arXiv subjects

Cyril Caliot

Publications and source records attributed to Cyril Caliot.

4 recordsLinked to original sources

arXiv2022

A physical model and a Monte Carlo estimate for the specific intensity spatial derivative, angular derivative and geometric sensitivity

Starting from the radiative transfer equation and its usual boundary conditions, the objective of this work is to design Monte Carlo algorithms estimating the specific intensity spatial and angular derivatives as well as its geometric sensitivity. The present document is structured in three parts, each of them dedicated to a specific derivative of the intensity. Although they are all assembled here in one document each derivative is of interest independently whether it be for radiative transfers analysis or engineering conception. Therefore, they are thought to be written as three different papers and are presented here as such. Estimating derivatives of the specific intensity when solving radiative transfers using a Monte-Carlo algorithm is challenging. Finite differences are often not sufficiently accurate and directly estimating the derivative from a specific Monte-Carlo algorithm can lead to arduous formal or numerical developments. The proposition here is to work from the radiative transfer equation and its boundary conditions to design a physical model for each derivatives. Only then Monte-Carlo algorithms are built from the derivatives differential equations using the usual equivalent path integral. Since the same methodology is applied to the specific intensity spatial derivative, angular derivative and geometric sensitivity we chose to keep the same writing structure for all three parts so that all common ideas and developments appears exactly the same. We believe this choice to be coherent to facilitate the reader's understanding. Finally, these are preliminary versions of the final papers: for each parts the theory is fully described, but, although they have been implemented, the examples and algorithms sections are not always complete. This will be mentioned in the introductions of the concerned sections.

physics.app-ph↗

arXiv2022

The "teapot in a city": a paradigm shift in urban climate modeling

Urban areas are a high-stake target of climate change mitigation and adaptation measures. To understand, predict and improve the energy performance of cities, the scientific community develops numerical models that describe how they interact with the atmosphere through heat and moisture exchanges at all scales. In this review, we present recent advances that are at the origin of last decade's revolution in computer graphics, and recent breakthroughs in statistical physics that extend well established path-integral formulations to non-linear coupled models. We argue that this rare conjunction of scientific advances in mathematics, physics, computer and engineering sciences opens promising avenues for urban climate modeling and illustrate this with coupled heat transfer simulations in complex urban geometries under complex atmospheric conditions. We highlight the potential of these approaches beyond urban climate modeling, for the necessary appropriation of the issues at the heart of the energy transition by societies.

physics.soc-ph↗

arXiv2020

Temperature dependence of the static permittivity andintegral formula for the Kirkwood correlation factor ofsimple polar fluids

An exact integral formula for the Kirkwood correlation factor of isotropic polar fluids $g_K$ is derived from the equilibrium averaged rotational Dean equation, which as compared to previous approaches easily lends itself to further approximations. The static linear permittivity of polar fluids $\epsilon$ is calculated as a function of temperature, density and molecular dipole moment in vacuo for arbitrary pair interaction potentials. Then, using the Kirkwood superposition approximation for the three-body orientational distribution function, we suggest a simple way to construct model potentials of mean torques considering permanent and induced dipole moments. We successfully compare the theory with the experimental temperature dependence of the static linear permittivity of various polar fluids such as a series of linear monohydroxy alcohols, water, tributyl phosphate, acetonitrile, acetone, nitrobenzene and dimethyl sulfoxide, by fitting only one single parameter, which describes the induction to dipole-dipole energy strength ratio. We demonstrate that comparing the value of $g_K$ with unity in order to deduce the alignment state of permanent dipole pairs, as is currently done is in many situations, is a misleading oversimplification, while the correct alignment state is revealed when considering the proper interaction potential. Moreover we show, that picturing H-bonding polar fluids as polar molecules with permanent and induced dipole moments without invoking any specific H-bonding mechanism is in many cases sufficient to explain experimental data of the static dielectric constant. In this light, the failure of the theory to describe the experimental temperature dependence of the static dielectric constant of glycerol, a non-rigid polyalcohol, is not due to the lack of specific H-bonding mechanisms, but rather to an oversimplified model potential for that particular molecule.

cond-mat.soft↗

arXiv2018

Addressing nonlinearities in Monte Carlo

Monte Carlo is famous for accepting model extensions and model refinements up to infinite dimension. However, this powerful incremental design is based on a premise which has severely limited its application so far: a state-variable can only be recursively defined as a function of underlying state-variables if this function is linear. Here we show that this premise can be alleviated by projecting nonlinearities onto a polynomial basis and increasing the configuration space dimension. Considering phytoplankton growth in light-limited environments, radiative transfer in planetary atmospheres, electromagnetic scattering by particles, and concentrated solar power plant production, we prove the real-world usability of this advance in four test cases which were previously regarded as impracticable using Monte Carlo approaches. We also illustrate an outstanding feature of our method when applied to acute problems with interacting particles: handling rare events is now straightforward. Overall, our extension preserves the features that made the method popular: addressing nonlinearities does not compromise on model refinement or system complexity, and convergence rates remain independent of dimension. Published: Dauchet J, Bezian J-J, Blanco S, Caliot C, Charon J, Coustet C, El Hafi M, Eymet V, Farges O, Forest V, Fournier R, Galtier M, Gautrais J, Khuong A, Pelissier L, Piaud B, Roger M, Terrée G, Weitz S (2018) Addressing nonlinearities in Monte Carlo. Sci. Rep. 8: 13302, DOI:10.1038/s41598-018-31574-4

physics.comp-ph↗