Examinando por Autor "Toro, M"

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    Ítem
    Shore erosion between Arboletes and Punta San Bernardo, caribbean coast of Colombia
    (Universidad Industrial de Santander, 2007-07-02) Correa-Arango, Ivan D.; Ríos, A; González, D; Toro, M; Ojeda, G; Restrepo, L; Universidad EAFIT. Departamento de Geología; Ivan D. Correa-Arango (icorrea@eafit.edu.co); Ciencias del Mar
    The present morphology and the inventory of the historical shoreline changes (1938-2005) between Arboletes and Punta San Bernardo evidenced a strong erosional trend along 160 of its 180lan tota1-1ength, resulting in the disparition/retreat of numerous beaches, followed by the consequent flooding/erosion of the adjacent littoral terraces and mangrove swamps. In general terms, the littoral Arbo1etes-Punta San Bernardo retreated 30 to 100m during the last seven decades, at rates between 0.5 and 1.5 m/year; maximum values were found at some critical sectors in the Arboletes-Punta Brava shore segment where magnitudes of coastline retreat were in the order of 900-1.500m at erosion rates up to 70 m/year during the period 19601975. Shore erosion in the study area results both from marine and subaerial processes and the combination of geological factors (neotectonism and effects of mud diapirism, minor stocks of sands, relative sea level rise, poor geotechnical characteristics of cliff's rocks) and human interventions (intensive sand mining from beaches and rivers, land uses with inadequate water management practices, adverse effects of groins and other rigid structures of defense). The precise definition of each one of these factors is necessary for planning the development of the area considering the future sea level rise associated to the Global Climate Change.
  • No hay miniatura disponible
    Ítem
    Wing profile evolution driven by computational fluid dynamics
    (UNIV INDUSTRIAL SANTANDER, 2019-04-01) Rendon, CC; Hernandez, JL; Ruiz-Salguero, O; Alvarez, CA; Toro, M; Rendon, CC; Hernandez, JL; Ruiz-Salguero, O; Alvarez, CA; Toro, M; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las Comunicaciones
    In the domain of fluid dynamics, the problem of shape optimization is relevant because is essential to increase lift and reduce drag forces on a body immersed in a fluid. The current state of the art in this aspect consists of two variants: (1) evolution from an initial guess, using optimization to achieve a very specific effect, (2) creation and genetic breeding of random individuals. These approaches achieve optimal shapes and evidence of response under parameter variation. Their disadvantages are the need of an approximated solution and/or the trial - and - error generation of individuals. In response to this situation, this manuscript presents a method which uses Fluid Mechanics indicators (e.g. streamline curvature, pressure difference, zero velocity neighborhoods) to directly drive the evolution of the individual (in this case a wing profile). This pragmatic strategy mimics what an artisan (knowledgeable in a specific technical domain) effects to improve the shape. Our approach is not general, and it is not fully automated. However, it shows to efficiently reach wing profiles with the desired performance. Our approach shows the advantage of application domain - specific rules to drive the optimization, in contrast with generic administration of the evolution.
  • No hay miniatura disponible
    Ítem
    Wing profile evolution driven by computational fluid dynamics
    (UNIV INDUSTRIAL SANTANDER, 2019-04-01) Rendon, CC; Hernandez, JL; Ruiz-Salguero, O; Alvarez, CA; Toro, M; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAE
    In the domain of fluid dynamics, the problem of shape optimization is relevant because is essential to increase lift and reduce drag forces on a body immersed in a fluid. The current state of the art in this aspect consists of two variants: (1) evolution from an initial guess, using optimization to achieve a very specific effect, (2) creation and genetic breeding of random individuals. These approaches achieve optimal shapes and evidence of response under parameter variation. Their disadvantages are the need of an approximated solution and/or the trial - and - error generation of individuals. In response to this situation, this manuscript presents a method which uses Fluid Mechanics indicators (e.g. streamline curvature, pressure difference, zero velocity neighborhoods) to directly drive the evolution of the individual (in this case a wing profile). This pragmatic strategy mimics what an artisan (knowledgeable in a specific technical domain) effects to improve the shape. Our approach is not general, and it is not fully automated. However, it shows to efficiently reach wing profiles with the desired performance. Our approach shows the advantage of application domain - specific rules to drive the optimization, in contrast with generic administration of the evolution.
  • No hay miniatura disponible
    Ítem
    Wing profile evolution driven by computational fluid dynamics
    (UNIV INDUSTRIAL SANTANDER, 2019-04-01) Rendon, CC; Hernandez, JL; Ruiz-Salguero, O; Alvarez, CA; Toro, M; Universidad EAFIT. Departamento de Ingeniería Mecánica; Estudios en Mantenimiento (GEMI)
    In the domain of fluid dynamics, the problem of shape optimization is relevant because is essential to increase lift and reduce drag forces on a body immersed in a fluid. The current state of the art in this aspect consists of two variants: (1) evolution from an initial guess, using optimization to achieve a very specific effect, (2) creation and genetic breeding of random individuals. These approaches achieve optimal shapes and evidence of response under parameter variation. Their disadvantages are the need of an approximated solution and/or the trial - and - error generation of individuals. In response to this situation, this manuscript presents a method which uses Fluid Mechanics indicators (e.g. streamline curvature, pressure difference, zero velocity neighborhoods) to directly drive the evolution of the individual (in this case a wing profile). This pragmatic strategy mimics what an artisan (knowledgeable in a specific technical domain) effects to improve the shape. Our approach is not general, and it is not fully automated. However, it shows to efficiently reach wing profiles with the desired performance. Our approach shows the advantage of application domain - specific rules to drive the optimization, in contrast with generic administration of the evolution.