arXiv subjects

Tomás Aquino

Publications and source records attributed to Tomás Aquino.

6 recordsLinked to original sources

arXiv2026

Topological origin of flow distributions in disordered porous media

We investigate steady Stokes flow through porous media composed of two-dimensional disordered arrays of circular obstacles. We develop a theory for the statistics of flow rates based on a pore-network model that captures local flow correlations. We show that the flow rate distribution across the ensemble of pore bodies follows a Gamma distribution, and that the flow rate distribution through pore throats is fully determined in terms of it. Furthermore, this Gamma distribution can be directly linked to simple geometrical properties such as the coefficient of variation of pore throat widths, rendering the model parameterisable from minimal medium information. The resulting predictions agree closely with computational fluid dynamics simulations and show markedly better agreement than prior mean-field models that neglect local flow-rate correlations, clarifying how local splitting and merging shape flow in disordered porous networks.

physics.flu-dyn↗

arXiv2021

Sharp transition to strongly anomalous transport in unsaturated porous media

The simultaneous presence of liquid and gas in porous media increases flow heterogeneity compared to saturated flows. However, so far the impact of saturation on flow statistics and transport dynamics remained unclear. Here, we develop a theoretical framework that captures the impact of flow reorganization on the statistics of pore-scale fluid velocities, due to the presence of gas in the pore space, which leads to the development of a highly-structured flow field. Preferential flow is distributed spatially through the denoted backbone and flow recirculation occurs in dead-end regions branching from it. This induces a marked change in the scaling of the velocity PDF compared to the saturated case, and a sharp transition to strongly anomalous transport. We develop a transport model based on the continuous time random walk theory that successfully predicts advective transport dynamics for all saturation degrees. Our results provide a new modelling framework linking phase heterogeneity to flow heterogeneity and to transport in unsaturated media.

physics.flu-dyn↗

arXiv2018

A Coupled Time Domain Random Walk Approach for Transport in Media Characterized by Broadly-distributed Heterogeneity Length Scales

We develop a time domain random walk approach for conservative solute transport in heterogeneous media where medium properties vary over a distribution of length scales. The spatial transition lengths are equal to the heterogeneity length scales, and thus determined by medium geometry. We derive analytical expressions for the associated transition times and probabilities in one spatial dimension. This approach determines the coarse-grained solute concentration at the interfaces between regions; we derive a generalized master equation for the evolution of the coarse-grained concentration and reconstruct the fine-scale concentration using the propagator of the subscale transport mechanism. The performance of this approach is demonstrated for diffusion under random retardation in power-law media characterized by heavy-tailed lengthscale and retardation distributions. The coarse representation preserves the correct late-time scaling of concentration variance, and the reconstructed fine-scale concentration is essentially identical to that obtained by direct numerical simulation by random walk particle tracking.

physics.flu-dyn↗

arXiv2017

Chemical continuous time random walks

Kinetic Monte Carlo methods such as the Gillespie algorithm model chemical reactions as random walks in particle number space. The inter-reaction times are exponentially distributed under the assumption that the system is well mixed. We introduce an arbitrary inter-reaction time distribution, which may account for the impact of incomplete mixing on chemical reactions, and in general stochastic reaction delay, which may represent the impact of extrinsic noise. This process defines an inhomogeneous continuous time random walk in particle number space, from which we derive a generalized chemical master equation. This leads naturally to a generalization of the Gillespie algorithm. Based on this formalism, we determine the modified chemical rate laws for different inter-reaction time distributions. This framework traces Michaelis--Menten-type kinetics back to finite-mean delay times, and predicts time-nonlocal macroscopic reaction kinetics as a consequence of broadly distributed delays. Non-Markovian kinetics exhibit weak ergodicity breaking and show key features of reactions under local non-equilibrium.

cond-mat.stat-mech↗

arXiv2014

Characterization of the Endemic Equilibrium and Response to Mutant Injection in a Multi-strain Disease Model

Starting from common assumptions, we build a rate equation model for multi-strain disease dynamics in terms of immune repertoire classes. We then move to a strain-level description where a low-order closure reminiscent of a pair approximation can be applied. We characterize the endemic equilibrium of the ensuing model in the absence of mutation and discuss the presence of degeneracy regarding the prevalence of the different strains. Finally we study the behavior of the system under the injection of mutant strains.

q-bio.PE↗

arXiv2012

Stochastic single-gene auto-regulation

A detailed stochastic model of single-gene auto-regulation is established and its solutions are explored when mRNA dynamics is fast compared with protein dynamics and in the opposite regime. The model includes all the sources of randomness that are intrinsic to the auto-regulation process and it considers both transcriptional and post transcriptional regulation. The timescale separation allows the derivation of analytic expressions for the equilibrium distributions of protein and mRNA. These distributions are generally well described in the continuous approximation, which is used to discuss the qualitative features of the protein equilibrium distributions as a function of the biological parameters in the fast mRNA regime. The performance of the timescale approximation is assessed by comparison with simulations of the full stochastic system, and a good quantitative agreement is found for a wide range of parameter values. We show that either unimodal or bimodal equilibrium protein distributions can arise, and we discuss the auto-regulation mechanisms associated with bimodality.

physics.bio-ph↗