Pure Drift Research Articles

Leaf functional trait evolution and its putative climatic drivers in African Coffea species.

Leaf traits are known to be strong predictors of plant performance and can be expected to (co)vary along environmental gradients. We investigated the variation, integration, environmental relationships, and evolutionary history of leaf functional traits in the genus Coffea L., typically a rainforest understory shrub, across Africa. A better understanding of the adaptive processes involved in leaf trait evolution can inform the use and conservation of coffee genetic resources in a changing climate. We used phylogenetic comparative methods to investigate the evolution of six leaf traits measured from herbarium specimens of 58 African Coffea species. We added environmental data and data on maximum plant height for each species to test trait-environment correlations in various (sub)clades, and we compared continuous trait evolution models to identify variables driving trait diversification. A substantial leaf trait variation was detected across the genus Coffea in Africa, which was mostly interspecific. Of these traits, stomatal size and stomatal density exhibited a clear trade-off. We observed low densities of large stomata in early branching lineages and higher densities of smaller stomata in more recent taxa, which we hypothesise to be related to declining CO2 levels since the mid-Miocene. Brownian Motion evolution was rejected in favour of White Noise or Ornstein-Uhlenbeck models for all traits, implying these traits are adaptively significant rather than driven by pure drift. The evolution of leaf area was likely driven by precipitation, with smaller leaves in dryer climates across the genus. Generally, Coffea leaf traits appear to be evolutionarily labile and governed by stabilising selection, though evolutionary patterns and correlations differ depending on the traits and clades considered. Our study highlights the importance of a phylogenetic perspective when studying trait relationships across related taxa, as well as the consideration of various taxonomic ranges.

Assessment of Numerical Captive Model Tests for Underwater Vehicles: The DARPA SUB-OFF Test Case

During the early design stage of an underwater vehicle, the correct assessment of its manoeuvrability is a crucial task. Conducting experimental tests still has high costs, especially when dealing with small vehicles characterized by low available budget. In the current investigation, virtual towing tank tests are simulated using the open-source OpenFOAM library in order to assess the reliability of CFD methods for the prediction of hydrodynamic forces and moments. A well-known case study, the Defence Advanced Research Projects Agency (DARPA) SUB-OFF model, is used, and the outcomes are compared to the experimental results available in the literature. Five different configurations are investigated for pure drift tests, rudder tests and pure rotation in both vertical and horizontal plane. The results show an overall good agreement with the experimental data with a quite low demanding mesh arrangement of 3M cells, a favourable balance between accuracy and computational time. In more detail, the expected error in the most significant forces during manoeuvres is less than 2% for the fully appended configuration (the submarine real operative condition), whereas the accuracy is moderately reduced for the barehull configuration (a case not representative of a real hull) with an expected error of 15%. A possible reason for the differences observed could be attributed to the description of the two streamwise vortices generated when manoeuvring. Apart from the lateral force and yaw moment, the results of the longitudinal force are also presented, having a greater disparity when compared to the experimental data. Nevertheless, the longitudinal force has no important role for the purpose of making stability and control predictions. The study contributes to the validation and consolidation of CFD methods, offering insights into their accuracy and limitations for practical applications in underwater vehicles.

Correlated evolution of seed mass and genome size varies among life forms in flowering plants

AbstractSeeds show important variation as plant regenerative units among species, but their evolutionary co-variations with other plant characteristics are still poorly understood. Whilst a positive association of seed mass with genome size (GS) and life forms has already been documented, a broad-scale quantification of their evolutionary correlation and adaptive selection has never been conducted. Here, we tested for correlated evolution of seed mass and GS towards distinct selective regimes related to life form in angiosperms. In particular, we tested the hypothesis that the selection toward lighter seeds and smaller genomes is stronger for annual plants, ensuring high regenerative potential. Using multivariate evolutionary models over a dataset containing 3242 species, we showed an overall positive correlated evolution of seed mass and GS deviating from a pure drift process. Instead, evolutionary changes in seed and genome sizes were driven by adaptive selection towards optimal values differing among life forms. Specifically, the evolutionary optima towards which the seed and genome sizes evolve show a covariation toward small values in annuals, intermediate values in perennial herbs and a trade-off between seed mass and GS in woody plants. Moreover, the evolutionary correlation between seed mass and GS is strongest in annuals as an adaption to complete their life cycle in a short time window, when environmental conditions are favourable for regeneration and development to maturity. The asymmetry in the correlated evolution acting on seed and genome sizes due to life form could explain how life-history traits interplay with functional traits and how plants have evolved diverse successful life-history strategies.

A 3D printed pure copper drift tube linac prototype.

Radio frequency cavities are among the most challenging and costly components of an accelerator facility. They are usually manufactured in individual parts, which are then joined by complex processes, e.g., several brazing steps. 3D printing has become an alternative to these conventional manufacturing methods due to higher cost efficiency, freedom in design, and recent achievement of high print quality for pure copper. A fully functional 3GHz drift tube linac (DTL) prototype was 3D printed in one piece, made from pure copper by selective laser melting (SLM). To achieve a higher surface quality, the DTL geometry was optimized for the SLM process. The DTL design is related to the design of the DTL part of the side-coupled DTL modules used in linac-based proton therapy facilities. The quality factor (8750) and the shunt impedance per unit length (102mΩm) of the printed prototype are already comparable to traditionally manufactured DTL structures and can be further enhanced by surface treatments.

Effect of relativistically degenerate electrons on linear and nonlinear structures in ion temperature gradient driven pure drift mode

Low frequency, electrostatic, pure drift mode is investigated in dense magnetized electron-ion plasma in the presence of relativistically degenerate electrons using quantum magnetohydrodynamic model (QMHD). Ions are considered as warm classical particles. Inhomogeneities in background ion density, ion temperature and external magnetic field are taken into account. In the linear regime, dispersion relation is obtained and plotted for both non-relativistic and ultra-relativistic regimes. Parametric study shows that for both non-relativistic and ultra-relativistic cases, growth rate of the wave increases by increasing, , which is the ratio of background ion temperature to density. In the nonlinear case, solitary solutions are obtained by using the functional variable method. Graphical illustrations are used to show the effect of relativistically degenerate electrons and other parameters like electron and ion number densities, magnetic field and ion temperature on nonlinear structures in both non relativistic and relativistic regimes. This work may be helpful to understand low frequency phenomena in dense inhomogeneous plasmas like neutron stars, white dwarfs and next generation lasers.

Formation of solitons and shocks in toroidal ion temperature gradient mode in the presence ofnon‐Maxwellianelectrons

AbstractLinear and nonlinear phenomena are investigated in toroidal ion temperature gradient (TITG)‐driven pure drift mode. The model includes inhomogeneity in background magnetic field, ion temperature, and density. Finite Larmor radius effect is incorporated to understand the effect of low‐frequency wave on ion dynamics. Electrons are assumed to follow nonthermal distribution, that is, kappa and Cairns distributions. Dispersion relation is obtained to analyse the linear behaviour of the TITG mode in the presence of non‐Maxwellian electron distribution. In the nonlinear regime, exact solutions (soliton and shocks) are obtained (in dispersive and dissipative medium respectively) by using functional variable method to solve the nonlinear partial differential equation obtained for the system under consideration. Graphical illustrations are used to exhibit the characteristics of linear and nonlinear structures and their dependence on different physical parameters. It is observed that for TITG‐driven pure drift mode, rarefactive solitons are formed for both thermal and nonthermal electron distributions. It is also observed that variation of electrons from standard thermal distribution affects the propagation characteristics of linear and nonlinear structures in TITG‐driven modes. Results of our investigations will be helpful to understand the low‐frequency waves in inhomogeneous plasmas in the presence of nonthermal electron distributions which are frequently observed by satellite missions and are also observed in laboratory plasmas.

A Generalized Hybrid RANSE/BEM Approach for the Analysis of Hull–Propeller Interaction in Off-Design Conditions

During maneuvers, propellers’ operation differs from their design due to strong modification of the wake field with respect to the straight-ahead motion. The consequent modification of the loads overstresses the mechanical components of the shaftline, exacerbates propeller side effects and worsens overall efficiency. Therefore, the analysis of these situations in the early design phase is pivotal to increase the operation capabilities and safety at sea. This task relies on novel tools capable to accurately predict the complex flow field that develops past the hull and the propeller loads. Since the solution of the fully coupled problem with the rotating propeller by viscous flow solver is impractical for routine applications, hybrid approaches are a viable alternative. In this paper, an interactive RANSE/BEM methodology is presented, where the propeller is replaced by rotating body forces that map the actual loading state of the blades, allowing a fully unsteady analysis of hull–propeller interaction. The methodology is applied to the straight ahead and 8.4° pure drift motions of a twin screw propulsive configuration. Last, but not least, the study presents a validation study with accurate experimental data of the nominal wake field and single blade loads.

Crow Search Algorithm for MEMS Gyroscope Temperature Drift Signal and Processing for Denoising

To solve the problem of micro‐electro‐mechanical system (MEMS) gyroscope noise, this paper presents a variational mode decomposition (VMD) method based on crow search algorithm. First, the signal was decomposed by variational mode decomposition for optimization of crow search algorithm (CSA‐VMD) method. The parameters required by the VMD method (penalty parameter α and decomposition number K) are given by the crow search algorithm, and then the signal is decomposed into the superposition of multiple subsignals, called intrinsic mode functions (IMFs). The sample entropy (SE) corresponding to each IMF is then obtained. By calculating the sample entropy, the noise signal can be divided into pure noise part, mixing part, and temperature drift part. Second, Savitzky–Golay smoothing denoising (SG) is used to filter the mixed noise signal to eliminate the influence of noise. Third, for the filtering of the drift part, the least square support vector machine optimized by the crow search algorithm (CSA‐LSSVM) was used to filter, so as to reduce the effect of temperature drift. Finally, the processed signal is reconstructed to achieve the goal of denoising. Through the results, it can be found that the optimized VMD and LSSVM using CSA algorithm can achieve more effective denoising. After using the method proposed in this paper, the angular random walk value is 1.1175 ∗ 10−4°/h/√Hz, and the bias stability is 0.0017°/h. Compared with the original signal, the two signals are optimized by 98.1% and 98.2%, respectively. It can be seen from the experimental results that the proposed CSA‐VMD method, SG method, and CSA‐LSSVM method can effectively eliminate noise effects.

A Temperature Compensation Approach for Dual-Mass MEMS Gyroscope Based on PE-LCD and ANFIS

Because the dual-mass MEMS gyroscope's output is greatly influenced by temperature, which can lead to errors that cannot be ignored. To solve this problem, a novel compensation method is proposed: a parallel processing algorithm, which integrates the Permutation entropy (PE), Local Characteristic-scale Decomposition (LCD) and Adaptive network-based fuzzy inference system (ANFIS). Firstly, LCD is used to decompose the output which contains temperature noises and drifts into a trend component and several intrinsic scale components (ISC), according to autocorrelation and complexity, three different categories will be obtained by PE: pure noise output, mixed output, and drift output. The different processes are as follows, the noise output is discarded, the mixed output is filtered by SG (Savitzky-Golay filter), then dual ANFIS is applied. Since the drift output completely reflects the temperature characteristics, the degree of non-linearity is high, the ANFIS with complex rules is used for processing. And the mixed output is composed of intermediate layer modes, containing a relatively small amount of temperature characteristics, simple rule ANFIS is adopted for processing. Finally, the signal is reconstructed. After that, the temperature error experiment is carried out, the result shows the method can effectively eliminate the error and compensate for the drift, it has a fast convergence speed and good effect, and has the advantage of good compensation efficiency.

Numerical analysis of escort tug manoeuvrability characteristics

The adoption of RANS techniques is widely spread in terms of resistance and self-propulsion prognosis for merchant and military vessels; however, on the other hand, the captive evaluation of hydrodynamic manoeuvring forces across numerical procedures still concerns great computational effort and challenge. When it comes to deal with Escort or tractor tugs, characterised by rather full hull forms, typical of harbour tugs, with the addition of extensive foiled shaped fore-skegs solutions, the ability of predicting manoeuvring and handling of such vessels becomes a great added value at an early design stage, as an alternative to physical model scale testing, since very scarce data are present in open literature. Escort vessels in particular, both operate at low and high speed, in addition to the typical harbour tasks entailed, making the manoeuvring modelling even more complicated. In present work, a low-speed and high-speed numerical methodology based on the OpenFOAM finite volume method on polyhedral unstructured mesh is investigated and validated against purposely designed model tests carried out in towing tank: Pure yaw, pure drift, drift and yaw, and drift and heel simulation results are compared with experimental data in terms of forces first, and impact on manoeuvring lastly, showing satisfactory agreement with experiments. Finally, Escort capability tests run at tank are compared with a purposely calibrated manoeuvring model on the RANS results.

Assessing the Impact of Drift Gas Polarizability in Polyatomic Ion Mobility Experiments.

Due to the core assumptions of kinetic theory and the drive toward realizing reproducible gas-phase measurements, ion mobility experiments are commonly conducted in the presence of an inert, neat buffer gas, usually nitrogen or helium. Mixing drift gases in defined, static ratios can provide useful information not only for optimizing the separation of analytes but also for defining the interaction between the ion and neutral particle. In a foundational effort, we seek to validate the role of the drift gas polarizability on the observed mobility of the ions by systematically mixing drift gases to discretely access a range of bulk gas polarizabilities not given by pure drift gases. Compared to historical efforts to probe the role of polarizability on the ion-neutral collisional cross section where a linear relationship was assumed, the data collected in the present effort clearly illustrate a quadratic dependency of the ion-neutral particle collision cross section and polarizability (R2 > 0.999). When translating these data into the mobility dimension, we illustrate that the gas-phase mobility of polyatomic ions conforms to Blanc's law. These observations combined with considerations related to Langevin's polarization limit provide an experimental mechanism to estimate to what degree an ion-neutral interaction conforms to either the hard-sphere or induced-dipole model. To support these observations, additional comparisons are made with the respective reduced masses, polarizabilities, and mobilities of ions in mixtures where different degrees of hard-sphere interactions are present.

Zonal Jet Creation from Secondary Instability of Drift Waves for Plasma Edge Turbulence

A new strategy is presented to explain the creation and persistence of zonal flows widely observed in plasma edge turbulence. The core physics in the edge regime of the magnetic-fusion tokamaks can be described qualitatively by the one-state modified Hasegawa-Mima (MHM) model, which creates enhanced zonal flows and more physically relevant features in comparison with the familiar Charney-Hasegawa-Mima (CHM) model for both plasma and geophysical flows. The generation mechanism of zonal jets is displayed from the secondary instability analysis via nonlinear interactions with a background base state. Strong exponential growth in the zonal modes is induced due to a non-zonal drift wave base state in the MHM model, while stabilizing damping effect is shown with a zonal flow base state. Together with the selective decay effect from the dissipation, the secondary instability offers a complete characterization of the convergence process to the purely zonal structure. Direct numerical simulations with and without dissipation are carried out to confirm the instability theory. It shows clearly the emergence of a dominant zonal flow from pure non-zonal drift waves with small perturbation in the initial configuration. In comparison, the CHM model does not create instability in the zonal modes and usually converges to homogeneous turbulence.

Evaluating Separation Selectivity and Collision Cross Section Measurement Reproducibility in Helium, Nitrogen, Argon, and Carbon Dioxide Drift Gases for Drift Tube Ion Mobility-Mass Spectrometry.

Previous ion mobility (IM) studies have demonstrated that varying the drift gas composition can be used to enhance chemical selectivity and resolution, yet there are few drift gas studies aimed at achieving quantitatively reproducible mobility measurements. Here, we critically evaluate the conditions necessary to achieve reproducible collision cross section (CCS) measurements in pure drift gases (helium, nitrogen, argon, and carbon dioxide) using a commercial uniform field drift tube instrument. Optimal experimental parameters are assessed based on the convergence of CCS measurements to reproducible values which are compared with literature values. A suite of calibration standards with diverse masses, biological classes, and charge states are examined to assess chemical selectivity and resolution achievable in each drift gas. Results indicate nitrogen and argon perform similarly and are sufficient for most applications where high resolving power and high peak capacity are desired. Carbon dioxide exhibits more selectivity for resolving structurally heterogeneous compounds, which may be preferable in specific analyte pair separations. Helium demonstrated modest separation capabilities but has utility for comparison to theoretical values and previously published work. In drift gases other than nitrogen, pressure differentials up to 230mTorr between the drift tube and upstream chamber were optimal for improving correlation to literature values, while in nitrogen, the recommended pressure differential of 150mTorr was found appropriate. We present recommended experimental parameters as well as gas-specific CCS measurements for structurally homogeneous sets of analytes which are suitable for use by other laboratories as standards for purposes of instrument calibration and overall assessment of IM separation performance.

Numerical complete solution for random genetic drift by energetic variational approach

In this paper, we focus on numerical solutions for random genetic drift problem, which is governed by a degenerated convection-dominated parabolic equation. Due to the fixation phenomenon of genes, Dirac delta singularities will develop at boundary points as time evolves. Based on an energetic variational approach (EnVarA), a balance between the maximal dissipation principle (MDP) and least action principle (LAP), we obtain the trajectory equation. In turn, a numerical scheme is proposed using a convex splitting technique, with the unique solvability (on a convex set) and the energy decay property (in time) justified at a theoretical level. Numerical examples are presented for cases of pure drift and drift with semi-selection. The remarkable advantage of this method is its ability to catch the Dirac delta singularity close to machine precision over any equidistant grid.

A general framework for moment-based analysis of genetic data.

In population genetics, the Dirichlet (also called the Balding-Nichols) model has for 20years been considered the key model to approximate the distribution of allele fractions within populations in a multi-allelic setting. It has often been noted that the Dirichlet assumption is approximate because positive correlations among alleles cannot be accommodated under the Dirichlet model. However, the validity of the Dirichlet distribution has never been systematically investigated in a general framework. This paper attempts to address this problem by providing a general overview of how allele fraction data under the most common multi-allelic mutational structures should be modeled. The Dirichlet and alternative models are investigated by simulating allele fractions from a diffusion approximation of the multi-allelic Wright-Fisher process with mutation, and applying a moment-based analysis method. The study shows that the optimal modeling strategy for the distribution of allele fractions depends on the specific mutation process. The Dirichlet model is only an exceptionally good approximation for the pure drift, Jukes-Cantor and parent-independent mutation processes with small mutation rates. Alternative models are required and proposed for the other mutation processes, such as a Beta-Dirichlet model for the infinite alleles mutation process, and a Hierarchical Beta model for the Kimura, Hasegawa-Kishino-Yano and Tamura-Nei processes. Finally, a novel Hierarchical Beta approximation is developed, a Pyramidal Hierarchical Beta model, for the generalized time-reversible and single-step mutation processes.

Analysis on interstory drift of high-rise residential quasi-megastructure

Based on the superior lateral resistant performance of mega-X layout pattern, the concept of quasi-megastructure was put forward to introduce quasi-mega mechanism in residential buildings, using normal members only, avoiding large architecture space occupation of mega members. Unlike the megastructures that are dominated by their primary structures, the quasi-megastructures mainly realize a synergistic mechanism between the frame structure and quasi-mega braces. In order to investigate its deformation mechanism and reduce the lateral stiffness irregularity, a simplified method for evaluating interstory drift of high-rise quasi-megastructure was proposed, based on three fundamental assumptions. Thus, the interstory drift formula for any specific layout scheme of quasi-megastructure can be deduced. The formula was validated by different layout schemes. By this method, the interstory drift proportion of quasi-megastructure was investigated, showing that the interstory drift of a target story mainly consists of drift due to rigid body rotation, pure shearing drift, and shear-lag added drift. And the vertical stiffness irregularity of the original scheme was due to great changes of shear-lag added drift in different neighboring stories. Thereafter, stiffened schemes were proposed, which effectively eliminate the interstory stiffness irregularity by complementing a quasi-mega cantilever wall of full height. Compared with mega frame structure, the original scheme has a similar overall deformation mechanism, while the properly stiffened quasi-megastructure scheme behaves quite close to mega braced frame structure, both in deformation mechanism and in structural efficiency.

On the possibility of track length based Monte-Carlo algorithms for stationary drift-diffusion systems with sources and sinks

The problem of constructing Monte-Carlo solutions of drift-diffusion systems corresponding to Fokker–Planck equations with sources and sinks is revisited. Firstly, a compact formalism is introduced for the specific problem of stationary solutions. This leads to identification of the dwell time as the key quantity to characterize the system and to obtain a proper normalization for statistical analysis of numerical results. Secondly, the question of appropriate track length estimators for drift-diffusion systems is discussed for a 1D model system. It is found that a simple track length estimator can be given only for pure drift motion without diffusion. The stochastic nature of the diffusive part cannot be appropriately described by the path length of simulation particles. Further analysis of the usual situation with inhomogeneous drift and diffusion coefficients leads to an error estimate based on particle trajectories. The result for limits in grid cell size and time step used for the construction of Monte-Carlo trajectories resembles the Courant-Friedrichs-Lewy and von Neumann conditions for explicit methods.

Investigation of surface boundary conditions for continuum modeling of RF plasmas

This work was motivated by a lacking general consensus in the exact form of the boundary conditions (BCs) required on the solid surfaces for the continuum modeling of Radiofrequency (RF) plasmas. Various kinds of number and energy density BCs on solid surfaces were surveyed, and how they interacted with the electric potential BC to affect the plasma was examined in two fundamental RF plasma reactor configurations. A second-order local mean energy approximation with equations governing the electron and ion number densities and the electron energy density was used to model the plasmas. Zero densities and various combinations of drift, diffusion, and thermal fluxes were considered to set up BCs. It was shown that the choice of BC can have a significant impact on the sheath and bulk plasma. The thermal and diffusion fluxes to the surface were found to be important. A pure drift BC for dielectric walls failed to produce a sheath.

Trends in genome-wide and region-specific genetic diversity in the Dutch-Flemish Holstein\u2013Friesian breeding program from 1986 to 2015

BackgroundIn recent decades, Holstein–Friesian (HF) selection schemes have undergone profound changes, including the introduction of optimal contribution selection (OCS; around 2000), a major shift in breeding goal composition (around 2000) and the implementation of genomic selection (GS; around 2010). These changes are expected to have influenced genetic diversity trends. Our aim was to evaluate genome-wide and region-specific diversity in HF artificial insemination (AI) bulls in the Dutch-Flemish breeding program from 1986 to 2015.MethodsPedigree and genotype data (~ 75.5 k) of 6280 AI-bulls were used to estimate rates of genome-wide inbreeding and kinship and corresponding effective population sizes. Region-specific inbreeding trends were evaluated using regions of homozygosity (ROH). Changes in observed allele frequencies were compared to those expected under pure drift to identify putative regions under selection. We also investigated the direction of changes in allele frequency over time.ResultsEffective population size estimates for the 1986–2015 period ranged from 69 to 102. Two major breakpoints were observed in genome-wide inbreeding and kinship trends. Around 2000, inbreeding and kinship levels temporarily dropped. From 2010 onwards, they steeply increased, with pedigree-based, ROH-based and marker-based inbreeding rates as high as 1.8, 2.1 and 2.8% per generation, respectively. Accumulation of inbreeding varied substantially across the genome. A considerable fraction of markers showed changes in allele frequency that were greater than expected under pure drift. Putative selected regions harboured many quantitative trait loci (QTL) associated to a wide range of traits. In consecutive 5-year periods, allele frequencies changed more often in the same direction than in opposite directions, except when comparing the 1996–2000 and 2001–2005 periods.ConclusionsGenome-wide and region-specific diversity trends reflect major changes in the Dutch-Flemish HF breeding program. Introduction of OCS and the shift in breeding goal were followed by a drop in inbreeding and kinship and a shift in the direction of changes in allele frequency. After introduction of GS, rates of inbreeding and kinship increased substantially while allele frequencies continued to change in the same direction as before GS. These results provide insight in the effect of breeding practices on genomic diversity and emphasize the need for efficient management of genetic diversity in GS schemes.

An improved model of fission gas atom transport in irradiated uranium dioxide

The hitherto standard approach to predicting fission gas release has been a pure diffusion gas atom transport model based upon Fick's law. An additional mechanism has subsequently been identified from experimental data at high burnup and has been summarised in an empirical model that is considered to embody a so-called fuel matrix ’saturation’ phenomenon whereby the fuel matrix has become saturated with fission gas so that the continued addition of extra fission gas atoms results in their expulsion from the fuel matrix into the fuel rod plenum.The present paper proposes a different approach by constructing an enhanced fission gas transport law consisting of two components: 1) Fick's law and 2) a so-called drift term. The new transport law can be shown to be effectively identical in its predictions to the ’saturation’ approach and is more readily physically justifiable. The method introduces a generalisation of the standard diffusion equation which is dubbed the Drift Diffusion Equation. According to the magnitude of a dimensionless Péclet number, P, the new equation can vary from pure diffusion to pure drift, which latter represents a collective motion of the fission gas atoms through the fuel matrix at a translational velocity.Comparison is made between the saturation and enhanced transport approaches. Because of its dependence on P, the Drift Diffusion Equation is shown to be more effective at managing the transition from one type of limiting transport phenomenon to the other. Thus it can adapt appropriately according to the reactor operation.