49,317 research outputs found
A Hybrid Design Optimization Method using Enriched Craig-Bampton Approach
A hybrid design optimization method is presented which combines a number of techniques such as Component Mode Synthesis (CMS), Design of Computer Experiments and Neural Networks for surrogate modeling with Genetic Algorithms and Sequential Quadratic Programming for optimization. In the method, the FE analysis is decomposed and reduced by a well-known CMS technique called the Craig-Bampton method. Since the optimization method requires CMS calculations of the updated model at each of its iterations due to the changes in the design variables, one can either reuse the reduction basis of the initial components or compute new reduction basis for the condensation of the system matrices. The first option usually leads to inaccurate results and the last one increases the omputation time. In the method, instead of using one of these options, the Enriched Craig-Bampton method, proposed by Masson et al., is employed for efficient optimization. New basis for the modified components are generated by extending the corresponding initial reduction basis with a set of static residual vectors which are calculated using prior knowledge of the initial component designs. Thus, time consuming complete component analyzes are prevented. A theoretical test problem is used for the demonstration of the method
Robust Cooperative Manipulation without Force/Torque Measurements: Control Design and Experiments
This paper presents two novel control methodologies for the cooperative
manipulation of an object by N robotic agents. Firstly, we design an adaptive
control protocol which employs quaternion feedback for the object orientation
to avoid potential representation singularities. Secondly, we propose a control
protocol that guarantees predefined transient and steady-state performance for
the object trajectory. Both methodologies are decentralized, since the agents
calculate their own signals without communicating with each other, as well as
robust to external disturbances and model uncertainties. Moreover, we consider
that the grasping points are rigid, and avoid the need for force/torque
measurements. Load distribution is also included via a grasp matrix
pseudo-inverse to account for potential differences in the agents' power
capabilities. Finally, simulation and experimental results with two robotic
arms verify the theoretical findings
Improving the NRTidal model for binary neutron star systems
Accurate and fast gravitational waveform (GW) models are essential to extract
information about the properties of compact binary systems that generate GWs.
Building on previous work, we present an extension of the NRTidal model for
binary neutron star (BNS) waveforms. The upgrades are: (i) a new closed-form
expression for the tidal contribution to the GW phase which includes further
analytical knowledge and is calibrated to more accurate numerical relativity
data than previously available; (ii) a tidal correction to the GW amplitude;
(iii) an extension of the spin-sector incorporating equation-of-state-dependent
finite size effects at quadrupolar and octupolar order; these appear in the
spin-spin tail terms and cubic-in-spin terms, both at 3.5PN. We add the new
description to the precessing binary black hole waveform model IMRPhenomPv2 to
obtain a frequency-domain precessing binary neutron star model. In addition, we
extend the SEOBNRv4_ROM and IMRPhenomD aligned-spin binary black hole waveform
models with the improved tidal phase corrections. Focusing on the new
IMRPhenomPv2_NRTidalv2 approximant, we test the model by comparing with
numerical relativity waveforms as well as hybrid waveforms combining tidal
effective-one-body and numerical relativity data. We also check consistency
against a tidal effective-one-body model across large regions of the BNS
parameter space.Comment: Accepted manuscrip
A hybrid approach to space power control
Conventional control systems have traditionally been utilized for space-based power designs. However, the use of expert systems is becoming important for NASA applications. Rocketdyne has been pursuing the development of expert systems to aid and enhance control designs of space-based power systems. The need for integrated expert systems is vital for the development of autonomous power systems
Inclusion of Enclosed Hydration Effects in the Binding Free Energy Estimation of Dopamine D3 Receptor Complexes
Confined hydration and conformational flexibility are some of the challenges
encountered for the rational design of selective antagonists of G-protein
coupled receptors. We present a set of C3-substituted (-)-stepholidine
derivatives as potent binders of the dopamine D3 receptor. The compounds are
characterized biochemically, as well as by computer modeling using a novel
molecular dynamics-based alchemical binding free energy approach which
incorporates the effect of the displacement of enclosed water molecules from
the binding site. The free energy of displacement of specific hydration sites
is obtained using the Hydration Site Analysis method with explicit solvation.
This work underscores the critical role of confined hydration and
conformational reorganization in the molecular recognition mechanism of
dopamine receptors and illustrates the potential of binding free energy models
to represent these key phenomena.Comment: This is the first report of using enclosed hydration in estimating
binding free energies of protein-ligand complexes using implicit solvatio
Modeling user navigation
This paper proposes the use of neural networks as a tool for studying navigation within virtual worlds. Results indicate that the network learned to predict the next step for a given trajectory. The analysis of hidden layer shows that the network was able to differentiate between two groups of users identified on the basis of their performance for a spatial task. Time series analysis of hidden node activation values and input vectors suggested that certain hidden units become specialised for place and heading, respectively. The benefits of this approach and the possibility of extending the methodology to the study of navigation in Human Computer Interaction applications are discussed
Evolutionary Synthesis of Analog Electronic Circuits Using EDA Algorithms
Disertační práce je zaměřena na návrh analogových elektronických obvodů pomocí algoritmů s pravěpodobnostními modely (algoritmy EDA). Prezentované metody jsou na základě požadovaných charakteristik cílových obvodů schopny navrhnout jak parametry použitých komponent tak také jejich topologii zapojení. Tři různé metody využití EDA algoritmů jsou navrženy a otestovány na příkladech skutečných problémů z oblasti analogových elektronických obvodů. První metoda je určena pro návrh pasivních analogových obvodů a využívá algoritmus UMDA pro návrh jak topologie zapojení tak také hodnot parametrů použitých komponent. Metoda je použita pro návrh admitanční sítě s požadovanou vstupní impedancí pro účely chaotického oscilátoru. Druhá metoda je také určena pro návrh pasivních analogových obvodů a využívá hybridní přístup - UMDA pro návrh topologie a metodu lokální optimalizace pro návrh parametrů komponent. Třetí metoda umožňuje návrh analogových obvodů obsahujících také tranzistory. Metoda využívá hybridní přístup - EDA algoritmus pro syntézu topologie a metoda lokální optimalizace pro určení parametrů použitých komponent. Informace o topologii je v jednotlivých jedincích populace vyjádřena pomocí grafů a hypergrafů.Dissertation thesis is focused on design of analog electronic circuits using Estimation of Distribution Algorithms (EDA). Based on the desired characteristics of the target circuits the proposed methods are able to design the parameters of the used components and theirs topology of connection as well. Three different methods employing EDA algorithms are proposed and verified on examples of real problems from the area of analog circuits design. The first method is capable to design passive analog circuits. The method employs UMDA algorithm which is used for determination of the parameters of the used components and synthesis of the topology of their connection as well. The method is verified on the problem of design of admittance network with desired input impedance function which is used as a part of chaotic oscillator circuit. The second method is also capable to design passive analog circuits. The method employs hybrid approach - UMDA for synthesis of the topology and local optimization method for determination of the parameters of the components. The third method is capable to design analog circuits which include also ac- tive components such as transistors. Hybrid approach is used. The topology is synthesized using EDA algorithm and the parameters are determined using a local optimization method. In the individuals of the population information about the topology is represented using graphs and hypergraphs.
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