STRING is an online database enabling to predict physical and functional protein protein interactions based on databases and literature.
This paper proposes a structure for an "active" model of driver that enables to predict behaviour and performances in dynamic changing traffic conditions, with potential application both offline and online.
The damage model is based on a generalized macroscopic continuum theory within the framework of irreversible thermodynamics and enables to predict the progressive damage and failure load.
These experiments showed that the proposed model enables to predict flow rates and net power consumptions with good accuracy.
This paper presents a hierarchical multiscale approach based on a micro-kinetic model enabling to predict temperature, pressure and species generated during the thermite reaction of Al nanoparticles mixed with CuO nanoparticles.
To do so, using chemical engineering tools (thermodynamic tables and a model enabling to predict activity coefficients, solvation Gibbs energies and pKa data), it becomes possible to determine the partial chemical potential of neutral and charged components in real metabolic conditions, even in concentrated mixtures.
A new leaching risk analysis combined with LCA of different mortars composition (cement and lime based) was implemented enabling to predict the longevity of the rendering and the embodied carbon expenditure on 20th century buildings.
The overall performance of this model is good and enabled to predict the future summer temperature of Ethiopia.
Model enables to trace the history of deviations from the Local Equilibrium condition in both matrix phases and enables to predict the redistribution of precipitates in both matrix phases.
The Thermographic Method, which takes temperature increment as the fatigue indicator, enables to predict the fatigue limit of materials and mechanical components in a relative short time.
