Léster Alfonso | Universidad Autónoma de la Ciudad de México (original) (raw)

Papers by Léster Alfonso

Research paper thumbnail of Reconstruction of the solution of the coagulation equation in two components from its orthogonal projections: an application to the physics of clouds

A proposal for the reconstruction of the solution of the Smoluchowski equation is established fro... more A proposal for the reconstruction of the solution of the Smoluchowski equation is established from the knowledge of its orthogonal projections. Some computational results are exhibited. This work is part of a research whose purpose is the calculation of the evolution of a bidimensional drops atmospherical spectrum, with liquid mass m and aerosol n, from the coagulation process.

Research paper thumbnail of Stochastic coalescence in finite systems: an algorithm for the numerical solution of the multivariate master equation

Bulletin of the American Physical Society, Apr 12, 2015

approach to coagulation considers the coalescence process going in a system of a finite number of... more approach to coagulation considers the coalescence process going in a system of a finite number of particles enclosed in a finite volume. Within this approach, the full description of the system can be obtained from the solution of the multivariate master equation, which models the evolution of the probability distribution of the state vector for the number of particles of a given mass. Unfortunately, due to its complexity, only limited results were obtained for certain type of kernels and monodisperse initial conditions. In this work, a novel numerical algorithm for the solution of the multivariate master equation for stochastic coalescence that works for any type of kernels and initial conditions is introduced. The performance of the method was checked by comparing the numerically calculated particle mass spectrum with analytical solutions obtained for the constant and sum kernels, with an excellent correspondence between the analytical and numerical solutions. In order to increase the speedup of the algorithm, software parallelization techniques with OpenMP standard were used, along with an implementation in order to take advantage of new accelerator technologies. Simulations results show an important speedup of the parallelized algorithms.

Research paper thumbnail of A Stochastic Model for the Collection Growth of Ice Particles in Mixed- Phase Clouds

Research paper thumbnail of Bayesian analysis of external corrosion data of non-piggable underground pipelines

Corrosion Science, 2015

Development of a physiologically relevant 3D model system for cancer research and drug developmen... more Development of a physiologically relevant 3D model system for cancer research and drug development is a current challenge. We have adopted a 3D culture system based on a transglutaminase-crosslinked gelatin gel (Col-Tgel) to mimic the tumor 3D microenvironment. The system has several unique advantages over other alternatives including presenting cell-matrix interaction sites from collagen-derived peptides, geometry-initiated multicellular tumor spheroids, and metabolic gradients in the tumor microenvironment. Also it provides a controllable wide spectrum of gel stiffness for mechanical signals, and technical compatibility with imaging based screening due to its transparent properties. In addition, the Col-Tgel provides a cure-in-situ delivery vehicle for tumor xenograft formation in animals enhancing tumor cell uptake rate. Overall, this distinctive 3D system could offer a platform to more accurately mimic in vivo situations to study tumor formation and progression both in vitro and in vivo.

Research paper thumbnail of Markov Chain Models for the Stochastic Modeling of Pitting Corrosion

Mathematical Problems in Engineering, 2013

The stochastic nature of pitting corrosion of metallic structures has been widely recognized. It ... more The stochastic nature of pitting corrosion of metallic structures has been widely recognized. It is assumed that this kind of deterioration retains no memory of the past, so only the current state of the damage influences its future development. This characteristic allows pitting corrosion to be categorized as a Markov process. In this paper, two different models of pitting corrosion, developed using Markov chains, are presented. Firstly, a continuous-time, nonhomogeneous linear growth (pure birth) Markov process is used to model external pitting corrosion in underground pipelines. A closed-form solution of the system of Kolmogorov's forward equations is used to describe the transition probability function in a discrete pit depth space. The transition probability function is identified by correlating the stochastic pit depth mean with the empirical deterministic mean. In the second model, the distribution of maximum pit depths in a pitting experiment is successfully modeled afte...

Research paper thumbnail of Statistical Analysis of Pitting Corrosion Field Data and Their Use for Realistic Reliability Estimations in Non-Piggable Pipeline Systems

CORROSION, 2014

The reliability and risk of non-piggable, corroding oil and gas pipelines can be estimated from h... more The reliability and risk of non-piggable, corroding oil and gas pipelines can be estimated from historical failure data and through reliability models based on the assumed or measured number of corrosion defects and defect size distribution. In this work, an extensive field survey carried out in an upstream gathering pipeline system in Southern Mexico is presented. It has helped determine realistic values for the number of corrosion defects per kilometer (defect density) and obtain a better description of the corrosion defect size distributions in this system. To illustrate the impact that these new corrosion data can have on pipeline risk management, a reliability study is also presented where the field-gathered corrosion data have been used as input to a reliability framework for the estimation of the failure index of non-piggable pipelines and pipeline systems when different amounts of corrosion data are available.

Research paper thumbnail of Stochastic modeling of pitting corrosion: A new model for initiation and growth of multiple corrosion pits

Corrosion Science, 2007

In this work, a new stochastic model capable of simulating pitting corrosion is developed and val... more In this work, a new stochastic model capable of simulating pitting corrosion is developed and validated. Pitting corrosion is modeled as the combination of two stochastic processes: pit initiation and pit growth. Pit generation is modeled as a nonhomogeneous Poisson process, in which induction time for pit initiation is simulated as the realization of a Weibull process. In this way, the exponential and Weibull distributions can be considered as the possible distributions for pit initiation time. Pit growth is simulated using a nonhomogeneous Markov process. Extreme value statistics is used to find the distribution of maximum pit depths resulting from the combination of the initiation and growth processes for multiple pits. The proposed model is validated using several published experiments on pitting corrosion. It is capable of reproducing the experimental observations with higher quality than the stochastic models available in the literature for pitting corrosion.

Research paper thumbnail of On the scaling of the distribution of daily price fluctuations in the Mexican financial market index

Physica A: Statistical Mechanics and its Applications, 2012

Research paper thumbnail of Parameterization of the collision-coalescence process using series of basis functions: COLNETv1.0.0 model development using a machine learning approach

Geoscientific Model Development Discussions, 2021

Abstract. A parameterization for the collision-coalescence process is presented, based on the met... more Abstract. A parameterization for the collision-coalescence process is presented, based on the methodology of basis functions. The whole drop spectra is depicted as a linear combination of two lognormal distribution functions, in which all distribution parameters are formulated by means of six distribution moments included in a system of equations, thus eliminating the need of fixing any parameters. This basis functions parameterization avoids the classification of drops in artificial categories such as cloud water (cloud droplets) or rain water (raindrops). The total moment tendencies are calculated using a machine learning approach, in which one deep neural network was trained for each of the total moment orders involved. The neural networks were trained using randomly generated data following a uniform distribution, over a wide range of parameters employed by the parameterization. An analysis of the predicted total moment errors was performed, aimed to stablish the accuracy of the...

Research paper thumbnail of Sedimentation calculations within an Eulerian framework using series of basis functions

Research paper thumbnail of A two-moment machine learning parameterization of the autoconversion process

Research paper thumbnail of Analysis of intra-day fluctuations in the Mexican financial market index

Revista Mexicana de Física

In this paper, a statistical analysis of high frequency fluctuations of the IPC, the Mexican Stoc... more In this paper, a statistical analysis of high frequency fluctuations of the IPC, the Mexican Stock Market Index, is presented. A sample of tick--to--tick data covering the period from January 1999 to December 2002 was analyzed, as well as several other sets obtained using temporal aggregation. Our results indicates that the highest frequency is not useful to understand the Mexican market because almost two thirds of the information corresponds to inactivity. For the frequency where fluctuations start to be relevant, the IPC data does not follows any alpha\alphaalpha-stable distribution, including the Gaussian, perhaps because of the presence of autocorrelations. For a long range of lower-frequencies, but still in the intra-day regime, fluctuations can be described as a truncated L\'evy flight, while for frequencies above two-days, a Gaussian distribution yields the best fit. Thought these results are consistent with other previously reported for several markets, there are significant d...

Research paper thumbnail of The Negative Binomial distribution as a model for external corrosion defect counts in buried pipelines

Corrosion Science, 2015

ABSTRACT

Research paper thumbnail of Statistical Calibration of Pipeline In-Line Inspection Data

This paper describes a statistical methodology for the calibration of in-line inspection (ILI) to... more This paper describes a statistical methodology for the calibration of in-line inspection (ILI) tools which is based on the comparison of the ILI readings with field-measurements results. The systematic and random errors that affect the ILI and the field tools are estimated and from this information, an unbiased estimation of the true depth of the defects detected by the ILI tool is produced. The influence of the number of field verifications on the reliability of the calibration process is addressed. The methodology is tested through Monte Carlo simulations and illustrated using a real-life ILI dataset produced by an UT tool.

Research paper thumbnail of P2.43 Monte Carlo Simulations of Drop Growth by Coalescence and Collision-Induced Breakup

Research paper thumbnail of Interactive comment on "The validity of the kinetic collection equation revisited" by L. Alfonso et al

Research paper thumbnail of The Role of Organic Compounds in Precipitation Development Using an Explicit Microphysical Model

Research paper thumbnail of An algorithm for the numerical solution of the multivariate master equation for stochastic coalescence

Atmospheric Chemistry and Physics Discussions, 2015

In cloud modeling studies, the time evolution of droplet size distributions due to collision-coal... more In cloud modeling studies, the time evolution of droplet size distributions due to collision-coalescence events is usually modeled with the kinetic collection equation (KCE) or Smoluchowski coagulation equation. However, the KCE is a deterministic equation with no stochastic fluctuations or correlations. Therefore, the full stochastic 5 description of cloud droplet growth in a coalescing system must be obtained from the solution of the multivariate master equation, which models the evolution of the state vector for the number of droplets of a given mass. Unfortunately, due to its complexity, only limited results were obtained for certain type of kernels and monodisperse initial conditions. In this work, a novel numerical algorithm for the solution of the multivariate

Research paper thumbnail of Monte carlo simulations of drop growth by coalescence and collision-induced breakup

Revista Mexicana de Fisica

Recibido el 7 de mayo de 2009; aceptado el 29 de septiembre de 2009 A Monte Carlo framework to si... more Recibido el 7 de mayo de 2009; aceptado el 29 de septiembre de 2009 A Monte Carlo framework to simulate the evolution of drop spectra by coalescence and collision-induced breakup is presented. The stochastic algorithm of Gillespie [1] for chemical reactions in the formulation proposed by Laurenzi and Diamond [2] was used to simulate the kinetic behavior of the drop population. Within Gillespie's framework, the collision-induced breakup process is modeled as a new "chemical reaction". The results of the Monte Carlo simulations were compared with the analytical solution to the collection-breakup equation obtained by Feingold et al. [3], for an exponential distribution of satellite drops, and a constant collection and breakup kernels. A good correspondence between the analytical and the stochastic algorithm was found for this case. Se presenta un algoritmo de Monte Carlo para simular la evolución del espectro de gotas por coalescencia y rompimiento inducido por colisiones...

Research paper thumbnail of The effect of stochastic correlations and fluctuations in the collision-coalescence process revisited: An algorithm for the numerical solution of the master equation and numerical results for realistic kernels

Generally, the modeling of size distribution in a collision-coalescence system is performed by th... more Generally, the modeling of size distribution in a collision-coalescence system is performed by the Smoluchowski equation or kinetic collection equation, which is a deterministic equation and has no stochastic correlations or fluctuations included. However, the full stochastic description of the growth of cloud particles in a coalescing system can be obtained from the solution of the master (or V-equation), which models the evolution of the state vector for the number of droplets of a given mass. Due to its complexity, only limited results were obtained for certain type of kernels (sum, product and constant kernels). In this work, a general algorithm for the solution of the master equation for stochastic coagulation was proposed. The performance of the method was checked by comparing the time evolution for the state probabilities with the analytical results obtained by other authors. Fluctuations and correlations were calculated for the hydrodynamic kernel, and true stochastic averag...

Research paper thumbnail of Reconstruction of the solution of the coagulation equation in two components from its orthogonal projections: an application to the physics of clouds

A proposal for the reconstruction of the solution of the Smoluchowski equation is established fro... more A proposal for the reconstruction of the solution of the Smoluchowski equation is established from the knowledge of its orthogonal projections. Some computational results are exhibited. This work is part of a research whose purpose is the calculation of the evolution of a bidimensional drops atmospherical spectrum, with liquid mass m and aerosol n, from the coagulation process.

Research paper thumbnail of Stochastic coalescence in finite systems: an algorithm for the numerical solution of the multivariate master equation

Bulletin of the American Physical Society, Apr 12, 2015

approach to coagulation considers the coalescence process going in a system of a finite number of... more approach to coagulation considers the coalescence process going in a system of a finite number of particles enclosed in a finite volume. Within this approach, the full description of the system can be obtained from the solution of the multivariate master equation, which models the evolution of the probability distribution of the state vector for the number of particles of a given mass. Unfortunately, due to its complexity, only limited results were obtained for certain type of kernels and monodisperse initial conditions. In this work, a novel numerical algorithm for the solution of the multivariate master equation for stochastic coalescence that works for any type of kernels and initial conditions is introduced. The performance of the method was checked by comparing the numerically calculated particle mass spectrum with analytical solutions obtained for the constant and sum kernels, with an excellent correspondence between the analytical and numerical solutions. In order to increase the speedup of the algorithm, software parallelization techniques with OpenMP standard were used, along with an implementation in order to take advantage of new accelerator technologies. Simulations results show an important speedup of the parallelized algorithms.

Research paper thumbnail of A Stochastic Model for the Collection Growth of Ice Particles in Mixed- Phase Clouds

Research paper thumbnail of Bayesian analysis of external corrosion data of non-piggable underground pipelines

Corrosion Science, 2015

Development of a physiologically relevant 3D model system for cancer research and drug developmen... more Development of a physiologically relevant 3D model system for cancer research and drug development is a current challenge. We have adopted a 3D culture system based on a transglutaminase-crosslinked gelatin gel (Col-Tgel) to mimic the tumor 3D microenvironment. The system has several unique advantages over other alternatives including presenting cell-matrix interaction sites from collagen-derived peptides, geometry-initiated multicellular tumor spheroids, and metabolic gradients in the tumor microenvironment. Also it provides a controllable wide spectrum of gel stiffness for mechanical signals, and technical compatibility with imaging based screening due to its transparent properties. In addition, the Col-Tgel provides a cure-in-situ delivery vehicle for tumor xenograft formation in animals enhancing tumor cell uptake rate. Overall, this distinctive 3D system could offer a platform to more accurately mimic in vivo situations to study tumor formation and progression both in vitro and in vivo.

Research paper thumbnail of Markov Chain Models for the Stochastic Modeling of Pitting Corrosion

Mathematical Problems in Engineering, 2013

The stochastic nature of pitting corrosion of metallic structures has been widely recognized. It ... more The stochastic nature of pitting corrosion of metallic structures has been widely recognized. It is assumed that this kind of deterioration retains no memory of the past, so only the current state of the damage influences its future development. This characteristic allows pitting corrosion to be categorized as a Markov process. In this paper, two different models of pitting corrosion, developed using Markov chains, are presented. Firstly, a continuous-time, nonhomogeneous linear growth (pure birth) Markov process is used to model external pitting corrosion in underground pipelines. A closed-form solution of the system of Kolmogorov's forward equations is used to describe the transition probability function in a discrete pit depth space. The transition probability function is identified by correlating the stochastic pit depth mean with the empirical deterministic mean. In the second model, the distribution of maximum pit depths in a pitting experiment is successfully modeled afte...

Research paper thumbnail of Statistical Analysis of Pitting Corrosion Field Data and Their Use for Realistic Reliability Estimations in Non-Piggable Pipeline Systems

CORROSION, 2014

The reliability and risk of non-piggable, corroding oil and gas pipelines can be estimated from h... more The reliability and risk of non-piggable, corroding oil and gas pipelines can be estimated from historical failure data and through reliability models based on the assumed or measured number of corrosion defects and defect size distribution. In this work, an extensive field survey carried out in an upstream gathering pipeline system in Southern Mexico is presented. It has helped determine realistic values for the number of corrosion defects per kilometer (defect density) and obtain a better description of the corrosion defect size distributions in this system. To illustrate the impact that these new corrosion data can have on pipeline risk management, a reliability study is also presented where the field-gathered corrosion data have been used as input to a reliability framework for the estimation of the failure index of non-piggable pipelines and pipeline systems when different amounts of corrosion data are available.

Research paper thumbnail of Stochastic modeling of pitting corrosion: A new model for initiation and growth of multiple corrosion pits

Corrosion Science, 2007

In this work, a new stochastic model capable of simulating pitting corrosion is developed and val... more In this work, a new stochastic model capable of simulating pitting corrosion is developed and validated. Pitting corrosion is modeled as the combination of two stochastic processes: pit initiation and pit growth. Pit generation is modeled as a nonhomogeneous Poisson process, in which induction time for pit initiation is simulated as the realization of a Weibull process. In this way, the exponential and Weibull distributions can be considered as the possible distributions for pit initiation time. Pit growth is simulated using a nonhomogeneous Markov process. Extreme value statistics is used to find the distribution of maximum pit depths resulting from the combination of the initiation and growth processes for multiple pits. The proposed model is validated using several published experiments on pitting corrosion. It is capable of reproducing the experimental observations with higher quality than the stochastic models available in the literature for pitting corrosion.

Research paper thumbnail of On the scaling of the distribution of daily price fluctuations in the Mexican financial market index

Physica A: Statistical Mechanics and its Applications, 2012

Research paper thumbnail of Parameterization of the collision-coalescence process using series of basis functions: COLNETv1.0.0 model development using a machine learning approach

Geoscientific Model Development Discussions, 2021

Abstract. A parameterization for the collision-coalescence process is presented, based on the met... more Abstract. A parameterization for the collision-coalescence process is presented, based on the methodology of basis functions. The whole drop spectra is depicted as a linear combination of two lognormal distribution functions, in which all distribution parameters are formulated by means of six distribution moments included in a system of equations, thus eliminating the need of fixing any parameters. This basis functions parameterization avoids the classification of drops in artificial categories such as cloud water (cloud droplets) or rain water (raindrops). The total moment tendencies are calculated using a machine learning approach, in which one deep neural network was trained for each of the total moment orders involved. The neural networks were trained using randomly generated data following a uniform distribution, over a wide range of parameters employed by the parameterization. An analysis of the predicted total moment errors was performed, aimed to stablish the accuracy of the...

Research paper thumbnail of Sedimentation calculations within an Eulerian framework using series of basis functions

Research paper thumbnail of A two-moment machine learning parameterization of the autoconversion process

Research paper thumbnail of Analysis of intra-day fluctuations in the Mexican financial market index

Revista Mexicana de Física

In this paper, a statistical analysis of high frequency fluctuations of the IPC, the Mexican Stoc... more In this paper, a statistical analysis of high frequency fluctuations of the IPC, the Mexican Stock Market Index, is presented. A sample of tick--to--tick data covering the period from January 1999 to December 2002 was analyzed, as well as several other sets obtained using temporal aggregation. Our results indicates that the highest frequency is not useful to understand the Mexican market because almost two thirds of the information corresponds to inactivity. For the frequency where fluctuations start to be relevant, the IPC data does not follows any alpha\alphaalpha-stable distribution, including the Gaussian, perhaps because of the presence of autocorrelations. For a long range of lower-frequencies, but still in the intra-day regime, fluctuations can be described as a truncated L\'evy flight, while for frequencies above two-days, a Gaussian distribution yields the best fit. Thought these results are consistent with other previously reported for several markets, there are significant d...

Research paper thumbnail of The Negative Binomial distribution as a model for external corrosion defect counts in buried pipelines

Corrosion Science, 2015

ABSTRACT

Research paper thumbnail of Statistical Calibration of Pipeline In-Line Inspection Data

This paper describes a statistical methodology for the calibration of in-line inspection (ILI) to... more This paper describes a statistical methodology for the calibration of in-line inspection (ILI) tools which is based on the comparison of the ILI readings with field-measurements results. The systematic and random errors that affect the ILI and the field tools are estimated and from this information, an unbiased estimation of the true depth of the defects detected by the ILI tool is produced. The influence of the number of field verifications on the reliability of the calibration process is addressed. The methodology is tested through Monte Carlo simulations and illustrated using a real-life ILI dataset produced by an UT tool.

Research paper thumbnail of P2.43 Monte Carlo Simulations of Drop Growth by Coalescence and Collision-Induced Breakup

Research paper thumbnail of Interactive comment on "The validity of the kinetic collection equation revisited" by L. Alfonso et al

Research paper thumbnail of The Role of Organic Compounds in Precipitation Development Using an Explicit Microphysical Model

Research paper thumbnail of An algorithm for the numerical solution of the multivariate master equation for stochastic coalescence

Atmospheric Chemistry and Physics Discussions, 2015

In cloud modeling studies, the time evolution of droplet size distributions due to collision-coal... more In cloud modeling studies, the time evolution of droplet size distributions due to collision-coalescence events is usually modeled with the kinetic collection equation (KCE) or Smoluchowski coagulation equation. However, the KCE is a deterministic equation with no stochastic fluctuations or correlations. Therefore, the full stochastic 5 description of cloud droplet growth in a coalescing system must be obtained from the solution of the multivariate master equation, which models the evolution of the state vector for the number of droplets of a given mass. Unfortunately, due to its complexity, only limited results were obtained for certain type of kernels and monodisperse initial conditions. In this work, a novel numerical algorithm for the solution of the multivariate

Research paper thumbnail of Monte carlo simulations of drop growth by coalescence and collision-induced breakup

Revista Mexicana de Fisica

Recibido el 7 de mayo de 2009; aceptado el 29 de septiembre de 2009 A Monte Carlo framework to si... more Recibido el 7 de mayo de 2009; aceptado el 29 de septiembre de 2009 A Monte Carlo framework to simulate the evolution of drop spectra by coalescence and collision-induced breakup is presented. The stochastic algorithm of Gillespie [1] for chemical reactions in the formulation proposed by Laurenzi and Diamond [2] was used to simulate the kinetic behavior of the drop population. Within Gillespie's framework, the collision-induced breakup process is modeled as a new "chemical reaction". The results of the Monte Carlo simulations were compared with the analytical solution to the collection-breakup equation obtained by Feingold et al. [3], for an exponential distribution of satellite drops, and a constant collection and breakup kernels. A good correspondence between the analytical and the stochastic algorithm was found for this case. Se presenta un algoritmo de Monte Carlo para simular la evolución del espectro de gotas por coalescencia y rompimiento inducido por colisiones...

Research paper thumbnail of The effect of stochastic correlations and fluctuations in the collision-coalescence process revisited: An algorithm for the numerical solution of the master equation and numerical results for realistic kernels

Generally, the modeling of size distribution in a collision-coalescence system is performed by th... more Generally, the modeling of size distribution in a collision-coalescence system is performed by the Smoluchowski equation or kinetic collection equation, which is a deterministic equation and has no stochastic correlations or fluctuations included. However, the full stochastic description of the growth of cloud particles in a coalescing system can be obtained from the solution of the master (or V-equation), which models the evolution of the state vector for the number of droplets of a given mass. Due to its complexity, only limited results were obtained for certain type of kernels (sum, product and constant kernels). In this work, a general algorithm for the solution of the master equation for stochastic coagulation was proposed. The performance of the method was checked by comparing the time evolution for the state probabilities with the analytical results obtained by other authors. Fluctuations and correlations were calculated for the hydrodynamic kernel, and true stochastic averag...