Dataset Information

Data on external walls from a multi-objective simulation for cold climates.

ABSTRACT: Data are related to the multi-objective optimization process applied to the building materials to obtain high energy-efficient precast walls for cold climate. The methodology has been explained on the paper entitled "High performance precast external walls for cold climate by a multi criteria methodology" (Baglivo and Congedo, 2016) [1]. The modeFRONTIER rel.4.3 optimization tool has been used to evaluate the dynamic behaviour of the building components in accordance with the UNI EN ISO 13786:2008 and to obtain a multitude of high efficiency configurations. The results are divided into three categories thick, thin and ultra-thin precast walls, in accordance with their thicknesses. The input data are the building materials with their thermal properties, sustainability characteristics and the supply and installation costs. The output values of the simulations are adapted to the cold climate and based on thermal properties, costs and sustainability score. Several combinations of external precast walls have been shown as optimal for cold climate.

SUBMITTER: Baglivo C

PROVIDER: S-EPMC5066207 | biostudies-other | 2016 Dec

REPOSITORIES: biostudies-other

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Data on external walls from a multi-objective simulation for cold climates.

Baglivo Cristina C Congedo Paolo Maria PM

Data in brief 20161005

Data are related to the multi-objective optimization process applied to the building materials to obtain high energy-efficient precast walls for cold climate. The methodology has been explained on the paper entitled "High performance precast external walls for cold climate by a multi criteria methodology" (Baglivo and Congedo, 2016) [1]. The modeFRONTIER rel.4.3 optimization tool has been used to evaluate the dynamic behaviour of the building components in accordance with the UNI EN ISO 13786:20 ...[more]

PMID: 27766289

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Project description:The advent of two-photon microscopy now reveals unprecedented, detailed spatio-temporal data on cellular motility and interactions in vivo. Understanding cellular motility patterns is key to gaining insight into the development and possible manipulation of the immune response. Computational simulation has become an established technique for understanding immune processes and evaluating hypotheses in the context of experimental data, and there is clear scope to integrate microscopy-informed motility dynamics. However, determining which motility model best reflects in vivo motility is non-trivial: 3D motility is an intricate process requiring several metrics to characterize. This complicates model selection and parameterization, which must be performed against several metrics simultaneously. Here we evaluate Brownian motion, Lévy walk and several correlated random walks (CRWs) against the motility dynamics of neutrophils and lymph node T cells under inflammatory conditions by simultaneously considering cellular translational and turn speeds, and meandering indices. Heterogeneous cells exhibiting a continuum of inherent translational speeds and directionalities comprise both datasets, a feature significantly improving capture of in vivo motility when simulated as a CRW. Furthermore, translational and turn speeds are inversely correlated, and the corresponding CRW simulation again improves capture of our in vivo data, albeit to a lesser extent. In contrast, Brownian motion poorly reflects our data. Lévy walk is competitive in capturing some aspects of neutrophil motility, but T cell directional persistence only, therein highlighting the importance of evaluating models against several motility metrics simultaneously. This we achieve through novel application of multi-objective optimization, wherein each model is independently implemented and then parameterized to identify optimal trade-offs in performance against each metric. The resultant Pareto fronts of optimal solutions are directly contrasted to identify models best capturing in vivo dynamics, a technique that can aid model selection more generally. Our technique robustly determines our cell populations' motility strategies, and paves the way for simulations that incorporate accurate immune cell motility dynamics.

Dataset Information

Data on external walls from a multi-objective simulation for cold climates.

Publications

Data on external walls from a multi-objective simulation for cold climates.

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