86,676 research outputs found
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
A fish shoal algorithm for global derivative-free simulation-based ship design optimization
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
All-solid state ion-selective carbon black-modified printed electrode for sodium detection in sweat
No full textThe synergic combination of printed electronics and printed electrochemical sensors has recently emerged as a new route for developing smart chemical wearable devices applied to sweat monitoring. Sodium ion is one of electrolytes monitored in sweat to evaluate sweating level for electrolyte replacement recommendations. Herein, we report the development of new designed screen-printed electrodes, in which working electrode has been easily modified by drop-casting with the nanomaterial carbon black and a selective membrane cocktail, and the reference electrode with a polyvinyl butyral-based membrane. Once optimised all conditions, the screen-printed electrochemical sensor demonstrated no aqueous layer formation between working electrode and selective membrane, long-term potential stability, good shelf life, and resistance to interferences from oxygen and light. The carbon black-based sensor allowed for the detection of sodium ions in range 10(-4) M e 1 M with a slope of 58 +/- 3 mV/decade and a detection limit of 63 mu M. The applicability for sweat analysis was evaluated by analysing three sweat samples collecting during running activity, obtaining concentrations of 44 +/- 4 mM, 55 +/- 6 mM, and 47 +/- 3 mM, values in agreements with sodium ions content in healthy people, as well as using artificial sweat with recovery values of 90 +/- 3%, 94 +/- 2%, and 94 +/- 5%
Deep autoencoder for off-line 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 has been developed in earlier research to build a reduced-dimensionality design-space, resolving the 95% of the original geometric variance. The paper presents an extension of the method to more efficient nonlinear approaches. Specifically, the use of a deep autoencoder is presented and discussed. The method is demonstrated for the design-space dimensionality reduction and hydrodynamic optimization of the hull form of a USS Arleigh Burke-class destroyer
Variations on the Author
No full text“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Formulation and parameter selection of multi-objective deterministic particle swarm for simulation-based optimization
No full textGlobal derivative-free deterministic algorithms are particularly suitable for simulation-based optimization, where often the existence of multiple local optima cannot be excluded a priori, the derivatives of the objective functions are not available, and the evaluation of the objectives is computationally expensive, thus a statistical analysis of the optimization outcomes is not practicable. Among these algorithms, particle swarm optimization (PSO) is advantageous for the ease of implementation and the capability of providing good approximate solutions to the optimization problem at a reasonable computational cost. PSO has been introduced for single-objective problems and several extension to multi-objective optimization are available in the literature. The objective of the present work is the systematic assessment and selection of the most promising formulation and setup parameters of multi-objective deterministic particle swarm optimization (MODPSO) for simulation-based problems. A comparative study of six formulations (varying the definition of cognitive and social attractors) and three setting parameters (number of particles, initialization method, and coefficient set) is performed using 66 analytical test problems. The number of objective functions range from two to three and the number of variables from two to eight, as often encountered in simulation-based engineering problems. The desired Pareto fronts are convex, concave, continuous, and discontinuous. A full-factorial combination of formulations and parameters is investigated, leading to more than 60,000 optimization runs, and assessed by three performance metrics. The most promising MODPSO formulation/parameter is identified and applied to the hull-form optimization of a high-speed catamaran in realistic ocean conditions. Its performance is finally compared with four stochastic algorithms, namely three versions of multi-objective PSO and the genetic algorithm NSGA-II
Parameter selection in synchronous and asynchronous deterministic particle swarm optimization for ship hydrodynamics problems
No full textDeterministic optimization algorithms are very attractive when the objective
function is computationally expensive and therefore the statistical analysis of the
optimization outcomes becomes too expensive. Among deterministic methods,
Deterministic Particle Swarm Optimization (DPSO) has several attractive characteristics such as the simplicity of the heuristics, the ease of implementation,
and its often fairly remarkable effectiveness. The performances of DPSO depend
on four main setting parameters: the number of swarm particles, their initialization, the set of coefficients defining the swarm behavior, and (for box-constrained
optimization) the method to handle the box constraints. Here, a parametric
study of DPSO is presented, with application to simulation-based design in ship
hydrodynamics. The objective is the identification of the most promising setup
for both synchronous and asynchronous implementations of DPSO. The analysis is performed under the assumption of limited computational resources and
large computational burden of the objective function evaluation. The analysis is conducted using 100 analytical test functions (with dimensionality from
two to fifty) and three different performance criteria, varying the swarm size,
initialization, coefficients, and the method for the box constraints, resulting in more than 40,000 optimizations. The most promising setup is applied to the
hull-form optimization of a high speed catamaran, for resistance reduction in
calm water and at fixed speed, using a potential-flow solver
[Newspaper Clipping: Author Claims Evidence of Second JFK Assassin #1]
No full textNewspaper article titled "Author Claims Evidence of Second JFK Assassin." The article states that author Richard J. Whalen concluded "that there is circumstantial evidence to support the theory of a second assassin in the shooting of President John F. Kennedy.
A Retrospective Multicenter Analysis of the Incidence of Bone-Only Disease at PSMA PET/CT in Castration Resistant Prostate Cancer Patients
No full textPSMA PET/CT has unprecedented accuracy for localization of initial or recurrent prostate cancer (PC), which can be applied in a metastasis-directed therapy approach. PSMA PET/CT (PET) also has a role in the selection of patients for metastasis-directed therapy or radioligand therapy and therapy assessment in CRPC patients. The purpose of this multicenter retrospective study was to determine the incidence of bone-only metastasis in CRPC patients who underwent PSMA PET/CT for restaging, as well as identifying potential predictors of bone-only PET positivity. The study analyzed data from 179 patients from two centers in Essen and Bologna. Results showed that 20.1% of the patients had PSMA uptake only in the bone, with the most frequent lesions located in the vertebrae, ribs, and hip bone. Half half of the patients showed oligo disease in bone and may benefit from a bone-metastasis-directed therapy. Initial positive nodal status and solitary ADT were shown to be negative predictors of osseous metastasis. The role of PSMA PET/TC in this patient population needs to be further explored in terms of its role in the evaluation and adoption of bone-specific therapies
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