation uncertainty, however, these new approaches typically assume the probability distributions which characterize the uncertainty and variability are known exactly. We formulate a robust chance constrained (RCC) OPF that accounts for uncertainty in the parameters of these probability distributions by allowing them to be within an uncertainty set. The RCC OPF is solved using a cutting-plane algorithm that scales to large power systems. We demonstrate the RRC OPF on a modified model of the Bonneville Power Administration network, which includes 2209 buses and 176 controllable generators. In conclusion, deterministic, chance constrained (CC), and RCC OPF formulations are compared using several metrics including cost of generation, area control error, ramping of controllable generators, and occurrence of transmission line overloads as well as the respective computational performance.
A Variant of the Topkis-Veinott Method for Solving Inequality Constrained Optimization Problems
Birge, J. R.; Qi, L.; Wei, Z.
2000-05-15
In this paper we give a variant of the Topkis-Veinott method for solving inequality constrained optimization problems. This method uses a linearly constrained positive semidefinite quadratic problem to generate a feasible descent direction at each iteration. Under mild assumptions, the algorithm is shown to be globally convergent in the sense that every accumulation point of the sequence generated by the algorithm is a Fritz-John point of the problem. We introduce a Fritz-John (FJ) function, an FJ1 strong second-order sufficiency condition (FJ1-SSOSC), and an FJ2 strong second-order sufficiency condition (FJ2-SSOSC), and then show, without any constraint qualification (CQ), that (i) if an FJ point z satisfies the FJ1-SSOSC, then there exists a neighborhood N(z) of z such that, for any FJ point y element of N(z) {l_brace}z {r_brace} , f{sub 0}(y) {ne} f{sub 0}(z) , where f{sub 0} is the objective function of the problem; (ii) if an FJ point z satisfies the FJ2-SSOSC, then z is a strict local minimum of the problem. The result (i) implies that the entire iteration point sequence generated by the method converges to an FJ point. We also show that if the parameters are chosen large enough, a unit step length can be accepted by the proposed algorithm.
A subgradient approach for constrained binary optimization via quantum adiabatic evolution
NASA Astrophysics Data System (ADS)
Karimi, Sahar; Ronagh, Pooya
2017-08-01
Outer approximation method has been proposed for solving the Lagrangian dual of a constrained binary quadratic programming problem via quantum adiabatic evolution in the literature. This should be an efficient prescription for solving the Lagrangian dual problem in the presence of an ideally noise-free quantum adiabatic system. However, current implementations of quantum annealing systems demand methods that are efficient at handling possible sources of noise. In this paper, we consider a subgradient method for finding an optimal primal-dual pair for the Lagrangian dual of a constrained binary polynomial programming problem. We then study the quadratic stable set (QSS) problem as a case study. We see that this method applied to the QSS problem can be viewed as an instance-dependent penalty-term approach that avoids large penalty coefficients. Finally, we report our experimental results of using the D-Wave 2X quantum annealer and conclude that our approach helps this quantum processor to succeed more often in solving these problems compared to the usual penalty-term approaches.
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
Ma, Jun; Chen, Si-Lu; Kamaldin, Nazir; Teo, Chek Sing; Tay, Arthur; Mamun, Abdullah Al; Tan, Kok Kiong
2017-08-18
The biaxial gantry is widely used in many industrial processes that require high precision Cartesian motion. The conventional rigid-link version suffers from breaking down of joints if any de-synchronization between the two carriages occurs. To prevent above potential risk, a flexure-linked biaxial gantry is designed to allow a small rotation angle of the cross-arm. Nevertheless, the chattering of control signals and inappropriate design of the flexure joint will possibly induce resonant modes of the end-effector. Thus, in this work, the design requirements in terms of tracking accuracy, biaxial synchronization, and resonant mode suppression are achieved by integrated optimization of the stiffness of flexures and PID controller parameters for a class of point-to-point reference trajectories with same dynamics but different steps. From here, an H2 optimization problem with defined constraints is formulated, and an efficient iterative solver is proposed by hybridizing direct computation of constrained projection gradient and line search of optimal step. Comparative experimental results obtained on the testbed are presented to verify the effectiveness of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
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.
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
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.
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.
A shape constrained parametric active contour model for breast contour detection.
Lee, Juhun; Muralidhar, Gautam S; Reece, Gregory P; Markey, Mia K
2012-01-01
Quantitative measures of breast morphology can help a breast cancer survivor to understand outcomes of reconstructive surgeries. One bottleneck of quantifying breast morphology is that there are only a few reliable automation algorithms for detecting the breast contour. This study proposes a novel approach for detecting the breast contour, which is based on a parametric active contour model. In addition to employing the traditional parametric active contour model, the proposed approach enforces a mathematical shape constraint based on the catenary curve, which has been previously shown to capture the overall shape of the breast contour reliably. The mathematical shape constraint regulates the evolution of the active contour and helps the contour evolve towards the breast, while minimizing the undesired effects of other structures such as, the nipple/areola and scars. The efficacy of the proposed approach was evaluated on anterior posterior photographs of women who underwent or were scheduled for breast reconstruction surgery including autologous tissue reconstruction. The proposed algorithm shows promising results for detecting the breast contour.
Analysis of Constrained Optimization Variants of the Map-Seeking Circuit Algorithm
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.
Sdika, Michaël
2008-02-01
This paper presents a new nonrigid monomodality image registration algorithm based on B-splines. The deformation is described by a cubic B-spline field and found by minimizing the energy between a reference image and a deformed version of a floating image. To penalize noninvertible transformation, we propose two different constraints on the Jacobian of the transformation and its derivatives. The problem is modeled by an inequality constrained optimization problem which is efficiently solved by a combination of the multipliers method and the L-BFGS algorithm to handle the large number of variables and constraints of the registration of 3-D images. Numerical experiments are presented on magnetic resonance images using synthetic deformations and atlas based segmentation.
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.
Three-dimensional aerodynamic shape optimization of supersonic delta wings
NASA Technical Reports Server (NTRS)
Burgreen, Greg W.; Baysal, Oktay
1994-01-01
A recently developed three-dimensional aerodynamic shape optimization procedure AeSOP(sub 3D) is described. This procedure incorporates some of the most promising concepts from the area of computational aerodynamic analysis and design, specifically, discrete sensitivity analysis, a fully implicit 3D Computational Fluid Dynamics (CFD) methodology, and 3D Bezier-Bernstein surface parameterizations. The new procedure is demonstrated in the preliminary design of supersonic delta wings. Starting from a symmetric clipped delta wing geometry, a Mach 1.62 asymmetric delta wing and two Mach 1. 5 cranked delta wings were designed subject to various aerodynamic and geometric constraints.
Optimization in nanocoated D-shaped optical fiber sensors.
Del Villar, Ignacio; Zubiate, Pablo; Zamarreño, Carlos R; Arregui, Francisco J; Matias, Ignacio R
2017-05-15
Nanocoated D-shaped optical fibers have been proven as effective sensors. Here, we show that the full width at half minimum (FWHM) of lossy mode resonance can be reduced by optimizing the nanocoating width, thickness and refractive index. As a counterpart, several resonances are observed in the optical spectrum for specific conditions. These resonances are caused by multiple modes guided in the nanocoating. By optimizing the width of the coating and the imaginary part of its refractive index, it is possible to isolate one of these resonances, which allows one to reduce the full width at half minimum of the device and, hence, to increase the figure of merit. Moreover, it is even possible to avoid the need of a polarizer by designing a device where the resonance bands for TE and TM polarization are centered at the same wavelength. This is interesting for the development of optical filters and sensors with a high figure of merit.
Optimal shape design of aerodynamic configurations: A Newton-Krylov approach
NASA Astrophysics Data System (ADS)
Nemec, Marian
Optimal shape design of aerodynamic configurations is a challenging problem due to the nonlinear effects of complex flow features such as shock waves, boundary layers, and separation. A Newton-Krylov algorithm is presented for aerodynamic design using gradient-based numerical optimization. The flow is governed by the two-dimensional compressible Navier-Stokes equations in conjunction with a one-equation turbulence model, which are discretized on multi-block structured grids. The discrete-adjoint method is applied to compute the objective function gradient. The adjoint equation is solved using the preconditioned generalized minimal residual (GMRES) method. A novel preconditioner is introduced, and together with a complete differentiation of the discretized Navier-Stokes and turbulence model equations, this results in an accurate and efficient evaluation of the gradient. The gradient is obtained in just one-fifth to one-half of the time required to converge a flow solution. Furthermore, fast flow solutions are obtained using the same preconditioned GMRES method in conjunction with an inexact-Newton approach. Optimization constraints are enforced through a penalty formulation, and the resulting unconstrained problem is solved via a quasi-Newton method. The performance of the new algorithm is demonstrated for several design examples that include lift enhancement, where the optimal position of a flap is determined within a high-lift configuration, lift-constrained drag minimization at multiple transonic operating points, and the computation of a Pareto front based on competing objectives. In all examples, the gradient is reduced by several orders of magnitude, indicating that a local minimum has been obtained. Overall, the results show that the new algorithm is among the fastest presently available for aerodynamic shape optimization and provides an effective approach for practical aerodynamic design.
A constrained theory for single crystal shape memory wires with application to restrained recovery
NASA Astrophysics Data System (ADS)
Rizzoni, Raffaella
2011-07-01
The theory of thin wires developed in Dret and Meunier (Comptes Rendus de l'Académie des Sciences. Série I. Mathématique 337:143-147, 2003) is adapted to phase-transforming materials with large elastic moduli in the sense discussed in James and Rizzoni (J Elast 59:399-436, 2000). The result is a one-dimensional constitutive model for shape memory wires, characterized by a small number of material constants. The model is used to analyze self-accommodated and detwinned microstructures and to study superelasticity. It also turns out that the model successfully reproduces the behavior of shape memory wires in experiments of restrained recovery (Tsoi et al. in Mater Sci Eng A 368:299-310, 2004; Tsoi in 50:3535-3544, 2002; S̆ittner et al. in Mater Sci Eng A 286:298-311, 2000; vokoun in Smart Mater Struct 12:680-685, 2003; Zheng and Cui in Intermetallics 12:1305-1309, 2004; Zheng et al. in J Mater Sci Technol 20(4):390-394, 2004). In particular, the model is able to predict the shift to higher transformation temperatures on heating. The model also captures the effect of prestraining on the evolution of the recovery stress and of the martensite volume fraction.
Performance Trades Study for Robust Airfoil Shape Optimization
NASA Technical Reports Server (NTRS)
Li, Wu; Padula, Sharon
2003-01-01
From time to time, existing aircraft need to be redesigned for new missions with modified operating conditions such as required lift or cruise speed. This research is motivated by the needs of conceptual and preliminary design teams for smooth airfoil shapes that are similar to the baseline design but have improved drag performance over a range of flight conditions. The proposed modified profile optimization method (MPOM) modifies a large number of design variables to search for nonintuitive performance improvements, while avoiding off-design performance degradation. Given a good initial design, the MPOM generates fairly smooth airfoils that are better than the baseline without making drastic shape changes. Moreover, the MPOM allows users to gain valuable information by exploring performance trades over various design conditions. Four simulation cases of airfoil optimization in transonic viscous ow are included to demonstrate the usefulness of the MPOM as a performance trades study tool. Simulation results are obtained by solving fully turbulent Navier-Stokes equations and the corresponding discrete adjoint equations using an unstructured grid computational fluid dynamics code FUN2D.
Thinking Inside the Box: The Optimal Filling of Shapes
NASA Astrophysics Data System (ADS)
Phillips, Carolyn; Andersaon, Joshua; Huber, Greg; Glotzer, Sharon
2013-03-01
We introduce a new spatial partitioning problem called filling, which combines aspects of traditional packing and covering problems from mathematical physics. Filling involves the optimal placement of overlapping objects lying entirely inside an arbitrary shape so as to cover the most interior volume. In n-dimensional space, if the objects are polydisperse n-balls, we show that solutions correspond to sets of maximal n-balls. We investigate the mathematical space of filling solutions and provide a heuristic for finding the optimal filling solutions for polygons filled with disks of varying radii. We consider the properties of ideal distributions of N disks as N approaches infinity. We discuss applications of filling to such problems as tumor irradiation, designing wave fronts and wireless networks, minimal information representations of complex shapes, and molecular modeling of nanoparticles and colloids. S. C. G. and C. L. P. were supported by the DOE under Grant No. DE-FG02-02ER46000. S. C. G. and J. A. A. were supported by the DOD/AD(R&E) under Grant No. N00244-09-1-0062.
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.
NASA Astrophysics Data System (ADS)
Wang, Yingjun; Benson, David J.
2016-12-01
In this paper, an approach based on the fast point-in-polygon (PIP) algorithm and trimmed elements is proposed for isogeometric topology optimization (TO) with arbitrary geometric constraints. The isogeometric parameterized level-set-based TO method, which directly uses the non-uniform rational basis splines (NURBS) for both level set function (LSF) parameterization and objective function calculation, provides higher accuracy and efficiency than previous methods. The integration of trimmed elements is completed by the efficient quadrature rule that can design the quadrature points and weights for arbitrary geometric shape. Numerical examples demonstrate the efficiency and flexibility of the method.
Smoothing neural network for constrained non-Lipschitz optimization with applications.
Bian, Wei; Chen, Xiaojun
2012-03-01
In this paper, a smoothing neural network (SNN) is proposed for a class of constrained non-Lipschitz optimization problems, where the objective function is the sum of a nonsmooth, nonconvex function, and a non-Lipschitz function, and the feasible set is a closed convex subset of . Using the smoothing approximate techniques, the proposed neural network is modeled by a differential equation, which can be implemented easily. Under the level bounded condition on the objective function in the feasible set, we prove the global existence and uniform boundedness of the solutions of the SNN with any initial point in the feasible set. The uniqueness of the solution of the SNN is provided under the Lipschitz property of smoothing functions. We show that any accumulation point of the solutions of the SNN is a stationary point of the optimization problem. Numerical results including image restoration, blind source separation, variable selection, and minimizing condition number are presented to illustrate the theoretical results and show the efficiency of the SNN. Comparisons with some existing algorithms show the advantages of the SNN.
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.
Ares-I Bending Filter Design using a Constrained Optimization Approach
NASA Technical Reports Server (NTRS)
Hall, Charles; Jang, Jiann-Woei; Hall, Robert; Bedrossian, Nazareth
2008-01-01
The Ares-I launch vehicle represents a challenging flex-body structural environment for control system design. Software filtering of the inertial sensor output is required to ensure adequate stable response to guidance commands while minimizing trajectory deviations. This paper presents a design methodology employing numerical optimization to develop the Ares-I bending filters. The design objectives include attitude tracking accuracy and robust stability with respect to rigid body dynamics, propellant slosh, and flex. Under the assumption that the Ares-I time-varying dynamics and control system can be frozen over a short period of time, the bending filters are designed to stabilize all the selected frozen-time launch control systems in the presence of parameter uncertainty. To ensure adequate response to guidance command, step response specifications are introduced as constraints in the optimization problem. Imposing these constrains minimizes performance degradation caused by the addition of the bending filters. The first stage bending filter design achieves stability by adding lag to the first structural frequency to phase stabilize the first flex mode while gain stabilizing the higher modes. The upper stage bending filter design gain stabilizes all the flex bending modes. The bending filter designs provided here have been demonstrated to provide stable first and second stage control systems in both Draper Ares Stability Analysis Tool (ASAT) and the MSFC MAVERIC 6DOF nonlinear time domain simulation.
High-Fidelity Aerodynamic Shape Optimization for Natural Laminar Flow
NASA Astrophysics Data System (ADS)
Rashad, Ramy
To ensure the long-term sustainability of aviation, serious effort is underway to mitigate the escalating economic, environmental, and social concerns of the industry. Significant improvement to the energy efficiency of air transportation is required through the research and development of advanced and unconventional airframe and engine technologies. In the quest to reduce airframe drag, this thesis is concerned with the development and demonstration of an effective design tool for improving the aerodynamic efficiency of subsonic and transonic airfoils. The objective is to advance the state-of-the-art in high-fidelity aerodynamic shape optimization by incorporating and exploiting the phenomenon of laminar-turbulent transition in an efficient manner. A framework for the design and optimization of Natural Laminar Flow (NLF) airfoils is developed and demonstrated with transition prediction capable of accounting for the effects of Reynolds number, freestream turbulence intensity, Mach number, and pressure gradients. First, a two-dimensional Reynolds-averaged Navier-Stokes (RANS) flow solver has been extended to incorporate an iterative laminar-turbulent transition prediction methodology. The natural transition locations due to Tollmien-Schlichting instabilities are predicted using the simplified eN envelope method of Drela and Giles or, alternatively, the compressible form of the Arnal-Habiballah-Delcourt criterion. The boundary-layer properties are obtained directly from the Navier-Stokes flow solution, and the transition to turbulent flow is modeled using an intermittency function in conjunction with the Spalart-Allmaras turbulence model. The RANS solver is subsequently employed in a gradient-based sequential quadratic programming shape optimization framework. The laminar-turbulent transition criteria are tightly coupled into the objective and gradient evaluations. The gradients are obtained using a new augmented discrete-adjoint formulation for non-local transition
Regulating the vibratory motion of beams using shape optimization
NASA Astrophysics Data System (ADS)
Katsikadelis, J. T.; Tsiatas, G. C.
2006-04-01
In this paper, shape optimization is used to regulate the vibrations of an Euler-Bernoulli beam having constant material volume. This is achieved by varying appropriately the beam cross-section and thus its stiffness and mass properties along its length, so that the beam vibrates with its minimum, maximum or a prescribed eigenfrequency as well as with the minimum or maximum difference between two successive eigenfrequencies. The problem is reduced to a nonlinear optimization problem under equality and inequality constraints as well as specified lower and upper bounds. The evaluation of the objective function requires the solution of the free vibration problem of a beam with variable mass and stiffness properties. This problem is solved using the analog equation method (AEM) for hyperbolic differential equations with variable coefficients. Besides its accuracy, this method overcomes the shortcoming of a FEM solution, which would require resizing of the elements and re-computation of their stiffness and mass properties during the optimization process. Certain example problems are presented, which illustrate the method and demonstrate its efficiency.
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
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
NASA Astrophysics Data System (ADS)
Nath, Bijoyendra
A methodology for aerodynamic shape optimization on two-dimensional unstructured grids using Euler equations is presented. The sensitivity derivatives are obtained using the discrete adjoint formulation. The Euler equations are solved using a fully implicit, upwind, cell-vertex, median-dual finite volume scheme. Roe's upwind flux-difference-splitting scheme is used to determine the inviscid fluxes. To enable discontinuities to be captured without oscillations, limiters are used at the reconstruction stage. The derivation of the accurate discretization of the flux Jacobians due to the conserved variables and the entire mesh required for the costate equation is developed and its efficient accumulation algorithm on an edge-based loop is implemented and documented. Exact linearization of Roe's approximate Riemann solver is incorporated into the aerodynamic analysis as well as the sensitivity analysis. Higher-order discretization is achieved by including all distance-one and -two terms due to the reconstruction and the limiter, although the limiter is not linearized. Two-dimensional body conforming grid movement strategy and grid sensitivity are obtained by considering the grid to be a system of interconnected springs. Arbitrary airfoil geometries are obtained using an algorithm for generalized von Mises airfoils with finite trailing edges. An incremental iterative formulation is used to solve the large sparse linear systems of equations obtained from the sensitivity analysis. The discrete linear systems obtained from the equations governing the flow and those from the sensitivity analysis are solved iteratively using the preconditioned GMRES (Generalized Minimum Residual) algorithm. For the optimization process, a constrained nonlinear programming package which uses a sequential quadratic programming algorithm is used. This study presents the process of analytically obtaining the exact discrete sensitivity derivatives and computationally cost-effective algorithms to
Optimized conical shaped charge design using the SCAP (Shaped Charge Analysis Program) code
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.
Dynamics of asteroid family halos constrained by spin/shape models
NASA Astrophysics Data System (ADS)
Broz, Miroslav
2016-10-01
A number of asteroid families cannot be identified solely on the basis of the Hierarchical Clustering Method (HCM), because they have additional 'former' members in the surroundings which constitute a so called halo (e.g. Broz & Morbidelli 2013). They are usually mixed up with the background population which has to be taken into account too.Luckily, new photometric observations allow to derive new spin/shape models, which serve as independent constraints for dynamical models. For example, a recent census of the Eos family shows 43 core and 27 halo asteroids (including background) with known spin orientations.To this point, we present a complex spin-orbital model which includes full N-body dynamics and consequently accounts for all mean-motion, secular, or three-body gravitational resonances, the Yarkovsky drift, YORP effect, collisional reorientations and also spin-orbital interactions. These are especially important for the Koronis family. In this project, we make use of data from the DAMIT database and ProjectSoft Blue Eye 600 observatory.
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
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
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.
Shape optimized headers and methods of manufacture thereof
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.
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).
Shaped optimal control pulses for increased excitation bandwidth in EPR.
Spindler, Philipp E; Zhang, Yun; Endeward, Burkhard; Gershernzon, Naum; Skinner, Thomas E; Glaser, Steffen J; Prisner, Thomas F
2012-05-01
A 1 ns resolution pulse shaping unit has been developed for pulsed EPR spectroscopy to enable 14-bit amplitude and phase modulation. Shaped broadband excitation pulses designed using optimal control theory (OCT) have been tested with this device at X-band frequency (9 GHz). FT-EPR experiments on organic radicals in solution have been performed with the new pulses, designed for uniform excitation over a significantly increased bandwidth compared to a classical rectangular π/2 pulse of the same B(1) amplitude. The concept of a dead-time compensated prefocused pulse has been introduced to EPR with a self-refocusing of 200 ns after the end of the pulse. Echo-like refocused signals have been recorded and compared to the performance of a classical Hahn-echo sequence. The impulse response function of the microwave setup has been measured and incorporated into the algorithm for designing OCT pulses, resulting in further significant improvements in performance. Experimental limitations and potential new applications of OCT pulses in EPR spectroscopy will be discussed.
Shape-Optimized Photoacoustic Cell: Numerical Consolidation and Experimental Confirmation
NASA Astrophysics Data System (ADS)
Wolff, M.; Kost, B.; Baumann, B.
2012-11-01
The signal of photoacoustic sensors depends considerably on the shape of the sample cell. Taking advantage of acoustical resonances results in a signal boost and enables highly sensitive analyzers with low detection limits. A numerical optimization of the cell geometry has been performed with the objective being maximization of the photoacoustic signal. The resulting shape consists of a thin central pipe with flaring ends to both sides and is called an "hourglass cell." In this article, the stability of the results and the limitations of the model are investigated. Influences of the absorbing molecule concentration and of the matrix gas are numerically examined. The results predict a stable signal increase of 32% to 36% compared to the well-established H cell and, thus, consolidate the model. A dependence on the absorption coefficient is not observed. The influence of matrix gas parameters (density, compressibility, speed of sound, specific heat, etc.) is small. Furthermore, an hourglass cell was manufactured and its performance for the detection of nitric oxide was compared to an H cell. These investigations demonstrate enhancements factors of 13.3% for the signal, 14.7% for the resonance quality, and 14.8% for the signal-to-noise ratio and adequately confirm the simulations.
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
Analysis and optimization of bellows with general shape
Koh, B.K.; Park, G.J.
1998-11-01
Bellows are commonly used in piping systems to absorb expansion and contraction in order to reduce stress. They have widespread applications which include industrial and chemical plants, fossil and nuclear power systems, heating and cooling systems, and vehicle exhaust systems. A bellows is a component in piping systems which absorbs mechanical deformation with flexibility. Its geometry is an axially symmetric shell which consists of two toroidal shells and one annular plate or conical shell. In order to analyze the bellows, this study presents the finite element analysis using a conical frustum shell element. A finite element analysis program is developed to analyze various bellows. The formula for calculating the natural frequency of bellows is made by the simple beam theory. The formula for fatigue life is also derived by experiments. A shape optimal design problem is formulated using multiple objective optimization. The multiple objective functions are transformed to a scalar function with weighting factors. The stiffness, strength, and specified stiffness are considered as the multiple objective function. The formulation has inequality constraints imposed on the natural frequencies, the fatigue limit, and the manufacturing conditions. Geometric parameters of bellows are the design variables. The recursive quadratic programming algorithm is utilized to solve the problem.
On the optimal identification of tag sets in time-constrained RFID configurations.
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.
Corrective Control to Handle Forecast Uncertainty: A Chance Constrained Optimal Power Flow
Roald, Line; Misra, Sidhant; Krause, Thilo; ...
2016-08-25
Higher shares of electricity generation from renewable energy sources and market liberalization is increasing uncertainty in power systems operation. At the same time, operation is becoming more flexible with improved control systems and new technology such as phase shifting transformers (PSTs) and high voltage direct current connections (HVDC). Previous studies have shown that the use of corrective control in response to outages contributes to a reduction in operating cost, while maintaining N-1 security. In this work, we propose a method to extend the use of corrective control of PSTs and HVDCs to react to uncertainty. We characterize the uncertainty asmore » continuous random variables, and define the corrective control actions through affine control policies. This allows us to efficiently model control reactions to a large number of uncertainty sources. The control policies are then included in a chance constrained optimal power flow formulation, which guarantees that the system constraints are enforced with a desired probability. Lastly, by applying an analytical reformulation of the chance constraints, we obtain a second-order cone problem for which we develop an efficient solution algorithm. In a case study for the IEEE 118 bus system, we show that corrective control for uncertainty leads to a decrease in operational cost, while maintaining system security. Further, we demonstrate the scalability of the method by solving the problem for the IEEE 300 bus and the Polish system test cases.« less
Corrective Control to Handle Forecast Uncertainty: A Chance Constrained Optimal Power Flow
Roald, Line; Misra, Sidhant; Krause, Thilo; Andersson, Goran
2016-08-25
Higher shares of electricity generation from renewable energy sources and market liberalization is increasing uncertainty in power systems operation. At the same time, operation is becoming more flexible with improved control systems and new technology such as phase shifting transformers (PSTs) and high voltage direct current connections (HVDC). Previous studies have shown that the use of corrective control in response to outages contributes to a reduction in operating cost, while maintaining N-1 security. In this work, we propose a method to extend the use of corrective control of PSTs and HVDCs to react to uncertainty. We characterize the uncertainty as continuous random variables, and define the corrective control actions through affine control policies. This allows us to efficiently model control reactions to a large number of uncertainty sources. The control policies are then included in a chance constrained optimal power flow formulation, which guarantees that the system constraints are enforced with a desired probability. Lastly, by applying an analytical reformulation of the chance constraints, we obtain a second-order cone problem for which we develop an efficient solution algorithm. In a case study for the IEEE 118 bus system, we show that corrective control for uncertainty leads to a decrease in operational cost, while maintaining system security. Further, we demonstrate the scalability of the method by solving the problem for the IEEE 300 bus and the Polish system test cases.
On the Optimal Identification of Tag Sets in Time-Constrained RFID Configurations
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
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
Proposal of a new plane shape of an opera house-optimized by genetic algorithms
NASA Astrophysics Data System (ADS)
Hotehama, Takuya; Ando, Yoichi; Tani, Akinori; Kawamura, Hiroshi
2004-05-01
The horseshoe-shaped theater has been the main shape from historical circumstances. However, from acoustical points of view, the rationality of the peculiar plane shape is not yet verified more than historical refinement. In this study, in order to make the theater shape more acoustically excellent, optimization for temporal and spatial factors in the theory of the subjective preference was made using genetic algorithms (GAs) by operating the positions of side walls. Results reconfirm that the plane shape of the optimized theater is a leaf shape, which has been verified to be acoustically rational in a concert hall. And, further possible shapes are also offered.
Lemanski, Natalie J; Fefferman, Nina H
2017-06-01
Honeybees are an excellent model system for examining how trade-offs shape reproductive timing in organisms with seasonal environments. Honeybee colonies reproduce two ways: producing swarms comprising a queen and thousands of workers or producing males (drones). There is an energetic trade-off between producing workers, which contribute to colony growth, and drones, which contribute only to reproduction. The timing of drone production therefore determines both the drones' likelihood of mating and when colonies reach sufficient size to swarm. Using a linear programming model, we ask when a colony should produce drones and swarms to maximize reproductive success. We find the optimal behavior for each colony is to produce all drones prior to swarming, an impossible solution on a population scale because queens and drones would never co-occur. Reproductive timing is therefore not solely determined by energetic trade-offs but by the game theoretic problem of coordinating the production of reproductives among colonies.
Li Kaile; Ma Lijun
2005-10-15
We developed a source blocking optimization algorithm for Gamma Knife radiosurgery, which is based on tracking individual source contributions to arbitrarily shaped target and critical structure volumes. A scalar objective function and a direct search algorithm were used to produce near real-time calculation results. The algorithm allows the user to set and vary the total number of plugs for each shot to limit the total beam-on time. We implemented and tested the algorithm for several multiple-isocenter Gamma Knife cases. It was found that the use of limited number of plugs significantly lowered the integral dose to the critical structures such as an optical chiasm in pituitary adenoma cases. The main effect of the source blocking is the faster dose falloff in the junction area between the target and the critical structure. In summary, we demonstrated a useful source-plugging algorithm for improving complex multi-isocenter Gamma Knife treatment planning cases.
Yen, Hong-Hsu
2009-01-01
In wireless sensor networks, data aggregation routing could reduce the number of data transmissions so as to achieve energy efficient transmission. However, data aggregation introduces data retransmission that is caused by co-channel interference from neighboring sensor nodes. This kind of co-channel interference could result in extra energy consumption and significant latency from retransmission. This will jeopardize the benefits of data aggregation. One possible solution to circumvent data retransmission caused by co-channel interference is to assign different channels to every sensor node that is within each other's interference range on the data aggregation tree. By associating each radio with a different channel, a sensor node could receive data from all the children nodes on the data aggregation tree simultaneously. This could reduce the latency from the data source nodes back to the sink so as to meet the user's delay QoS. Since the number of radios on each sensor node and the number of non-overlapping channels are all limited resources in wireless sensor networks, a challenging question here is to minimize the total transmission cost under limited number of non-overlapping channels in multi-radio wireless sensor networks. This channel constrained data aggregation routing problem in multi-radio wireless sensor networks is an NP-hard problem. I first model this problem as a mixed integer and linear programming problem where the objective is to minimize the total transmission subject to the data aggregation routing, channel and radio resources constraints. The solution approach is based on the Lagrangean relaxation technique to relax some constraints into the objective function and then to derive a set of independent subproblems. By optimally solving these subproblems, it can not only calculate the lower bound of the original primal problem but also provide useful information to get the primal feasible solutions. By incorporating these Lagrangean multipliers
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
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
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.
NASA Astrophysics Data System (ADS)
Benjamini, Dan; Basser, Peter J.
2016-10-01
Measuring multidimensional (e.g., 2D) relaxation spectra in NMR and MRI clinical applications is a holy grail of the porous media and biomedical MR communities. The main bottleneck is the inversion of Fredholm integrals of the first kind, an ill-conditioned problem requiring large amounts of data to stabilize a solution. We suggest a novel experimental design and processing framework to accelerate and improve the reconstruction of such 2D spectra that uses a priori information from the 1D projections of spectra, or marginal distributions. These 1D marginal distributions provide powerful constraints when 2D spectra are reconstructed, and their estimation requires an order of magnitude less data than a conventional 2D approach. This marginal distributions constrained optimization (MADCO) methodology is demonstrated here with a polyvinylpyrrolidone-water phantom that has 3 distinct peaks in the 2D D-T1 space. The stability, sensitivity to experimental parameters, and accuracy of this new approach are compared with conventional methods by serially subsampling the full data set. While the conventional, unconstrained approach performed poorly, the new method had proven to be highly accurate and robust, only requiring a fraction of the data. Additionally, synthetic T1 -T2 data are presented to explore the effects of noise on the estimations, and the performance of the proposed method with a smooth and realistic 2D spectrum. The proposed framework is quite general and can also be used with a variety of 2D MRI experiments (D-T2,T1 -T2, D -D, etc.), making these potentially feasible for preclinical and even clinical applications for the first time.
NASA Astrophysics Data System (ADS)
Bakir, Pelin Gundes; Reynders, Edwin; De Roeck, Guido
2007-08-01
The use of changes in dynamic system characteristics to detect damage has received considerable attention during the last years. Within this context, FE model updating technique, which belongs to the class of inverse problems in classical mechanics, is used to detect, locate and quantify damage. In this study, a sensitivity-based finite element (FE) model updating scheme using a trust region algorithm is developed and implemented in a complex structure. A damage scenario is applied on the structure in which the stiffness values of the beam elements close to the beam-column joints are decreased by stiffness reduction factors. A worst case and complex damage pattern is assumed such that the stiffnesses of adjacent elements are decreased by substantially different stiffness reduction factors. The objective of the model updating is to minimize the differences between the eigenfrequency and eigenmodes residuals. The updating parameters of the structure are the stiffness reduction factors. The changes of these parameters are determined iteratively by solving a nonlinear constrained optimization problem. The FE model updating algorithm is also tested in the presence of two levels of noise in simulated measurements. In all three cases, the updated MAC values are above 99% and the relative eigenfrequency differences improve substantially after model updating. In cases without noise and with moderate levels of noise; detection, localization and quantification of damage are successfully accomplished. In the case with substantially noisy measurements, detection and localization of damage are successfully realized. Damage quantification is also promising in the presence of high noise as the algorithm can still predict 18 out of 24 damage parameters relatively accurately in that case.
Bassen, David M; Vilkhovoy, Michael; Minot, Mason; Butcher, Jonathan T; Varner, Jeffrey D
2017-01-25
Ensemble modeling is a promising approach for obtaining robust predictions and coarse grained population behavior in deterministic mathematical models. Ensemble approaches address model uncertainty by using parameter or model families instead of single best-fit parameters or fixed model structures. Parameter ensembles can be selected based upon simulation error, along with other criteria such as diversity or steady-state performance. Simulations using parameter ensembles can estimate confidence intervals on model variables, and robustly constrain model predictions, despite having many poorly constrained parameters. In this software note, we present a multiobjective based technique to estimate parameter or models ensembles, the Pareto Optimal Ensemble Technique in the Julia programming language (JuPOETs). JuPOETs integrates simulated annealing with Pareto optimality to estimate ensembles on or near the optimal tradeoff surface between competing training objectives. We demonstrate JuPOETs on a suite of multiobjective problems, including test functions with parameter bounds and system constraints as well as for the identification of a proof-of-concept biochemical model with four conflicting training objectives. JuPOETs identified optimal or near optimal solutions approximately six-fold faster than a corresponding implementation in Octave for the suite of test functions. For the proof-of-concept biochemical model, JuPOETs produced an ensemble of parameters that gave both the mean of the training data for conflicting data sets, while simultaneously estimating parameter sets that performed well on each of the individual objective functions. JuPOETs is a promising approach for the estimation of parameter and model ensembles using multiobjective optimization. JuPOETs can be adapted to solve many problem types, including mixed binary and continuous variable types, bilevel optimization problems and constrained problems without altering the base algorithm. JuPOETs is open
NASA Astrophysics Data System (ADS)
Jaouadi, A.; Barrez, E.; Justum, Y.; Desouter-Lecomte, M.
2013-07-01
We simulate the implementation of a 3-qubit quantum Fourier transform gate in the hyperfine levels of ultracold polar alkali dimers in their first two lowest rotational levels. The chosen dimer is 41K87Rb supposed to be trapped in an optical lattice. The hyperfine levels are split by a static magnetic field. The pulses operating in the microwave domain are obtained by optimal control theory. We revisit the problem of phase control in information processing. We compare the efficiency of two optimal fields. The first one is obtained from a functional based on the average of the transition probabilities for each computational basis state but constrained by a supplementary transformation to enforce phase alignment. The second is obtained from a functional constructed on the phase sensitive fidelity involving the sum of the transition amplitudes without any supplementary constrain.
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.
Polak, E.
1994-12-31
Unlike the situation with most other problems, the concept of a solution to an optimization problem is not unique, since it includes global solutions, local solutions, and stationary points. Earlier definitions of a consistent approximation to an optimization problem were in terms of properties that ensured that the global minimizers of the approximating problems (as well as uniformly strict local minimizers) converge only to global minimizers (local minimizers) of the original problems. Our definition of a consistent approximation addresses the properties not only of global and local solutions of the approximating problems, but also of their stationary points. Hence we always consider a pair, consisting of an optimization problem and its optimality function, (P, {theta}), with the zeros of the optimality function being the stationary points of P. We define consistency of approximating problem-optimality function pairs, (P{sub N}, {theta}{sub N}) to (P, {theta}), in terms of the epigraphical convergence of the P{sub N} to P, and the hypographical convergence of the optimality functions {theta}{sub N} to {theta}. As a companion to the characterization of consistent approximations, we will present two types of {open_quotes}diagonalization{close_quotes} techniques for using consistent approximations and {open_quotes}hot starts{close_quotes} in obtaining an approximate solution of the original problems. The first is a {open_quotes}filter{close_quotes} type technique, similar to that used in conjunction with penalty functions, the second one is an adaptive discretization technique with nicer convergence properties. We will illustrate the use of our concept of consistent approximations with examples from semi-infinite optimization, optimal control, and shape optimization.
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.
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
Optimization of the shapes of obstacles in jet-separation flow
NASA Astrophysics Data System (ADS)
Monakhov, V. N.; Gubkina, E. V.
2007-05-01
The model of an ideal incompressible fluid is used to study the solvability of optimal control problems for the shape of a nozzle which discharges free-boundary fluid flow with and without accounting for gravity (internal aerodynamics) and shape optimization problems for an obstacle with jet separation (external aerodynamics). The qualitative properties of such flows are studied.
Shape Optimization for Navier-Stokes Equations with Algebraic Turbulence Model: Existence Analysis
Bulicek, Miroslav Haslinger, Jaroslav Malek, Josef Stebel, Jan
2009-10-15
We study a shape optimization problem for the paper machine headbox which distributes a mixture of water and wood fibers in the paper making process. The aim is to find a shape which a priori ensures the given velocity profile on the outlet part. The mathematical formulation leads to an optimal control problem in which the control variable is the shape of the domain representing the header, the state problem is represented by a generalized stationary Navier-Stokes system with nontrivial mixed boundary conditions. In this paper we prove the existence of solutions both to the generalized Navier-Stokes system and to the shape optimization problem.
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.
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.
Vinding, Mads S.; Guérin, Bastien; Vosegaard, Thomas; Nielsen, Niels Chr.
2016-01-01
Purpose To present a constrained optimal-control (OC) framework for designing large-flip-angle parallel-transmit (pTx) pulses satisfying hardware peak-power as well as regulatory local and global specific-absorption-rate (SAR) limits. The application is 2D and 3D spatial-selective 90° and 180° pulses. Theory and Methods The OC gradient-ascent-pulse-engineering method with exact gradients and the limited-memory Broyden-Fletcher-Goldfarb-Shanno method is proposed. Local SAR is constrained by the virtual-observation-points method. Two numerical models facilitated the optimizations, a torso at 3 T and a head at 7 T, both in eight-channel pTx coils and acceleration-factors up to 4. Results The proposed approach yielded excellent flip-angle distributions. Enforcing the local-SAR constraint, as opposed to peak power alone, reduced the local SAR 7 and 5-fold with the 2D torso excitation and inversion pulse, respectively. The root-mean-square errors of the magnetization profiles increased less than 5% with the acceleration factor of 4. Conclusion A local and global SAR, and peak-power constrained OC large-flip-angle pTx pulse design was presented, and numerically validated for 2D and 3D spatial-selective 90° and 180° pulses at 3 T and 7 T. PMID:26715084
Vinding, Mads S; Guérin, Bastien; Vosegaard, Thomas; Nielsen, Niels Chr
2017-01-01
To present a constrained optimal-control (OC) framework for designing large-flip-angle parallel-transmit (pTx) pulses satisfying hardware peak-power as well as regulatory local and global specific-absorption-rate (SAR) limits. The application is 2D and 3D spatial-selective 90° and 180° pulses. The OC gradient-ascent-pulse-engineering method with exact gradients and the limited-memory Broyden-Fletcher-Goldfarb-Shanno method is proposed. Local SAR is constrained by the virtual-observation-points method. Two numerical models facilitated the optimizations, a torso at 3 T and a head at 7 T, both in eight-channel pTx coils and acceleration-factors up to 4. The proposed approach yielded excellent flip-angle distributions. Enforcing the local-SAR constraint, as opposed to peak power alone, reduced the local SAR 7 and 5-fold with the 2D torso excitation and inversion pulse, respectively. The root-mean-square errors of the magnetization profiles increased less than 5% with the acceleration factor of 4. A local and global SAR, and peak-power constrained OC large-flip-angle pTx pulse design was presented, and numerically validated for 2D and 3D spatial-selective 90° and 180° pulses at 3 T and 7 T. Magn Reson Med 77:374-384, 2017. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Zhang, Chenglong; Guo, Ping
2017-10-01
The vague and fuzzy parametric information is a challenging issue in irrigation water management problems. In response to this problem, a generalized fuzzy credibility-constrained linear fractional programming (GFCCFP) model is developed for optimal irrigation water allocation under uncertainty. The model can be derived from integrating generalized fuzzy credibility-constrained programming (GFCCP) into a linear fractional programming (LFP) optimization framework. Therefore, it can solve ratio optimization problems associated with fuzzy parameters, and examine the variation of results under different credibility levels and weight coefficients of possibility and necessary. It has advantages in: (1) balancing the economic and resources objectives directly; (2) analyzing system efficiency; (3) generating more flexible decision solutions by giving different credibility levels and weight coefficients of possibility and (4) supporting in-depth analysis of the interrelationships among system efficiency, credibility level and weight coefficient. The model is applied to a case study of irrigation water allocation in the middle reaches of Heihe River Basin, northwest China. Therefore, optimal irrigation water allocation solutions from the GFCCFP model can be obtained. Moreover, factorial analysis on the two parameters (i.e. λ and γ) indicates that the weight coefficient is a main factor compared with credibility level for system efficiency. These results can be effective for support reasonable irrigation water resources management and agricultural production.
Liu, Xing; Hou, Kun Mean; de Vaulx, Christophe; Xu, Jun; Yang, Jianfeng; Zhou, Haiying; Shi, Hongling; Zhou, Peng
2014-12-23
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.
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
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.
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.
Optimized Shapes of Ocsillating Resonators for Generating High-Amplitude Pressure Waves
NASA Technical Reports Server (NTRS)
Li, Xiao-Fan; Finkbeiner, Joshua; Daniels, Christopher; Steinetz, Bruce M.
2003-01-01
It is well known that the resonator geometry strongly influences the resonant frequencies of an acoustical resonator and the generated nonlinear standing pressure waveform. Maximizing the ratio of maximum to minimum gas pressure at an end of an oscillating resonator by optimizing the cavity contour is investigated numerically. A quasi-Newton type scheme is used to find optimized axisymmetric resonator shapes to achieve the maximum pressure compression ratio. The acoustical field is solved using a one-dimensional model, and the resonance frequency shift and hysteresis effects are obtained through an automation scheme based on continuation methods. Results are presented from optimizing cone, horn-cone, and cosine resonator geometries. Significant performance improvement is found in the optimized shapes over others previously published. Different optimized shapes are found when starting with different initial guesses, indicating multiple local extrema. The numerical model is validated by comparing with the experimental results of a horn-cone shaped resonator.
NASA Astrophysics Data System (ADS)
Vasilyev, Oleg V.; Gazzola, Mattia; Koumoutsakos, Petros
2009-11-01
In this talk we discuss preliminary results for the use of hybrid wavelet collocation - Brinkman penalization approach for shape and topology optimization of fluid flows. Adaptive wavelet collocation method tackles the problem of efficiently resolving a fluid flow on a dynamically adaptive computational grid in complex geometries (where grid resolution varies both in space and time time), while Brinkman volume penalization allows easy variation of flow geometry without using body-fitted meshes by simply changing the shape of the penalization region. The use of Brinkman volume penalization approach allow seamless transition from shape to topology optimization by combining it with level set approach and increasing the size of the optimization space. The approach is demonstrated for shape optimization of a variety of fluid flows by optimizing single cost function (time averaged Drag coefficient) using covariance matrix adaptation (CMA) evolutionary algorithm.
NASA Astrophysics Data System (ADS)
Hau, L. C.; Fung, E. H. K.; Yau, D. T. W.
2006-12-01
This paper describes the use of the multi-objective genetic algorithm (MOGA) to solve an integrated optimization problem of a rotating flexible arm with active constrained layer damping (ACLD) treatment. The arm is rotating in a horizontal plane with triangular velocity profiles. The ACLD patch is placed at the clamped end of the arm. The design objectives are to minimize the total treatment weight, the control voltage and the tip displacement of the arm, as well as to maximize the passive damping characteristic of the arm. Design variables include the control gains, the maximum angular velocity, the shear modulus of the viscoelastic layer, the thickness of the piezoelectric constraining and viscoelastic layers, and the length of the ACLD patch. In order to evaluate the effect of different combinations of design variables on the system, the finite element method, in conjunction with the Golla-Hughes-McTavish (GHM) method, is employed to model the flexible arm with ACLD treatment to predict its dynamic behavior, in which the effects of centrifugal stiffening due to the rotation of flexible arm are taken into account. As a result of optimization, reasonable Pareto solutions are successfully obtained. It is shown that the MOGA is applicable to the present integrated optimization problem.
NASA Astrophysics Data System (ADS)
Mirzaei, Mahmood; Tibaldi, Carlo; Hansen, Morten H.
2016-09-01
PI/PID controllers are the most common wind turbine controllers. Normally a first tuning is obtained using methods such as pole-placement or Ziegler-Nichols and then extensive aeroelastic simulations are used to obtain the best tuning in terms of regulation of the outputs and reduction of the loads. In the traditional tuning approaches, the properties of different open loop and closed loop transfer functions of the system are not normally considered. In this paper, an assessment of the pole-placement tuning method is presented based on robustness measures. Then a constrained optimization setup is suggested to automatically tune the wind turbine controller subject to robustness constraints. The properties of the system such as the maximum sensitivity and complementary sensitivity functions (Ms and Mt ), along with some of the responses of the system, are used to investigate the controller performance and formulate the optimization problem. The cost function is the integral absolute error (IAE) of the rotational speed from a disturbance modeled as a step in wind speed. Linearized model of the DTU 10-MW reference wind turbine is obtained using HAWCStab2. Thereafter, the model is reduced with model order reduction. The trade-off curves are given to assess the tunings of the poles- placement method and a constrained optimization problem is solved to find the best tuning.
Controls-structures integrated design optimization with shape variations
NASA Technical Reports Server (NTRS)
Koganti, Gopichand; Hou, Gene
1993-01-01
The shape design variables have been introduced into the set of design variables of the Controls-Structure Integrated (CSI) Design of space-structures. The importance of the shape variations in improving the design (obtained with only control and sizing variables) has been aptly illustrated. Two different types of design variables that describe the shape variations of the structure have been introduced. In the first case, the nodal coordinates have been considered as design variables. This has the inherent difficulty of having too many design variables. This not only is time consuming but also memory intensive and may not yield a manufacturable shape to the structure. The second approach has been introduced to overcome this difficulty. The structure is allowed to vary in a particular pre defined pattern. The coefficients of these patterns are considered as the shape design variables. The eigenvalue and eigenvector sensitivity equations with respect to these coefficient design variables have been developed and are used to approximate the eigenvalues and eigenvectors in a perturbed design.
Vehicle Hull Shape Optimization for Minimum Weight Under Blast Loading
2013-03-01
the catenary curve, the idealized shape that a chain assumes under its own weight. The reasoning...How the Gateway Arch Got its Shape. NEXUS NETWORK JOURNAL, 2010. 12(2): p. 167-‐189. 14. Ngo, T
NASA Astrophysics Data System (ADS)
Swaidan, Waleeda; Hussin, Amran
2015-10-01
Most direct methods solve finite time horizon optimal control problems with nonlinear programming solver. In this paper, we propose a numerical method for solving nonlinear optimal control problem with state and control inequality constraints. This method used quasilinearization technique and Haar wavelet operational matrix to convert the nonlinear optimal control problem into a quadratic programming problem. The linear inequality constraints for trajectories variables are converted to quadratic programming constraint by using Haar wavelet collocation method. The proposed method has been applied to solve Optimal Control of Multi-Item Inventory Model. The accuracy of the states, controls and cost can be improved by increasing the Haar wavelet resolution.
MADCAT Aircraft Wings Optimize Their Shape For Efficient Flight
2016-11-09
The Mission Adaptive Digital Composites Aerostructures Technology (MADCAT) project is designing an aircraft wing that can change its shape to adapt to changing flight conditions. Constructed of lightweight lattice structures made of carbon fiber materials, the goal is to reduce drag, leading to more efficient airplanes.
Novel free-form hohlraum shape design and optimization for laser-driven inertial confinement fusion
Jiang, Shaoen; Jing, Longfei Ding, Yongkun; Huang, Yunbao
2014-10-15
The hohlraum shape attracts considerable attention because there is no successful ignition method for laser-driven inertial confinement fusion at the National Ignition Facility. The available hohlraums are typically designed with simple conic curves, including ellipses, parabolas, arcs, or Lame curves, which allow only a few design parameters for the shape optimization, making it difficult to improve the performance, e.g., the energy coupling efficiency or radiation drive symmetry. A novel free-form hohlraum design and optimization approach based on the non-uniform rational basis spline (NURBS) model is proposed. In the present study, (1) all kinds of hohlraum shapes can be uniformly represented using NURBS, which is greatly beneficial for obtaining the optimal available hohlraum shapes, and (2) such free-form uniform representation enables us to obtain an optimal shape over a large design domain for the hohlraum with a more uniform radiation and higher drive temperature of the fuel capsule. Finally, a hohlraum is optimized and evaluated with respect to the drive temperature and symmetry at the Shenguang III laser facility in China. The drive temperature and symmetry results indicate that such a free-form representation is advantageous over available hohlraum shapes because it can substantially expand the shape design domain so as to obtain an optimal hohlraum with high performance.
NASA Astrophysics Data System (ADS)
Nguyen, Q. H.; Lang, V. T.; Nguyen, N. D.; Choi, S. B.
2014-01-01
When designing a magneto-rheological brake (MRB), it is well known that the shape of the brake envelope significantly affects the performance characteristics of the brake. In this study, different shapes for the MR brake envelope, such as rectangular, polygonal or spline shape, are considered and the most suitable shape identified. MRBs with different envelope shapes are introduced followed by the derivation of the braking torque based on Bingham-plastic behavior of the magneto-rheological fluid (MRF). Optimization of the design of the MRB with different envelope shapes is then done. The optimization problem is to find the optimal value for the significant geometric dimensions of the MRB that can produce a certain required braking torque while the brake mass is minimized. A finite element analysis integrated with an optimization tool is employed to obtain optimal solutions for the MRBs. From the results, the most suitable shape for the brake envelope is identified and discussed with the reduction of mass. In addition, the results of the analysis are compared with the experimental results to verify the proposed optimal design characteristics.
Trade-offs and efficiencies in optimal budget-constrained multispecies corridor networks
Bistra Dilkina; Rachel Houtman; Carla P. Gomes; Claire A. Montgomery; Kevin S. McKelvey; Katherine Kendall; Tabitha A. Graves; Richard Bernstein; Michael K. Schwartz
2016-01-01
Conservation biologists recognize that a system of isolated protected areas will be necessary but insufficient to meet biodiversity objectives. Current approaches to connecting core conservation areas through corridors consider optimal corridor placement based on a single optimization goal: commonly, maximizing the movement for a target species across a...
Adjoint-based constrained topology optimization for viscous flows, including heat transfer
NASA Astrophysics Data System (ADS)
Kontoleontos, E. A.; Papoutsis-Kiachagias, E. M.; Zymaris, A. S.; Papadimitriou, D. I.; Giannakoglou, K. C.
2013-08-01
In fluid mechanics, topology optimization is used for designing flow passages, connecting predefined inlets and outlets, with optimal performance based on selected criteria. In this article, the continuous adjoint approach to topology optimization in incompressible ducted flows with heat transfer is presented. A variable porosity field, to be determined during the optimization, is the means to define the optimal topology. The objective functions take into account viscous losses and the amount of heat transfer. Turbulent flows are handled using the Spalart-Allmaras model and the proposed adjoint is exact, i.e. the adjoint to the turbulence model equation is formulated and solved, too. This is an important novelty in this article which extends the porosity-based method to account for heat transfer flow problems in turbulent flows. In problems such as the design of manifolds, constraints on the outlet flow direction, rates and mean outlet temperatures are imposed.
Automated Finite Element Modeling of Wing Structures for Shape Optimization
NASA Technical Reports Server (NTRS)
Harvey, Michael Stephen
1993-01-01
The displacement formulation of the finite element method is the most general and most widely used technique for structural analysis of airplane configurations. Modem structural synthesis techniques based on the finite element method have reached a certain maturity in recent years, and large airplane structures can now be optimized with respect to sizing type design variables for many load cases subject to a rich variety of constraints including stress, buckling, frequency, stiffness and aeroelastic constraints (Refs. 1-3). These structural synthesis capabilities use gradient based nonlinear programming techniques to search for improved designs. For these techniques to be practical a major improvement was required in computational cost of finite element analyses (needed repeatedly in the optimization process). Thus, associated with the progress in structural optimization, a new perspective of structural analysis has emerged, namely, structural analysis specialized for design optimization application, or.what is known as "design oriented structural analysis" (Ref. 4). This discipline includes approximation concepts and methods for obtaining behavior sensitivity information (Ref. 1), all needed to make the optimization of large structural systems (modeled by thousands of degrees of freedom and thousands of design variables) practical and cost effective.
Zarepisheh, M; Li, R; Xing, L; Ye, Y; Boyd, S
2014-06-01
Purpose: Station Parameter Optimized Radiation Therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital LINACs, in which the station parameters of a delivery system, (such as aperture shape and weight, couch position/angle, gantry/collimator angle) are optimized altogether. SPORT promises to deliver unprecedented radiation dose distributions efficiently, yet there does not exist any optimization algorithm to implement it. The purpose of this work is to propose an optimization algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: We build a mathematical model whose variables are beam angles (including non-coplanar and/or even nonisocentric beams) and aperture shapes. To solve the resulting large scale optimization problem, we devise an exact, convergent and fast optimization algorithm by integrating three advanced optimization techniques named column generation, gradient method, and pattern search. Column generation is used to find a good set of aperture shapes as an initial solution by adding apertures sequentially. Then we apply the gradient method to iteratively improve the current solution by reshaping the aperture shapes and updating the beam angles toward the gradient. Algorithm continues by pattern search method to explore the part of the search space that cannot be reached by the gradient method. Results: The proposed technique is applied to a series of patient cases and significantly improves the plan quality. In a head-and-neck case, for example, the left parotid gland mean-dose, brainstem max-dose, spinal cord max-dose, and mandible mean-dose are reduced by 10%, 7%, 24% and 12% respectively, compared to the conventional VMAT plan while maintaining the same PTV coverage. Conclusion: Combined use of column generation, gradient search and pattern search algorithms provide an effective way to optimize simultaneously the large collection of station parameters and significantly improves
Multi-objective aerodynamic shape optimization of small livestock trailers
NASA Astrophysics Data System (ADS)
Gilkeson, C. A.; Toropov, V. V.; Thompson, H. M.; Wilson, M. C. T.; Foxley, N. A.; Gaskell, P. H.
2013-11-01
This article presents a formal optimization study of the design of small livestock trailers, within which the majority of animals are transported to market in the UK. The benefits of employing a headboard fairing to reduce aerodynamic drag without compromising the ventilation of the animals' microclimate are investigated using a multi-stage process involving computational fluid dynamics (CFD), optimal Latin hypercube (OLH) design of experiments (DoE) and moving least squares (MLS) metamodels. Fairings are parameterized in terms of three design variables and CFD solutions are obtained at 50 permutations of design variables. Both global and local search methods are employed to locate the global minimum from metamodels of the objective functions and a Pareto front is generated. The importance of carefully selecting an objective function is demonstrated and optimal fairing designs, offering drag reductions in excess of 5% without compromising animal ventilation, are presented.
Aerodynamic shape optimization of Airfoils in 2-D incompressible flow
NASA Astrophysics Data System (ADS)
Rangasamy, Srinivethan; Upadhyay, Harshal; Somasekaran, Sandeep; Raghunath, Sreekanth
2010-11-01
An optimization framework was developed for maximizing the region of 2-D airfoil immersed in laminar flow with enhanced aerodynamic performance. It uses genetic algorithm over a population of 125, across 1000 generations, to optimize the airfoil. On a stand-alone computer, a run takes about an hour to obtain a converged solution. The airfoil geometry was generated using two Bezier curves; one to represent the thickness and the other the camber of the airfoil. The airfoil profile was generated by adding and subtracting the thickness curve from the camber curve. The coefficient of lift and drag was computed using potential velocity distribution obtained from panel code, and boundary layer transition prediction code was used to predict the location of onset of transition. The objective function of a particular design is evaluated as the weighted-average of aerodynamic characteristics at various angles of attacks. Optimization was carried out for several objective functions and the airfoil designs obtained were analyzed.
Co-Optimization of Blunt Body Shapes for Moving Vehicles
NASA Technical Reports Server (NTRS)
Brown, James L. (Inventor); Garcia, Joseph A (Inventor); Kinney, David J. (Inventor); Bowles, Jeffrey V (Inventor); Mansour, Nagi N (Inventor)
2014-01-01
A method and associated system for multi-disciplinary optimization of various parameters associated with a space vehicle that experiences aerocapture and atmospheric entry in a specified atmosphere. In one embodiment, simultaneous maximization of a ratio of landed payload to vehicle atmospheric entry mass, maximization of fluid flow distance before flow separation from vehicle, and minimization of heat transfer to the vehicle are performed with respect to vehicle surface geometric parameters, and aerostructure and aerothermal vehicle response for the vehicle moving along a specified trajectory. A Pareto Optimal set of superior performance parameters is identified.
An Optimally constrained V3 peptide is a better immunogen than its linear homolog or HIV-1 gp120
Moseri, Adi; Tantry, Subramanyam; Sagi, Yael; Arshava, Boris; Naider, Fred; Anglister, Jacob
2010-01-01
Synthetic peptides offer an attractive option for development of a V3-directed vaccine. However, immunization with flexible linear peptides may result in an immune response to multiple conformations, many of which differ from the native conformation of the corresponding region in the protein. Here we show that optimization of the location of a disulfide bond in peptides constrained to mimic the β-hairpin conformation of the V3, yields an immunogen that elicits a 30-fold stronger HIV-1 neutralizing response in rabbits compared with the homologous linear V3 peptide. The HIV-1 neutralizing response elicited by the optimally constrained peptide is also significantly stronger than that elicited by a gp120 construct in which the V3 is exposed. Neutralization of an HIV-1 strain that shares only 72% identity with the immunizing peptide was demonstrated. The most effective immunogen was also able to neutralize primary isolates that are more resistant to neutralization such as SS1196 and 6535. PMID:20347111
Finite dimensional approximation of a class of constrained nonlinear optimal control problems
NASA Technical Reports Server (NTRS)
Gunzburger, Max D.; Hou, L. S.
1994-01-01
An abstract framework for the analysis and approximation of a class of nonlinear optimal control and optimization problems is constructed. Nonlinearities occur in both the objective functional and in the constraints. The framework includes an abstract nonlinear optimization problem posed on infinite dimensional spaces, and approximate problem posed on finite dimensional spaces, together with a number of hypotheses concerning the two problems. The framework is used to show that optimal solutions exist, to show that Lagrange multipliers may be used to enforce the constraints, to derive an optimality system from which optimal states and controls may be deduced, and to derive existence results and error estimates for solutions of the approximate problem. The abstract framework and the results derived from that framework are then applied to three concrete control or optimization problems and their approximation by finite element methods. The first involves the von Karman plate equations of nonlinear elasticity, the second, the Ginzburg-Landau equations of superconductivity, and the third, the Navier-Stokes equations for incompressible, viscous flows.
Optimization of ultrasonic array inspections using an efficient hybrid model and real crack shapes
NASA Astrophysics Data System (ADS)
Felice, Maria V.; Velichko, Alexander; Wilcox, Paul D.; Barden, Tim; Dunhill, Tony
2015-03-01
Models which simulate the interaction of ultrasound with cracks can be used to optimize ultrasonic array inspections, but this approach can be time-consuming. To overcome this issue an efficient hybrid model is implemented which includes a finite element method that requires only a single layer of elements around the crack shape. Scattering Matrices are used to capture the scattering behavior of the individual cracks and a discussion on the angular degrees of freedom of elastodynamic scatterers is included. Real crack shapes are obtained from X-ray Computed Tomography images of cracked parts and these shapes are inputted into the hybrid model. The effect of using real crack shapes instead of straight notch shapes is demonstrated. An array optimization methodology which incorporates the hybrid model, an approximate single-scattering relative noise model and the real crack shapes is then described.
Optimization of ultrasonic array inspections using an efficient hybrid model and real crack shapes
Felice, Maria V.; Velichko, Alexander Wilcox, Paul D.; Barden, Tim; Dunhill, Tony
2015-03-31
Models which simulate the interaction of ultrasound with cracks can be used to optimize ultrasonic array inspections, but this approach can be time-consuming. To overcome this issue an efficient hybrid model is implemented which includes a finite element method that requires only a single layer of elements around the crack shape. Scattering Matrices are used to capture the scattering behavior of the individual cracks and a discussion on the angular degrees of freedom of elastodynamic scatterers is included. Real crack shapes are obtained from X-ray Computed Tomography images of cracked parts and these shapes are inputted into the hybrid model. The effect of using real crack shapes instead of straight notch shapes is demonstrated. An array optimization methodology which incorporates the hybrid model, an approximate single-scattering relative noise model and the real crack shapes is then described.
Optimized shapes of magnetic arrays for drug targeting applications
NASA Astrophysics Data System (ADS)
Barnsley, Lester C.; Carugo, Dario; Stride, Eleanor
2016-06-01
Arrays of permanent magnet elements have been utilized as light-weight, inexpensive sources for applying external magnetic fields in magnetic drug targeting applications, but they are extremely limited in the range of depths over which they can apply useful magnetic forces. In this paper, designs for optimized magnet arrays are presented, which were generated using an optimization routine to maximize the magnetic force available from an arbitrary arrangement of magnetized elements, depending on a set of design parameters including the depth of targeting (up to 50 mm from the magnet) and direction of force required. A method for assembling arrays in practice is considered, quantifying the difficulty of assembly and suggesting a means for easing this difficulty without a significant compromise to the applied field or force. Finite element simulations of in vitro magnetic retention experiments were run to demonstrate the capability of a subset of arrays to retain magnetic microparticles against flow. The results suggest that, depending on the choice of array, a useful proportion of particles (more than 10% ) could be retained at flow velocities up to 100 mm s-1 or to depths as far as 50 mm from the magnet. Finally, the optimization routine was used to generate a design for a Halbach array optimized to deliver magnetic force to a depth of 50 mm inside the brain.
Optimal pulse shaping for coherent control by the penalty algorithm
NASA Astrophysics Data System (ADS)
Shen, Hai; Dussault, Jean-Pièrre; Bandrauk, André D.
1994-04-01
We use penalty methods coupled with unitary exponential operator methods to solve the optimal control problem for molecular time-dependent Schrödinger equations involving laser pulse excitations. A stable numerical algorithm is presented which propagates directly from initial states to given final states. Results are reported for an analytically solvable model for the complete inversion of a three-state system.
NASA Technical Reports Server (NTRS)
Pandya, Mohagna J.; Baysal, Oktay
1997-01-01
A gradient-based shape optimization based on quasi-analytical sensitivities has been extended for practical three-dimensional aerodynamic applications. The flow analysis has been rendered by a fully implicit, finite-volume formulation of the Euler and Thin-Layer Navier-Stokes (TLNS) equations. Initially, the viscous laminar flow analysis for a wing has been compared with an independent computational fluid dynamics (CFD) code which has been extensively validated. The new procedure has been demonstrated in the design of a cranked arrow wing at Mach 2.4 with coarse- and fine-grid based computations performed with Euler and TLNS equations. The influence of the initial constraints on the geometry and aerodynamics of the optimized shape has been explored. Various final shapes generated for an identical initial problem formulation but with different optimization path options (coarse or fine grid, Euler or TLNS), have been aerodynamically evaluated via a common fine-grid TLNS-based analysis. The initial constraint conditions show significant bearing on the optimization results. Also, the results demonstrate that to produce an aerodynamically efficient design, it is imperative to include the viscous physics in the optimization procedure with the proper resolution. Based upon the present results, to better utilize the scarce computational resources, it is recommended that, a number of viscous coarse grid cases using either a preconditioned bi-conjugate gradient (PbCG) or an alternating-direction-implicit (ADI) method, should initially be employed to improve the optimization problem definition, the design space and initial shape. Optimized shapes should subsequently be analyzed using a high fidelity (viscous with fine-grid resolution) flow analysis to evaluate their true performance potential. Finally, a viscous fine-grid-based shape optimization should be conducted, using an ADI method, to accurately obtain the final optimized shape.
Shape optimization and material gradient design of the sharp hot structure
NASA Astrophysics Data System (ADS)
Ma, Yinji; Yao, Xuefeng; Su, Yunquan
2014-10-01
In this paper, the shape and material gradient of the sharp hot structure are designed and optimized to meet the hypersonic flight conditions. First, based on the single-objective optimization for the volume, the aerodynamic loading and the heat flow, respectively, the genetic algorithm (GA) is employed for optimizing the shape of the sharp hot structure. Second, the shape of the sharp hot structure is optimized using multi-objective GA by means of the objectives of the volume, the aerodynamic loading and the heat flow. Finally, the ABAQUS software is used to simulate both the temperature and the stress distribution with different material gradient distributions for the sharp hot structure. The optimal distributions of gradient materials for the sharp hot structure are proposed. The results will provide an important guidance for the design of the sharp hot structure.
Annicchiarico, W
2001-01-01
Structural optimization is an engineering field which deal with the improvement of existing solutions or even more find new solutions that are better than the previous ones under some selected criterion. Shape optimization is a research area in this field and it is involved in developing new methodologies to find better structural design based on the shape as resistant element, as for example solutions with the less stress concentration zones and made with the minimum amount of material. The goal of this doctoral dissertation is to present and discuss a general structural shape optimization methodology able to optimize several structural systems or mechanical devices. The approach presented herein is based on global search optimization tools such as Genetic Algorithms and geometric design elements by means of beta-splines curves and surfaces representation. Finally the great versatility of the developed tool is presented and discussed with an application example.
A multi-agent technique for contingency constrained optimal power flows
Talukdar, S.; Ramesh, V.C. . Engineering Design Research Center)
1994-05-01
This paper does three things. First, it proposes that each critical contingency in a power system be represented by a correction time'' (the time required to eliminate the violations produced by the contingency), rather than by a set of hard constraints. Second, it adds these correction times to an optimal power flow and decomposes the resulting problem into a number of smaller optimization problems. Third, it proposes a multiagent technique for solving the smaller problems in parallel. The agents encapsulate traditional optimization algorithms as well as a new algorithm, called the voyager, that generates starting points for the traditional algorithms. All the agents communicate asynchronously, meaning that they can work in parallel without ever interrupting or delaying one another. The resulting scheme has potential for handling power system contingencies and other difficult global optimization problems.
NASA Astrophysics Data System (ADS)
Orito, Yukiko; Yamamoto, Hisashi; Tsujimura, Yasuhiro; Kambayashi, Yasushi
The portfolio optimizations are to determine the proportion-weighted combination in the portfolio in order to achieve investment targets. This optimization is one of the multi-dimensional combinatorial optimizations and it is difficult for the portfolio constructed in the past period to keep its performance in the future period. In order to keep the good performances of portfolios, we propose the extended information ratio as an objective function, using the information ratio, beta, prime beta, or correlation coefficient in this paper. We apply the simulated annealing (SA) to optimize the portfolio employing the proposed ratio. For the SA, we make the neighbor by the operation that changes the structure of the weights in the portfolio. In the numerical experiments, we show that our portfolios keep the good performances when the market trend of the future period becomes different from that of the past period.
Hybrid methods for determining time-optimal, constrained spacecraft reorientation maneuvers
NASA Astrophysics Data System (ADS)
Melton, Robert G.
2014-01-01
Time-optimal spacecraft slewing maneuvers with path constraints are difficult to compute even with direct methods. This paper examines the use of a hybrid, two-stage approach, in which a heuristic method provides a rough estimate of the solution, which then serves as the input to a pseudospectral optimizer. Three heuristic methods are examined for the first stage: particle swarm optimization (PSO), differential evolution (DE), and bacteria foraging optimization (BFO). In this two-stage method, the PSO-pseudospectral combination is approximately three times faster than the pseudospectral method alone, and the BFO-pseudospectral combination is approximately four times faster; however, the DE does not produce an initial estimate that reduces total computation time.
Trade-offs and efficiencies in optimal budget-constrained multispecies corridor networks.
Dilkina, Bistra; Houtman, Rachel; Gomes, Carla P; Montgomery, Claire A; McKelvey, Kevin S; Kendall, Katherine; Graves, Tabitha A; Bernstein, Richard; Schwartz, Michael K
2017-02-01
Conservation biologists recognize that a system of isolated protected areas will be necessary but insufficient to meet biodiversity objectives. Current approaches to connecting core conservation areas through corridors consider optimal corridor placement based on a single optimization goal: commonly, maximizing the movement for a target species across a network of protected areas. We show that designing corridors for single species based on purely ecological criteria leads to extremely expensive linkages that are suboptimal for multispecies connectivity objectives. Similarly, acquiring the least-expensive linkages leads to ecologically poor solutions. We developed algorithms for optimizing corridors for multispecies use given a specific budget. We applied our approach in western Montana to demonstrate how the solutions may be used to evaluate trade-offs in connectivity for 2 species with different habitat requirements, different core areas, and different conservation values under different budgets. We evaluated corridors that were optimal for each species individually and for both species jointly. Incorporating a budget constraint and jointly optimizing for both species resulted in corridors that were close to the individual species movement-potential optima but with substantial cost savings. Our approach produced corridors that were within 14% and 11% of the best possible corridor connectivity for grizzly bears (Ursus arctos) and wolverines (Gulo gulo), respectively, and saved 75% of the cost. Similarly, joint optimization under a combined budget resulted in improved connectivity for both species relative to splitting the budget in 2 to optimize for each species individually. Our results demonstrate economies of scale and complementarities conservation planners can achieve by optimizing corridor designs for financial costs and for multiple species connectivity jointly. We believe that our approach will facilitate corridor conservation by reducing acquisition costs
Trade-offs and efficiencies in optimal budget-constrained multispecies corridor networks
Dilkina, Bistra; Houtman, Rachel; Gomes, Carla P.; Montgomery, Claire A.; McKelvey, Kevin; Kendall, Katherine; Graves, Tabitha A.; Bernstein, Richard; Schwartz, Michael K.
2017-01-01
Conservation biologists recognize that a system of isolated protected areas will be necessary but insufficient to meet biodiversity objectives. Current approaches to connecting core conservation areas through corridors consider optimal corridor placement based on a single optimization goal: commonly, maximizing the movement for a target species across a network of protected areas. We show that designing corridors for single species based on purely ecological criteria leads to extremely expensive linkages that are suboptimal for multispecies connectivity objectives. Similarly, acquiring the least-expensive linkages leads to ecologically poor solutions. We developed algorithms for optimizing corridors for multispecies use given a specific budget. We applied our approach in western Montana to demonstrate how the solutions may be used to evaluate trade-offs in connectivity for 2 species with different habitat requirements, different core areas, and different conservation values under different budgets. We evaluated corridors that were optimal for each species individually and for both species jointly. Incorporating a budget constraint and jointly optimizing for both species resulted in corridors that were close to the individual species movement-potential optima but with substantial cost savings. Our approach produced corridors that were within 14% and 11% of the best possible corridor connectivity for grizzly bears (Ursus arctos) and wolverines (Gulo gulo), respectively, and saved 75% of the cost. Similarly, joint optimization under a combined budget resulted in improved connectivity for both species relative to splitting the budget in 2 to optimize for each species individually. Our results demonstrate economies of scale and complementarities conservation planners can achieve by optimizing corridor designs for financial costs and for multiple species connectivity jointly. We believe that our approach will facilitate corridor conservation by reducing acquisition costs
Fixed structure compensator design using a constrained hybrid evolutionary optimization approach.
Ghosh, Subhojit; Samanta, Susovon
2014-07-01
This paper presents an efficient technique for designing a fixed order compensator for compensating current mode control architecture of DC-DC converters. The compensator design is formulated as an optimization problem, which seeks to attain a set of frequency domain specifications. The highly nonlinear nature of the optimization problem demands the use of an initial parameterization independent global search technique. In this regard, the optimization problem is solved using a hybrid evolutionary optimization approach, because of its simple structure, faster execution time and greater probability in achieving the global solution. The proposed algorithm involves the combination of a population search based optimization approach i.e. Particle Swarm Optimization (PSO) and local search based method. The op-amp dynamics have been incorporated during the design process. Considering the limitations of fixed structure compensator in achieving loop bandwidth higher than a certain threshold, the proposed approach also determines the op-amp bandwidth, which would be able to achieve the same. The effectiveness of the proposed approach in meeting the desired frequency domain specifications is experimentally tested on a peak current mode control dc-dc buck converter.
NASA Astrophysics Data System (ADS)
Dao, Son Duy; Abhary, Kazem; Marian, Romeo
2017-01-01
Integration of production planning and scheduling is a class of problems commonly found in manufacturing industry. This class of problems associated with precedence constraint has been previously modeled and optimized by the authors, in which, it requires a multidimensional optimization at the same time: what to make, how many to make, where to make and the order to make. It is a combinatorial, NP-hard problem, for which no polynomial time algorithm is known to produce an optimal result on a random graph. In this paper, the further development of Genetic Algorithm (GA) for this integrated optimization is presented. Because of the dynamic nature of the problem, the size of its solution is variable. To deal with this variability and find an optimal solution to the problem, GA with new features in chromosome encoding, crossover, mutation, selection as well as algorithm structure is developed herein. With the proposed structure, the proposed GA is able to "learn" from its experience. Robustness of the proposed GA is demonstrated by a complex numerical example in which performance of the proposed GA is compared with those of three commercial optimization solvers.
NASA Astrophysics Data System (ADS)
Dao, Son Duy; Abhary, Kazem; Marian, Romeo
2017-01-01
Integration of production planning and scheduling is a class of problems commonly found in manufacturing industry. This class of problems associated with precedence constraint has been previously modeled and optimized by the authors, in which, it requires a multidimensional optimization at the same time: what to make, how many to make, where to make and the order to make. It is a combinatorial, NP-hard problem, for which no polynomial time algorithm is known to produce an optimal result on a random graph. In this paper, the further development of Genetic Algorithm (GA) for this integrated optimization is presented. Because of the dynamic nature of the problem, the size of its solution is variable. To deal with this variability and find an optimal solution to the problem, GA with new features in chromosome encoding, crossover, mutation, selection as well as algorithm structure is developed herein. With the proposed structure, the proposed GA is able to "learn" from its experience. Robustness of the proposed GA is demonstrated by a complex numerical example in which performance of the proposed GA is compared with those of three commercial optimization solvers.
Li, H; Yun, X; Li, J; Shi, L; Fok, A S; Madden, M J; Labuz, J F
2010-02-01
This study aims to validate a cavity shape optimization approach for improving the debonding resistance of dental restorations by carrying out fracture tests on restored model teeth with standard and optimized cavity designs. The bio-mimetic stress-induced material transformation (SMT) optimization method was incorporated into the finite element (FE) program ABAQUS as a user material (UMAT) subroutine. The method uses stress minimization to optimize the cavity shape of a MOD restoration in an artificial premolar with special reference to the tooth-restoration interface under occlusal loads. The mechanical performance of the optimized design was first verified through FE analysis and then compared with that of the conventional design using fracture tests on model teeth. The SMT optimization process indicated a T-shape cavity as a more favorable design for the MOD restoration in the artificial premolar. Compared with the conventional parallel wall, or undercut design, the T-shape cavity was shown numerically to reduce the interfacial stresses by up to 69%, and experimentally to increase the mean debonding resistance of the model teeth by 23% (p<0.05). Cavity shape optimization can help increase the debonding resistance of restored teeth by reducing the interfacial stresses between tooth and restoration under occlusal loads. Copyright 2009 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.
Convergence Constrained Multiuser Transmitter-Receiver Optimization in Single-Carrier FDMA
NASA Astrophysics Data System (ADS)
Tervo, Valtteri; Tolli, Antti; Karjalainen, Juha; Matsumoto, Tad
2015-03-01
Convergence constrained power allocation (CCPA) in single carrier multiuser (MU) single-input multiple-output (SIMO) systems with turbo equalization is considered in this paper. In order to exploit full benefit of the iterative receiver, its convergence properties need to be considered also at the transmitter side. The proposed scheme can guarantee that the desired quality of service (QoS) is achieved after sufficient amount of iterations. We propose two different successive convex approximations for solving the non-convex power minimization problem subject to user specific QoS constraints. The results of extrinsic information transfer (EXIT) chart analysis demonstrate that the proposed CCPA scheme can achieve the design objective. Numerical results show that the proposed schemes can achieve superior performance in terms of power consumption as compared to linear receivers with and without precoding as well as to the iterative receiver without precoding.
Optimal segmentation of pupillometric images for estimating pupil shape parameters.
De Santis, A; Iacoviello, D
2006-12-01
The problem of determining the pupil morphological parameters from pupillometric data is considered. These characteristics are of great interest for non-invasive early diagnosis of the central nervous system response to environmental stimuli of different nature, in subjects suffering some typical diseases such as diabetes, Alzheimer disease, schizophrenia, drug and alcohol addiction. Pupil geometrical features such as diameter, area, centroid coordinates, are estimated by a procedure based on an image segmentation algorithm. It exploits the level set formulation of the variational problem related to the segmentation. A discrete set up of this problem that admits a unique optimal solution is proposed: an arbitrary initial curve is evolved towards the optimal segmentation boundary by a difference equation; therefore no numerical approximation schemes are needed, as required in the equivalent continuum formulation usually adopted in the relevant literature.
Suppression of vortex-shedding noise via derivative-free shape optimization
NASA Astrophysics Data System (ADS)
Marsden, Alison L.; Wang, Meng; Dennis, J. E.; Moin, Parviz
2004-10-01
In this Letter we describe the application of a derivative-free optimization technique, the surrogate management framework (SMF), for designing the shape of an airfoil trailing edge which minimizes the noise of vortex shedding. Constraints on lift and drag are enforced within SMF using a filter. Several optimal shapes have been identified for the case of laminar vortex shedding with reasonable computational cost using several shape parameters, and results show a significant reduction in acoustic power. Physical mechanisms for noise reduction are discussed.
Haslinger, Jaroslav; Stebel, Jan
2011-04-15
We study the shape optimization problem for the paper machine headbox which distributes a mixture of water and wood fibers in the paper making process. The aim is to find a shape which a priori ensures the given velocity profile on the outlet part. The mathematical formulation leads to the optimal control problem in which the control variable is the shape of the domain representing the header, the state problem is represented by the generalized Navier-Stokes system with nontrivial boundary conditions. This paper deals with numerical aspects of the problem.
ERIC Educational Resources Information Center
Parkes, Jay; Suen, Hoi K.
This study demonstrates the advantages of using a constrained optimization algorithm to explore the optimal number of prompts, modes of discourse, and raters for achieving an acceptable level of reliability during a direct writing assessment. Writing samples elicited from 50 college students were rated by 3 graduate students and the scores…
PDE constrained optimization of electrical defibrillation in a 3D ventricular slice geometry.
Chamakuri, Nagaiah; Kunisch, Karl; Plank, Gernot
2016-04-01
A computational study of an optimal control approach for cardiac defibrillation in a 3D geometry is presented. The cardiac bioelectric activity at the tissue and bath volumes is modeled by the bidomain model equations. The model includes intramural fiber rotation, axially symmetric around the fiber direction, and anisotropic conductivity coefficients, which are extracted from a histological image. The dynamics of the ionic currents are based on the regularized Mitchell-Schaeffer model. The controls enter in the form of electrodes, which are placed at the boundary of the bath volume with the goal of dampening undesired arrhythmias. The numerical optimization is based on Newton techniques. We demonstrated the parallel architecture environment for the computation of potentials on multidomains and for the higher order optimization techniques.
A linearized theory method of constrained optimization for supersonic cruise wing design
NASA Technical Reports Server (NTRS)
Miller, D. S.; Carlson, H. W.; Middleton, W. D.
1976-01-01
A linearized theory wing design and optimization procedure which allows physical realism and practical considerations to be imposed as constraints on the optimum (least drag due to lift) solution is discussed and examples of application are presented. In addition to the usual constraints on lift and pitching moment, constraints are imposed on wing surface ordinates and wing upper surface pressure levels and gradients. The design procedure also provides the capability of including directly in the optimization process the effects of other aircraft components such as a fuselage, canards, and nacelles.
NASA Technical Reports Server (NTRS)
Lacasse, James M.
1995-01-01
A multiblock sensitivity analysis method is applied in a numerical aerodynamic shape optimization technique. The Sensitivity Analysis Domain Decomposition (SADD) scheme which is implemented in this study was developed to reduce the computer memory requirements resulting from the aerodynamic sensitivity analysis equations. Discrete sensitivity analysis offers the ability to compute quasi-analytical derivatives in a more efficient manner than traditional finite-difference methods, which tend to be computationally expensive and prone to inaccuracies. The direct optimization procedure couples CFD analysis based on the two-dimensional thin-layer Navier-Stokes equations with a gradient-based numerical optimization technique. The linking mechanism is the sensitivity equation derived from the CFD discretized flow equations, recast in adjoint form, and solved using direct matrix inversion techniques. This investigation is performed to demonstrate an aerodynamic shape optimization technique on a multiblock domain and its applicability to complex geometries. The objectives are accomplished by shape optimizing two aerodynamic configurations. First, the shape optimization of a transonic airfoil is performed to investigate the behavior of the method in highly nonlinear flows and the effect of different grid blocking strategies on the procedure. Secondly, shape optimization of a two-element configuration in subsonic flow is completed. Cases are presented for this configuration to demonstrate the effect of simultaneously reshaping interfering elements. The aerodynamic shape optimization is shown to produce supercritical type airfoils in the transonic flow from an initially symmetric airfoil. Multiblocking effects the path of optimization while providing similar results at the conclusion. Simultaneous reshaping of elements is shown to be more effective than individual element reshaping due to the inclusion of mutual interference effects.
Effect of Local Junction Losses in the Optimization of T-shaped Flow Channels
NASA Astrophysics Data System (ADS)
Kosaraju, Srinivas
2015-11-01
T-shaped channels are extensively used in flow distribution applications such as irrigation, chemical dispersion, gas pipelines and space heating and cooling. The geometry of T-shaped channels can be optimized to reduce the overall pressure drop in stem and branch sections. Results of such optimizations are in the form of geometric parameters such as the length and diameter ratios of the stem and branch sections. The traditional approach of this optimization accounts for the pressure drop across the stem and branch sections, however, ignores the pressure drop in the T-junction. In this paper, we conduct geometry optimization while including the effect of local junction losses in laminar flows. From the results, we are able to identify a non-dimensional parameter that can be used to predict the optimal geometric configurations. This parameter can also be used to identify the conditions in which the local junction losses can be ignored during the optimization.
Shape Optimization of Cylindrical Shell for Interior Noise
NASA Technical Reports Server (NTRS)
Robinson, Jay H.
1999-01-01
In this paper an analytic method is used to solve for the cross spectral density of the interior acoustic response of a cylinder with nonuniform thickness subjected to turbulent boundary layer excitation. The cylinder is of honeycomb core construction with the thickness of the core material expressed as a cosine series in the circumferential direction. The coefficients of this series are used as the design variable in the optimization study. The objective function is the space and frequency averaged acoustic response. Results confirm the presence of multiple local minima as previously reported and demonstrate the potential for modest noise reduction.
Numerical Modeling of Surface and Volumetric Cooling using Optimal T- and Y-shaped Flow Channels
NASA Astrophysics Data System (ADS)
Kosaraju, Srinivas
2015-11-01
The T- and Y-shaped flow channels can be optimized for reduced pressure drop and pumping power. The results of the optimization are in the form of geometric parameters such as length and diameter ratios of the stem and branch sections. While these flow channels are optimized for minimum pressure drop, they can also be used for surface and volumetric cooling applications such as heat exchangers, air conditioning and electronics cooling. In this paper, we studied the heat transfer characteristics of multiple T- and Y-shaped flow channel configurations using numerical simulations. All configurations are subjected to same pumping power and heat generation constraints and their heat transfer performance is studied.
A Local Pursuit Strategy for Bio-Inspired Optimal Control with Partially-Constrained Final State
2005-01-01
Martin Institute of Technol- ogy/A. James Clark School of Engineering. It is a National Science Foundation Engineering Research Center. Web site http...Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man and Cybernetics, Part B, 26(1):29–41, 1996. [6] R. Fierro , P. Song, A. Das, and
Constrained Optimization Problems in Cost and Managerial Accounting--Spreadsheet Tools
ERIC Educational Resources Information Center
Amlie, Thomas T.
2009-01-01
A common problem addressed in Managerial and Cost Accounting classes is that of selecting an optimal production mix given scarce resources. That is, if a firm produces a number of different products, and is faced with scarce resources (e.g., limitations on labor, materials, or machine time), what combination of products yields the greatest profit…
A policy iteration approach to online optimal control of continuous-time constrained-input systems.
Modares, Hamidreza; Naghibi Sistani, Mohammad-Bagher; Lewis, Frank L
2013-09-01
This paper is an effort towards developing an online learning algorithm to find the optimal control solution for continuous-time (CT) systems subject to input constraints. The proposed method is based on the policy iteration (PI) technique which has recently evolved as a major technique for solving optimal control problems. Although a number of online PI algorithms have been developed for CT systems, none of them take into account the input constraints caused by actuator saturation. In practice, however, ignoring these constraints leads to performance degradation or even system instability. In this paper, to deal with the input constraints, a suitable nonquadratic functional is employed to encode the constraints into the optimization formulation. Then, the proposed PI algorithm is implemented on an actor-critic structure to solve the Hamilton-Jacobi-Bellman (HJB) equation associated with this nonquadratic cost functional in an online fashion. That is, two coupled neural network (NN) approximators, namely an actor and a critic are tuned online and simultaneously for approximating the associated HJB solution and computing the optimal control policy. The critic is used to evaluate the cost associated with the current policy, while the actor is used to find an improved policy based on information provided by the critic. Convergence to a close approximation of the HJB solution as well as stability of the proposed feedback control law are shown. Simulation results of the proposed method on a nonlinear CT system illustrate the effectiveness of the proposed approach.
Trade-Off Analysis vs. Constrained Optimization with an Economic Control Chart Model
1994-01-01
description of this technique can be found in Luenberger (1989) or Reklaitis et al. (1983). Similar to the economic statistical designs, the trade-off...15] Reklaitis , G. V.; Ravindran, A.; and Ragsdell, K. M., Engineering Optimization, Methods and Applications, John Wiley & Sons, New York (1983). [16
Shape optimization in exoskeletons and endoskeletons: a biomechanics analysis
Taylor, David; Dirks, Jan-Henning
2012-01-01
This paper addresses the question of strength and mechanical failure in exoskeletons and endoskeletons. We developed a new, more sophisticated model to predict failure in bones and other limb segments, modelled as hollow tubes of radius r and thickness t. Five failure modes were considered: transverse fracture; buckling (of three different kinds) and longitudinal splitting. We also considered interactions between failure modes. We tested the hypothesis that evolutionary adaptation tends towards an optimum value of r/t, this being the value which gives the highest strength (i.e. load-carrying capacity) for a given weight. We analysed two examples of arthropod exoskeletons: the crab merus and the locust tibia, using data from the literature and estimating the stresses during typical activities. In both cases, the optimum r/t value for bending was found to be different from that for axial compression. We found that the crab merus experiences similar levels of bending and compression in vivo and that its r/t value represents an ideal compromise to resist these two types of loading. The locust tibia, however, is loaded almost exclusively in bending and was found to be optimized for this loading mode. Vertebrate long bones were found to be far from optimal, having much lower r/t values than predicted, and in this respect our conclusions differ from those of previous workers. We conclude that our theoretical model, though it has some limitations, is useful for investigating evolutionary development of skeletal form in exoskeletons and endoskeletons. PMID:22977103
Shape optimization in exoskeletons and endoskeletons: a biomechanics analysis.
Taylor, David; Dirks, Jan-Henning
2012-12-07
This paper addresses the question of strength and mechanical failure in exoskeletons and endoskeletons. We developed a new, more sophisticated model to predict failure in bones and other limb segments, modelled as hollow tubes of radius r and thickness t. Five failure modes were considered: transverse fracture; buckling (of three different kinds) and longitudinal splitting. We also considered interactions between failure modes. We tested the hypothesis that evolutionary adaptation tends towards an optimum value of r/t, this being the value which gives the highest strength (i.e. load-carrying capacity) for a given weight. We analysed two examples of arthropod exoskeletons: the crab merus and the locust tibia, using data from the literature and estimating the stresses during typical activities. In both cases, the optimum r/t value for bending was found to be different from that for axial compression. We found that the crab merus experiences similar levels of bending and compression in vivo and that its r/t value represents an ideal compromise to resist these two types of loading. The locust tibia, however, is loaded almost exclusively in bending and was found to be optimized for this loading mode. Vertebrate long bones were found to be far from optimal, having much lower r/t values than predicted, and in this respect our conclusions differ from those of previous workers. We conclude that our theoretical model, though it has some limitations, is useful for investigating evolutionary development of skeletal form in exoskeletons and endoskeletons.
A sparse superlinearly convergent SQP with applications to two-dimensional shape optimization.
Anitescu, M.
1998-04-15
Discretization of optimal shape design problems leads to very large nonlinear optimization problems. For attaining maximum computational efficiency, a sequential quadratic programming (SQP) algorithm should achieve superlinear convergence while preserving sparsity and convexity of the resulting quadratic programs. Most classical SQP approaches violate at least one of the requirements. We show that, for a very large class of optimization problems, one can design SQP algorithms that satisfy all these three requirements. The improvements in computational efficiency are demonstrated for a cam design problem.
NASA Astrophysics Data System (ADS)
Xu, Qi; Qin, Yong
2017-07-01
The average power is one of the key parameters of piezoelectric nanogenerators (PENGs). In this paper, we demonstrate that the PENG's output can be gigantically improved by choosing driving force with an appropriate shape. When the load resistance is 100 MΩ and the driven forces have a magnitude of 19.6 nN, frequency of 10 Hz, the average power of PENG driven by square shaped force is six orders of magnitude higher than that driven by triangular shaped and sinusoidal shaped forces. These results are of importance for optimizing the average power of the PENGs in practical applications.
Optimal Shape Design in Heat Transfer Based on Body-Fitted Grid Generation
NASA Astrophysics Data System (ADS)
Mohebbi, Farzad; Sellier, Mathieu
2013-04-01
This paper deals with an inverse steady-state heat transfer problem. We develop in this work a new numerical methodology to infer the shape a heated body should have for the temperature distribution on part of its boundary to match a prescribed one. This new numerical methodology solves this shape optimization problem using body-fitted grid generation to map the unknown optimal shape onto a fixed computational domain. This mapping enables a simple discretization of the Heat Equation using finite differences and allows us to remesh the physical domain, which varies at each optimization iteration. A novel aspect of this work is the sensitivity analysis, which is expressed explicitly in the fixed computational domain. This allows a very efficient evaluation of the sensitivities. The Conjugate Gradient method is used to minimize the objective function and this work proposes an efficient redistribution method to maintain the quality of the mesh throughout the optimization procedure.
Shape optimization in unsteady blood flow: a numerical study of non-Newtonian effects.
Abraham, Feby; Behr, Marek; Heinkenschloss, Matthias
2005-06-01
This paper presents a numerical study of non-Newtonian effects on the solution of shape optimization problems involving unsteady pulsatile blood flow. We consider an idealized two dimensional arterial graft geometry. Our computations are based on the Navier-Stokes equations generalized to non-Newtonian fluid, with the modified Cross model employed to account for the shear-thinning behavior of blood. Using a gradient-based optimization algorithm, we compare the optimal shapes obtained using both the Newtonian and generalized Newtonian constitutive equations. Depending on the shear rate prevalent in the domain, substantial differences in the flow as well as in the computed optimal shape are observed when the Newtonian constitutive equation is replaced by the modified Cross model. By varying a geometric parameter in our test case, we investigate the influence of the shear rate on the solution.
NASA Technical Reports Server (NTRS)
Karman, Steve L., Jr.
2011-01-01
The Aeronautics Research Mission Directorate (ARMD) sent out an NASA Research Announcement (NRA) for proposals soliciting research and technical development. The proposed research program was aimed at addressing the desired milestones and outcomes of ROA (ROA-2006) Subtopic A.4.1.1 Advanced Computational Methods. The second milestone, SUP.1.06.02 Robust, validated mesh adaptation and error quantification for near field Computational Fluid Dynamics (CFD), was addressed by the proposed research. Additional research utilizing the direct links to geometry through a CAD interface enabled by this work will allow for geometric constraints to be applied and address the final milestone, SUP2.07.06 Constrained low-drag supersonic aerodynamic design capability. The original product of the proposed research program was an integrated system of tools that can be used for the mesh mechanics required for rapid high fidelity analysis and for design of supersonic cruise vehicles. These Euler and Navier-Stokes volume grid manipulation tools were proposed to efficiently use parallel processing. The mesh adaptation provides a systematic approach for achieving demonstrated levels of accuracy in the solutions. NASA chose to fund only the mesh generation/adaptation portion of the proposal. So this report describes the completion of the proposed tasks for mesh creation, manipulation and adaptation as it pertains to sonic boom prediction of supersonic configurations.
FastRFS: fast and accurate Robinson-Foulds Supertrees using constrained exact optimization.
Vachaspati, Pranjal; Warnow, Tandy
2017-03-01
The estimation of phylogenetic trees is a major part of many biological dataset analyses, but maximum likelihood approaches are NP-hard and Bayesian MCMC methods do not scale well to even moderate-sized datasets. Supertree methods, which are used to construct trees from trees computed on subsets, are critically important tools for enabling the statistical estimation of phylogenies for large and potentially heterogeneous datasets. Supertree estimation is itself NP-hard, and no current supertree method has sufficient accuracy and scalability to provide good accuracy on the large datasets that supertree methods were designed for, containing thousands of species and many subset trees. We present FastRFS, a new method based on a dynamic programming method we have developed to find an exact solution to the Robinson-Foulds Supertree problem within a constrained search space. FastRFS has excellent accuracy in terms of criterion scores and topological accuracy of the resultant trees, substantially improving on competing methods on a large collection of biological and simulated data. In addition, FastRFS is extremely fast, finishing in minutes on even very large datasets, and in under an hour on a biological dataset with 2228 species. FastRFS is available on github at https://github.com/pranjalv123/FastRFS. warnow@illinois.edu. Supplementary data are available at Bioinformatics online.
Optimal apodization design for medical ultrasound using constrained least squares part I: theory.
Guenther, Drake A; Walker, William F
2007-02-01
Aperture weighting functions are critical design parameters in the development of ultrasound systems because beam characteristics affect the contrast and point resolution of the final output image. In previous work by our group, we developed a metric that quantifies a broadband imaging system's contrast resolution performance. We now use this metric to formulate a novel general ultrasound beamformer design method. In our algorithm, we use constrained least squares (CLS) techniques and a linear algebra formulation to describe the system point spread function (PSF) as a function of the aperture weightings. In one approach, we minimize the energy of the PSF outside a certain boundary and impose a linear constraint on the aperture weights. In a second approach, we minimize the energy of the PSF outside a certain boundary while imposing a quadratic constraint on the energy of the PSF inside the boundary. We present detailed analysis for an arbitrary ultrasound imaging system and discuss several possible applications of the CLS techniques, such as designing aperture weightings to maximize contrast resolution and improve the system depth of field.
Laplacian networks: Growth, local symmetry, and shape optimization
NASA Astrophysics Data System (ADS)
Devauchelle, O.; Szymczak, P.; Pecelerowicz, M.; Cohen, Y.; Seybold, H. J.; Rothman, D. H.
2017-03-01
Inspired by river networks and other structures formed by Laplacian growth, we use the Loewner equation to investigate the growth of a network of thin fingers in a diffusion field. We first review previous contributions to illustrate how this formalism reduces the network's expansion to three rules, which respectively govern the velocity, the direction, and the nucleation of its growing branches. This framework allows us to establish the mathematical equivalence between three formulations of the direction rule, namely geodesic growth, growth that maintains local symmetry, and growth that maximizes flux into tips for a given amount of growth. Surprisingly, we find that this growth rule may result in a network different from the static configuration that optimizes flux into tips.
Shaping an Optimal Soil by Root-Soil Interaction.
Jin, Kemo; White, Philip J; Whalley, William R; Shen, Jianbo; Shi, Lei
2017-10-01
Crop production depends on the availability of water and mineral nutrients, and increased yields might be facilitated by a greater focus on roots-soil interactions. Soil properties affecting plant growth include drought, compaction, nutrient deficiency, mineral toxicity, salinity, and submergence. Plant roots respond to the soil environment both spatially and temporally by avoiding stressful soil environments and proliferating in more favorable environments. We observe that crops can be bred for specific root architectural and biochemical traits that facilitate soil exploration and resource acquisition, enabling greater crop yields. These root traits affect soil physical and chemical properties and might be utilized to improve the soil for subsequent crops. We argue that optimizing root-soil interactions is a prerequisite for future food security. Copyright © 2017 Elsevier Ltd. All rights reserved.
Optimization of Compton Source Performance through Electron Beam Shaping
Malyzhenkov, Alexander; Yampolsky, Nikolai
2016-09-26
We investigate a novel scheme for significantly increasing the brightness of x-ray light sources based on inverse Compton scattering (ICS) - scattering laser pulses off relativistic electron beams. The brightness of ICS sources is limited by the electron beam quality since electrons traveling at different angles, and/or having different energies, produce photons with different energies. Therefore, the spectral brightness of the source is defined by the 6d electron phase space shape and size, as well as laser beam parameters. The peak brightness of the ICS source can be maximized then if the electron phase space is transformed in a way so that all electrons scatter off the x-ray photons of same frequency in the same direction, arriving to the observer at the same time. We describe the x-ray photon beam quality through the Wigner function (6d photon phase space distribution) and derive it for the ICS source when the electron and laser rms matrices are arbitrary.
Optimization of compton source performance through electron beam shaping
NASA Astrophysics Data System (ADS)
Malyzhenkov, Alexander; Yampolsky, Nikolai
2017-03-01
We investigate a novel scheme for significantly increasing the brightness of x-ray light sources based on inverse Compton scattering (ICS) - scattering laser pulses off relativistic electron beams. The brightness of ICS sources is limited by the electron beam quality, since electrons traveling at different angles, and/or having different energies, produce photons with different energies. Therefore, the spectral brightness of the source is defined by the 6D electron phase space shape and size, as well as laser beam parameters. The peak brightness of the ICS source can be maximized, then, if the electron phase space is transformed in a way such that all electrons scatter off the x-ray photons of same frequency in the same direction, arriving to the observer at the same time. We describe the x-ray photon beam quality through the Wigner function (6D photon phase space distribution), and derive it for the ICS source when the electron and laser rms matrices are arbitrary.
How does network design constrain optimal operation of intermittent water supply?
NASA Astrophysics Data System (ADS)
Lieb, Anna; Wilkening, Jon; Rycroft, Chris
2015-11-01
Urban water distribution systems do not always supply water continuously or reliably. As pipes fill and empty, pressure transients may contribute to degraded infrastructure and poor water quality. To help understand and manage this undesirable side effect of intermittent water supply--a phenomenon affecting hundreds of millions of people in cities around the world--we study the relative contributions of fixed versus dynamic properties of the network. Using a dynamical model of unsteady transition pipe flow, we study how different elements of network design, such as network geometry, pipe material, and pipe slope, contribute to undesirable pressure transients. Using an optimization framework, we then investigate to what extent network operation decisions such as supply timing and inflow rate may mitigate these effects. We characterize some aspects of network design that make them more or less amenable to operational optimization.
Fast Bundle-Level Type Methods for Unconstrained and Ball-Constrained Convex Optimization
2014-12-01
ZHANG ¶ Abstract. It has been shown in [14] that the accelerated prox-level ( APL ) method and its variant, the uniform smoothing level (USL) method...introduce two new variants of level methods, i.e., the fast APL (FAPL) method and the fast USL (FUSL) method, for solving large scale black-box and...structured convex programming problems respectively. Both FAPL and FUSL enjoy the same optimal iteration complexity as APL and USL, while the number of
Constrained optimal controller for linear systems with state and control dependent disturbance
NASA Technical Reports Server (NTRS)
Basuthakur, S.
1975-01-01
The problem is posed with the additional constraints that the dynamic controller uses only noise-corrupted outputs, and that its dimension is significantly lower than that of a Kalman filter. The unknown disturbance is viewed as an adversary which tries to maximize a performance criterion: a criterion that the controller gains attempt to minimize. The optimal controller gains are determined by solving a nonlinear matrix two-point boundary value problem.
Model-Constrained Optimization Methods for Reduction of Parameterized Large-Scale Systems
2007-05-01
colorful with his stereo karaoke system. Anh Hai, thanks for helping me move my furnitures many times, and for all the beers too! To all Vietnamese...visit them. My trips to Springfield would have been very boring if Anh Tung (+ Thao) and Anh Danh (+ Thuy) had not turn on their super stereo karaoke ...expensive to solve, e.g. for applications such as optimal design or probabilistic analyses. Model order reduction is a powerful tool that permits the
Constraining the atmosphere of GJ 1214b using an optimal estimation technique
NASA Astrophysics Data System (ADS)
Barstow, J. K.; Aigrain, S.; Irwin, P. G. J.; Fletcher, L. N.; Lee, J.-M.
2013-09-01
We explore cloudy, extended H2-He atmosphere scenarios for the warm super-Earth GJ 1214b using an optimal estimation retrieval technique. This planet, orbiting an M4.5 star only 13 pc from the Earth, is of particular interest because it lies between the Earth and Neptune in size and may be a member of a new class of planet that is neither terrestrial nor gas giant. Its relatively flat transmission spectrum has so far made atmospheric characterization difficult. The Non-linear optimal Estimator for MultivariateE spectral analySIS (NEMESIS) algorithm is used to explore the degenerate model parameter space for a cloudy, H2-He-dominated atmosphere scenario. Optimal estimation is a data-led approach that allows solutions beyond the range permitted by ab initio equilibrium model atmosphere calculations, and as such prevents restriction from prior expectations. We show that optimal estimation retrieval is a powerful tool for this kind of study, and present an exploration of the degenerate atmospheric scenarios for GJ 1214b. Whilst we find a family of solutions that provide a very good fit to the data, the quality and coverage of these data are insufficient for us to more precisely determine the abundances of cloud and trace gases given an H2-He atmosphere, and we also cannot rule out the possibility of a high molecular weight atmosphere. Future ground- and space-based observations will provide the opportunity to confirm or rule out an extended H2-He atmosphere, but more precise constraints will be limited by intrinsic degeneracies in the retrieval problem, such as variations in cloud top pressure and temperature.
The Army Reserve: Optimally Seeking Relevance and Readiness in a Fiscally Constrained Environment
2013-05-23
foundation in theory and proof in reality. For example, Sir Isaac Newton’s Philosophiæ Naturalis Principia Mathematica (“the Principia”), published...Einstein superseded Newton with his general theory of relativity. Einstein’s theory accounted for additional variables outside Newton’s observations...of Dido, some 2,600 years before Sir Isaac Newton’s 74Klaus Krippendorff, “Optimization Theory,” Klaus Krippendorff’s Dictionary of Cybernetics
NASA Astrophysics Data System (ADS)
Guo, Weian; Li, Wuzhao; Zhang, Qun; Wang, Lei; Wu, Qidi; Ren, Hongliang
2014-11-01
In evolutionary algorithms, elites are crucial to maintain good features in solutions. However, too many elites can make the evolutionary process stagnate and cannot enhance the performance. This article employs particle swarm optimization (PSO) and biogeography-based optimization (BBO) to propose a hybrid algorithm termed biogeography-based particle swarm optimization (BPSO) which could make a large number of elites effective in searching optima. In this algorithm, the whole population is split into several subgroups; BBO is employed to search within each subgroup and PSO for the global search. Since not all the population is used in PSO, this structure overcomes the premature convergence in the original PSO. Time complexity analysis shows that the novel algorithm does not increase the time consumption. Fourteen numerical benchmarks and four engineering problems with constraints are used to test the BPSO. To better deal with constraints, a fuzzy strategy for the number of elites is investigated. The simulation results validate the feasibility and effectiveness of the proposed algorithm.
Analytical optimal controls for the state constrained addition and removal of cryoprotective agents
Chicone, Carmen C.; Critser, John K.
2014-01-01
Cryobiology is a field with enormous scientific, financial and even cultural impact. Successful cryopreservation of cells and tissues depends on the equilibration of these materials with high concentrations of permeating chemicals (CPAs) such as glycerol or 1,2 propylene glycol. Because cells and tissues are exposed to highly anisosmotic conditions, the resulting gradients cause large volume fluctuations that have been shown to damage cells and tissues. On the other hand, there is evidence that toxicity to these high levels of chemicals is time dependent, and therefore it is ideal to minimize exposure time as well. Because solute and solvent flux is governed by a system of ordinary differential equations, CPA addition and removal from cells is an ideal context for the application of optimal control theory. Recently, we presented a mathematical synthesis of the optimal controls for the ODE system commonly used in cryobiology in the absence of state constraints and showed that controls defined by this synthesis were optimal. Here we define the appropriate model, analytically extend the previous theory to one encompassing state constraints, and as an example apply this to the critical and clinically important cell type of human oocytes, where current methodologies are either difficult to implement or have very limited success rates. We show that an enormous increase in equilibration efficiency can be achieved under the new protocols when compared to classic protocols, potentially allowing a greatly increased survival rate for human oocytes, and pointing to a direction for the cryopreservation of many other cell types. PMID:22527943
Analytical optimal controls for the state constrained addition and removal of cryoprotective agents.
Benson, James D; Chicone, Carmen C; Critser, John K
2012-07-01
Cryobiology is a field with enormous scientific, financial, and even cultural impact. Successful cryopreservation of cells and tissues depends on the equilibration of these materials with high concentrations of permeating chemicals (CPAs) such as glycerol or 1,2 propylene glycol. Because cells and tissues are exposed to highly anisosmotic conditions, the resulting gradients cause large volume fluctuations that have been shown to damage cells and tissues. On the other hand, there is evidence that toxicity to these high levels of chemicals is time dependent, and therefore it is ideal to minimize exposure time as well. Because solute and solvent flux is governed by a system of ordinary differential equations, CPA addition and removal from cells is an ideal context for the application of optimal control theory. Recently, we presented a mathematical synthesis of the optimal controls for the ODE system commonly used in cryobiology in the absence of state constraints and showed that controls defined by this synthesis were optimal. Here we define the appropriate model, analytically extend the previous theory to one encompassing state constraints, and as an example apply this to the critical and clinically important cell type of human oocytes, where current methodologies are either difficult to implement or have very limited success rates. We show that an enormous increase in equilibration efficiency can be achieved under the new protocols when compared to classic protocols, potentially allowing a greatly increased survival rate for human oocytes and pointing to a direction for the cryopreservation of many other cell types.
NASA Astrophysics Data System (ADS)
Pandiyan, Vimal Prabhu; Khare, Kedar; John, Renu
2016-10-01
We demonstrate a single-shot near on-axis digital holographic microscope that uses a constrained optimization approach for retrieval of the complex object function in the hologram plane. The recovered complex object is back-propagated from the hologram plane to image plane using the Fresnel back-propagation algorithm. A numerical aberration compensation algorithm is employed for correcting the aberrations in the object beam. The reference beam angle is calculated automatically using the modulation property of Fourier transform without any additional recording. We demonstrate this approach using a United States Air Force (USAF) resolution target as an object on our digital holographic microscope. We also demonstrate this approach by recovering the quantitative phase images of live yeast cells, red blood cells and dynamics of live dividing yeast cells.
Rafique, Rashid; Kumar, Sandeep; Luo, Yiqi; Kiely, Gerard; Asrar, Ghassem R.
2015-02-01
he accurate calibration of complex biogeochemical models is essential for the robust estimation of soil greenhouse gases (GHG) as well as other environmental conditions and parameters that are used in research and policy decisions. DayCent is a popular biogeochemical model used both nationally and internationally for this purpose. Despite DayCent’s popularity, its complex parameter estimation is often based on experts’ knowledge which is somewhat subjective. In this study we used the inverse modelling parameter estimation software (PEST), to calibrate the DayCent model based on sensitivity and identifi- ability analysis. Using previously published N2 O and crop yield data as a basis of our calibration approach, we found that half of the 140 parameters used in this study were the primary drivers of calibration dif- ferences (i.e. the most sensitive) and the remaining parameters could not be identified given the data set and parameter ranges we used in this study. The post calibration results showed improvement over the pre-calibration parameter set based on, a decrease in residual differences 79% for N2O fluxes and 84% for crop yield, and an increase in coefficient of determination 63% for N2O fluxes and 72% for corn yield. The results of our study suggest that future studies need to better characterize germination tem- perature, number of degree-days and temperature dependency of plant growth; these processes were highly sensitive and could not be adequately constrained by the data used in our study. Furthermore, the sensitivity and identifiability analysis was helpful in providing deeper insight for important processes and associated parameters that can lead to further improvement in calibration of DayCent model.
NASA Astrophysics Data System (ADS)
Morimoto, Kenichi; Kinoshita, Hidenori; Suzuki, Yuji
2016-11-01
In the present study, an adjoint-based shape-optimization method has been developed for designing extended heat transfer surfaces in conjugate heat transfer problems. Here we specifically consider heat conduction-dominated solidification problem under different thermal boundary conditions: (i) the isothermal condition, and (ii) the conjugate condition with thermal coupling between the solidified liquid and the solid wall inside the domain bounded by the extended heat transfer surface. In the present shape-optimization scheme, extended heat transfer surfaces are successively refined in a local way based on the variational information of a cost functional with respect to the shape modification. In the computation of the developed scheme, a meshless method is employed for dealing with the complex boundary shape. For high-resolution analyses with boundary-fitted node arrangement, we have introduced a bubble-mesh method combined with a high-efficiency algorithm for searching neighboring bubbles within a cut-off distance. The present technique can be easily applied to convection problems including high Reynolds number flow. We demonstrate, for the isothermal boundary condition, that the present optimization leads to tree-like fin shapes, which achieve the temperature field with global similarity for different initial fin shapes. We will also show the computational results for the conjugate condition, which would regularize the present optimization due to the fin-efficiency effect.
Correction of linear-array lidar intensity data using an optimal beam shaping approach
NASA Astrophysics Data System (ADS)
Xu, Fan; Wang, Yuanqing; Yang, Xingyu; Zhang, Bingqing; Li, Fenfang
2016-08-01
The linear-array lidar has been recently developed and applied for its superiority of vertically non-scanning, large field of view, high sensitivity and high precision. The beam shaper is the key component for the linear-array detection. However, the traditional beam shaping approaches can hardly satisfy our requirement for obtaining unbiased and complete backscattered intensity data. The required beam distribution should roughly be oblate U-shaped rather than Gaussian or uniform. Thus, an optimal beam shaping approach is proposed in this paper. By employing a pair of conical lenses and a cylindrical lens behind the beam expander, the expanded Gaussian laser was shaped to a line-shaped beam whose intensity distribution is more consistent with the required distribution. To provide a better fit to the requirement, off-axis method is adopted. The design of the optimal beam shaping module is mathematically explained and the experimental verification of the module performance is also presented in this paper. The experimental results indicate that the optimal beam shaping approach can effectively correct the intensity image and provide ~30% gain of detection area over traditional approach, thus improving the imaging quality of linear-array lidar.
On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications
NASA Technical Reports Server (NTRS)
Madavan, Nateri K.
2004-01-01
Differential Evolution (DE) is a simple and robust evolutionary strategy that has been provEn effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. Several approaches that have proven effective for other evolutionary algorithms are modified and implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for standard test optimization problems and for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.
Transient operation and shape optimization of a single PEM fuel cell
NASA Astrophysics Data System (ADS)
Chen, Sheng; Ordonez, Juan C.; Vargas, Jose V. C.; Gardolinski, Jose E. F.; Gomes, Maria A. B.
Geometric design, including the internal structure and external shape, considerably affect the thermal, fluid, and electrochemical characteristics of a polymer electrolyte membrane (PEM) fuel cell, which determine the polarization curves as well as the thermal and power inertias. Shape optimization is a natural alternative to improve the fuel cell performance and make fuel cells more attractive for power generation. This paper investigates the internal and external structure effects on the fuel cell steady and transient operation with consideration of stoichiometric ratios, pumping power, and working temperature limits. The maximal steady state net power output and the fuel cell start-up time under a step-changed current load characterize the fuel cell steady and transient performance respectively. The one-dimensional PEM fuel cell (PEMFC) thermal model introduced in a previous work [J.V.C. Vargas, J.C. Ordonez, A. Bejan, Constructal flow structure for a PEM fuel cell, Int. J. Heat Mass Transfer 47 (2004) 4177-4193] is amended to simulate the fuel cell transient start-up process. The shape optimization consists of the internal and external PEMFC structure optimization. The internal optimization focuses on the optimal allocation of fuel cell compartment thicknesses. The external optimization process seeks the PEM fuel cell optimal external aspect ratios. These two levels of optimizations pursue the optimal geometric design with quick response to the step loads and large power densities. Appropriate dimensionless groups are identified and the numerical results are presented in dimensionless charts for general engineering design. The universality of the general optimal shape found is also discussed.
Optimization of a constrained linear monochromator design for neutral atom beams.
Kaltenbacher, Thomas
2016-04-01
A focused ground state, neutral atom beam, exploiting its de Broglie wavelength by means of atom optics, is used for neutral atom microscopy imaging. Employing Fresnel zone plates as a lens for these beams is a well established microscopy technique. To date, even for favorable beam source conditions a minimal focus spot size of slightly below 1μm was reached. This limitation is essentially given by the intrinsic spectral purity of the beam in combination with the chromatic aberration of the diffraction based zone plate. Therefore, it is important to enhance the monochromaticity of the beam, enabling a higher spatial resolution, preferably below 100nm. We propose to increase the monochromaticity of a neutral atom beam by means of a so-called linear monochromator set-up - a Fresnel zone plate in combination with a pinhole aperture - in order to gain more than one order of magnitude in spatial resolution. This configuration is known in X-ray microscopy and has proven to be useful, but has not been applied to neutral atom beams. The main result of this work is optimal design parameters based on models for this linear monochromator set-up followed by a second zone plate for focusing. The optimization was performed for minimizing the focal spot size and maximizing the centre line intensity at the detector position for an atom beam simultaneously. The results presented in this work are for, but not limited to, a neutral helium atom beam.
Atkinson, Ian C.; Lu, Aiming; Thulborn, Keith R.
2011-01-01
The rapid transverse relaxation of the sodium magnetic resonance (MR) signal during spatial encoding causes a loss of image resolution, an effect known as T2-blurring. Conventional wisdom suggests that spatial resolution is maximized by keeping the readout duration as short as possible to minimize T2-blurring. Flexible twisted projection imaging (flexTPI) performed with an ultra-short echo time, relative to T2, and a long repetition time, relative to T1, has been shown to be effective for quantitative sodium MR imaging. A minimized readout duration requires a very large number of projections and, consequentially, results in an impractically long total acquisition time to meet these conditions. When the total acquisition time is limited to a clinically practical duration (e.g., 10 minutes), the optimal parameters for maximal spatial resolution of a flexTPI acquisition do not correspond to the shortest possible readout. Simulation and experimental results for resolution optimized acquisition parameters of quantitative sodium flexTPI of parenchyma and cerebrospinal fluid are presented for the human brain at 9.4T and 3T. The effect of signal loss during data collection on sodium quantification bias and image signal-to-noise ratio are discussed. PMID:21446034
NASA Technical Reports Server (NTRS)
Madavan, Nateri K.
2004-01-01
Differential Evolution (DE) is a simple, fast, and robust evolutionary algorithm that has proven effective in determining the global optimum for several difficult single-objective optimization problems. The DE algorithm has been recently extended to multiobjective optimization problem by using a Pareto-based approach. In this paper, a Pareto DE algorithm is applied to multiobjective aerodynamic shape optimization problems that are characterized by computationally expensive objective function evaluations. To improve computational expensive the algorithm is coupled with generalized response surface meta-models based on artificial neural networks. Results are presented for some test optimization problems from the literature to demonstrate the capabilities of the method.
NASA Astrophysics Data System (ADS)
El Abdi, R.; Touratier, M.; Convert, P.; Lalanne, B.
1994-06-01
The structural shape optimization of a complex shell under complex criteria is presented. The shell is one of various cases of a turboshaft, and optimization criteria are associated with the cost, the technology, and above all the working conditions for the turboshaft. Optimization criteria involved are of course the weight of the structure, but also the plastic flow, plastic instability and fatigue life. The fatigue life criterion is an extension to the three-dimensional state of the one-dimensional Lemaitre-Chaboche rule, taking into account the elasto-plastic Neuber correction. All computations have been made with the ANSYS finite element program in which an optimization module exists.
A multi-fidelity analysis selection method using a constrained discrete optimization formulation
NASA Astrophysics Data System (ADS)
Stults, Ian C.
The purpose of this research is to develop a method for selecting the fidelity of contributing analyses in computer simulations. Model uncertainty is a significant component of result validity, yet it is neglected in most conceptual design studies. When it is considered, it is done so in only a limited fashion, and therefore brings the validity of selections made based on these results into question. Neglecting model uncertainty can potentially cause costly redesigns of concepts later in the design process or can even cause program cancellation. Rather than neglecting it, if one were to instead not only realize the model uncertainty in tools being used but also use this information to select the tools for a contributing analysis, studies could be conducted more efficiently and trust in results could be quantified. Methods for performing this are generally not rigorous or traceable, and in many cases the improvement and additional time spent performing enhanced calculations are washed out by less accurate calculations performed downstream. The intent of this research is to resolve this issue by providing a method which will minimize the amount of time spent conducting computer simulations while meeting accuracy and concept resolution requirements for results. In many conceptual design programs, only limited data is available for quantifying model uncertainty. Because of this data sparsity, traditional probabilistic means for quantifying uncertainty should be reconsidered. This research proposes to instead quantify model uncertainty using an evidence theory formulation (also referred to as Dempster-Shafer theory) in lieu of the traditional probabilistic approach. Specific weaknesses in using evidence theory for quantifying model uncertainty are identified and addressed for the purposes of the Fidelity Selection Problem. A series of experiments was conducted to address these weaknesses using n-dimensional optimization test functions. These experiments found that model
Shape optimization and characterization of polysaccharide beads prepared by ionotropic gelation.
Smrdel, Polona; Bogataj, Marija; Zega, Anamarija; Planinsek, Odon; Mrhar, Ales
2008-03-01
The shape of drug loaded polysaccharide beads produced by ionotropic gelation has been optimized, with the aim of producing spherical beads suitable for further technological operations, such as coating. The optimization was performed on a model system sodium alginate/theophylline by inclusion of various fillers. Incorporation of excipients markedly influenced the morphological characteristics of the beads. The undesired irregular shape of beads caused by incorporation of the drug could only be improved by incorporating a combination of polycarbophil (PK) and polyvinylpyrrolidone (PVP). The spherical shape of these beads was stabilized mechanically by numerous air bubbles trapped inside the beads, which prevented the collapse of the beads during drying. The optimized method was shown to be applicable to a target system of pectin and an anti-inflammatory drug, LK-423.
Optimal shapes of surface-slip driven self-propelled swimmers
NASA Astrophysics Data System (ADS)
Vilfan, Andrej; Osterman, Natan
2012-11-01
If one defines the swimming efficiency of a microorganism as the power needed to move it against viscous drag, divided by the total dissipated power, one usually finds values no better than 1%. In order to find out how close this is to the theoretically achievable optimum, we first introduced a new efficiency measure at the level of a single cilium or an infinite ciliated surface and numerically determined the optimal beating patterns according to this criterion. In the following we also determined 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.
Using High Resolution Design Spaces for Aerodynamic Shape Optimization Under Uncertainty
NASA Technical Reports Server (NTRS)
Li, Wu; Padula, Sharon
2004-01-01
This paper explains why high resolution design spaces encourage traditional airfoil optimization algorithms to generate noisy shape modifications, which lead to inaccurate linear predictions of aerodynamic coefficients and potential failure of descent methods. By using auxiliary drag constraints for a simultaneous drag reduction at all design points and the least shape distortion to achieve the targeted drag reduction, an improved algorithm generates relatively smooth optimal airfoils with no severe off-design performance degradation over a range of flight conditions, in high resolution design spaces parameterized by cubic B-spline functions. Simulation results using FUN2D in Euler flows are included to show the capability of the robust aerodynamic shape optimization method over a range of flight conditions.
Optimization of the heating surface shape in the contact melting problem
NASA Technical Reports Server (NTRS)
Fomin, Sergei A.; Cheng, Shangmo
1991-01-01
The theoretical analysis of contact melting by the migrating heat source with an arbitrary shaped isothermal heating surface is presented. After the substantiated simplification, the governing equations are transformed to the convenient equations for engineering calculations relationships. Analytical solutions are used for numerical prediction of optimal shape of the heating surface. The problem is investigated for the constant and for temperature dependent physical properties of the melt.
NASA Technical Reports Server (NTRS)
Nash, Stephen G.; Polyak, R.; Sofer, Ariela
1994-01-01
When a classical barrier method is applied to the solution of a nonlinear programming problem with inequality constraints, the Hessian matrix of the barrier function becomes increasingly ill-conditioned as the solution is approached. As a result, it may be desirable to consider alternative numerical algorithms. We compare the performance of two methods motivated by barrier functions. The first is a stabilized form of the classical barrier method, where a numerically stable approximation to the Newton direction is used when the barrier parameter is small. The second is a modified barrier method where a barrier function is applied to a shifted form of the problem, and the resulting barrier terms are scaled by estimates of the optimal Lagrange multipliers. The condition number of the Hessian matrix of the resulting modified barrier function remains bounded as the solution to the constrained optimization problem is approached. Both of these techniques can be used in the context of a truncated-Newton method, and hence can be applied to large problems, as well as on parallel computers. In this paper, both techniques are applied to problems with bound constraints and we compare their practical behavior.
Xu, Y; Li, N
2014-09-01
Biological species have produced many simple but efficient rules in their complex and critical survival activities such as hunting and mating. A common feature observed in several biological motion strategies is that the predator only moves along paths in a carefully selected or iteratively refined subspace (or manifold), which might be able to explain why these motion strategies are effective. In this paper, a unified linear algebraic formulation representing such a predator-prey relationship is developed to simplify the construction and refinement process of the subspace (or manifold). Specifically, the following three motion strategies are studied and modified: motion camouflage, constant absolute target direction and local pursuit. The framework constructed based on this varying subspace concept could significantly reduce the computational cost in solving a class of nonlinear constrained optimal trajectory planning problems, particularly for the case with severe constraints. Two non-trivial examples, a ground robot and a hypersonic aircraft trajectory optimization problem, are used to show the capabilities of the algorithms in this new computational framework.
Tooth shape optimization of brushless permanent magnet motors for reducing torque ripples
NASA Astrophysics Data System (ADS)
Hsu, Liang-Yi; Tsai, Mi-Ching
2004-11-01
This paper presents a tooth shape optimization method based on a generic algorithm to reduce the torque ripple of brushless permanent magnet motors under two different magnetization directions. The analysis of this design method mainly focuses on magnetic saturation and cogging torque and the computation of the optimization process is based on an equivalent magnetic network circuit. The simulation results, obtained from the finite element analysis, are used to confirm the accuracy and performance. Finite element analysis results from different tooth shapes are compared to show the effectiveness of the proposed method.
NASA Astrophysics Data System (ADS)
Molina, Andrew; Smereka, Peter; Zimmerman, Paul M.
2016-03-01
The use of alternate coordinate systems as a means to improve the efficiency and accuracy of anharmonic vibrational structure analysis has seen renewed interest in recent years. While normal modes (which diagonalize the mass-weighted Hessian matrix) are a typical choice, the delocalized nature of this basis makes it less optimal when anharmonicity is in play. When a set of modes is not designed to treat anharmonicity, anharmonic effects will contribute to inter-mode coupling in an uncontrolled fashion. These effects can be mitigated by introducing locality, but this comes at its own cost of potentially large second-order coupling terms. Herein, a method is described which partially localizes vibrations to connect the fully delocalized and fully localized limits. This allows a balance between the treatment of harmonic and anharmonic coupling, which minimizes the error that arises from neglected coupling terms. Partially localized modes are investigated for a range of model systems including a tetramer of hydrogen fluoride, water dimer, ethene, diphenylethane, and stilbene. Generally, partial localization reaches ˜75% of maximal locality while introducing less than ˜30% of the harmonic coupling of the fully localized system. Furthermore, partial localization produces mode pairs that are spatially separated and thus weakly coupled to one another. It is likely that this property can be exploited in the creation of model Hamiltonians that omit the coupling parameters of the distant (and therefore uncoupled) pairs.
Copy number variants calling for single cell sequencing data by multi-constrained optimization.
Xu, Bo; Cai, Hongmin; Zhang, Changsheng; Yang, Xi; Han, Guoqiang
2016-08-01
Variations in DNA copy number carry important information on genome evolution and regulation of DNA replication in cancer cells. The rapid development of single-cell sequencing technology allows one to explore gene expression heterogeneity among single-cells, thus providing important cancer cell evolution information. Single-cell DNA/RNA sequencing data usually have low genome coverage, which requires an extra step of amplification to accumulate enough samples. However, such amplification will introduce large bias and makes bioinformatics analysis challenging. Accurately modeling the distribution of sequencing data and effectively suppressing the bias influence is the key to success variations analysis. Recent advances demonstrate the technical noises by amplification are more likely to follow negative binomial distribution, a special case of Poisson distribution. Thus, we tackle the problem CNV detection by formulating it into a quadratic optimization problem involving two constraints, in which the underling signals are corrupted by Poisson distributed noises. By imposing the constraints of sparsity and smoothness, the reconstructed read depth signals from single-cell sequencing data are anticipated to fit the CNVs patterns more accurately. An efficient numerical solution based on the classical alternating direction minimization method (ADMM) is tailored to solve the proposed model. We demonstrate the advantages of the proposed method using both synthetic and empirical single-cell sequencing data. Our experimental results demonstrate that the proposed method achieves excellent performance and high promise of success with single-cell sequencing data.
Scheduling Multilevel Deadline-Constrained Scientific Workflows on Clouds Based on Cost Optimization
Malawski, Maciej; Figiela, Kamil; Bubak, Marian; ...
2015-01-01
This paper presents a cost optimization model for scheduling scientific workflows on IaaS clouds such as Amazon EC2 or RackSpace. We assume multiple IaaS clouds with heterogeneous virtual machine instances, with limited number of instances per cloud and hourly billing. Input and output data are stored on a cloud object store such as Amazon S3. Applications are scientific workflows modeled as DAGs as in the Pegasus Workflow Management System. We assume that tasks in the workflows are grouped into levels of identical tasks. Our model is specified using mathematical programming languages (AMPL and CMPL) and allows us to minimize themore » cost of workflow execution under deadline constraints. We present results obtained using our model and the benchmark workflows representing real scientific applications in a variety of domains. The data used for evaluation come from the synthetic workflows and from general purpose cloud benchmarks, as well as from the data measured in our own experiments with Montage, an astronomical application, executed on Amazon EC2 cloud. We indicate how this model can be used for scenarios that require resource planning for scientific workflows and their ensembles.« less
Moissenet, Florent; Chèze, Laurence; Dumas, Raphaël
2012-06-01
Inverse dynamics combined with a constrained static optimization analysis has often been proposed to solve the muscular redundancy problem. Typically, the optimization problem consists in a cost function to be minimized and some equality and inequality constraints to be fulfilled. Penalty-based and Lagrange multipliers methods are common optimization methods for the equality constraints management. More recently, the pseudo-inverse method has been introduced in the field of biomechanics. The purpose of this paper is to evaluate the ability and the efficiency of this new method to solve the muscular redundancy problem, by comparing respectively the musculo-tendon forces prediction and its cost-effectiveness against common optimization methods. Since algorithm efficiency and equality constraints fulfillment highly belong to the optimization method, a two-phase procedure is proposed in order to identify and compare the complexity of the cost function, the number of iterations needed to find a solution and the computational time of the penalty-based method, the Lagrange multipliers method and pseudo-inverse method. Using a 2D knee musculo-skeletal model in an isometric context, the study of the cost functions isovalue curves shows that the solution space is 2D with the penalty-based method, 3D with the Lagrange multipliers method and 1D with the pseudo-inverse method. The minimal cost function area (defined as the area corresponding to 5% over the minimal cost) obtained for the pseudo-inverse method is very limited and along the solution space line, whereas the minimal cost function area obtained for other methods are larger or more complex. Moreover, when using a 3D lower limb musculo-skeletal model during a gait cycle simulation, the pseudo-inverse method provides the lowest number of iterations while Lagrange multipliers and pseudo-inverse method have almost the same computational time. The pseudo-inverse method, by providing a better suited cost function and an
NASA Astrophysics Data System (ADS)
Widdle, Richard D., Jr.; Grimshaw, Matthew T.; Shome, Moushumi
2009-03-01
A method is described for solving an inverse design problem to find the unassembled, stress-free component shapes of a structure thatis integrally actuated with shape memory alloy (SMA) actuators. Morphing and multifunctional structures are of interest in the aerospace industry becasue of the potential for improving structural and aerodynamic performance across multiple operating conditions. The focus of this work is on structures that are morphed with SMA flexural actuators. For the case where the geometry is known for unassembled components, assembly can be simulated to find the assembled shapes of the morphing structure. In the usual design case, however, only the desired shapes as assembled are known in multiple actuation states, and the corresponding unassembled shapes must be determined by an iterative solution process. An iterative finite element analysis approach to this problem is reported here. First an initial guess for the unassembled shapes is made and assembly is simulated with the finite element method. The resulting shapes are found for both SMA phases and compared with the desired shapes. A gradient-based optimization method is employed to update the initial geometry and iteration continues until the desired shapes are achieved. A simplified method of modeling the SMA material behavior is used for computational efficiently. It is found that this approach provides a practical way to solve the inverse design problem for structures that are integrally actuated with SMA material.
On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications
NASA Technical Reports Server (NTRS)
Madavan, Nateri K.
2004-01-01
Differential Evolution (DE) is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. These approaches are implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.
Shape optimization in steady blood flow: a numerical study of non-Newtonian effects.
Abraham, Feby; Behr, Marek; Heinkenschloss, Matthias
2005-04-01
We investigate the influence of the fluid constitutive model on the outcome of shape optimization tasks, motivated by optimal design problems in biomedical engineering. Our computations are based on the Navier-Stokes equations generalized to non-Newtonian fluid, with the modified Cross model employed to account for the shear-thinning behavior of blood. The generalized Newtonian treatment exhibits striking differences in the velocity field for smaller shear rates. We apply sensitivity-based optimization procedure to a flow through an idealized arterial graft. For this problem we study the influence of the inflow velocity, and thus the shear rate. Furthermore, we introduce an additional factor in the form of a geometric parameter, and study its effect on the optimal shape obtained.
Effective Alternating Direction Optimization Methods for Sparsity-Constrained Blind Image Deblurring
Xiong, Naixue; Liu, Ryan Wen; Liang, Maohan; Wu, Di; Liu, Zhao; Wu, Huisi
2017-01-01
Single-image blind deblurring for imaging sensors in the Internet of Things (IoT) is a challenging ill-conditioned inverse problem, which requires regularization techniques to stabilize the image restoration process. The purpose is to recover the underlying blur kernel and latent sharp image from only one blurred image. Under many degraded imaging conditions, the blur kernel could be considered not only spatially sparse, but also piecewise smooth with the support of a continuous curve. By taking advantage of the hybrid sparse properties of the blur kernel, a hybrid regularization method is proposed in this paper to robustly and accurately estimate the blur kernel. The effectiveness of the proposed blur kernel estimation method is enhanced by incorporating both the L1-norm of kernel intensity and the squared L2-norm of the intensity derivative. Once the accurate estimation of the blur kernel is obtained, the original blind deblurring can be simplified to the direct deconvolution of blurred images. To guarantee robust non-blind deconvolution, a variational image restoration model is presented based on the L1-norm data-fidelity term and the total generalized variation (TGV) regularizer of second-order. All non-smooth optimization problems related to blur kernel estimation and non-blind deconvolution are effectively handled by using the alternating direction method of multipliers (ADMM)-based numerical methods. Comprehensive experiments on both synthetic and realistic datasets have been implemented to compare the proposed method with several state-of-the-art methods. The experimental comparisons have illustrated the satisfactory imaging performance of the proposed method in terms of quantitative and qualitative evaluations. PMID:28106764
Xiong, Naixue; Liu, Ryan Wen; Liang, Maohan; Wu, Di; Liu, Zhao; Wu, Huisi
2017-01-18
Single-image blind deblurring for imaging sensors in the Internet of Things (IoT) is a challenging ill-conditioned inverse problem, which requires regularization techniques to stabilize the image restoration process. The purpose is to recover the underlying blur kernel and latent sharp image from only one blurred image. Under many degraded imaging conditions, the blur kernel could be considered not only spatially sparse, but also piecewise smooth with the support of a continuous curve. By taking advantage of the hybrid sparse properties of the blur kernel, a hybrid regularization method is proposed in this paper to robustly and accurately estimate the blur kernel. The effectiveness of the proposed blur kernel estimation method is enhanced by incorporating both the L 1 -norm of kernel intensity and the squared L 2 -norm of the intensity derivative. Once the accurate estimation of the blur kernel is obtained, the original blind deblurring can be simplified to the direct deconvolution of blurred images. To guarantee robust non-blind deconvolution, a variational image restoration model is presented based on the L 1 -norm data-fidelity term and the total generalized variation (TGV) regularizer of second-order. All non-smooth optimization problems related to blur kernel estimation and non-blind deconvolution are effectively handled by using the alternating direction method of multipliers (ADMM)-based numerical methods. Comprehensive experiments on both synthetic and realistic datasets have been implemented to compare the proposed method with several state-of-the-art methods. The experimental comparisons have illustrated the satisfactory imaging performance of the proposed method in terms of quantitative and qualitative evaluations.
Aerodynamic Shape Optimization Using A Real-Number-Encoded Genetic Algorithm
NASA Technical Reports Server (NTRS)
Holst, Terry L.; Pulliam, Thomas H.
2001-01-01
A new method for aerodynamic shape optimization using a genetic algorithm with real number encoding is presented. The algorithm is used to optimize three different problems, a simple hill climbing problem, a quasi-one-dimensional nozzle problem using an Euler equation solver and a three-dimensional transonic wing problem using a nonlinear potential solver. Results indicate that the genetic algorithm is easy to implement and extremely reliable, being relatively insensitive to design space noise.
Khodabakhshi, F.; Kazeminezhad, M. Kokabi, A.H.
2012-07-15
Constrained groove pressing as a severe plastic deformation method is utilized to produce ultra-fine grained low carbon steel sheets. The ultra-fine grained sheets are joined via resistance spot welding process and the characteristics of spot welds are investigated. Resistance spot welding process is optimized for welding of the sheets with different severe deformations and their results are compared with those of as-received samples. The effects of failure mode and expulsion on the performance of ultra-fine grained sheet spot welds have been investigated in the present paper and the welding current and time of resistance spot welding process according to these subjects are optimized. Failure mode and failure load obtained in tensile-shear test, microhardness, X-ray diffraction, transmission electron microscope and scanning electron microscope images have been used to describe the performance of spot welds. The region between interfacial to pullout mode transition and expulsion limit is defined as the optimum welding condition. The results show that optimum welding parameters (welding current and welding time) for ultra-fine grained sheets are shifted to lower values with respect to those for as-received specimens. In ultra-fine grained sheets, one new region is formed named recrystallized zone in addition to fusion zone, heat affected zone and base metal. It is shown that microstructures of different zones in ultra-fine grained sheets are finer than those of as-received sheets. - Highlights: Black-Right-Pointing-Pointer Resistance spot welding process is optimized for joining of UFG steel sheets. Black-Right-Pointing-Pointer Optimum welding current and time are decreased with increasing the CGP pass number. Black-Right-Pointing-Pointer Microhardness at BM, HAZ, FZ and recrystallized zone is enhanced due to CGP.
NASA Astrophysics Data System (ADS)
Jung, Jaewoon; Re, Suyong; Sugita, Yuji; Ten-no, Seiichiro
2013-01-01
The nudged elastic band (NEB) and string methods are widely used to obtain the reaction path of chemical reactions and phase transitions. In these methods, however, it is difficult to define an accurate Lagrangian to generate the conservative forces. On the other hand, the constrained optimization with locally updated planes (CO-LUP) scheme defines target function properly and suitable for micro-iteration optimizations in quantum mechanical/molecular mechanical (QM/MM) systems, which uses the efficient second order QM optimization. However, the method does have problems of inaccurate estimation of reactions and inappropriate accumulation of images around the energy minimum. We introduce three modifications into the CO-LUP scheme to overcome these problems: (1) An improved tangent estimation of the reaction path, which is used in the NEB method, (2) redistribution of images using an energy-weighted interpolation before updating local tangents, and (3) reduction of the number of constraints, in particular translation/rotation constraints, for improved convergence. First, we test the method on the isomerization of alanine dipeptide without QM/MM calculation, showing that the method is comparable to the string method both in accuracy and efficiency. Next, we apply the method for defining the reaction paths of the rearrangement reaction catalyzed by chorismate mutase (CM) and of the phosphoryl transfer reaction catalyzed by cAMP-dependent protein kinase (PKA) using generalized hybrid orbital QM/MM calculations. The reaction energy barrier of CM is in high agreement with the experimental value. The path of PKA reveals that the enzyme reaction is associative and there is a late transfer of the substrate proton to Asp 166, which is in agreement with the recently published result using the NEB method.
Shape Optimization of Supersonic Turbines Using Response Surface and Neural Network Methods
NASA Technical Reports Server (NTRS)
Papila, Nilay; Shyy, Wei; Griffin, Lisa W.; Dorney, Daniel J.
2001-01-01
Turbine performance directly affects engine specific impulse, thrust-to-weight ratio, and cost in a rocket propulsion system. A global optimization framework combining the radial basis neural network (RBNN) and the polynomial-based response surface method (RSM) is constructed for shape optimization of a supersonic turbine. Based on the optimized preliminary design, shape optimization is performed for the first vane and blade of a 2-stage supersonic turbine, involving O(10) design variables. The design of experiment approach is adopted to reduce the data size needed by the optimization task. It is demonstrated that a major merit of the global optimization approach is that it enables one to adaptively revise the design space to perform multiple optimization cycles. This benefit is realized when an optimal design approaches the boundary of a pre-defined design space. Furthermore, by inspecting the influence of each design variable, one can also gain insight into the existence of multiple design choices and select the optimum design based on other factors such as stress and materials considerations.
NASA Technical Reports Server (NTRS)
Koschny, D.; Gritsevich, M.; Barentsen, G.
2011-01-01
Different authors have produced models for the physical properties of meteoroids based on the shape of a meteor's light curve, typically from short observing campaigns. We here analyze the height profiles and light curves of approx.200 double-station meteors from the Leonids and Perseids using data from the Virtual Meteor Observatory, to demonstrate that with this web-based meteor database it is possible to analyze very large datasets from different authors in a consistent way. We compute the average heights for begin point, maximum luminosity, and end heights for Perseids and Leonids. We also compute the skew of the light curve, usually called the F-parameter. The results compare well with other author's data. We display the average light curve in a novel way to assess the light curve shape in addition to using the F-parameter. While the Perseids show a peaked light curve, the average Leonid light curve has a more flat peak. This indicates that the particle distribution of Leonid meteors can be described by a Gaussian distribution; the Perseids can be described with a power law. The skew for Leonids is smaller than for Perseids, indicating that the Leonids are more fragile than the Perseids.
Sridar, Pradeeba; Kumar, Ashnil; Li, Changyang; Woo, Joyce; Quinton, Ann; Benzie, Ron; Peek, Michael J; Feng, Dagan; Kumar, R Krishna; Nanan, Ralph; Kim, Jinman
2017-07-01
We derived an automated algorithm for accurately measuring the thalamic diameter from 2-D fetal ultrasound (US) brain images. The algorithm overcomes the inherent limitations of the US image modality: nonuniform density; missing boundaries; and strong speckle noise. We introduced a "guitar" structure that represents the negative space surrounding the thalamic regions. The guitar acts as a landmark for deriving the widest points of the thalamus even when its boundaries are not identifiable. We augmented a generalized level-set framework with a shape prior and constraints derived from statistical shape models of the guitars; this framework was used to segment US images and measure the thalamic diameter. Our segmentation method achieved a higher mean Dice similarity coefficient, Hausdorff distance, specificity, and reduced contour leakage when compared to other well-established methods. The automatic thalamic diameter measurement had an interobserver variability of -0.56 ± 2.29 mm compared to manual measurement by an expert sonographer. Our method was capable of automatically estimating the thalamic diameter, with the measurement accuracy on par with clinical assessment. Our method can be used as part of computer-assisted screening tools that automatically measure the biometrics of the fetal thalamus; these biometrics are linked to neurodevelopmental outcomes.
Caustic and its use in designing optimal absorber shapes for 2D concentrators
NASA Astrophysics Data System (ADS)
Ries, Harald; Spirkl, Wolfgang
1995-08-01
The caustic of a set of edge rays is defined as the set of intersection points of adjacent edge rays. For a body having a smooth differentiable contour, the caustic of its edge rays coincides with the contour of the body. Therefore one would assume that by calculating the caustic of the edge rays as they are produced by a 2D concentrator such as a trough, the optimal shape for the absorber, e.g. the minimal surface absorber capable of intercepting all rays, should also coincide with the shape of the caustic. We show that this conjecture is not valid in general, but only if the caustic indeed forms a closed smooth curve. For parabolic trough systems, the caustic intersects and forms closed domains for half rim angles of around 60 degrees and 120 degrees. In both cases the contour is not smooth. Therefore the optimal shape is not given by the domain enclosed by the caustic. We present a general recipe of how to construct minimum surface absorbers for given caustics in 2D and apply this to the case of trough parabolic concentrators. We show practical absorber shapes for parabolic troughs with various rim angles. The optimal contour depends discontinuously on the rim angle. The area of the optimum shape for a rim angle of 90 degrees is 0.72 of the area of the smallest cylindric absorber capable of intersecting all rays.
Forging tool shape optimization using pseudo inverse approach and adaptive incremental approach
NASA Astrophysics Data System (ADS)
Halouani, A.; Meng, F. J.; Li, Y. M.; Labergère, C.; Abbès, B.; Lafon, P.; Guo, Y. Q.
2013-05-01
This paper presents a simplified finite element method called "Pseudo Inverse Approach" (PIA) for tool shape design and optimization in multi-step cold forging processes. The approach is based on the knowledge of the final part shape. Some intermediate configurations are introduced and corrected by using a free surface method to consider the deformation paths without contact treatment. A robust direct algorithm of plasticity is implemented by using the equivalent stress notion and tensile curve. Numerical tests have shown that the PIA is very fast compared to the incremental approach. The PIA is used in an optimization procedure to automatically design the shapes of the preform tools. Our objective is to find the optimal preforms which minimize the equivalent plastic strain and punch force. The preform shapes are defined by B-Spline curves. A simulated annealing algorithm is adopted for the optimization procedure. The forging results obtained by the PIA are compared to those obtained by the incremental approach to show the efficiency and accuracy of the PIA.
Three-dimensional canard-wing shape optimization in aircraft cruise and maneuver environments
NASA Technical Reports Server (NTRS)
De Silva, B. M. E.; Carmichael, R. L.
1978-01-01
This paper demonstrates a numerical technique for canard-wing shape optimization at two operating conditions. For purposes of simplicity, a mean surface wing paneling code is employed for the aerodynamic calculations. The optimization procedures are based on the method of feasible directions. The shape functions for describing the thickness, camber, and twist are based on polynomial representations. The primary design requirements imposed restrictions on the canard and wing volumes and on the lift coefficients at the operating conditions. Results indicate that significant improvements in minimum drag and lift-to-drag ratio are possible with reasonable aircraft geometries. Calculations were done for supersonic speeds with Mach numbers ranging from 1 to 6. Planforms were mainly of a delta shape with aspect ratio of 1.
Optimal ligand descriptor for pocket recognition based on the Beta-shape.
Kim, Jae-Kwan; Won, Chung-In; Cha, Jehyun; Lee, Kichun; Kim, Deok-Soo
2015-01-01
Structure-based virtual screening is one of the most important and common computational methods for the identification of predicted hit at the beginning of drug discovery. Pocket recognition and definition is frequently a prerequisite of structure-based virtual screening, reducing the search space of the predicted protein-ligand complex. In this paper, we present an optimal ligand shape descriptor for a pocket recognition algorithm based on the beta-shape, which is a derivative structure of the Voronoi diagram of atoms. We investigate six candidates for a shape descriptor for a ligand using statistical analysis: the minimum enclosing sphere, three measures from the principal component analysis of atoms, the van der Waals volume, and the beta-shape volume. Among them, the van der Waals volume of a ligand is the optimal shape descriptor for pocket recognition and best tunes the pocket recognition algorithm based on the beta-shape for efficient virtual screening. The performance of the proposed algorithm is verified by a benchmark test.
Optimal Ligand Descriptor for Pocket Recognition Based on the Beta-Shape
Kim, Jae-Kwan; Won, Chung-In; Cha, Jehyun; Lee, Kichun; Kim, Deok-Soo
2015-01-01
Structure-based virtual screening is one of the most important and common computational methods for the identification of predicted hit at the beginning of drug discovery. Pocket recognition and definition is frequently a prerequisite of structure-based virtual screening, reducing the search space of the predicted protein-ligand complex. In this paper, we present an optimal ligand shape descriptor for a pocket recognition algorithm based on the beta-shape, which is a derivative structure of the Voronoi diagram of atoms. We investigate six candidates for a shape descriptor for a ligand using statistical analysis: the minimum enclosing sphere, three measures from the principal component analysis of atoms, the van der Waals volume, and the beta-shape volume. Among them, the van der Waals volume of a ligand is the optimal shape descriptor for pocket recognition and best tunes the pocket recognition algorithm based on the beta-shape for efficient virtual screening. The performance of the proposed algorithm is verified by a benchmark test. PMID:25835497
NASA Astrophysics Data System (ADS)
Osusky, Lana Maria
The increase in the availability and power of computational resources over the last fifteen years has contributed to the development of many different types of numerical optimization methods and created a large area of research focussed on numerical aerodynamic shape optimization and, more recently, high-fidelity multidisciplinary optimization. Numerical optimization provides dramatic savings when designing new aerodynamic configurations, as it allows the designer to focus more on the development of a well-posed design problem rather than on performing an exhaustive search of the design space via the traditional cut-and-try approach, which is expensive and time-consuming. It also reduces the dependence on the designer's experience and intuition, which can potentially lead to more optimal designs. Numerical optimization methods are particularly attractive when designing novel, unconventional aircraft for which the designer has no pre-existing studies or experiences from which to draw; these methods have the potential to discover new designs that might never have been arrived at without optimization. This work presents an extension of an efficient gradient-based numerical aerodynamic shape optimization algorithm to enable optimization in turbulent flow. The algorithm includes an integrated geometry parameterization and mesh movement scheme, an efficient parallel Newton-Krylov-Schur algorithm for solving the Reynolds-Averaged Navier-Stokes (RANS) equations, which are fully coupled with the one-equation Spalart-Allmaras turbulence model, and a discrete-adjoint gradient evaluation. In order to develop an efficient methodology for optimization in turbulent flows, the viscous and turbulent terms in the ii governing equations were linearized by hand. Additionally, a set of mesh refinement tools was introduced in order to obtain both an acceptable control volume mesh and a sufficiently refined computational mesh from an initial coarse mesh. A series of drag minimization
Efficient Gradient-Based Shape Optimization Methodology Using Inviscid/Viscous CFD
NASA Technical Reports Server (NTRS)
Baysal, Oktay
1997-01-01
The formerly developed preconditioned-biconjugate-gradient (PBCG) solvers for the analysis and the sensitivity equations had resulted in very large error reductions per iteration; quadratic convergence was achieved whenever the solution entered the domain of attraction to the root. Its memory requirement was also lower as compared to a direct inversion solver. However, this memory requirement was high enough to preclude the realistic, high grid-density design of a practical 3D geometry. This limitation served as the impetus to the first-year activity (March 9, 1995 to March 8, 1996). Therefore, the major activity for this period was the development of the low-memory methodology for the discrete-sensitivity-based shape optimization. This was accomplished by solving all the resulting sets of equations using an alternating-direction-implicit (ADI) approach. The results indicated that shape optimization problems which required large numbers of grid points could be resolved with a gradient-based approach. Therefore, to better utilize the computational resources, it was recommended that a number of coarse grid cases, using the PBCG method, should initially be conducted to better define the optimization problem and the design space, and obtain an improved initial shape. Subsequently, a fine grid shape optimization, which necessitates using the ADI method, should be conducted to accurately obtain the final optimized shape. The other activity during this period was the interaction with the members of the Aerodynamic and Aeroacoustic Methods Branch of Langley Research Center during one stage of their investigation to develop an adjoint-variable sensitivity method using the viscous flow equations. This method had algorithmic similarities to the variational sensitivity methods and the control-theory approach. However, unlike the prior studies, it was considered for the three-dimensional, viscous flow equations. The major accomplishment in the second period of this project
Stacking sequence and shape optimization of laminated composite plates via a level-set method
NASA Astrophysics Data System (ADS)
Allaire, G.; Delgado, G.
2016-12-01
We consider the optimal design of composite laminates by allowing a variable stacking sequence and in-plane shape of each ply. In order to optimize both variables we rely on a decomposition technique which aggregates the constraints into one unique constraint margin function. Thanks to this approach, an exactly equivalent bi-level optimization problem is established. This problem is made up of an inner level represented by the combinatorial optimization of the stacking sequence and an outer level represented by the topology and geometry optimization of each ply. We propose for the stacking sequence optimization an outer approximation method which iteratively solves a set of mixed integer linear problems associated to the evaluation of the constraint margin function. For the topology optimization of each ply, we lean on the level set method for the description of the interfaces and the Hadamard method for boundary variations by means of the computation of the shape gradient. Numerical experiments are performed on an aeronautic test case where the weight is minimized subject to different mechanical constraints, namely compliance, reserve factor and buckling load.
Shape optimization of pulsatile ventricular assist devices using FSI to minimize thrombotic risk
NASA Astrophysics Data System (ADS)
Long, C. C.; Marsden, A. L.; Bazilevs, Y.
2014-10-01
In this paper we perform shape optimization of a pediatric pulsatile ventricular assist device (PVAD). The device simulation is carried out using fluid-structure interaction (FSI) modeling techniques within a computational framework that combines FEM for fluid mechanics and isogeometric analysis for structural mechanics modeling. The PVAD FSI simulations are performed under realistic conditions (i.e., flow speeds, pressure levels, boundary conditions, etc.), and account for the interaction of air, blood, and a thin structural membrane separating the two fluid subdomains. The shape optimization study is designed to reduce thrombotic risk, a major clinical problem in PVADs. Thrombotic risk is quantified in terms of particle residence time in the device blood chamber. Methods to compute particle residence time in the context of moving spatial domains are presented in a companion paper published in the same issue (Comput Mech, doi: 10.1007/s00466-013-0931-y, 2013). The surrogate management framework, a derivative-free pattern search optimization method that relies on surrogates for increased efficiency, is employed in this work. For the optimization study shown here, particle residence time is used to define a suitable cost or objective function, while four adjustable design optimization parameters are used to define the device geometry. The FSI-based optimization framework is implemented in a parallel computing environment, and deployed with minimal user intervention. Using five SEARCH/ POLL steps the optimization scheme identifies a PVAD design with significantly better throughput efficiency than the original device.
Optimal input shaping for Fisher identifiability of control-oriented lithium-ion battery models
NASA Astrophysics Data System (ADS)
Rothenberger, Michael J.
This dissertation examines the fundamental challenge of optimally shaping input trajectories to maximize parameter identifiability of control-oriented lithium-ion battery models. Identifiability is a property from information theory that determines the solvability of parameter estimation for mathematical models using input-output measurements. This dissertation creates a framework that exploits the Fisher information metric to quantify the level of battery parameter identifiability, optimizes this metric through input shaping, and facilitates faster and more accurate estimation. The popularity of lithium-ion batteries is growing significantly in the energy storage domain, especially for stationary and transportation applications. While these cells have excellent power and energy densities, they are plagued with safety and lifespan concerns. These concerns are often resolved in the industry through conservative current and voltage operating limits, which reduce the overall performance and still lack robustness in detecting catastrophic failure modes. New advances in automotive battery management systems mitigate these challenges through the incorporation of model-based control to increase performance, safety, and lifespan. To achieve these goals, model-based control requires accurate parameterization of the battery model. While many groups in the literature study a variety of methods to perform battery parameter estimation, a fundamental issue of poor parameter identifiability remains apparent for lithium-ion battery models. This fundamental challenge of battery identifiability is studied extensively in the literature, and some groups are even approaching the problem of improving the ability to estimate the model parameters. The first approach is to add additional sensors to the battery to gain more information that is used for estimation. The other main approach is to shape the input trajectories to increase the amount of information that can be gained from input
Adaptive feature selection using v-shaped binary particle swarm optimization
Dong, Hongbin; Zhou, Xiurong
2017-01-01
Feature selection is an important preprocessing method in machine learning and data mining. This process can be used not only to reduce the amount of data to be analyzed but also to build models with stronger interpretability based on fewer features. Traditional feature selection methods evaluate the dependency and redundancy of features separately, which leads to a lack of measurement of their combined effect. Moreover, a greedy search considers only the optimization of the current round and thus cannot be a global search. To evaluate the combined effect of different subsets in the entire feature space, an adaptive feature selection method based on V-shaped binary particle swarm optimization is proposed. In this method, the fitness function is constructed using the correlation information entropy. Feature subsets are regarded as individuals in a population, and the feature space is searched using V-shaped binary particle swarm optimization. The above procedure overcomes the hard constraint on the number of features, enables the combined evaluation of each subset as a whole, and improves the search ability of conventional binary particle swarm optimization. The proposed algorithm is an adaptive method with respect to the number of feature subsets. The experimental results show the advantages of optimizing the feature subsets using the V-shaped transfer function and confirm the effectiveness and efficiency of the feature subsets obtained under different classifiers. PMID:28358850
Pulse shape optimization for electron-positron production in rotating fields
NASA Astrophysics Data System (ADS)
Fillion-Gourdeau, François; Hebenstreit, Florian; Gagnon, Denis; MacLean, Steve
2017-07-01
We optimize the pulse shape and polarization of time-dependent electric fields to maximize the production of electron-positron pairs via strong field quantum electrodynamics processes. The pulse is parametrized in Fourier space by a B -spline polynomial basis, which results in a relatively low-dimensional parameter space while still allowing for a large number of electric field modes. The optimization is performed by using a parallel implementation of the differential evolution, one of the most efficient metaheuristic algorithms. The computational performance of the numerical method and the results on pair production are compared with a local multistart optimization algorithm. These techniques allow us to determine the pulse shape and field polarization that maximize the number of produced pairs in computationally accessible regimes.
Overview of Sensitivity Analysis and Shape Optimization for Complex Aerodynamic Configurations
NASA Technical Reports Server (NTRS)
Newman, James C., III; Taylor, Arthur C., III; Barnwell, Richard W.; Newman, Perry A.; Hou, Gene J.-W.
1999-01-01
This paper presents a brief overview of some of the more recent advances in steady aerodynamic shape-design sensitivity analysis and optimization, based on advanced computational fluid dynamics (CFD). The focus here is on those methods particularly well-suited to the study of geometrically complex configurations and their potentially complex associated flow physics. When nonlinear state equations are considered in the optimization process, difficulties are found in the application of sensitivity analysis. Some techniques for circumventing such difficulties are currently being explored and are included here. Attention is directed to methods that utilize automatic differentiation to obtain aerodynamic sensitivity derivatives for both complex configurations and complex flow physics. Various examples of shape-design sensitivity analysis for unstructured-grid CFD algorithms are demonstrated for different formulations of the sensitivity equations. Finally, the use of advanced, unstructured-grid CFDs in multidisciplinary analyses and multidisciplinary sensitivity analyses within future optimization processes is recommended and encouraged.
Overview of Sensitivity Analysis and Shape Optimization for Complex Aerodynamic Configurations
NASA Technical Reports Server (NTRS)
Newman, Perry A.; Newman, James C., III; Barnwell, Richard W.; Taylor, Arthur C., III; Hou, Gene J.-W.
1998-01-01
This paper presents a brief overview of some of the more recent advances in steady aerodynamic shape-design sensitivity analysis and optimization, based on advanced computational fluid dynamics. The focus here is on those methods particularly well- suited to the study of geometrically complex configurations and their potentially complex associated flow physics. When nonlinear state equations are considered in the optimization process, difficulties are found in the application of sensitivity analysis. Some techniques for circumventing such difficulties are currently being explored and are included here. Attention is directed to methods that utilize automatic differentiation to obtain aerodynamic sensitivity derivatives for both complex configurations and complex flow physics. Various examples of shape-design sensitivity analysis for unstructured-grid computational fluid dynamics algorithms are demonstrated for different formulations of the sensitivity equations. Finally, the use of advanced, unstructured-grid computational fluid dynamics in multidisciplinary analyses and multidisciplinary sensitivity analyses within future optimization processes is recommended and encouraged.
NASA Astrophysics Data System (ADS)
Zemcov, Michael; Crill, Brendan; Ryan, Matthew; Staniszewski, Zak
2016-06-01
Mega-pixel charge-integrating detectors are common in near-IR imaging applications. Optimal signal-to-noise ratio estimates of the photocurrents, which are particularly important in the low-signal regime, are produced by fitting linear models to sequential reads of the charge on the detector. Algorithms that solve this problem have a long history, but can be computationally intensive. Furthermore, the cosmic ray background is appreciable for these detectors in Earth orbit, particularly above the Earth’s magnetic poles and the South Atlantic Anomaly, and on-board reduction routines must be capable of flagging affected pixels. In this paper, we present an algorithm that generates optimal photocurrent estimates and flags random transient charge generation from cosmic rays, and is specifically designed to fit on a computationally restricted platform. We take as a case study the Spectro-Photometer for the History of the Universe, Epoch of Reionization, and Ices Explorer (SPHEREx), a NASA Small Explorer astrophysics experiment concept, and show that the algorithm can easily fit in the resource-constrained environment of such a restricted platform. Detailed simulations of the input astrophysical signals and detector array performance are used to characterize the fitting routines in the presence of complex noise properties and charge transients. We use both Hubble Space Telescope Wide Field Camera-3 and Wide-field Infrared Survey Explorer to develop an empirical understanding of the susceptibility of near-IR detectors in low earth orbit and build a model for realistic cosmic ray energy spectra and rates. We show that our algorithm generates an unbiased estimate of the true photocurrent that is identical to that from a standard line fitting package, and characterize the rate, energy, and timing of both detected and undetected transient events. This algorithm has significant potential for imaging with charge-integrating detectors in astrophysics, earth science, and remote
Shape optimization of the diffuser blade of an axial blood pump by computational fluid dynamics.
Zhu, Lailai; Zhang, Xiwen; Yao, Zhaohui
2010-03-01
Computational fluid dynamics (CFD) has been a viable and effective way to predict hydraulic performance, flow field, and shear stress distribution within a blood pump. We developed an axial blood pump with CFD and carried out a CFD-based shape optimization of the diffuser blade to enhance pressure output and diminish backflow in the impeller-diffuser connecting region at a fixed design point. Our optimization combined a computer-aided design package, a mesh generator, and a CFD solver in an automation environment with process integration and optimization software. A genetic optimization algorithm was employed to find the pareto-optimal designs from which we could make trade-off decisions. Finally, a set of representative designs was analyzed and compared on the basis of the energy equation. The role of the inlet angle of the diffuser blade was analyzed, accompanied by its relationship with pressure output and backflow in the impeller-diffuser connecting region.
Shape optimization of axisymmetric solids with the finite cell method using a fixed grid
NASA Astrophysics Data System (ADS)
Meng, Liang; Zhang, Wei-Hong; Zhu, Ji-Hong; Xu, Zhao; Cai, Shou-Hu
2016-06-01
In this work, a design procedure extending the B-spline based finite cell method into shape optimization is developed for axisymmetric solids involving the centrifugal force effect. We first replace the traditional conforming mesh in the finite element method with structured cells that are fixed during the whole design process with a view to avoid the sophisticated re-meshing and eventual mesh distortion. Then, B-spline shape functions are further implemented to yield a high-order continuity field along the cell boundary in stress analysis. By means of the implicit description of the shape boundary, stress sensitivity is analytically derived with respect to shape design variables. Finally, we illustrate the efficiency and accuracy of the proposed protocol by several numerical test cases as well as a whole design procedure carried out on an aeronautic turbine disk.
NASA Astrophysics Data System (ADS)
Ning, Xiaojuan; Wang, Yinghui; Meng, Weiliang; Zhang, Xiaopeng
2016-10-01
To understand and recognize the three-dimensional (3-D) objects represented as point cloud data, we use an optimized shape semantic graph (SSG) to describe 3-D objects. Based on the decomposed components of an object, the boundary surface of different components and the topology of components, the SSG gives a semantic description that is consistent with human vision perception. The similarity measurement of the SSG for different objects is effective for distinguishing the type of object and finding the most similar one. Experiments using a shape database show that the SSG is valuable for capturing the components of the objects and the corresponding relations between them. The SSG is not only suitable for an object without any loops but also appropriate for an object with loops to represent the shape and the topology. Moreover, a two-step progressive similarity measurement strategy is proposed to effectively improve the recognition rate in the shape database containing point-sample data.
NASA Astrophysics Data System (ADS)
Lee, D. H.; Kwak, B. M.
A general procedure to perform shape design sensitivity analysis for two-dimensional periodic thermal diffusion problems is developed using boundary integral equation formulation. The material derivative concept to describe shape variation is used. The temperature is decomposed into a steady state component and a perturbation component. The adjoint variable method is used by utilizing integral identities for each component. The primal and adjoint systems are solved by boundary element method. The sensitivity results compared with those by finite difference show good accuracy. The shape optimal design problem of a plunger model for the panel of a television bulb, which operates periodically, is solved as an example. Different objectives and amounts of heat flux allowed are studied. Corresponding optimum shapes of the cooling boundary of the plunger are obtained and discussed.
NASA Astrophysics Data System (ADS)
Scirè Mammano, G.; Dragoni, E.
2014-07-01
The availability of engineering strength data on shape memory alloys (SMAs) under cyclic thermal activation (thermomechanical fatigue) is central to the rational design of smart actuators based on these materials. Test results on SMAs under thermomechanical fatigue are scarce in the technical literature, and even the few data that are available are mainly limited to constant-stress loading. Since the SMA elements used within actuators are normally biased by elastic springs or by antagonist SMA elements, their stress states are far from being constant in operation. The mismatch between actual working conditions and laboratory settings leads to suboptimal designs and undermines the prediction of the actuator lifetime. This paper aims at bridging the gap between experiment and reality by completing an experimental campaign involving four fatigue test conditions, which cover most of the typical situations occurring in practice: constant stress, constant-strain, constant stress with limited maximum strain, and linear stress-strain variation with limited maximum strain. The results from the first three test settings, recovered from the previously published works, are critically reviewed and compared with the outcome of the newly performed tests under the fourth arrangement (linear stress-strain variation). General design recommendations emerging from the experimental data are put forward for engineering use.
NASA Astrophysics Data System (ADS)
Meng, Fanjuan; Labergere, Carl; Lafon, Pascal
2011-05-01
In metal forming process, the forging die design is the most important step for products quality control. Reasonable dies shape can not only reduce raw material cost but also improving material flow and eliminating defects. The main objective of this paper is to obtain some optimal parameters of the initial billet and forging dies shape according to the simulation results of a two-step metal forming process (platting step and forging step). To develop this metal forming process optimization system several numerical tools are required: geometric modelling (CATIA V5™), FEM analysis (ABAQUS®), work-flow control and optimization computation (MODEFRONTIER®). This study is done in three stages: simulating the two-step metal forming process, building surrogate meta-models to relate response and variables and optimizing the process by using advanced optimization algorithms. In this paper, a two-step axisymmetric metal forming project was studied as an example. By using our simulation model, we get 581 correct real simulation results totally. According to all these real values, we build the surrogate meta-models and obtain Pareto points for a two-objective optimization process. The choice of a solution in all Pareto points will be done by the engineer who can choose his best values according to their criterions of project.
NASA Astrophysics Data System (ADS)
Stephenson, David; Patronis, Alexander; Holland, David M.; Lockerby, Duncan A.
2015-11-01
Murray's law states that the volumetric flow rate is proportional to the cube of the radius in a cylindrical channel optimized to require the minimum work to drive and maintain the fluid. However, application of this principle to the biomimetic design of micro/nano fabricated networks requires optimization of channels with arbitrary cross-sectional shape (not just circular) and smaller than is valid for Murray's original assumptions. We present a generalized law for symmetric branching that (a) is valid for any cross-sectional shape, providing that the shape is constant through the network; (b) is valid for slip flow and plug flow occurring at very small scales; and (c) is valid for networks with a constant depth, which is often a requirement for lab-on-a-chip fabrication procedures. By considering limits of the generalized law, we show that the optimum daughter-parent area ratio Γ, for symmetric branching into N daughter channels of any constant cross-sectional shape, is Γ=N-2 /3 for large-scale channels, and Γ=N-4 /5 for channels with a characteristic length scale much smaller than the slip length. Our analytical results are verified by comparison with a numerical optimization of a two-level network model based on flow rate data obtained from a variety of sources, including Navier-Stokes slip calculations, kinetic theory data, and stochastic particle simulations.
Shape optimization of three-dimensional stamped and solid automotive components
NASA Technical Reports Server (NTRS)
Botkin, M. E.; Yang, R.-J.; Bennett, J. A.
1987-01-01
The shape optimization of realistic, 3-D automotive components is discussed. The integration of the major parts of the total process: modeling, mesh generation, finite element and sensitivity analysis, and optimization are stressed. Stamped components and solid components are treated separately. For stamped parts a highly automated capability was developed. The problem description is based upon a parameterized boundary design element concept for the definition of the geometry. Automatic triangulation and adaptive mesh refinement are used to provide an automated analysis capability which requires only boundary data and takes into account sensitivity of the solution accuracy to boundary shape. For solid components a general extension of the 2-D boundary design element concept has not been achieved. In this case, the parameterized surface shape is provided using a generic modeling concept based upon isoparametric mapping patches which also serves as the mesh generator. Emphasis is placed upon the coupling of optimization with a commercially available finite element program. To do this it is necessary to modularize the program architecture and obtain shape design sensitivities using the material derivative approach so that only boundary solution data is needed.
Multi-objective shape optimization of runner blade for Kaplan turbine
NASA Astrophysics Data System (ADS)
Semenova, A.; Chirkov, D.; Lyutov, A.; Chemy, S.; Skorospelov, V.; Pylev, I.
2014-03-01
Automatic runner shape optimization based on extensive CFD analysis proved to be a useful design tool in hydraulic turbomachinery. Previously the authors developed an efficient method for Francis runner optimization. It was successfully applied to the design of several runners with different specific speeds. In present work this method is extended to the task of a Kaplan runner optimization. Despite of relatively simpler blade shape, Kaplan turbines have several features, complicating the optimization problem. First, Kaplan turbines normally operate in a wide range of discharges, thus CFD analysis of each variant of the runner should be carried out for several operation points. Next, due to a high specific speed, draft tube losses have a great impact on the overall turbine efficiency, and thus should be accurately evaluated. Then, the flow in blade tip and hub clearances significantly affects the velocity profile behind the runner and draft tube behavior. All these features are accounted in the present optimization technique. Parameterization of runner blade surface using 24 geometrical parameters is described in details. For each variant of runner geometry steady state three-dimensional turbulent flow computations are carried out in the domain, including wicket gate, runner, draft tube, blade tip and hub clearances. The objectives are maximization of efficiency in best efficiency and high discharge operation points, with simultaneous minimization of cavitation area on the suction side of the blade. Multiobjective genetic algorithm is used for the solution of optimization problem, requiring the analysis of several thousands of runner variants. The method is applied to optimization of runner shape for several Kaplan turbines with different heads.
Optimal design at inner core of the shaped pyramidal truss structure
Lee, Sung-Uk; Yang, Dong-Yol
2013-12-16
Sandwich material is a type of composite material with lightweight, high strength, good dynamic properties and high bending stiffness-to-weight ratio. This can be found well such structures in the nature (for example, internal structure of bones, plants, etc.). New trend which prefers eco-friendly products and energy efficiency is emerging in industries recently. Demand for materials with high strength and light weight is also increasing. In line with these trends, researches about manufacturing methods of sandwich material have been actively conducted. In this study, a sandwich structure named as “Shaped Pyramidal Truss Structure” is proposed to improve mechanical strength and to apply a manufacturing process suitable for massive production. The new sandwich structure was designed to enhance compressive strength by changing the cross-sectional shape at the central portion of the core. As the next step, optimization of the shape was required. Optimization technique used here was the SZGA(Successive Zooming Genetic Algorithm), which is one of GA(Genetic Algorithm) methods gradually reducing the area of design variable. The objective function was defined as moment of inertia of the cross-sectional shape of the strut. The control points of cubic Bezier curve, which was assumed to be the shape of the cross section, were used as design variables. By using FEM simulation, it was found that the structure exhibited superior mechanical properties compared to the simple design of the prior art.
Optimal design at inner core of the shaped pyramidal truss structure
NASA Astrophysics Data System (ADS)
Lee, Sung-Uk; Yang, Dong-Yol
2013-12-01
Sandwich material is a type of composite material with lightweight, high strength, good dynamic properties and high bending stiffness-to-weight ratio. This can be found well such structures in the nature (for example, internal structure of bones, plants, etc.). New trend which prefers eco-friendly products and energy efficiency is emerging in industries recently. Demand for materials with high strength and light weight is also increasing. In line with these trends, researches about manufacturing methods of sandwich material have been actively conducted. In this study, a sandwich structure named as "Shaped Pyramidal Truss Structure" is proposed to improve mechanical strength and to apply a manufacturing process suitable for massive production. The new sandwich structure was designed to enhance compressive strength by changing the cross-sectional shape at the central portion of the core. As the next step, optimization of the shape was required. Optimization technique used here was the SZGA(Successive Zooming Genetic Algorithm), which is one of GA(Genetic Algorithm) methods gradually reducing the area of design variable. The objective function was defined as moment of inertia of the cross-sectional shape of the strut. The control points of cubic Bezier curve, which was assumed to be the shape of the cross section, were used as design variables. By using FEM simulation, it was found that the structure exhibited superior mechanical properties compared to the simple design of the prior art.
Efficient searching of globally optimal and smooth multi-surfaces with shape priors
NASA Astrophysics Data System (ADS)
Xu, Lei; Stojkovic, Branislav; Ding, Hu; Song, Qi; Wu, Xiaodong; Sonka, Milan; Xu, Jinhui
2012-02-01
Despite extensive studies in the past, the problem of segmenting globally optimal multiple surfaces in 3D volumetric images remains challenging in medical imaging. The problem becomes even harder in highly noisy and edge-weak images. In this paper we present a novel and highly efficient graph-theoretical iterative method based on a volumetric graph representation of the 3D image that incorporates curvature and shape prior information. Compared with the graph-based method, applying the shape prior to construct the graph on a specific preferred shape model allows easy incorporation of a wide spectrum of shape prior information. Furthermore, the key insight that computation of the objective function can be done independently in the x and y directions makes local improvement possible. Thus, instead of using global optimization technique such as maximum flow algorithm, the iteration based method is much faster. Additionally, the utilization of the curvature in the objective function ensures the smoothness. To the best of our knowledge, this is the first paper to combine the shape-prior penalties with utilizing curvature in objective function to ensure the smoothness of the generated surfaces while striving for achieving global optimality. To evaluate the performance of our method, we test it on a set of 14 3D OCT images. Comparing to the best existing approaches, our experiments suggest that the proposed method reduces the unsigned surface positioning errors form 5.44 +/- 1.07(μm) to 4.52 +/- 0.84(μm). Moreover, our method has a much improved running time, yields almost the same global optimality but with much better smoothness, which makes it especially suitable for segmenting highly noisy images. The proposed method is also suitable for parallel implementation on GPUs, which could potentially allow us to segment highly noisy volumetric images in real time.
A genetic algorithm based multi-objective shape optimization scheme for cementless femoral implant.
Chanda, Souptick; Gupta, Sanjay; Kumar Pratihar, Dilip
2015-03-01
The shape and geometry of femoral implant influence implant-induced periprosthetic bone resorption and implant-bone interface stresses, which are potential causes of aseptic loosening in cementless total hip arthroplasty (THA). Development of a shape optimization scheme is necessary to achieve a trade-off between these two conflicting objectives. The objective of this study was to develop a novel multi-objective custom-based shape optimization scheme for cementless femoral implant by integrating finite element (FE) analysis and a multi-objective genetic algorithm (GA). The FE model of a proximal femur was based on a subject-specific CT-scan dataset. Eighteen parameters describing the nature of four key sections of the implant were identified as design variables. Two objective functions, one based on implant-bone interface failure criterion, and the other based on resorbed proximal bone mass fraction (BMF), were formulated. The results predicted by the two objective functions were found to be contradictory; a reduction in the proximal bone resorption was accompanied by a greater chance of interface failure. The resorbed proximal BMF was found to be between 23% and 27% for the trade-off geometries as compared to ∼39% for a generic implant. Moreover, the overall chances of interface failure have been minimized for the optimal designs, compared to the generic implant. The adaptive bone remodeling was also found to be minimal for the optimally designed implants and, further with remodeling, the chances of interface debonding increased only marginally.
Rankin, Jeffery W; Neptune, Richard R
2008-01-01
Previous studies have sought to improve cycling performance by altering various aspects of the pedaling motion using novel crank-pedal mechanisms and non-circular chainrings. However, most designs have been based on empirical data and very few have provided significant improvements in cycling performance. The purpose of this study was to use a theoretical framework that included a detailed musculoskeletal model driven by individual muscle actuators, forward dynamic simulations and design optimization to determine if cycling performance (i.e., maximal power output) could be improved by optimizing the chainring shape to maximize average crank power during isokinetic pedaling conditions. The optimization identified a consistent non-circular chainring shape at pedaling rates of 60, 90 and 120 rpm with an average eccentricity of 1.29 that increased crank power by an average of 2.9% compared to a conventional circular chainring. The increase in average crank power was the result of the optimal chainrings slowing down the crank velocity during the downstroke (power phase) to allow muscles to generate power longer and produce more external work. The data also showed that chainrings with higher eccentricity increased negative muscle work following the power phase due to muscle activation-deactivation dynamics. Thus, the chainring shape that maximized average crank power balanced these competing demands by providing enough eccentricity to increase the external work generated by muscles during the power phase while minimizing negative work during the subsequent recovery phase.
NASA Astrophysics Data System (ADS)
Eisa, Fabian; Brauweiler, Robert; Peetz, Alexander; Hupfer, Martin; Nowak, Tristan; Kalender, Willi A.
2012-05-01
One of the biggest challenges in dynamic contrast-enhanced CT is the optimal synchronization of scan start and duration with contrast medium administration in order to optimize image contrast and to reduce the amount of contrast medium. We present a new optically based approach, which was developed to investigate and optimize bolus timing and shape. The time-concentration curve of an intravenously injected test bolus of a dye is measured in peripheral vessels with an optical sensor prior to the diagnostic CT scan. The curves can be used to assess bolus shapes as a function of injection protocols and to determine contrast medium arrival times. Preliminary results for phantom and animal experiments showed the expected linear behavior between dye concentration and absorption. The kinetics of the dye was compared to iodinated contrast medium and was found to be in good agreement. The contrast enhancement curves were reliably detected in three mice with individual bolus shapes and delay times of 2.1, 3.5 and 6.1 s, respectively. The optical sensor appears to be a promising approach to optimize injection protocols and contrast enhancement timing and is applicable to all modalities without implying any additional radiation dose. Clinical tests are still necessary.
Three-Dimensional Optimal Shape Design in Heat Transfer Based on Body-fitted Grid Generation
NASA Astrophysics Data System (ADS)
Mohebbi, Farzad; Sellier, Mathieu
2013-10-01
This paper is concerned with an optimal shape design (shape optimization) problem in heat transfer. As an inverse steady-state heat transfer problem, given a body locally heated by a specified heat flux and exposed to convective heat transfer on parts of its boundary, the aim is to find the optimal shape of this body such that the temperature is constant on a desired subset of its boundary. The numerical method to achieve this aim consists of a three-dimensional elliptic grid generation technique to generate a mesh over the body and solve for a heat conduction equation. This paper describes a novel sensitivity analysis scheme to compute the sensitivity of the temperatures to variation of grid node positions and the conjugate gradient method (CGM) is used as an optimization algorithm to minimize the difference between the computed temperature on the boundary and desired temperature. The elliptic grid generation technique allows us to map the physical domain (body) onto a fixed computational domain and to discretize the heat conduction equation using the finite difference method (FDM).
Suarez-Bagnasco, Diego; Armentano-Feijoo, R; Suarez-Antola, R
2010-01-01
An analytical approach to threshold problems in functional magnetic stimulation of nerve and skeletal muscle fibers was recently proposed, framed in the concept of excitation functional. Three generations of available equipments for magnetic stimulation are briefly considered, stressing the corresponding pulse shape in the stimulation coils. Using the criterion of minimum energy dissipated in biological tissues, an optimal shape for a current pulse in the coil that produces a just threshold depolarization in a nerve or skeletal muscle fiber is found. The method can be further developed and applied to other threshold problems in functional electric stimulation.