2,583 research outputs found
Decomposition of stochastic flows with automorphism of subbundles component
We show that given a -structure on a differentiable manifold , if
the group of automorphisms of is big enough, then there exists the
quotient of an stochastic flows by , in the sense that where , the remainder has
derivative which is vertical but transversal to the fibre of . This
geometrical context generalizes previous results where is a Riemannian
manifold and is decomposed with an isometric component, see Liao
\cite{Liao1} and Ruffino \cite{Ruffino}, which in our context corresponds to
the particular case of an SO(n)-structure on .Comment: To appear in Stochastics and Dynamics, 201
From rapid prototyping to building in real scale: methodologies for upscaling additive manufacturing in architecture
The manufacture of architectural components mediated by computer-controlled Additive Manufacturing (AM) technologies has highlighted several positive aspects of their application, namely by enabling customised design solutions and high-performance complex geometries. Taking into account the experience of the Advanced Ceramics R&D Lab, in the production of small- / medium- scale prototypes, this paper explores the main variables and constraints of the production of real-scale architectural components. This information points to a set of procedures that should be avoided and others that should be privileged, allowing to anticipate how AM can contribute for the achievement of high performance components on a large scale.This work has the financial support of the Project Lab2PT – Landscapes, Heritage and Territory laboratory – AUR/04509 and FCT through national founds and when applicable of the FEDER
cofinancing, in the aim of the new partnership agreement PT2020 and COMPETE2020 – POCI 01 0145FEDER 007528
Predictive Optimal Matrix Converter Control for a Dynamic Voltage Restorer with Flywheel Energy Storage
This paper presents a predictive optimal matrix converter controller for a flywheel energy storage system used as Dynamic Voltage Restorer (DVR). The flywheel energy storage device is based on a steel seamless tube mounted as a vertical axis flywheel to store kinetic energy. The motor/generator is a Permanent Magnet Synchronous Machine driven by the AC-AC Matrix Converter. The matrix control method uses a discrete-time model of the converter system to predict the expected values of the input and output currents for all the 27 possible vectors generated by the matrix converter. An optimal controller minimizes control errors using a weighted cost functional. The flywheel and control process was tested as a DVR to mitigate voltage sags and swells. Simulation results show that the DVR is able to compensate the critical load voltage without delays, voltage undershoots or overshoots, overcoming the input/output coupling of matrix converters
Idade, origem e protólitos de granitos variscos de três áreas portuguesas
Publicação digital - Online em 5 Fev. 201
Immobilization of proteases with a water soluble–insoluble reversible polymer for treatment of wool
A commercial protease, Esperase, was covalently linked to Eudragit S-100, a reversible soluble–insoluble polymer by carbodiimide coupling.
When compared to the native enzyme, the immobilized form presented a lower specific activity towards high molecular weight substrates but a higher thermal stability at all temperatures tested. The optimum pH of the immobilized protease was shifted towards the alkaline side by about one pH unit while there was no change in optimum temperature between the free and immobilized protease. The immobilized protease exhibited a good storage stability and re-usability.
Enzymatic treatment of wool using proteases has been investigated for wool shrink-resist finishing. It was found that using the immobilized
protease in the enzymatic treatment of wool there was a reduction of weight and fibre tensile strength loss because the proteolytic attack is only limited to the cuticle surfaces of wool fibres. This novel approach is a promising alternative for wool shrink-resist finishing to replace the conventional chlorine treatments. This environmentally friendly bioprocess needs to be further characterized to a complete understanding and optimization
A cone-continuity constraint qualification and algorithmic consequences
PRONEX - PROGRAMA DE APOIO A NÚCLEOS DE EXCELÊNCIAFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOREvery local minimizer of a smooth constrained optimization problem satisfies the sequential approximate Karush-Kuhn-Tucker (AKKT) condition. This optimality condition is used to define the stopping criteria of many practical nonlinear programming algorithms. It is natural to ask for conditions on the constraints under which AKKT implies KKT. These conditions will be called strict constraint qualifications (SCQs). In this paper we define a cone-continuity property (CCP) that will be shown to be the weakest possible SCQ. Its relation to other constraint qualifications will also be clarified. In particular, it will be proved that CCP is strictly weaker than the constant positive generator constraint qualification.Every local minimizer of a smooth constrained optimization problem satisfies the sequential approximate Karush-Kuhn-Tucker (AKKT) condition. This optimality condition is used to define the stopping criteria of many practical nonlinear programming algorithms. It is natural to ask for conditions on the constraints under which AKKT implies KKT. These conditions will be called strict constraint qualifications (SCQs). In this paper we define a cone-continuity property (CCP) that will be shown to be the weakest possible SCQ. Its relation to other constraint qualifications will also be clarified. In particular, it will be proved that CCP is strictly weaker than the constant positive generator constraint qualification26196110PRONEX - PROGRAMA DE APOIO A NÚCLEOS DE EXCELÊNCIAFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIORPRONEX - PROGRAMA DE APOIO A NÚCLEOS DE EXCELÊNCIAFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIORE-26/111.449/2010-APQ12013/07375-0; 2012/20339-0; 2013/05475-7304618/2013-6; 482549/2013-0; 303750/2014-6; 303013/2013-3sem informaçã
Two new weak constraint qualifications and applications
We present two new constraint qualifications (CQs) that are weaker than the recently introduced relaxed constant positive linear dependence (RCPLD) CQ. RCPLD is based on the assumption that many subsets of the gradients of the active constraints preserve positive linear dependence locally. A major open question was to identify the exact set of gradients whose properties had to be preserved locally and that would still work as a CQ. This is done in the first new CQ, which we call the constant rank of the subspace component (CRSC) CQ. This new CQ also preserves many of the good properties of RCPLD, such as local stability and the validity of an error bound. We also introduce an even weaker CQ, called the constant positive generator (CPG), which can replace RCPLD in the analysis of the global convergence of algorithms. We close this work by extending convergence results of algorithms belonging to all the main classes of nonlinear optimization methods: sequential quadratic programming, augmented Lagrangians, interior point algorithms, and inexact restoration.Facultad de Ciencias ExactasDepartamento de Matemátic
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