Global sensitivity study for irreversible electroporation: Towards treatment planning under uncertainty.

Background: Electroporation-based cancer treatments are minimally invasive, nonthermal interventional techniques that leverage cell permeabilization to ablate the target tumor. However, the amount of permeabilization is susceptible to the numerous uncertainties during treatment, such as patient-specific variations in the tissue, type of the tumor, and the resolution of imaging equipment. These uncertainties can reduce the extent of ablation in the tissue, thereby affecting the effectiveness of the treatment.

Global Sensitivity Analysis for Patient-Specific Aortic Simulations: The Role of Geometry, Boundary Condition and Large Eddy Simulation Modeling Parameters.

Numerical simulations for computational hemodynamics in clinical settings require a combination of many ingredients, mathematical models, solvers and patient-specific data. The sensitivity of the solutions to these factors may be critical, particularly when we have a partial or noisy knowledge of data. Uncertainty quantification is crucial to assess the reliability of the results.

Diffusion-reaction compartmental models formulated in a continuum mechanics framework: application to COVID-19, mathematical analysis, and numerical study.

The outbreak of COVID-19 in 2020 has led to a surge in interest in the research of the mathematical modeling of epidemics. Many of the introduced models are so-called , in which the total quantities characterizing a certain system may be decomposed into two (or more) species that are distributed into two (or more) homogeneous units called compartments. We propose herein a formulation of compartmental models based on partial differential equations (PDEs) based on concepts familiar to continuum mechanics, interpreting such models in terms of fundamental equations of balance and compatibility, joined by a constitutive relation.

Simulating the spread of COVID-19 a spatially-resolved susceptible-exposed-infected-recovered-deceased (SEIRD) model with heterogeneous diffusion.

We present an early version of a Susceptible-Exposed-Infected-Recovered-Deceased (SEIRD) mathematical model based on partial differential equations coupled with a heterogeneous diffusion model. The model describes the spatio-temporal spread of the COVID-19 pandemic, and aims to capture dynamics also based on human habits and geographical features. To test the model, we compare the outputs generated by a finite-element solver with measured data over the Italian region of Lombardy, which has been heavily impacted by this crisis between February and April 2020.

Coupled molecular-dynamics and finite-element-method simulations for the kinetics of particles subjected to field-mediated forces.

A computational approach that couples molecular-dynamics (MD) and the-finite-element-method (FEM) technique is here proposed for the theoretical study of the dynamics of particles subjected to electromechanical forces. The system consists of spherical particles (modeled as micrometric rigid bodies with proper densities and dielectric functions) suspended in a colloidal solution, which flows in a microfluidic channel in the presence of a generic nonuniform variable electric field generated by electrodes. The particles are subjected to external forces (e.

A Mass Conservative Kalman Filter Algorithm for Computational Thermo-Fluid Dynamics.

This paper studies Kalman filtering applied to Reynolds-Averaged Navier⁻Stokes (RANS) equations for turbulent flow. The integration of the Kalman estimator is extended to an implicit segregated method and to the thermodynamic analysis of turbulent flow, adding a sub-stepping procedure that ensures mass conservation at each time step and the compatibility among the unknowns involved. The accuracy of the algorithm is verified with respect to the heated lid-driven cavity benchmark, incorporating also temperature observations, comparing the augmented prediction of the Kalman filter with the Computational Fluid-Dynamic solution found on a fine grid.