Abstract Fuel elements in a high-temperature gas-cooled reactor (HTGR) core may be stacked with a hexagonal close-packed (HCP) structure; therefore, analyzing the temperature distribution and heat transfer efficiency in the HCP pebble bed is of great significance to the design and safety of HTGR cores. In this study, the heat transfer characteristics of an HCP pebble bed are studied using CFD. The thermal fields and convective heat transfer coefficients under different coolant inlet velocities are obtained, and the velocity fields in the gap areas are also analyzed in different planes. It is found that the strongest heat transfer is shown near the right vertices of the top and bottom spheres,while the weakest heat transfer takes place in areas near the contact points where no fluid flows over; in addition, the correlation of the overall heat transfer coefficient with the Reynolds number is proposed as havg = 0.1545(k/L)Re0.8 (Pr = 0.712, 1.6 × 104 ≤ Re ≤ 4 × 104). It is also found that the heat transfer intensity of the HCP structure is weaker than that of the face-centered-cubic structure .These findings provide a reference for reactor designers and will contribute to the development of safer pebble-bed cores.

Abstract An infectious disease can cause a detrimental effect on national security. A group such as the military called a “closed population”, which is a subset of the general population but has many distinct characteristics, must survive even in the event of a pandemic. Hence, it requires its own distinct solution during a pandemic. In this study, we investigate a simulation analysis for implementing an agent-based model that reflects the characteristics of agents and the environment in a closed population and finds effective control measures for making the closed population functional in the course of disease spreading.

Abstract : In this investigation, a comprehensive numerical analysis of the flow involved in an open ended straight channel fully filled with a porous metal foam saturated and a phase change material (paraffin) has been performed using a single relaxation time lattice Boltzmann method (SRT-LBM) at the representative elementary volume (REV) scale. The enthalpy-based approach with three density functions has been employed to cope with the governing equations under the local thermal non-equilibrium (LTNE) condition. The in-house code has been validated through a comparison with a previous case in literature. The pore per inch density (10 ≤ PPI ≤ 60) and porosity (0.7 ≤ ε ≤ 0.9)effects of the metal structure were analyzed during melting/solidifying phenomena at two Reynolds numbers (Re = 200 and 400). The relevant findings are discussed for the LTNE intensity and the entropy generation rate (Ns). Through the simulations, the LTNE hypothesis turned out to be secure and valid. In addition, it is maximum for small PPI value (=10) whatever the parameters deemed. On the other hand, high porosity (=0.9) is advised to reduce the system’s irreversibility. However, at a moderate Re (=200), a small PPI (=10) would be appropriate to mitigate the system irreversibility during the charging case, while a large value (PPI = 60) might be advised for the discharging case. In this context, it can be stated that during the melting period, low porosity (=0.7) with low PPI (=10) improves thermal performance, reduces the system irreversibility and speeds up the melting rate, while for high porosity (=0.9), a moderate PPI (=30) should be used during the melting process to achieve an optimal system.

Abstract This article demonstrates the feasibility of porous separation on the performance of displacement ventilation in a rectangular enclosure. A jet of fresh air enters the cavity through an opening at the bottom of the left wall and exits through an opening at the top of the right wall. The porous separation is placed in the center of the cavity and its height varies between 0.2 and 0.8 with three values of thickness, 0.1, 0.2, and 0.3. The heat transfer rate was calculated for different intervals of Darcy (10−6 ≤ Da ≤ 10), Rayleigh (10 ≤ Ra ≤ 106 ), and Reynolds (50 ≤ Re ≤ 500) numbers. The momentum and the energy equations were solved by the lattice Boltzmann method with multiple relaxation times (LB-MRT). Schemes D2Q9 and D2Q5 were chosen for the velocity and temperature fields, respectively. For porous separation, the generalized Darcy–Brinkman– Forchheimer model was adopted. It is represented by a term added in the standard LB equations. For the dynamic domain ,numerical simulations revealed complex flow structures depending on all control parameters. The results showed that the thermal field, mainly in the second compartment, is very dependent on the size and permeability of the porous separation. However, they have no influence on the transfer rate.

Abstract When catastrophic failure phenomena in aircraft structures, such as debonding, are numerically analyzed during their design process in the frame of “Damage Tolerance” philosophy ,extreme requirements in terms of time and computational resources arise. Here, a decrease in these requirements is achieved by developing a numerical model that efficiently treats the debonding phenomena that occur due to the buckling behavior of composite stiffened panels under compressive loads. The Finite Element (FE) models developed in the ANSYS© software (Canonsburg, PA, USA)are calibrated and validated by using published experimental and numerical results of single-stringer compression specimens (SSCS). Different model features, such as the type of the element used (solid and solid shell) and Cohesive Zone Modeling (CZM) parameters are examined for their impact on the efficiency of the model regarding the accuracy versus computational cost. It is proved that a significant reduction in computational time is achieved, and the accuracy is not compromised when the proposed FE model is adopted. The outcome of the present work leads to guidelines for the development of FE models of stiffened panels, accurately predicting the buckling and post buckling behavior leading to debonding phenomena, with minimized computational and time cost.The methodology is proved to be a tool for the generation of a universal parametric numerical model for the analysis of debonding phenomena of any stiffened panel configuration by modifying the corresponding geometric, material and damage properties.

Abstract The unprecedented global health threat of SARS-CoV-2 has sparked a continued interest in discovering novel anti-COVID-19 agents. To this end, we present here a computer-based protocol for identifying potential compounds targeting RNA-dependent RNA polymerase (RdRp). Starting from our previous study wherein, using a virtual screening campaign, we identified a fumiquinazolinone alkaloid quinadoline B (Q3), an antiviral fungal metabolite with significant activity against SARSCoV-2 RdRp, we applied in silico combinatorial methodologies for generating and screening a library of anti-SARS-CoV-2 candidates with strong in silico affinity for RdRp. For this study, the quinadoline pharmacophore was subjected to structural iteration, obtaining a Q3-focused library of over 900,000 unique structures. This chemical library was explored to identify binders of RdRp with greater affinity with respect to the starting compound Q3. Coupling this approach with the evaluation of physchem profile, we found 26 compounds with significant affinities for the RdRp binding site.Moreover, top-ranked compounds were submitted to molecular dynamics to evaluate the stability of the systems during a selected time, and to deeply investigate the binding mode of the most promising derivatives. Among the generated structures, five compounds, obtained by inserting nucleotidelike scaffolds (1, 2, and 5), heterocyclic thiazolyl benzamide moiety (compound 3), and a peptide residue (compound 4), exhibited enhanced binding affinity for SARS-CoV-2 RdRp, deserving further investigation as possible antiviral agents. Remarkably, the presented in silico procedure provides a useful computational procedure for hit-to-lead optimization, having implications in anti-SARS-CoV-2 drug discovery and in general in the drug optimization process.

Abstract The present study evaluated a newly developed computational tool (CT) to assess the alveolar bone space and the alveolar crest angle and compares it to dentist assessment (GT). The novel tool consisted of a set of processes initiated with image enhancement, points localization, and angle and area calculations. In total, we analyzed 148 sites in 39 radiographic images, and among these, 42 sites were selected and divided into two groups of non-periodontitis and periodontitis. The alveolar space area (ASA) and alveolar crest angle (ACA) were estimated. The agreement between the computer software and the ground truth was analyzed using the Bland–Altman plot. The sensitivity and specificity of the computer tool were measured using the ROC curve. The Bland–Altman plot showed an agreement between the ground truth and the computational tool in all of the parameters assessed. The ROC curve showed 100% sensitivity and 100% specificity for 12.67 mm of the alveolar space area. The maximum percentage of sensitivity and specificity were 80.95% for 13.63 degrees of the alveolar crest angle. Computer tool assessment provides accurate disease severity and treatment monitoring for evaluating the alveolar space area (ASA) and the alveolar crest angle (ACA).

Abstract The residue number system (RNS) is widely used in different areas due to the efficiency of modular addition and multiplication operations. However, non-modular operations, such as sign and division operations, are computationally complex. A fractional representation based on the Chinese remainder theorem is widely used. In some cases, this method gives an incorrect result associated with round-off calculation errors. In this paper, we optimize the division operation in RNS using the Akushsky core function without critical cores. We show that the proposed method reduces the size of the operands by half and does not require additional restrictions on the divisor as in the division algorithm in RNS based on the approximate method.

Abstract The aim of this research was to design a physically consistent model for the forced torsional vibrations of automotive driveshafts that considered aspects of the following phenomena: excitation due to the transmission of the combustion engine through the gearbox, excitation due to the road geometry, the quasi-isometry of the automotive driveshaft, the effect of nonuniformity of the inertial moment with respect to the longitudinal axis of the tulip–tripod joint and of the bowl–balls–inner race joint, the torsional rigidity, and the torsional damping of each joint. To resolve the equations of motion describing the forced torsional nonlinear parametric vibrations of automotive driveshafts,a variational approach that involves Hamilton’s principle was used, which considers the isometric nonuniformity, where it is known that the joints of automotive driveshafts are quasi-isometric in terms of the twist angle, even if, in general, they are considered CVJs (constant velocity joints).This effect realizes the link between the terms for the torsional vibrations between the elements of the driveshaft: tripode–tulip, midshaft, and bowl–balls–inner race joint elements. The induced torsional loads (as gearbox torsional moments that enter the driveshaft through the tulip axis) can be of harmonic type, while the reactive torsional loads (as reactive torsional moments that enter the driveshaft through the bowl axis) are impulsive. These effects induce the resulting nonlinear dynamic behavior. Also considered was the effect of nonuniformity on the axial moment of inertia of the tripod–tulip element as well as on the axial moment of inertia of the bowl–balls–inner race joint element, that vary with the twist angle of each element. This effect induces parametric dynamic behavior. Moreover, the torsional rigidity was taken into consideration, as was the torsional damping for each joint of the driveshaft: tripod–joint and bowl–balls–inner race joint. This approach was used to obtain a system of equations of nonlinear partial derivatives that describes the torsional vibrations of the driveshaft as nonlinear parametric dynamic behavior. This model was used to compute variation in the natural frequencies of torsion in the global tulip (a given imposed geometry) using the angle between the tulip–midshaft for an automotive driveshaft designed for heavy-duty SUVs as well as the characteristic amplitude frequency in the region of principal parametric resonance together the method of harmonic balance for the steady-state forced torsional nonlinear vibration of the driveshaft. This model of dynamic behavior for the driveshaft can be used during the early stages of design as well in predicting the durability of automotive driveshafts. In addition, it is important that this model be added in the design algorithm for predicting the comfort elements of the automotive environment to adequately account for this kind of dynamic behavior that induces excitations in the car structure.

Abstract In the Oil and Gas industry, installing pipe loops is a well-known hydraulic practice to increase oil pipeline capacities. Nevertheless, pipe loops could promote an unfavorable phenomenon known as fouling. That means that in a heavy oil-water mixture gathering system with low flow velocities, an oil-water stratified flow pattern will appear. In consequence, due to high viscosity, the oil stick on the pipe, causing a reduction of the effective diameter, reducing handled fluids production,and increasing energy consumption. As jet pumps increase total handled flow, increase the fluid velocities, and promote the homogenous mixture of oil and water, this type of pump could result attractive compared to other multiphase pump systems in reactivating heavy crude oil transport lines. Jet pumps are highly reliable, robust equipment with modest maintenance, ideal for many applications, mainly in the oil and gas industry. Nevertheless, their design method and performance analysis are rarely known in the literature and keep a high experimental component similar to most pumping equipment. This paper proposes a numerical study and the optimization of a booster multiphase jet pump system installed in a heavy oil conventional loop of a gathering system. First,the optimization of a traditionally designed jet pump, combining CFD simulation and optimization algorithms using commercials software (ANSYS CFX® and PIPEIT® tool), has been carried out. This method allowed evaluating the effect of multiple geometrical and operational variables that influence the global performance of the pump to run more than 400 geometries automatically in a reduced time frame. The optimized pump offers a substantial improvement over the original concerning total flow capacity (+17%), energy, and flow distribution. Then, the effect of the three jet pump plugin configurations in a heavy oil conventional trunkline loop was analyzed. Simulations were carried out for different driving fluid pressures and compared against a traditional pipeline loop’s performance .Optimum plugin connection increases fluid production by 30%. Finally, a new eccentric jet pump geometry has been proposed to improve exit velocities and pressure fields. This eccentric jet pump with the best connection was analyzed over the same conditions as the concentric optimized one. An improvement of 2% on handled fluid was achieved consistently with the observed uniform velocity field at the exit of the pump. A better total fluid distribution between the main and the loop line is obtained, handling around half of the complete fluid each.

Abstract The internal steady and unsteady flows with a frequency and amplitude are examined through a backward facing step (expansion ratio 2), for low Reynolds numbers (Re = 400, Re = 800),using the immersed boundary method. A lower part of the backward facing step is oscillating with the same frequency as the unsteady flow. The effect of the frequency, the amplitude, and the length of this oscillation is investigated. By suitable active control regulation, the recirculation lengths are reduced, and, for a percentage of the time period, no upper wall, negative velocity, region occurs.Moreover, substituting the prescriptively moving surface by a pressure responsive homogeneous membrane, the fluid–structure interaction is examined. We show that, by selecting proper values for the membrane parameters, such as membrane tension and applied external pressure, the upper wall flow separation bubble vanishes, while the lower one diminishes significantly in both the steady and the unsteady cases. Furthermore, for the time varying case, the length fluctuation of the lower wall reversed flow region is fairly contracted. The findings of the study have applications at the control of confined and external flows where separation occurs.

Abstract The lowest-energy singlet (S1) and triplet (T1) excited states of organic conjugated chromophores are known to be accurately calculated by modern wavefunction and Time-Dependent Density Functional Theory (TD-DFT) methods, with the accuracy of the latter heavily relying on the exchange-correlation functional employed. However, there are challenging cases for which this cannot be the case, due to the fact that those excited states are not exclusively formed by single excitations and/or are affected by marked correlation effects, and thus TD-DFT might fall short. We will tackle here a set of molecules belonging to the azaphenalene family, for which research recently documented an inversion of the relative energy of S1 and T1 excited states giving rise to a negative energy difference (∆EST) between them and, thereby, contrary to most of the systems thus far treated by TD-DFT. Since methods going beyond standard TD-DFT are not extensively applied to excited-state calculations and considering how challenging this case is for the molecules investigated, we will prospectively employ here a set of non-standard methods (Multi-Configurational Pair Density Functional Theory or MC-PDFT) and correlation functionals (i.e., Lie–Clementi and Colle–Salvetti) relying not only on the electronic density but also on some modifications considering the intricate electronic structure of these systems.

Abstract The UV–visible spectra of a series of subphthalocyanines (SubPcs) characterized by three different axial substituents (An) in combination with H, F, NO2 , SO2H and SO2CH3 peripheral substituents (Ri ) were predicted and analyzed by means of time-dependent DFT calculations, including chloroform as a solvent. In this analysis, we paid particular attention to the Q band, which remained almost unchanged regardless of the nature of the axial substituent. For the same axial substituent, changes in the Q band were also rather small when hydrogens at the periphery were replaced by R1 = SO2H and R1 = R2 = SO2H. However, the shifting of the Q band was almost 10 times larger when R1 = NO2 and R1 = R2 = NO2 due to the participation of this substituent in the π SubPc cloud. In most cases, the characteristics of the spectra can be explained considering only the transitions involving the HOMO-1, HOMO, LUMO and LUMO + 1 orbitals, where the Q band can be decomposed into two main contributions, leading to charge separation. Only for SubPc(A3 ,F,F,H) would one of the two contributions from the deepest orbital involved not lead to charge transfer. For this latter case,the HOMO-2 orbital must also be taken into account. In summary, the results obtained with the analysis of the MO indicate that the studied SubPcs are appropriate for photochemical devices.

Abstract For the inverse problem in physical models, one measures the solution and infers the model parameters using information from the collected data. Oftentimes, these data are inadequate and render the inverse problem ill-posed. We study the ill-posedness in the context of optical imaging,which is a medical imaging technique that uses light to probe (bio-)tissue structure. Depending on the intensity of the light, the forward problem can be described by different types of equations.High-energy light scatters very little, and one uses the radiative transfer equation (RTE) as the model; low-energy light scatters frequently, so the diffusion equation (DE) suffices to be a good approximation. A multiscale approximation links the hyperbolic-type RTE with the parabolic-type DE. The inverse problems for the two equations have a multiscale passage as well, so one expects that as the energy of the photons diminishes, the inverse problem changes from well- to ill-posed. We study this stability deterioration using the Bayesian inference. In particular, we use the Kullback– Leibler divergence between the prior distribution and the posterior distribution based on the RTE to prove that the information gain from the measurement vanishes as the energy of the photons decreases, so that the inverse problem is ill-posed in the diffusive regime. In the linearized setting,we also show that the mean square error of the posterior distribution increases as we approach the diffusive regime.

Abstract Bolted joints are widely used in composite aircraft structures, for their assembly. The appropriate bolted joint configuration (hole/bolt diameter, pitch, etc.) is carefully selected during the detail design phase, where high fidelity numerical models are required with substantial computational cost and time. This work presents a design criterion, which allows the selection of the bolted joint configuration during the preliminary design phase with less computational time. The developed design criterion is based on a fully parametric finite element (FE) model, built in ANSYS V19 (Canonsburg, PA, USA), of a bolted joint with progressive damage modelling (PDM) capabilities,so that the failure of the joint can be predicted. From the numerical analyses, the bearing load and the load that bypasses the hole are calculated, up to failure, for a variety of joint configurations and loading conditions. The results of each analysis are used for plotting the failure envelope for the investigated bolted-joint configuration. Consequently, a design criterion is generated for the bolted joint. The availability of these failure envelopes, as design criterion, permit the appropriate selection of the bolted-joint configuration in an earlier design phase saving valuable time and computational cost.

Abstract Fully Homomorphic Encryption (FHE) permits processing information in the form of ciphertexts without decryption. It can ensure the security of information in common technologies used today, such as cloud computing, the Internet of Things, and machine learning, among others. A primary disadvantage for its practical application is the low efficiency of sign and comparison operations. Several FHE schemes use the Residue Number System (RNS) to decrease the time complexity of these operations. Converting from the RNS to the positional number system and calculating the positional characteristic of a number are standard approaches for both operations in the RNS domain.In this paper, we propose a new method for comparing numbers and determining the sign of a number in RNS. We focus on the even ranges that are computationally simple due to their peculiarities.We compare the performance of several state-of-art algorithms based on an implementation in C++ and relatively simple moduli with a bit depth from 24 to 64 bits. The experimental analysis shows a better performance of our approach for all the test cases; it improves the sign detection between 1.93 and 15.3 times and the number comparison within 1.55–11.35 times with respect to all the methods and configurations.

Abstract The modulation of intermolecular interactions upon aggregation induces changes in excited state properties of organic molecules that can be detrimental for some optoelectronic applications but can be exploited for others. The time-dependent density functional theory (TDDFT) is a cost effective approach to determining the exciton states of molecular aggregates, and it has been shown to provide reliable results when coupled with the appropriate choice of the functional. Here we apply a general procedure to analyze the aggregates’ exciton states derived from TDDFT calculations in terms of diabatic states chosen to coincide with local (LE) and charge-transfer (CT) excitations within a restricted orbital space. We apply the approach to study energy profiles, interstate couplings, and the charge-transfer character of singlet and triplet exciton states of perylene di-imide aggregates (PDI). We focus on the intermolecular displacement along the longitudinal translation coordinate, which mimics different amounts of slip-stacking observed in PDI crystals. The analysis, in terms of symmetry-adapted Frenkel excitations (FE) and charge-resonance (CR) states and their interactions, discloses how the interchange of the H/J character for small longitudinal shifts, previously reported for singlet exciton states, also occurs for triplet excitons.

Abstract Employing first-principles calculations based on density functional theory (DFT), we designed a novel two-dimensional (2D) elemental monolayer allotrope of carbon called hexatetracarbon. In the hexatetra-carbon structure, each carbon atom bonds with its four neighboring atoms in a 2D double layer crystal structure, which is formed by a network of carbon hexagonal prisms.Based on our calculations, it is found that hexatetra-carbon exhibits a good structural stability as confirmed by its rather high calculated cohesive energy −6.86 eV/atom, and the absence of imaginary phonon modes in its phonon dispersion spectra. Moreover, compared with its hexagonal counterpart,i.e., graphene, which is a gapless material, our designed hexatetra-carbon is a semiconductor with an indirect band gap of 2.20 eV. Furthermore, with a deeper look at the hexatetra-carbon, one finds that this novel monolayer may be obtained from bilayer graphene under external mechanical strain conditions. As a semiconductor with a moderate band gap in the visible light range, once synthesized,hexatetra-carbon would show promising applications in new opto-electronics technologies.

Abstract The plane–cube intersection problem has been discussed in the literature since 1984 and iterative solutions to it have been used as part of piecewise linear interface construction (PLIC) in computational fluid dynamics simulation codes ever since. In many cases, PLIC is the bottleneck of these simulations regarding computing time, so a faster analytic solution to the plane–cube intersection would greatly reduce the computing time for such simulations. We derive an analytic solution for all intersection cases and compare it to the previous solution from Scardovelli and Zaleski (Scardovelli, R.; Zaleski, S. Analytical relations connecting linear interfaces and volume fractions in rectangular grids. J. Comput. Phys. 2000, 164, 228–237), which we further improve to include edge cases and micro-optimize to reduce arithmetic operations and branching. We then extend our comparison regarding computing time and accuracy to include two different iterative solutions as well. We find that the best choice depends on the employed hardware platform: on the CPU, Newton–Raphson is fastest with compiler optimization enabled, while analytic solutions perform better than iterative solutions without. On the GPU, the fastest method is our optimized version of the analytic SZ solution. We finally provide details on one of the applications of PLIC—curvature calculation for the Volume-of-Fluid model used for free surface fluid simulations in combination with the lattice Boltzmann method.

Abstract Hybrid exchange-correlation functionals provide superior electronic structure and optical properties of semiconductors or insulators as compared to semilocal exchange-correlation potentials due to admixing a portion of the non-local exact exchange potential from a Hartree–Fock theory. Since the non-local potential does not commute with the position operator, the momentum matrix elements do not fully capture the oscillator strength, while the length-gauge velocity matrix elements do. So far,length-gauge velocity matrix elements were not accessible in the all-electron full-potential WIEN2k package. We demonstrate the feasibility of computing length-gauge matrix elements in WIEN2k for a hybrid exchange-correlation functional based on a finite difference approach. To illustrate the implementation we determined matrix elements for optical transitions between the conduction and valence bands in GaAs, GaN, (CH3NH3)PbI3 and a monolayer MoS2. The non-locality of the Hartree–Fock exact exchange potential leads to a strong enhancement of the oscillator strength as noticed recently in calculations employing pseudopotentials (Laurien and Rubel: arXiv:2111.14772 (2021)).We obtained an analytical expression for the enhancement factor for the difference in eigenvalues not captured by the kinetic energy. It is expected that these results can also be extended to other non-local potentials, e.g., a many-body GW approximation.

Abstract The focus of the present paper is on clustering, namely the problem of finding distinct groups in a dataset so that each group consists of similar observations. We consider the finite mixtures of regression models, given their flexibility in modeling heterogeneous time series. Our study aims to implement a novel approach, which fits mixture models based on the spline and polynomial regression in the case of auto-correlated data, to cluster time series in an unsupervised machine learning framework. Given the assumption of auto-correlated data and the usage of exogenous variables in the mixture model, the usual approach of estimating the maximum likelihood parameters using the Expectation–Maximization (EM) algorithm is computationally prohibitive. Therefore, we provide a novel algorithm for model fitting combining auto-correlated observations with spline and polynomial regression. The case study of this paper consists of the task of clustering the time series of sales data influenced by promotional campaigns. We demonstrate the effectiveness of our method in a case study of 131 sales series data from a real-world company. Numerical outcomes demonstrate the efficacy of the proposed method for clustering auto-correlated time series. Despite the specific case study of this paper, the proposed method can be used in several real-world application fields.

Abstract Electromagnetic field propagation inside composite materials represents a challenge where fiber-scale simulation remains intractable using classical simulation methods. The present work proposes an original 3D simulation with a mesh resolution fine enough to resolve the fiber scale, thanks to the use of Proper Generalized Decomposition (PGD)-based space decomposition, which avoids the necessity of considering homogenized properties and considers the richest description of the involved physics from the solution of the Maxwell equations. This high-resolution simulation enables comparing the electromagnetic field propagation in a composite part, depending on the considered frequency and the fiber’s/wave polarization’s relative orientation. The electromagnetic fields are then post-processed to identify the heat generation terms and- the resulting induced thermal field. The results prove the ability of the PGD-based discretization to attain extremely high levels of resolution,the equivalent of 1010 finite-element degrees of freedom. The obtained results show an enhanced wave penetration when the electric field polarization coincides with the fiber orientation. On the contrary, when the electric field is polarized along the normal to the fiber orientation, both the penetration and the associated heating reduce significantly, compromising the use of homogenized models, rendering them unable to reproduce the observed behaviors.