The combination of image quantification, model building, and computer simulation is illustrated here using the example of diffusion in the endoplasmic reticulum.
The quantification of the building performance is discussed by using stochastic finite element modeling techniques.
The simulation includes shading calculations for each segment of the façades and roofs and thus allows a very detailed quantification of the building energy demand.
One methodology is proposed to estimate the quantification and composition of building-related construction and demolition (C&D) waste in a fast developing region like Shanghai, PR China.
In this paper a Monte Carlo based methodology for uncertainty quantification that combines the building simulation and the cost-benefit calculation is developed and demonstrated.
Quantification is achieved by building the relationship between the liquid mass flow rate through each microchannel tube and the air-side capacity calculated from the infrared measurement of the wall temperature.
The study focuses on the economic quantification of the residential building damage caused by an earthquake, and adopts the housing market value provided by OMI as a reliable economic indicator, instead of the cost of construction, which is commonly used, but is difficult to quantify.
This paper proposes a Monte Carlo based methodology for uncertainty quantification that combines parametric building simulation and LCC analysis, showing a great potential in the possibility of combining several EEMs and undertake the uncertainty calculation with low computational costs and high accuracy of the result.
A total of 91 out of 1,016 samples (9.1%) were quantified below the limit of quantification and omitted during model building.
Hereafter, we highlight just a few applications of computational Systems Toxicology covering Computational Toxicology, biological network model building, biological impact quantification, and predictive modeling to exemplify some recent developments in these four areas.
