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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Distributionally robust facility location problem under decision-dependent stochastic demand

While the traditional facility location problem considers exogenous demand, in some applications, locations of facilities could affect the willingness of customers to use certain types of services, e.g., carsharing, and therefore they also affect realizations of random demand. Moreover, a decision maker may not know the exact distribution of such endogenous demand and how it is affected by location choices. In this paper, we consider a distributionally robust facility location problem, in which we interpret the moments of stochastic demand as functions of facility-location decisions. We reformulate a two-stage decision-dependent distributionally robust optimization model as a monolithic formulation, and then derive exact mixed-integer linear programming reformulation as well as valid inequalities when the means and variances of demand are piecewise linear functions of location solutions. We conduct extensive computational studies, in which we compare our model with a decision-dependent deterministic model, as well as stochastic programming and distributionally robust models without the decision-dependent assumption. Here, the results show superior performance of our approach with remarkable improvement in profit and quality of service under various settings, in addition to computational speed-ups given by formulation enhancements. These results draw attention to the need of considering the impact of location decisions on customer demand within this strategic-level planning problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Intrinsic size dependent plasticity in BCC micro-pillars under uniaxial tension and pure torsion

The mechanical behavior of submicron body-centered cubic (BCC) micro-pillars is investigated by three-dimensional dislocation dynamics (DD) simulations to better understand the governing mechanisms for size dependent plasticity under uniaxial tension and pure torsion. A formula is developed to compute the incremental plastic twist due to dislocation motion in DD simulations. The DD simulations show that different dislocation microstructures are created depending on the loading conditions, which leads to different size dependent mechanical behavior. While in tension plasticity is mainly governed by the kinetics of dislocation motion controlled partly by the surface dislocation sources, plastic flow in torsion is controlled by dislocation pile-ups associated with strain gradients. The simulation results also reveal a Bauschinger effect and plastic recovery under cyclic twist, which have been observed in recent experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2024

PINN surrogate of Li-ion battery models for parameter inference, Part II: Regularization and application of the pseudo-2D model

Bayesian parameter inference is useful to improve Li-ion battery diagnostics and can help formulate battery aging models. However, it is computationally intensive and cannot be easily repeated for multiple cycles, multiple operating conditions, or multiple replicate cells. To reduce the computational cost of Bayesian calibration, numerical solvers for physics-based models can be replaced with faster surrogates. A physics-informed neural network (PINN) is developed as a surrogate for the pseudo-2D (P2D) battery model calibration. For the P2D surrogate, additional training regularization was needed as compared to the PINN single-particle model (SPM) developed in Part I. Both the PINN SPM and P2D surrogate models are exercised for parameter inference and compared to data obtained from a direct numerical solution of the governing equations. A parameter inference study highlights the ability to use these PINNs to calibrate scaling parameters for the cathode Li diffusion and the anode exchange current density. By realizing computational speed-ups of ~2250x for the P2D model, as compared to using standard integrating methods, the PINN surrogates enable rapid state-of-health diagnostics. Finally, in the low-data availability scenario, the testing error was estimated to ~2 mV for the SPM surrogate and ~10 mV for the P2D surrogate which could be mitigated with additional data.

25 ENERGY STORAGE↗
DOE OSTI2020

Determination of permeability for hydrocarbon release due to excavation-induced stress redistribution in rock salt

Due to a stress redistribution after the excavation of an underground tunnel for radioactive waste disposal, an Ed/DZ (excavation disturbed/damaged zone) will be generated in the near field of the opening, resulting in significant changes in the hydraulic and mechanical properties of the rock mass in the zone. Initially more or less randomly distributed hydrocarbons at grain boundaries in rock salt, which sometimes can only be observed with ultraviolet light, can then be mobilised and migrate at a potentially significant rate towards the excavation. Within the international cooperative project DECOVALEX 2019, the migration mechanism of such fluid inclusions in rock salt is being studied intensively. Specifically, a multi-scale modelling strategy has been developed. A macroscale coupled hydro-mechanical modelling of an underground excavation was performed to determine hydraulic and time-dependent deviatoric stress conditions, by taking into account the rock salt creep behaviour. Under the obtained macro-scale constraints, micro-scale modelling of a pathway dilation along halite grain boundaries was performed using different model strategies: a) coupled hydromechanical modelling with a consideration of hydraulic pressure-induced dilatant deformation, b) nonlinear dynamic model taking account of fluid migration, stress-dependent grain boundary wetting and shear-induced dilatancy of salt, and c) phase-field modelling of flow pathway propagation. The permeability increase resulting from the pathway dilation is estimated to be as high as two orders of magnitude. Based on the permeability determined, a series of pressure buildups measured from a borehole with a high hydrocarbon release rate, a total of 430 build-ups within a monitoring time of 938 days, can be simulated with a macro-scale compressible flow model accounting for different zones around the opening.

58 GEOSCIENCES↗
DOE OSTI2021

Maximum bound principle preserving integrating factor Runge–Kutta methods for semilinear parabolic equations

A large class of semilinear parabolic equations satisfy the maximum bound principle (MBP) in the sense that the time-dependent solution preserves for any time a uniform pointwise bound imposed by its initial and boundary conditions. Here, the MBP plays a crucial role in understanding the physical meaning and the well-posedness of the mathematical model. Investigation on numerical algorithms with preservation of the MBP has attracted increasingly attentions in recent years, especially for the temporal discretizations, since the violation of MBP may lead to nonphysical solutions or even blow-ups of the algorithms. In this paper, we study high-order MBP-preserving time integration schemes by means of the integrating factor Runge-Kutta (IFRK) method. Beginning with the space-discrete system of semilinear parabolic equations, we present the IFRK method in general form and derive the sufficient conditions for the method to preserve the MBP. In particular, we show that the classic four-stage, fourth-order IFRK scheme is MBP preserving for some typical semilinear systems although not strong stability preserving, which can be instantly applied to the Allen-Cahn type of equations. To our best knowledge, this is the first time to present a fourth-order linear numerical method preserving the MBP. In addition, convergence of these numerical schemes is proved theoretically and verified numerically, as well as their efficiency by simulations of 2D and 3D long-time evolutional behaviors. Numerical experiments are also carried out for a model which is not a typical gradient flow as the Allen-Cahn type of equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A physics-informed and hierarchically regularized data-driven model for predicting fluid flow through porous media

This paper presents a new deep learning data-driven model for predicting structure dependent pore-fluid velocity fields in rock. The model is based on a Convolutional Auto-Encoder (CAE) artificial neural network capable of learning from image data generated by direct numerical simulations of fluid flow through pore-structures, such as by Lattice Boltzmann or molecular dynamics methods. The main novelty of the model in comparison to previous CAE-based data-driven approaches consists of three parts. The first is a methodology for decomposing the full-domain of the porous media into sub-regions, or “sub-domains”, in order to reduce the overall size of the CAE, batch process the sub-domains in parallel, and enable the CAE to learn local and generalizable nonlinear mappings of pore-fluid velocities. The second consists of embedding the finite difference solutions of the incompressible Navier-Stokes and continuity equations into convolutional layers prior to the CAE in order to provide the CAE with knowledge of fluid dynamics physics (PhyFlow). The third main novelty is that the training of the CAE is regularized with a hierarchical loss function that encourages the learning of fluid flow patterns (in a way similar to ranked modes in principal component analysis), ranking from most to least important. This is shown to increase the stability in learning, reduce over-fitting, and promote interpretability of the CAE neural network layers (HierCAE). The comprehensive new data-driven model, which we call the PhyFlow-HierCAE model, is shown to exhibit improved accuracy and generalizability of flow field predictions over conventional CAE models, attributable to the embedded physical knowledge and the hierarchical regularization, as well as realize orders of magnitude speed-ups in computation times as a surrogate for the direct numerical simulations. Examples of training and forward predictions on unseen pore-structures are provided and evaluated for data from Lattice Boltzmann and molecular dynamics simulations of pore-fluid flow. The model is shown to be a fast and accurate emulator (or “surrogate”) for predicting effective permeability of unseen pore-structures based on learning from relatively small direct numerical simulation datasets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Asymptotic-preserving gyrokinetic implicit particle-orbit integrator for arbitrary electromagnetic fields

We extend the asymptotic preserving and energy conserving time integrator for charged-particle motion developed in Ricketson and Chacón (2020) to include finite Larmor-radius (FLR) effects in the presence of electric-field length-scales comparable to the particle gyro-radius (the gyro-kinetic limit). We introduce two modifications to the earlier scheme. The first is the explicit gyro-averaging of the electric field at the half time-step, along with an analogous modification to the current deposition, which we show preserves total energy conservation in implicit PIC schemes. The number of gyrophase samples is chosen adaptively, ensuring proper averaging for large timesteps and the recovery of full-orbit dynamics in the small time-step limit. The second modification is an alternating large and small time-step strategy that ensures the particle trajectory samples gyrophases evenly. We show that this strategy relaxes the time-step restrictions on the scheme, allowing even larger speed-ups than previously achievable. We demonstrate the new method with several single-particle motion tests in a variety of electromagnetic field configurations featuring gyro-scale variation in the electric field. Finally, the results demonstrate the advertised ability to capture FLR effects accurately even when significantly stepping over the gyration time-scale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Conservative velocity mappings for discontinuous Galerkin kinetics

Continuum computational kinetic plasma models evolve the distribution function of a plasma species f s on a phase-space grid over time. In many problems of interest the distribution function has limited extent in velocity space; hence, using a uniform, highly refined mesh would be costly and slow. Nonuniform velocity grids can reduce the computational cost by placing more degrees of freedom where f s is appreciable and fewer where it is not. In this work we introduce a first-of-its kind discontinuous Galerkin approach to nonuniform velocity-space discretization using mapped velocity coordinates. This new method is presented in the context of a gyrokinetic model used to study magnetized plasmas. We create discretizations of collisionless and collisional terms using mappings in a way that exactly conserves particles and energy. Numerical tests of such properties are presented, and we show that this new discretization can reproduce earlier gyrokinetic simulations using grids with up to 6–60 times fewer cells and 22X-60X speed-ups depending on dimensionality, geometry and plasma parameters.

Discontinuous Galerkin↗
DOE OSTI2026

TANTE: Time-adaptive operator learning via neural Taylor expansion

Operator learning for time-dependent partial differential equations (PDEs) has seen rapid progress in recent years, enabling efficient approximation of complex spatiotemporal dynamics. However, most existing methods rely on fixed time step sizes during rollout, which limits their ability to adapt to varying temporal complexity and often leads to error accumulation. In this work, we propose the Time-Adaptive Transformer with Neural Taylor Expansion (TANTE), a novel operator-learning framework that produces continuous-time predictions with adaptive step sizes. TANTE predicts future states by performing a Taylor expansion at the current state, where neural networks learn both the higher-order temporal derivatives and the local radius of convergence. This allows the model to dynamically adjust its rollout based on the local behavior of the solution, thereby reducing cumulative error and improving computational efficiency. We demonstrate the effectiveness of TANTE across a wide range of PDE benchmarks, achieving superior accuracy and adaptability compared to fixed-step baselines, delivering accuracy gains of 60-80 % and speed-ups of 30-40 % at inference time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Third international challenge to model the medium- to long-range transport of radioxenon to four Comprehensive Nuclear-Test-Ban Treaty monitoring stations

In 2015 and 2016, atmospheric transport modeling challenges were conducted in the context of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) verification, however, with a more limited scope with respect to emission inventories, simulation period and number of relevant samples (i.e., those above the Minimum Detectable Concentration (MDC)) involved. Therefore, a more comprehensive atmospheric transport modeling challenge was organized in 2019. Stack release data of Xe-133 were provided by the Institut National des Radioéléments/IRE (Belgium) and the Canadian Nuclear Laboratories/CNL (Canada) and accounted for in the simulations over a three (mandatory) or six (optional) months period. Best estimate emissions of additional facilities (radiopharmaceutical production and nuclear research facilities, commercial reactors or relevant research reactors) of the Northern Hemisphere were included as well. Model results were compared with observed atmospheric activity concentrations at four International Monitoring System (IMS) stations located in Europe and North America with overall considerable influence of IRE and/or CNL emissions for evaluation of the participants’ runs. Participants were prompted to work with controlled and harmonized model set-ups to make runs more comparable, but also to increase diversity. It was found that using the stack emissions of IRE and CNL with daily resolution does not lead to better results than disaggregating annual emissions of these two facilities taken from the literature if an overall score for all stations covering all valid observed samples is considered. A moderate benefit of roughly 10% is visible in statistical scores for samples influenced by IRE and/or CNL to at least 50% and there can be considerable benefit for individual samples. Effects of transport errors, not properly characterized remaining emitters and long IMS sampling times (12–24 h) undoubtedly are in contrast to and reduce the benefit of high-quality IRE and CNL stack data. Complementary best estimates for remaining emitters push the scores up by 18% compared to just considering IRE and CNL emissions alone. Despite the efforts undertaken the full multi-model ensemble built is highly redundant. An ensemble based on a few arbitrary runs is sufficient to model the Xe-133 background at the stations investigated. The effective ensemble size is below five. An optimized ensemble at each station has on average slightly higher skill compared to the full ensemble. However, the improvement (maximum of 20% and minimum of 3% in RMSE) in skill is likely being too small for being exploited for an independent period.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A stress-sensitive precipitate nucleation model beyond classical nucleation theory

The dynamic evolution of precipitates and second phases dictates the strength and stability of most engineering alloys. By design, or as a consequence of thermo-mechanical aging, engineering metals and alloys often form precipitates of second phases when subjecting to diverse thermal and mechanical loads. Precipitation is governed by several factors, including the alloy’s composition, processing/operating temperature, and stresses — either as a result of external loads or from residual stresses. However, state-of-the-art models for precipitate nucleation (i.e., classical nucleation theory) typically lacks consistent method to capture the effects of externally applied and/or internal stresses on nucleation; thereby severely limiting the applicability of these models to complex materials systems and to representative loading scenarios. Here, in this work, we extend upon classical nucleation theory to account for the effect of stresses on precipitation kinetics and thermodynamics. This is achieved via the use of an Eshelbian micromechanics framework keeping track of (i) the stress build up resulting from second phase formation as a function of mechanical load and, (ii) the effects of dislocations on precipitate formation. This new model is applied to σ precipitate in Fe–Cr binary alloys and M 23 C 6 precipitate in 316H stainless steel (SS). Simulations demonstrate the important role of both the remotely applied loads and dislocation pile ups on precipitate nucleation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Deformation behavior of metallic glass composites and plasticity accommodation at microstructural length-scales

Bulk metallic glass matrix composites represent a unique microstructural design strategy for overcoming the strength/ductility trade-off in structural alloys. Site-specific mechanical behavior of a Ti-based bulk metallic glass composite was evaluated at microstructural length-scale. The micro-pillars on the amorphous matrix showed on average a yield point of 1.9 GPa followed by serrated plastic deformation characteristic of shear banding. In contrast, micro-pillars on the crystalline dendritic phase showed a much lower yield strength of 0.72 GPa on average for the four different crystallographic orientations chosen, smooth plastic flow with no recognizable load burst, and stable strain-hardening after yield point. A number of micro-pillars were made at the interface between the glassy matrix and the crystalline dendrite. The mixed micro-pillars showed homogeneous deformation and greater plasticity which was attributed to their smaller stored elastic energy. Shear bands initiated in the amorphous matrix were arrested by the crystalline dendrite, which accommodated plasticity through slip bands and dislocations pile-ups. The interface remained intact after plastic deformation, with no observable signs of devitrification in the amorphous phase.

Bulk metallic glass matrix composite, Micro-pillar↗
DOE OSTI2020

Layout and performance of HPK prototype LGAD sensors for the High-Granularity Timing Detector

The High-Granularity Timing Detector is a detector proposed for the ATLAS Phase II upgrade. The detector, based on the Low-Gain Avalanche Detector (LGAD) technology, will cover the pseudo-rapidity region of 2.4 < |n| < 4.0 with two end caps on each side and a total area of 6.4 m 2 . The timing performance can be improved by implanting an internal gain layer that can produce signals with a fast rising edge. It significantly improves the signal-to-noise ratio. The required average timing resolution per track for a minimum ionizing particle is 30 ps at the start and 50 ps at the end of the HL-LHC operation. This is achieved with several layers of LGAD. The innermost region of the detector would accumulate a 1MeV neutron-equivalent fluence up to 2.5 10 15 n eq /cm 2 including a safety factor of 1.5 before being replaced during the scheduled shutdowns. The addition of this new detector is expected to play an important role in the mitigation of high pile-ups at the HL-LHC. The layout and performance of the various versions of LGAD prototypes produced by Hamamatsu (HPK) have been studied by the ATLAS Collaboration. The breakdown voltages, depletion voltages, inter-pad gaps, collected charge as well as the time resolution have been measured and the production yield of large size sensors has been evaluated.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Rate-capability of the VMM3a front-end in the RD51 Scalable Readout System

The VMM3a is an Application Specific Integrated Circuit (ASIC), specifically developed for the readout of gaseous detectors. Originally developed within the ATLAS New Small Wheel (NSW) upgrade, it has been successfully integrated into the Scalable Readout System (SRS) of the RD51 collaboration. This allows, to use the VMM3a also in small laboratory set-ups and mid-scale experiments, which make use of Micro-Pattern Gaseous Detectors (MPGDs). As part of the integration of the VMM3a into the SRS, the readout and data transfer scheme was optimised to reach a high rate-capability of the entire readout system and profit from the VMM3a's high single-channel rate-capability of 3.6Mhits/s. The optimisation focused mainly on the handling of the data output stream of the VMM3a, but also on the development of a trigger-logic between the front-end cards and the DAQ computer. In this article, two firmware implementations of the non-ATLAS continuous readout mode are presented, as well as the implementation of the trigger-logic. Afterwards, a short overview on X-ray imaging results is presented, to illustrate the high rate-capability from an application point-of-view.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Autonomous nondestructive evaluation of resistance spot welded joints

The application of non-destructive evaluation approaches has attracted strong interests in modern automotive industries. Here, we present an autonomous deep-computing framework to analyze raw videos from infrared systems and to predict weld nugget shape and size with unprecedented accuracy and speed. In a comprehensive training and testing experiment with 90 videos (seven sets of welding material stack-ups), a new method was developed to assemble sufficient datasets for neural network training. Our framework successfully predicts all the nugget shapes with F1 scores that range from 0.84 to 0.92. The total training time on Nvidia DGX station takes less than 10 min for each set of welding material stack-up. The real inference time of an individual dataset (with 30 video frames) takes about 0.005 s. The procedure and methods developed in the study can be applied to other image-based weld property prediction, as well as other manufacturing processes. Furthermore, our well-trained neural networks take limited memory resources (2.3 MB) and are suitable for embedded microprocessors for in-situ welding quality control as edge computing within an intelligent welding framework.

42 ENGINEERING↗
DOE OSTI2022

Spectroscopic investigation of the electronic and excited state properties of para-substituted tetraphenyl porphyrins and their electrochemically generated ions

Porphyrins play pivotal roles in many crucial biological processes including photosynthesis. However, there is still a knowledge gap in understanding electronic and excited state implications associated with functionalization of the porphyrin ring system. These effects can have electrochemical and spectroscopic signatures that reveal the complex nature of these somewhat minor substitutions, beyond simple inductive or electronic effect correlations. To obtain a deeper insight into the influences of porphyrin functionalization, four free-base, meso-substituted porphyrins: tetraphenyl porphyrin (TPP), tetra(4-hydroxyphenyl) porphyrin (THPP), tetra(4-carboxyphenyl) porphyrin (TCPP), and tetra(4-nitrophenyl) porphyrin (TNPP), were synthesized, characterized, and investigated. The influence of various substituents, (-hydroxy,-carboxy, and -nitro) in the para position of the meso-substituted phenyl moieties were evaluated by spectroelectrochemical techniques (absorption and fluorescence), femtosecond transient absorption spectroscopy, cyclic and differential pulse voltammetry, ultraviolet photoelectron spectroscopy (UPS), and time-dependent density functional theory (TD-DFT). Spectral features were evaluated for the neutral porphyrins and differences observed among the various porphyrins were further explained using rendered frontier molecular orbitals pertaining to the relevant transitions. Electrochemically generated anionic and cationic porphyrin species indicate similar absorbance spectroscopic signatures attributed to a red-shift in the Soret band. Emissive behavior reveals the emergence of one new fluorescence decay pathway for the ionic porphyrin, distinct from the neutral macrocycle. Femtosecond transient absorption spectroscopy analysis provided further analysis of the implications on the excited-state as a function of the para substituent of the free-base meso-substituted tetraphenyl porphyrins. Herein, we provide an in-depth and comprehensive analysis of the electronic and excited state effects associated with systematically varying the induced dipole at the methine bridge of the free-base porphyrin macrocycle and the spectroscopic signatures related to the neutral, anionic, and cationic species of these porphyrins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

De-ubiquitination of p300 by USP12 Critically Enhances METTL3 Expression and Ang II-induced cardiac hypertrophy

Highlights: • The expression of USP12 is increased in Ang II-induced cardiac hypertrophy in vitro and in vivo. • USP12 aggravates Ang II-induced cardiomyocyte hypertrophy via upregulating METTL3. • USP12 promoted METTL3 expression via modulating p300. • USP12 suppresses the ubiquitination of p300 to block its degradation. Stresses, such as neurohumoral activation, induced pathological cardiac hypertrophy is the main risk factor for heart failure. The ubiquitin-proteasome system (UPS) plays a key role in maintaining protein homeostasis and cardiac function. However, research on the role and mechanism of deubiquitinating enzymes (DUBs) in cardiac hypertrophy is limited. Here, we observe that the deubiquitinating enzyme ubiquitin-specific protease 12(USP12) is upregulated in Ang II-induced hypertrophic hearts and primary neonatal rat cardiomyocytes (NRCMs). Inhibition of USP12 ameliorate Ang II-induced myocardial hypertrophy, while overexpression of USP12 have the opposite effect. USP12 deficiency also significantly attenuate the phenotype of Ang II-induced cardiac hypertrophy in vivo. Moreover, we demonstrate that USP12 aggravate Ang II-induced cardiac hypertrophy by enhancing METTL3, a methyltransferase which catalyze N{sup 6}-methyladenosine (m{sup 6}A) modification on messenger RNA and acts as a harmful factor in pathological cardiac hypertrophy. Upregulation of METTL3 reverse the reduction of myocardial hypertrophy induced by USP12 silencing in NRCMs. In contrast, knockdown of METTL3 attenuate the aggravation of myocardial hypertrophy in USP12-overexpressing NRCMs. Furthermore, we discover that USP12 promote the expression of METTL3 via upregulating p300. Mechanistically, USP12 binds and stabilizes p300, thereby activating the transcription of its downstream gene METTL3. Finally, our data show that USP12 is partially dependent on the stabilization of p300 to activate METTL3 expression and promote myocardial hypertrophy. Taken together, our results demonstrate that USP12 acts as a pro-hypertrophic deubiquitinating enzyme via enhancing p300/METTL3 axis, indicating that targeting USP12 could be a potential treatment strategy for pathological cardiac hypertrophy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Collisionless conduction in a high-beta plasma: a collision operator for whistler turbulence

The regulation of electron heat transport in high-β, weakly collisional, magnetized plasma is investigated. A temperature gradient oriented along a mean magnetic field can induce a kinetic heat-flux-driven whistler instability (HWI), which back-reacts on the transport by scattering electrons and impeding their flow. Previous analytical and numerical studies have shown that the heat flux for the saturated HWI scales as β$^{-1}_{e}$. These numerical studies, however, had limited scale separation and consequently large fluctuation amplitudes, which calls into question their relevance at astrophysical scales. To this end, we perform a series of particle-in-cell simulations of the HWI across a range of β$_e$ and temperature-gradient length scales under two different physical set-ups. The saturated heat flux in all of our simulations follows the expected β$^{-1}_{e}$ scaling, supporting the robustness of the result. We also use our simulation results to develop and implement several methods to construct an effective collision operator for whistler turbulence. The results point to an issue with the standard quasi-linear explanation of HWI saturation, which is analogous to the well-known 90° scattering problem in the cosmic-ray community. Despite this limitation, the methods developed here can serve as a blueprint for future work seeking to characterize the effective collisionality caused by kinetic instabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗