8,970 research outputs found
On the combined effect of design-space dimensionality reduction and optimization methods on shape optimization efficiency
No full textThe curse of dimensionality represents a relevant issue in simulation-based shape optimiza-tion, especially when complex physics and high-fidelity computationally-expensive solvers areinvolved in the process and a global optimum is sought after. In order to have a deeper insightinto this problem and indicate possible remedies, the present paper studies the effects of bothdesign-space dimensionality reduction (DR) and optimization methods on the shape optimiza-tion efficiency. Linear and non-linear DR methods are used for the design-space DR, basedon principal component analysis and deep autoencoders. Global and hybrid global/local deter-ministic derivative-free optimization algorithms (Deterministic Particle Swarm Optimization,DIviding RECTangles, Dolphin Pod Optimization, LSDFPSO, and DIRMIN-2) are applied tothe original and the reduced-dimensionality design-spaces, investigating their efficiency andeffectiveness. Example application is shown for the shape optimization of a destroyer-typevessel sailing in calm water at fixed spee
Design-space assessment and dimensionality reduction: An off-line method for shape reparameterization in simulation-based optimization
No full textA method based on the Karhunen–Loève expansion (KLE) is formulated for the assessment of arbitrary design spaces in shape optimization, assessing the shape modification variability and providing the definition of a reduced-dimensionality global model of the shape modification vector. The method is based on the concept of geometric variance and does not require design-performance analyses. Specifically, the KLE is applied to the continuous shape modification vector, requiring the solution of a Fredholm integral equation of the second kind. Once the equation is discretized, the problem reduces to the principal component analysis (PCA) of discrete geometrical data. The objective of the present work is to demonstrate how this method can be used to (a) assess different design spaces and shape parameterization methods before optimization is performed and without the need of running simulations for the performance prediction, and (b) reduce the dimensionality of the design space, providing a shape reparameterization using KLE/PCA eigenvalues and eigenmodes. A demonstration for the hull-form optimization of the DTMB 5415 model in calm water is shown, where three design spaces are investigated, namely provided by free-form deformation, radial basis functions, and global modification functions
Single- and multi-objective design optimization study for DTMB 5415, based on low fidelity solvers
No full textThe report presents the research activities conducted within the NATO RTO Task Group AVT-204 "Assess the Ability to Optimize Hull Forms of Sea Vehicles for Best Performance in a Sea Environment." Specifically, single- and multi-objective simulation-based design optimization studies for a USS Arleigh Burke-class destroyer, namely the DDG-51, are performed, based on low fidelity solvers. The DTMB 5415 model, an open-to-public early concept of the DDG-51, is used in the current study. The present work aims at the reduction of two different objective functions, namely (F1) the weighted sum of the total resistance in calm water at 18 and 30 kn, and (F2) a seakeeping merit factor based on the vertical acceleration of the bridge and the roll motion. A potential flow code and a linear strip theory are used for the analysis. Results by single- and multi-objective deterministic particle swarm optimization algorithms are presented. Bare hull and sonar dome shape modifications are defined in terms of orthogonal basis functions. Six design spaces are investigated varying the space dimension and the associated design variables bounds. The optimal shape selected provides an improvement by 6.7% and 6.8% for F1 and F2, respectively
Optimal Design of Phononic Crystals Using Higher-Order Boundary Elements and a Swarm Optimization Scheme
No full textNonlinear methods for design-space dimensionality reduction in shape optimization
No full textIn shape optimization, design improvements significantly depend on the dimension and variability of the design space. High dimensional and variability spaces are more difficult to explore, but also usually allow for more significant improvements. The assessment and breakdown of design-space dimensionality and variability are therefore key elements to shape optimization. A linear method based on the principal component analysis (PCA) has been developed in earlier research to build a reduced-dimensionality design-space, resolving the 95% of the original geometric variance. The present work introduces an extension to more efficient nonlinear approaches. Specifically the use of Kernel PCA, Local PCA, and Deep Autoencoder (DAE) is discussed. The methods are demonstrated for the design-space dimensionality reduction of the hull form of a USS Arleigh Burke-class destroyer. Nonlinear methods are shown to be more effective than linear PCA. DAE shows the best performance overall
A fish shoal algorithm for global derivative-free simulation-based ship design optimization
No full textAssessing the interplay of shape and physical parameters by unsupervised nonlinear dimensionality reduction methods
No full textThe article presents an exploratory study on the application to ship hydrodynamics of unsupervised nonlinear design-space dimensionality reductionmethods, assessing the interaction of shape and physical parameters. Nonlinear extensions of the principal component analysis (PCA) are applied, namely local PCA (LPCA) and kernel PCA (KPCA). An artificial neural network approach, specifically a deep autoencoder (DAE) method, is also applied and comparedwith PCA-based approaches. The data set under investigation is formed by the results of 9000 potential flow simulations coming froman extensive exploration of a 27-dimensional design space, associated with a shape optimization problem of the DTMB 5415 model in calm water at 18 kn (Froude number, Fr = 25). Data include three heterogeneous distributed and suitably discretized parameters (shape modification vector, pressure distribution on the hull, and wave elevation pattern) and one lumped parameter (wave resistance coefficient), for a total of 9000 x 5101 elements. The reduced-dimensionality representation of shape and physical parameters is set to provide a normalizedmean squared error smaller than 5%. The standard PCA meets the requirement using 19 principal components/parameters. LPCA and KPCA provide the most promising compression capability with 14 parameters required by the reduced-dimensionality parametrizations, indicating significant nonlinear interactions in the data structure of shape and physical parameters. The DAE achieves the same error with 17 components. Although the focus of the current work is on design-space dimensionality reduction, the formulation goes beyond shape optimization and can be applied to large sets of heterogeneous physical data from simulations, experiments, and real operation measurement
Andrea Bacová
No full textAndrea Bacová focuses on research and teaching in the field of residential architecture. Her work includes systematic research on residential buildings and their urban context. She actively participates in promoting Slovak architecture and is the author of several publications and exhibitions
Viewer-, Author-, and Ownership in the Work of Andrea Zittel
No full textAndrea Zittel invites others to collapse the distinctions between artist, viewer, and collaborator by interacting with her usable works. This thesis explores the process of interacting with Zittel\u27s works, and how it affects viewer-, author- and ownership
The Lettere of Andrea Calmo: authorial artifices and historical reality
No full textopenNonostante l’edizione di Vittorio Rossi del 1888, la raccolta di "ingegnosi cheribizzi" e di "fantastiche fantasie" di Andrea Calmo è ancora avvolta da un certo mistero. L’autore, dissimulando la propria identità dietro alla “maschera” dell’umile pescatore veneziano, è stato in grado di offrire uno spaccato della cultura e della società nella Venezia cinquecentesca.
In particolare, è il quarto libro delle Lettere ad aver suscitato maggiore interesse tra gli studiosi ed i lettori: pubblicato nel 1566, a diversi anni di distanza dai primi tre, questo libro si distingue per il fatto che tutte le epistole sono indirizzate a delle donne immaginarie o realmente esistite.
In questa sede si propone, in primo luogo, uno studio della biografia del Calmo accompagnata da un’analisi del contesto storico-culturale della Venezia cinquecentesca; in secondo luogo, invece, viene proposto un commento di alcune lettere dell’ultimo libro dell’opera calmiana, che cerchi di far luce principalmente sull’aspetto linguistico e contenutistico del testo.Despite Vittorio Rossi's 1888 edition, Andrea Calmo's collection of "ingegnosi cheribizzi" and "fantastiche fantasie" is still shrouded in a certain mystery. The author, dissimulating his own identity behind the "mask" of the humble Venetian fisherman, was able to offer a cross-section of culture and society in sixteenth-century Venice.
In particular, it is the fourth book of the Letters that has aroused greater interest among scholars and readers: published in 1566, several years after the first three, this book stands out for the fact that all the epistles are addressed to women imaginary or actually existed.
Here we propose, first of all, a study of Calmo's biography accompanied by an analysis of the historical-cultural context of sixteenth-century Venice; secondly, however, a commentary on some letters from the last book of Calmo's work is proposed, which seeks to shed light mainly on the linguistic and content aspect of the text
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