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Lachenmaier, Nicolas, Daniel Baumgärtner, Heinz-Peter Schiffer, and Johannes Kech. "Gradient-Free and Gradient-Based Optimization of a Radial Turbine." International Journal of Turbomachinery, Propulsion and Power 5, no. 3 (July 6, 2020): 14. http://dx.doi.org/10.3390/ijtpp5030014.
A turbocharger’s radial turbine has a strong impact on the fuel consumption and transient response of internal combustion engines. This paper summarizes the efforts to design a new radial turbine aiming at high efficiency and low inertia by applying two different optimization techniques to a parametrized CAD model. The first workflow wraps 3D fluid and solid simulations within a meta-model assisted genetic algorithm to find an efficient turbine subjected to several constraints. In the next step, the chosen turbine is re-parametrized and fed into the second workflow which makes use of a gradient projection algorithm to further fine-tune the design. This requires the computation of gradients with respect to the CAD parametrization, which is done by calculating and combining surface sensitivities and design velocities. Both methods are applied successfully, i.e., the first delivers a well-performing turbine, which, by the second method, is further improved by 0.34% in efficiency.
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Carriero, M., A. Leaci, and F. Tomarelli. "Free gradient discontinuity and image inpainting." Journal of Mathematical Sciences 181, no. 6 (March 2012): 805–19. http://dx.doi.org/10.1007/s10958-012-0716-4.
Bosch, Jaime, and Juan Carlos García-Pagán. "Calculating Hepatic Venous Pressure Gradient: Feel Free to Stay Free." Journal of Vascular and Interventional Radiology 27, no. 8 (August 2016): 1138–39. http://dx.doi.org/10.1016/j.jvir.2016.03.048.
Diest, Kenneth, Luke A. Sweatlock, and Daniel E. Marthaler. "Metamaterials design using gradient-free numerical optimization." Journal of Applied Physics 108, no. 8 (October 15, 2010): 084303. http://dx.doi.org/10.1063/1.3498816.
De Silva, Daniela, and David Jerison. "A gradient bound for free boundary graphs." Communications on Pure and Applied Mathematics 64, no. 4 (December 13, 2010): 538–55. http://dx.doi.org/10.1002/cpa.20354.
Huang, C., J. M. Lei, M. B. Liu, and X. Y. Peng. "A kernel gradient free (KGF) SPH method." International Journal for Numerical Methods in Fluids 78, no. 11 (April 21, 2015): 691–707. http://dx.doi.org/10.1002/fld.4037.
Werner, Tino [Verfasser], Peter [Akademischer Betreuer] Ruckdeschel, and Matthias [Akademischer Betreuer] Schmid. "Gradient-Free Gradient Boosting / Tino Werner ; Peter Ruckdeschel, Matthias Schmid." Oldenburg : BIS der Universität Oldenburg, 2020. http://d-nb.info/120419968X/34.
Yucelen, Tansel. "Advances in adaptive control theory: gradient- and derivative-free approaches." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/43731.
In this dissertation, we present new approaches to improve standard designs in adaptive control theory, and novel adaptive control architectures.
We first present a novel Kalman filter based approach for approximately enforcing a linear constraint in standard adaptive control design. One application is that this leads to alternative forms for well known modification terms such as e-modification. In addition, it leads to smaller tracking errors without incurring significant oscillations in the system response and without requiring high modification gain. We derive alternative forms of e- and adaptive loop recovery (ALR-) modifications.
Next, we show how to use Kalman filter optimization to derive a novel adaptation law. This results in an optimization-based time-varying adaptation gain that reduces the need for adaptation gain tuning.
A second major contribution of this dissertation is the development of a novel derivative-free, delayed weight update law for adaptive control. The assumption of constant unknown ideal weights is relaxed to the existence of time-varying weights, such that fast and possibly discontinuous variation in weights are allowed. This approach is particularly advantageous for applications to systems that can undergo a sudden change in dynamics, such as might be due to reconfiguration, deployment of a payload, docking, or structural damage, and for rejection of external disturbance processes.
As a third and final contribution, we develop a novel approach for extending all the methods developed in this dissertation to the case of output feedback. The approach is developed only for the case of derivative-free adaptive control, and the extension of the other approaches developed previously for the state feedback case to output feedback is left as a future research topic.
The proposed approaches of this dissertation are illustrated in both simulation and flight test.
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Harrison, Stephen C. W. "Free field modeling of a MEMS-Based pressure gradient microphone." Thesis, Monterey, California : Naval Postgraduate School, 2009. http://edocs.nps.edu/npspubs/scholarly/theses/2009/Dec/09Dec%5FHarrison.pdf.
Thesis (M.S. in Engineering Acoustics and M.S. in Applied Physics)--Naval Postgraduate School, December 2009. Thesis Advisor(s): Karunasiri, Gamani; Baker, Steven. "December 2009." Description based on title screen as viewed on January 26, 2010. Author(s) subject terms: MEMS, Model, Simulation, Pressure Gradient, Particle Velocity, Directional, Microphone, SOMSOL, Acoustic. Includes bibliographical references (p. 51-52). Also available in print.
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Nutini, Julie Ann. "A derivative-free approximate gradient sampling algorithm for finite minimax problems." Thesis, University of British Columbia, 2012. http://hdl.handle.net/2429/42200.
Mathematical optimization is the process of minimizing (or maximizing) a function. An algorithm is used to optimize a function when the minimum cannot be found by hand, or finding the minimum by hand is inefficient. The minimum of a function is a critical point and corresponds to a gradient (derivative) of 0. Thus, optimization algorithms commonly require gradient calculations. When gradient information of the objective function is unavailable, unreliable or ‘expensive’ in terms of computation time, a derivative-free optimization algorithm is ideal. As the name suggests, derivative-free optimization algorithms do not require gradient calculations. In this thesis, we present a derivative-free optimization algorithm for finite minimax problems. Structurally, a finite minimax problem minimizes the maximum taken over a finite set of functions. We focus on the finite minimax problem due to its frequent appearance in real-world applications. We present convergence results for a regular and a robust version of our algorithm, showing in both cases that either the function is unbounded below (the minimum is −∞) or we have found a critical point. Theoretical results are explored for stopping conditions. Additionally, theoretical and numerical results are presented for three examples of approximate gradients that can be used in our algorithm: the simplex gradient, the centered simplex gradient and the Gupal estimate of the gradient of the Steklov averaged function. A performance comparison is made between the regular and robust algorithm, the three approximate gradients, and the regular and robust stopping conditions. Finally, an application in seismic retrofitting is discussed.
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Refsnæs, Runar Heggelien. "Matrix-Free Conjugate Gradient Methods for Finite Element Simulations on GPUs." Thesis, Norges Teknisk-Naturvitenskaplige Universitet, Institutt for fysikk, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-10826.
A block-structured approach for solving 2-dimensional finite element approximations of the Poisson equation on graphics processing units(GPUs) is developed. Linear triangular elements are used, and a matrix-free version of the conjugate gradient method is utilized for solving test problems with over 30 million elements. A speedup of 24 is achieved on a NVIDIA Tesla C1060 GPU when compared to a serial CPU version of the same solution approach, and a comparison is made with previous GPU implementations of the same problem.
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Fejes, Niklas. "High Performance Multi-Objective Voyage Planning Using Local Gradient-Free Methods." Thesis, Uppsala universitet, Avdelningen för beräkningsvetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-305582.
A number of parallel gradient-free local optimization methods are investigated in application to problems of voyage planning for maritime ships. Two optimization algorithms are investigated, a parallel version of the Nelder-Mead Simplex method and the Subplex method with Nelder-Mead Simplex as its inner solver. Additionally, two new formulations of the optimization problem are suggested which together with an improved implementation of the objective function increases the overall performance of the model. Numerical results show the efficiency of these methods in comparison with the earlier introduced Grid search method and solvers from an open-source optimization library.
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Li, Futong. "Global Optimization Techniques Based on Swarm-intelligent and Gradient-free Algorithms." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42307.
The need for solving nonlinear optimization problems is pervasive in many fields. Particle swarm optimization, advantageous with the simple underlying implementation logic, and simultaneous perturbation stochastic approximation, which is famous for its saving in the computational power with the gradient-free attribute, are two solutions that deserve attention. Many researchers have exploited their merits in widely challenging applications. However, there is a known fact that both of them suffer from a severe drawback, non- effectively converging to the global best solution, because of the local “traps” spreading on the searching space. In this article, we propose two approaches to remedy this issue by combined their advantages.
In the first algorithm, the gradient information helps optimize half of the particles at the initialization stage and then further updates the global best position. If the global best position is located in one of the local optima, the searching surface’s additional gradient estimation can help it jump out. The second algorithm expands the implementation of the gradient information to all the particles in the swarm to obtain the optimized personal best position. Both have to obey the rule created for updating the particle(s); that is, the solution found after employing the gradient information to the particle(s) has to perform more optimally.
In this work, the experiments include five cases. The three previous methods with a similar theoretical basis and the two basic algorithms take participants in all five. The experimental results prove that the proposed two algorithms effectively improved the basic algorithms and even outperformed the previously designed three algorithms in some scenarios.
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Cantergiani, Elisa. "Mechanical Properties of Functionally Graded Materials: Carbon Gradient inside Interstitial Free Steel." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/34314.
In the last decade aluminium started to be considered as an alternative to steel to produce car body panels, especially considering the strict demands to decrease fuel consumption which require vehicle weight reduction. In order to keep their leading role, steel companies have to produce stronger materials to reduce the thickness of steel sheets used in cars and are now considering non-conventional steel making processes.
The purpose of this PhD research was to investigate the possibility of strengthening thin sheets of interstitial free steel (IF steel) by using carbon rich films deposited on the steel surface using Physical Vapour Deposition (PVD). These films then act as a carbon reservoir which upon heat treatment release carbon in the IF steel and strengthen it.
Coated tensile coupons 200 μm thick were annealed at different temperatures under high vacuum. Tensile tests show that a 100 MPa increase in yield stress can be obtained after annealing at 430 ˚C for 1h in high vacuum. The effects of annealing environment, film thickness and prestrain on carbon diffusion were also investigated. It was shown that carbon diffusion from the film to the IF steel substrate is limited by the film transformation into cementite at temperatures equal or higher than 530 ˚C.
All tensile curves showed a plastic instability known as Lüders plateau, which is undesirable as it results in surface markings on the deformed part. FEM analyses were performed to find ways to suppress the Lüders plateau, proving that increasing strain-hardening or having a graded instead of uniform carbon content through thickness can suppress or limit Lüdering.
The possibility of creating a through thickness gradient of microstructure was investigated as it could suppress Lüdering and result in higher strength. For these tests, FeC coated coupons were induction heated to 820 ˚C followed by water quenching. After only 2 minutes of heat treatment the yield stress was increased by 250 MPa and the ultimate tensile strength reached 400 MPa. With an annealing of 4 minutes, the Lüders plateau was fully suppressed and the microstructure consisted in ferrite grains and TiC nanocarbides. This work demonstrates that FeC films can be effectively used to diffuse carbon into steel and that a significant increase in mechanical properties can be obtained after a heat treatment of only a few minutes.
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Alkhamis, A. T. A. "Structural optimization for static and free vibration conditions using genetic and gradient-based algorithms." Thesis, Swansea University, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.635759.
This thesis is concerned with the development and application of reliable, creative and efficient computational tools for the analysis and structural optimization of 2D and 3D trusses under static and free vibration conditions and prismatic structures under static and free vibration conditions. The first part of the thesis deals with the analysis and optimization of 2D and 3D trusses under static and free vibration conditions. The second part of the thesis deals with prismatic structures under static and free vibration conditions which are idealised as effectively one-dimensional problems. The procedures used to define the structural shape and incorporating automatic mesh generation are described and the basic formulations of curved, Mindlin-Reissner finite elements and finite strips are presented for prismatic shells. The accuracy of the elements and strips is verified using several benchmark tests. The basic algorithm of structural shape optimization is then presented and several examples are carried out. In both parts the optimization analysis is carried out using two different algorithms: sequential quadratic programming (SQP) and genetic algorithms (GAs). The optimized structures are not checked for buckling. Six main computer FORTRAN programs are developed, documented and tested.
Wang, Yan Ming. Downward continuation of the free-air gravity anomalies to the ellipsoid using the gradient solution, Poisson's integral and terrain correction-numerical comparison and the computations. Columbus, Ohio: Dept. of Geodetic Science and Surveying, Ohio State University, 1988.
L, Healey D., United States. Dept. of Energy. Nevada Operations Office., and Geological Survey (U.S.), eds. Free-air gradient observations in Yucca Flat, Nye County, Nevada. Denver, Colo: U.S. Dept. of Interior, Geological Survey, 1985.
L, Healey D., United States. Dept. of Energy. Nevada Operations Office., and Geological Survey (U.S.), eds. Free-air gradient observations in Yucca Flat, Nye County, Nevada. Denver, Colo: U.S. Dept. of Interior, Geological Survey, 1985.
L, Healey D., United States. Dept. of Energy. Nevada Operations Office., and Geological Survey (U.S.), eds. Free-air gradient observations in Yucca Flat, Nye County, Nevada. Denver, Colo: U.S. Dept. of Interior, Geological Survey, 1985.
L, Healey D., United States. Dept. of Energy. Nevada Operations Office, and Geological Survey (U.S.), eds. Free-air gradient observations in Yucca Flat, Nye County, Nevada. Denver, Colo: U.S. Dept. of Interior, Geological Survey, 1985.
This chapter shows how the Newtonian law of motion of a particle subject to a gradient force derived from a ‘potential energy’ can always be obtained from an extremal principle, or ‘principle of least action’. According to Newton’s first law, the trajectory representing the motion of a free particle between two points p1 and p2 is a straight line. In other words, out of all the possible paths between p1 and p2, the trajectory effectively followed by a free particle is the one that minimizes the length. However, even though the use of the principle of extremal length of the paths between two points gives the straight line joining the points, this does not mean that the straight-line path is traced with constant velocity in an inertial frame. Moreover, the trajectory describing the motion of a particle subject to a force is not uniform and rectilinear.
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Aarts, D. G. A. L. Soft interfaces: the case of colloid–polymer mixtures. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198789352.003.0013.
In this chapter we discuss the interface of a phase separated colloid-polymer mixture. We start by highlighting a number of experimental studies, illustrating the richness of colloidal interface phenomena. This is followed by a derivation of the bulk phase behaviour within free volume theory. We subsequently calculate the interfacial tension using a squared gradient approach. The interfacial tension turns out to be ultralow, easily a million times smaller than a molecular interfacial tension. From the bulk and interface calculations we obtain the capillary length and compare to experiments, where good overall agreement is found. Finally, we focus on the thermal capillary waves of the interface and derive the static and dynamic height–height correlation functions, which describe the experimental data very well. We end with an outlook, where we address some outstanding questions concerning the behaviour of interfaces, to which colloids may provide unique insights.
Частини книг з теми "Gradient-free":
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Mielke, Alexander. "Free Energy, Free Entropy, and a Gradient Structure for Thermoplasticity." In Innovative Numerical Approaches for Multi-Field and Multi-Scale Problems, 135–60. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39022-2_7.
Yuan, Xin, Liangliang Ren, Jiwen Lu, and Jie Zhou. "Relaxation-Free Deep Hashing via Policy Gradient." In Computer Vision – ECCV 2018, 141–57. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01225-0_9.
Croce, Francesco, and Matthias Hein. "A Randomized Gradient-Free Attack on ReLU Networks." In Lecture Notes in Computer Science, 215–27. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12939-2_16.
Ghosh, Ranadhir, Moumita Ghosh, and Adil Bagirov. "Derivative Free Stochastic Discrete Gradient Method with Adaptive Mutation." In Advances in Data Mining. Applications in Medicine, Web Mining, Marketing, Image and Signal Mining, 264–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11790853_21.
Ge, Hao, Yan Yan, Jianhua Li, Ying Guo, and Shenghong Li. "A Parameter-Free Gradient Bayesian Two-Action Learning Automaton Scheme." In Proceedings of the 2015 International Conference on Communications, Signal Processing, and Systems, 963–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49831-6_100.
Zhang, Shuai, Xiang Chen, Kongqiao Wang, Jiangwei Li, Yanwei Pang, and He Yan. "Active Histogram of Oriented Gradient Based Learning for Free Palm Tracking." In Frontiers in Computer Education, 683–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27552-4_91.
Charan, K. C., and Siva Prasad AVS. "Kernel Gradient Free Smoothed Particle Hydrodynamics for Transient Boundary Value Problems." In Recent Advances in Computational Mechanics and Simulations, 519–26. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8315-5_44.
Zeidler, Eberhard. "Free Minima for Convex Functionals, Ritz Method and the Gradient Method." In Nonlinear Functional Analysis and its Applications, 244–69. New York, NY: Springer New York, 1985. http://dx.doi.org/10.1007/978-1-4612-5020-3_7.
Qu, Liang, and Yuhui Shi. "Gradient-free Algorithms for Graph Embedding." In 2019 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2019. http://dx.doi.org/10.1109/cec.2019.8790139.
Birmiwal, Sarwal, and Sinha. "A new gradient-free learning algorithm." In International Joint Conference on Neural Networks. IEEE, 1989. http://dx.doi.org/10.1109/ijcnn.1989.118512.
Hajinezhad, Davood, and Michael M. Zavlanos. "Gradient-Free Multi-Agent Nonconvex Nonsmooth Optimization." In 2018 IEEE Conference on Decision and Control (CDC). IEEE, 2018. http://dx.doi.org/10.1109/cdc.2018.8619333.
Wang, Lingfei, Yinghui Wang, and Yiguang Hong. "Distributed Online Optimization With Gradient-free Design." In 2019 Chinese Control Conference (CCC). IEEE, 2019. http://dx.doi.org/10.23919/chicc.2019.8865143.
Turgeman, Avi, Adwait Datar, and Herbert Werner. "Gradient Free Source-Seeking Using Flocking Behavior." In 2019 American Control Conference (ACC). IEEE, 2019. http://dx.doi.org/10.23919/acc.2019.8815372.
Bastl, Bohumír, Marek Brandner, Jiří Egermaier, Hana Horníková, Kristýna Michálková, and Eva Turnerová. "Gradient-free and gradient-based methods for shape optimization of water turbine blade." In Programs and Algorithms of Numerical Mathematics 19. Institute of Mathematics, Czech Academy of Sciences, 2019. http://dx.doi.org/10.21136/panm.2018.02.
Pekkucuksen, Ibrahim, and Yucel Altunbasak. "Gradient based threshold free color filter array interpolation." In 2010 17th IEEE International Conference on Image Processing (ICIP 2010). IEEE, 2010. http://dx.doi.org/10.1109/icip.2010.5654327.
Pinto, J. W. O., J. A. R. Tueros, B. Horowitz, S. M. B. Silva, and R. B. Willmersdorf. "Gradient-free Strategies to Robust Well Control Optimization." In EAGE/TNO Workshop on OLYMPUS Field Development Optimization. Netherlands: EAGE Publications BV, 2018. http://dx.doi.org/10.3997/2214-4609.201802299.
Williams, Brian J., Kayla Coleman, Ralph C. Smith, and Max D. Morris. Gradient-Free Construction of Active Subspaces for Dimension Reduction. Office of Scientific and Technical Information (OSTI), May 2019. http://dx.doi.org/10.2172/1523205.
Cruz, Edward J. Chemical Free Surface Processing for High Gradient Superconducting RF Cavities. Office of Scientific and Technical Information (OSTI), June 2015. http://dx.doi.org/10.2172/1464736.
Hartemann, F. V., A. L. Troha, and H. A. Baldis. Chirped-Pulse Inverse Free Electron Laser: A Tabletop, High-Gradient Vacuum Laser Accelerator. Office of Scientific and Technical Information (OSTI), March 2001. http://dx.doi.org/10.2172/15007297.
