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Artículo

On the efficiency of quantization-based integration methods for building simulation

Bergero, FedericoIcon ; Casella, Francesco; Kofman, Ernesto JavierIcon ; Fernández, JoaquínIcon
Fecha de publicación: 04/2018
Editorial: Springer
Revista: Building Simulation
ISSN: 1996-3599
e-ISSN: 1996-8744
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:
Otras Ciencias de la Computación e Información

Resumen

Models describing energy consumption, heating, and cooling of buildings usually impose difficulties to the numerical integration algorithms used to simulate them. Stiffness and the presence of frequent discontinuities are among the main causes of those difficulties, that become critical when the models grow in size. Quantized State Systems (QSS) methods are a family of numerical integration algorithms that can efficiently handle discontinuities and stiffness in large models. For this reason, they are promising candidates for overcoming the mentioned problems. Based on this observation, this article studies the performance of QSS methods in some systems that are relevant to the field of building simulation. The study includes a performance comparison of different QSS algorithms against state-of-the-art classic numerical solvers, showing that the former can be more than one order of magnitude faster.
Palabras clave: BUILDING SIMULATION , HVAC , HYBRID MODELS , LARGE SCALE SYSTEM , QUANTIZED STATE SYSTEMS
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info:eu-repo/semantics/openAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/185862
URL: https://link.springer.com/article/10.1007/s12273-017-0400-1
DOI: http://dx.doi.org/10.1007/s12273-017-0400-1
Colecciones
Articulos(CIFASIS)
Articulos de CENTRO INT.FRANCO ARG.D/CS D/L/INF.Y SISTEM.
Citación
Bergero, Federico; Casella, Francesco; Kofman, Ernesto Javier; Fernández, Joaquín; On the efficiency of quantization-based integration methods for building simulation; Springer; Building Simulation; 11; 2; 4-2018; 405-418
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