1,720,995 research outputs found
Optimización del desempeño térmico y energético de viviendas en la región Litoral Argentina
Full text linkPara lograr el diseño de un edificio energéticamente eficiente, el desempeño térmico y energético de una gran serie de diseños alternativos de dicho edificio deben analizarse en busca de una solución suficientemente buena o incluso óptima. Esta es una tarea generalmente muy compleja que involucra múltiples variables y objetivos. En este contexto, en esta Tesis se desarrolla una metodología de optimización basada en simulación numérica, generando una serie de novedosas herramientas computacionales. Estas tienen gran versatilidad debido a que acoplan EnergyPlus, uno de los software más populares para la simulación del comportamiento de edificios, con algoritmos genéticos de optimización permitiendo optimizar uno o varios objetivos a la vez. Inicialmente, para obtener resultados precisos de los modelos termo-energéticos usando el código EnergyPlus y subsanar una deficiencia importante de nuestro país, se desarrollan los años meteorológicos típicos y sus correspondientes archivos en formato de EnergyPlus para 15 localidades en el Litoral. Posteriormente, se implementan dos algoritmos genéticos, uno mono- y otro multi-objetivo, capaces de resolver problemas de múltiples variables. Además, para obtener resultados de optimización con tiempos razonables, se realiza la paralelización del código de optimización para su uso en PCs y clusters de varios procesadores o núcleos.Finalmente, las herramientas desarrolladas son aplicadas de forma detallada para el diseño óptimo con múltiples objetivos de una vivienda unifamiliar en el Litoral. Los resultados obtenidos indican que la metodología propuesta y las herramientas desarrolladas permiten explorar el espacio de diseño de forma automática y eficiente logrando diseños edilicios de alto desempeño.Fil: Bre, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentin
Optimization of multilayered walls for building envelopes including PCM-based composites
Full text linkThis work proposes a numerical procedure to simulate and optimize the thermal response of a multilayered wallboard system for building envelopes, where each layer can be possibly made of Phase Change Materials (PCM)-based composites to take advantage of their Thermal-Energy Storage (TES) capacity. The simulation step consists in solving the transient heat conduction equation across the whole wallboard using the enthalpy-based finite element method. The weather is described in detail by the Typical Meteorological Year (TMY) of the building location. Taking the TMY as well as the wall azimuth as inputs, EnergyPlusTM is used to define the convective boundary conditions at the external surface of the wall. For each layer, the material is chosen from a predefined vade mecum, including several PCM-based composites developed at the Institut für Werkstoffe im Bauwesen of TU Darmstadt together with standard insulating materials (i.e., EPS or Rockwool). Finally, the optimization step consists in using genetic algorithms to determine the stacking sequence of materials across the wallboard to minimize the undesired heat loads. The current simulation-based optimization procedure is applied to the design of envelopes for minimal undesired heat losses and gains in two locations with considerably different weather conditions, viz. Sauce Viejo in Argentina and Frankfurt in Germany. In general, for each location and all the considered orientations (north, east, south and west), optimal results consist of EPS walls containing a thin layer made of the PCM-based composite with highest TES capacity, placed near the middle of the wall and closer to the internal surface.Fil: Fachinotti, Victor Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; ArgentinaFil: Bre, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; ArgentinaFil: Mankel, Christoph. Universitat Technische Darmstadt; AlemaniaFil: Koenders, Eduardus A. B.. Universitat Technische Darmstadt; AlemaniaFil: Caggiano, Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Tecnologías y Ciencias de la Ingeniería "Hilario Fernández Long". Universidad de Buenos Aires. Facultad de Ingeniería. Instituto de Tecnologías y Ciencias de la Ingeniería "Hilario Fernández Long"; Argentin
Generación del año meteorológico típico para la ciudad de Santa Fe en la región litoral argentina
Full text linkEste trabajo está dedicado a la definición del año meteorológico típico (TMY, del inglés Typical Meteorological Year) en la ciudad de Santa Fe, ubicada en la región Litoral de la República Argentina. La definición del año típico es fundamental para la elaboración del archivo climático utilizado por los códigos de Simulación Energética de Edificios (BES, del inglés Building Energy Simulation). Se partió de datos proporcionados por el Servicio Meteorológico Nacional (SMN) de Argentina sobre diversas variables meteorológicas (temperatura de bulbo seco, temperatura de punto de rocío, humedad, etc.) registradas en intervalos horarios a lo largo de 14 años (2000-2013) en el Aeropuerto de Sauce Viejo (latitud 31.70°S, longitud 60.82°O, elevación 17 msnm). En base a criterios estadísticos, por cada mes del año, uno de todos los meses de muestra se cataloga como Mes Meteorológico Típico (TMM, del inglés Typical Meteorological Month). La concatenación de los doce TMMs define el TMY.Fil: Bre, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; ArgentinaFil: Fachinotti, Victor Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentin
Generation of typical meteorological years for the Argentine Littoral Region
Full text linkThis work describes the generation of the typical meteorological year (TMY) for 15 locations all around the Littoral Region in northeastern Argentina, southeastern South America. The originally available weather data at each location contain, among others, dry-bulb and dew-point temperatures, wind velocity, and total sky cover, hourly measured during the period 1994–2014 by the National Meteorological Service (SMN) of Argentina. From other sources, two of these locations have hourly measured solar radiation during a few years. These radiation measurements were used to calibrate an existing Zhang–Huang solar radiation model that was then used to calculate the hourly solar radiation for the entire weather data base. Once we complete the long-term weather database at a given location, we define the typical meteorological year (TMY) at this location as the concatenation of 12 typical meteorological months (TMM). The typicality of a month is measured using Finkelstein–Schafer statistics based on nine daily indices (maximum, minimum and mean dry-bulb and dew-point temperatures, maximum and mean wind velocity, and global solar radiation). We finally show an example of application of the current TMYs for building energy simulation in a location deep inside Littoral. Subsequently we show the importance of the newly developed local TMY above using original TMY from neighbouring locations.Fil: Bre, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentina. Universidad Tecnológica Nacional. Facultad Regional Concepción del Uruguay; ArgentinaFil: Fachinotti, Victor Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentina. Universidad Tecnológica Nacional. Facultad Regional Concepción del Uruguay; Argentin
Optimization of RANS turbulence models using genetic algorithms to improve the prediction of wind pressure coefficients on low-rise buildings
No full textBeing associated with natural ventilation, the pressure distribution on surfaces is relevant for energy consumption, thermal comfort, and air quality in buildings. The aim of this work is to present a simulation-based optimization methodology to recalibrate the closure coefficients of Reynolds-averaged Navier-Stokes (RANS) turbulence models in order to improve the prediction of wind surface-averaged pressure coefficients on a wide range of isolated low-rise buildings. To accomplish this, genetic algorithms and Computational Fluid Dynamics (CFD) simulations are dynamically coupled to find the closure coefficients set which minimize the CFD prediction error regarding wind-tunnel experimental data. The methodology is applied to two turbulence models, the renormalization group k-epsilon model (RNG) and the Spalart-Allmaras model (SA), considering as target cases buildings with different roof types (flat, gable and hip) and wind incidence angles. In order to show the strength of the novel optimal sets of closure coefficients obtained, an exhaustive validation is performed over other low-rise buildings (52 new cases) which were not calibrated against. Results validate using the optimal sets because the recalibrated RNG and SA models decrease the prediction error between 11-64% and 8?45%, respectively, regarding using the standard ones.Fil: Gimenez, Juan Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; ArgentinaFil: Bre, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentin
Optimization of thermal and energy performance of dwellings in the Argentine Litoral region
No full textFil: Bre, Facundo. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina.To achieve the design of an energy-efficient building, the thermal and energetic performance of a large series of alternative designs of such building must be analyzed in search of a sufficiently good or even optimal solution. This is usually a very complex task that involves multiple variables and objectives.
In this context, a numerical simulation-based optimization methodology is developed in this Thesis, generating a series of novel computational tools. These have great versatility due to the fact that they couple EnergyPlus, one of the most popular software for building performance simulations, with genetic optimization algorithms allowing to optimize one or several objectives at the same time. Initially, in order to obtain accurate results of the thermo-energetic models using the EnergyPlus code and to remedy an important deficiency of our country, the typical meteorological years and their corresponding files in EnergyPlus format for 15 locations in the Argentine Littoral region are developed. Subsequently, two genetic algorithms are implemented, one mono- and one multi-objective, capable of solving multiple variable problems. In addition, to obtain optimization results in reasonable computation times, the optimization code is parallelized for its use in PCs and clusters of several processors or cores. Finally, the tools developed are applied in detail to the optimal design with multiple objectives of a local, single-family dwelling. The obtained results indicate that the proposed methodology and the developed tools allow to explore the design space automatic and efficiently achieving high-performance building designs.Para lograr el diseño de un edificio energéticamente eficiente, el desempeño térmico y energético de una gran serie de diseños alternativos de dicho edificio deben analizarse en busca de una solución suficientemente buena o incluso óptima. Esta es una tarea generalmente muy compleja que involucra múltiples variables y objetivos. En este contexto, en esta Tesis se desarrolla una metodología de optimización basada en simulación numérica, generando una serie de novedosas herramientas computacionales. Estas tienen gran versatilidad debido a que acoplan EnergyPlus, uno de los software más populares para la simulación del comportamiento de edificios, con algoritmos genéticos de optimización permitiendo optimizar uno o varios objetivos a la vez. Inicialmente, para obtener resultados precisos de los modelos termo-energéticos usando el código EnergyPlus y subsanar una deficiencia importante de nuestro país, se desarrollan los años meteorológicos típicos y sus correspondientes archivos en formato de EnergyPlus para 15 localidades en el Litoral. Posteriormente, se implementan dos algoritmos genéticos, uno mono- y otro multi-objetivo, capaces de resolver problemas de múltiples variables. Además, para obtener resultados de optimización con tiempos razonables, se realiza la paralelización del código de optimización para su uso en PCs y clusters de varios procesadores o núcleos.
Finalmente, las herramientas desarrolladas son aplicadas de forma detallada para el diseño óptimo con múltiples objetivos de una vivienda unifamiliar en el Litoral. Los resultados obtenidos indican que la metodología propuesta y las herramientas desarrolladas permiten explorar el espacio de diseño de forma automática y eficiente logrando diseños edilicios de alto desempeño.Consejo Nacional de Investigaciones Científicas y Técnica
Optimization of thermal and energy performance of dwellings in the Argentine Litoral region
No full textFil: Bre, Facundo. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina.To achieve the design of an energy-efficient building, the thermal and energetic performance of a large series of alternative designs of such building must be analyzed in search of a sufficiently good or even optimal solution. This is usually a very complex task that involves multiple variables and objectives.
In this context, a numerical simulation-based optimization methodology is developed in this Thesis, generating a series of novel computational tools. These have great versatility due to the fact that they couple EnergyPlus, one of the most popular software for building performance simulations, with genetic optimization algorithms allowing to optimize one or several objectives at the same time. Initially, in order to obtain accurate results of the thermo-energetic models using the EnergyPlus code and to remedy an important deficiency of our country, the typical meteorological years and their corresponding files in EnergyPlus format for 15 locations in the Argentine Littoral region are developed. Subsequently, two genetic algorithms are implemented, one mono- and one multi-objective, capable of solving multiple variable problems. In addition, to obtain optimization results in reasonable computation times, the optimization code is parallelized for its use in PCs and clusters of several processors or cores. Finally, the tools developed are applied in detail to the optimal design with multiple objectives of a local, single-family dwelling. The obtained results indicate that the proposed methodology and the developed tools allow to explore the design space automatic and efficiently achieving high-performance building designs.Para lograr el diseño de un edificio energéticamente eficiente, el desempeño térmico y energético de una gran serie de diseños alternativos de dicho edificio deben analizarse en busca de una solución suficientemente buena o incluso óptima. Esta es una tarea generalmente muy compleja que involucra múltiples variables y objetivos. En este contexto, en esta Tesis se desarrolla una metodología de optimización basada en simulación numérica, generando una serie de novedosas herramientas computacionales. Estas tienen gran versatilidad debido a que acoplan EnergyPlus, uno de los software más populares para la simulación del comportamiento de edificios, con algoritmos genéticos de optimización permitiendo optimizar uno o varios objetivos a la vez. Inicialmente, para obtener resultados precisos de los modelos termo-energéticos usando el código EnergyPlus y subsanar una deficiencia importante de nuestro país, se desarrollan los años meteorológicos típicos y sus correspondientes archivos en formato de EnergyPlus para 15 localidades en el Litoral. Posteriormente, se implementan dos algoritmos genéticos, uno mono- y otro multi-objetivo, capaces de resolver problemas de múltiples variables. Además, para obtener resultados de optimización con tiempos razonables, se realiza la paralelización del código de optimización para su uso en PCs y clusters de varios procesadores o núcleos.
Finalmente, las herramientas desarrolladas son aplicadas de forma detallada para el diseño óptimo con múltiples objetivos de una vivienda unifamiliar en el Litoral. Los resultados obtenidos indican que la metodología propuesta y las herramientas desarrolladas permiten explorar el espacio de diseño de forma automática y eficiente logrando diseños edilicios de alto desempeño.Consejo Nacional de Investigaciones Científicas y Técnica
New metrics for thermal resilience of passive buildings during heat events
No full textIn the last years, the concept of thermal resilience has been gaining increasing relevance in building design. Several frameworks for resilience analysis were recently developed, which need to be tested and discussed through real case studies. However, few cases exist in the literature of passive and free-running buildings where thermal resilience against heat waves is analyzed from measured data. This paper aims to better understand and propose improvements to currently used overheating metrics. An in-depth analysis is performed of the thermal resilience against heat waves of a bioclimatic office building with passive strategies for indoor comfort in an arid region of central Argentina. Indoor conditions are obtained from both thermal simulations for two scenarios (with/without air conditioning) and in-situ monitoring. The results show that the selected metrics –also used by IEA-EBC Annex 80 - cannot fully describe the daily behavior of the building. Therefore, two new additional metrics are proposed, which account for solar radiation and the previous thermal history of the building. Their inclusion is a valuable contribution for passive and non-conditioned buildings towards a deeper understanding and improvement of thermal resilience against heat waves.Fil: Flores Larsen, Silvana Elinor. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones en Energía no Convencional. Universidad Nacional de Salta. Facultad de Ciencias Exactas. Departamento de Física. Instituto de Investigaciones en Energía no Convencional; ArgentinaFil: Filippin, Maria Celina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Bre, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentina. Universitat Technische Darmstadt; Alemani
A computational multi-objective optimization method to improve energy efficiency and thermal comfort in dwellings
Full text linkIn the last years, multi-objective optimization techniques became into one of the main challenges of the building energy efficiency area. The objective of this paper is to develop and validate a computational code for multi-objective building performance optimization by linking an evolutionary algorithm and a building simulation software in a powerful cluster. A sophisticated version of the multi-objective Non-dominated Sorting Genetic Algorithm-II (NSGA-II) was implemented in Python code to determine the optimal building design, which allows working with categorical and discrete variables, and the objectives were evaluated using the building energy simulation software EnergyPlus. NSGA-II was implemented to run in a high-performance cluster for the parallel computing of the fitness of each population (set of possible designs). In this work, the strengths of the proposed method were demonstrated by its application to the optimal design of a typical single-family house, located in the Argentine Littoral region. This house has some rooms conditioned only by natural ventilation, and other rooms with natural ventilation supplemented by mechanical air-conditioning (hybrid ventilation). The most influential design variables like roof types, external and internal wall types, solar orientation, solar absorptance, size, type, and windows shading of this house among others were studied in two complex cases of 108 and 1016 possibilities to obtain the best trade-off (Pareto front) between heating and cooling performance. Finally, a decision-making method was applied to select one configuration of the Pareto front. Optimal simulation results for the study cases indicated that is possible to improve up to 95% the thermal comfort in naturally ventilated rooms and up to 82% energy performance in air-conditioned rooms of the building with respect to the original configuration by using a design that takes simultaneous advantage of passive strategies like thermal inertia and natural ventilation. The methodology was proved to give a robust and powerful tool to design efficient dwellings reducing the optimization time from almost 12 days to 4.4 h.Fil: Bre, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentina. Universidad Tecnológica Nacional. Facultad Regional Concepción del Uruguay; ArgentinaFil: Fachinotti, Victor Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentin
Environmental benchmarks for the European cement industry
No full textThe urgent need to address climate change has pushed Europe to the forefront of environmental legislation initiatives, such as the Environment Action Program (EAP) within the European Green Deal and the disclosure of Environmental Product Declarations (EPDs) in the construction sector. The cement industry plays a vital role in this transition because it is one of the biggest contributors to greenhouse gas emissions worldwide. EPDs have managed to articulate the environmental information flow across different stakeholders, allowing them to incorporate sustainability design practices at the manufacturing, construction, and design levels. However, current EPDs are deterministically disclosed and lack benchmarks, hindering effective comparison and impeding sustainable material development. To address this challenge, the present research introduces a novel Life Cycle Assessment (LCA)-based probabilistic analysis to develop clinker and cement benchmarks. The proposed method incorporates data from industry reports, environmental databases, and EPDs, to generate the stochastic benchmarks. Moreover, a wide range of environmental performance indicators at a national level in Europe are covered, offering a holistic perspective beyond climate change. The results highlight the benefits of using country-specific environmental benchmarks, reducing the standard deviation of results by 2 to 7 times compared to background datasets. The reduction of clinker content proved to reduce 7 to 9 kg CO2eq/t for every 1% reduction in all countries. However, it also increased other indicators depending on the mineral component used as a replacement, underscoring the need for holistic analysis. The research also exposes discrepancies between EPDs and industry-related data, accentuating the need for stochastic information disclosure to enhance reliability and facilitate decision-making by stakeholders. Another significant contribution of this research is the development of an extensive open-access database, providing a reference for future developments regarding sustainable cement and concrete.Fil: Sambataro, Luciano. Universitat Technische Darmstadt; AlemaniaFil: Bre, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; ArgentinaFil: Ukrainczyk, Neven. Universitat Technische Darmstadt; AlemaniaFil: Koenders, Eduardus A. B.. Universitat Technische Darmstadt; Alemani
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