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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Simulation and measurement of the dynamic strain response in a prototypical spallation target

The Second Target Station (STS) at the Spallation Neutron Source (SNS) will address emerging scientific challenges by providing a source of intense cold neutrons to instruments optimized for this source. The STS target will use rotating tungsten blocks and will receive 1.3 GeV proton beam pulses from the SNS accelerator at a repetition rate of 15 Hz. The facility life is planned for 40 years, and each target assembly life is expected to be approximately 10 years. An accurate strain prediction is then critical for fatigue life assessment of STS target blocks because they will be subject to approximately 10 8 beam pulses per lifetime. As an R&D activity, the Los Alamos Neutron Science Center (LANSCE) Weapons Neutron Research (WNR) Target 2 (Blue Room) facility was used to test the strain response of prototypical target blocks to the thermal shock of a proton pulse. The blue room was well suited for a pulsed proton beam impact test of subscale STS target blocks; the 800 MeV proton energy is approximately 60 % of the 1.3 GeV proton energy expected from the SNS accelerator to the STS. The LANSCE Proton Storage Ring (PSR) and SNS are both short-pulse proton beam sources with nominal pulse widths of 250 ns and 661 ns, respectively, so the energy deposition in the target occurs in <1 μs pulse duration. Strain measurements on the outer surface of three target blocks (bare tungsten, tantalum-clad tungsten, niobium-clad tungsten) were recorded for comparison against neutronics and structural simulations. In conclusion, this experiment and the supporting simulations satisfied the following primary research goals for the STS target.

Dynamic strain response↗
DOE OSTI2018

Dynamic simulation of powder packing structure for powder bed additive manufacturing

Here, powder packing structure is a critical parameter of powder bed-based additive manufacturing (AM). Experimental characterization of powder is typically limited to measuring bulk properties, whereas many numerical models of AM powder packing are based on geometrical consideration without accounting for particle-to-particle interactions. In the present paper, the powder packing dynamics is simulated using a discrete element method (DEM)-based model that solves the mechanical contact forces and moments between individual particles. As DEM uses explicit time integration, a main challenge in modeling dynamics of metallic powder packing is the need for extremely fine time increment size (e.g., in the order of 1 ns for a 10-μm-diameter particle). The effect of mass scaling, employed for speeding up the calculation, on the simulation results is examined in a test case of powder particles packed inside a box container. The calculated packing density for two different particle size distributions is validated against independent literature data for laser powder bed AM with AISI 316L stainless steel powder. The sensitivity of key input parameters (e.g., friction coefficient) is further evaluated in this test case. The powder packing model is then applied to a practical situation of binder jet AM involving rolling of multiple layers of IN718 powder particles onto a powder bed, for which the calculated packing density is also validated with independent literature data.

42 ENGINEERING↗
DOE OSTI2019

Exploring the capabilities of optical pump X-ray probe NEXAFS spectroscopy to track photo-induced dynamics mediated by conical intersections

X-ray spectroscopy is gaining a growing interest in the scientific community, as it represents a versatile and powerful experimental toolbox for probing the dynamics of both core and valence electronic excitations, nuclear motions and material structure, with element and site specificity. Among the various X-ray based techniques, near-edge X-ray absorption fine structure (NEXAFS) spectroscopy, which investigates the energy and probability of resonant core-to-valence transitions, has started to be applied to organic molecules: a recent UV-pump X-ray probe time-resolved NEXAFS experiment [Wolf et al., Nat. Commun., 2017, 8, 1] has shown the capability of the technique to provide information about the ultrafast internal conversion between the bright ππ* and the dark nπ* electronic states of the nucleobase thymine. In the present contribution we introduce an accurate theoretical approach for the simulation of NEXAFS spectra of organic molecules, employing azobenzene as a test case. The electronic structure calculations, which provide both energy levels and transition probabilities of core-to-valence excitations, were here performed with a high level multiconfigurational method, the restricted active space self consistent field (RASSCF/RASPT2). GS- and nπ*-NEXAFS spectra were obtained on the top of key molecular geometries (as the optimized cis, trans and conical intersection(s) structures) as well as along the fundamental isomerization coordinates (namely, symmetric and asymmetric bendings of the phenyl rings, and torsion around the central dihedral). We eventually characterize and explain the origin of the simulated signals, highlighting the specific signatures that make it possible to follow the excited state evolution from the nπ* Franck–Condon point, towards the conical intersection(s).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Skluma: An extensible metadata extraction pipeline for disorganized data

To mitigate the effects of high-velocity data expansion and to automate the organization of filesystems and data repositories, we have developed Skluma-a system that automatically processes a target filesystem or repository, extracts content-and context-based metadata, and organizes extracted metadata for subsequent use. Skluma is able to extract diverse metadata, including aggregate values derived from embedded structured data; named entities and latent topics buried within free-text documents; and content encoded in images. Skluma implements an overarching probabilistic pipeline to extract increasingly specific metadata from files. It applies machine learning methods to determine file types, dynamically prioritizes and then executes a suite of metadata extractors, and explores contextual metadata based on relationships among files. The derived metadata, represented in JSON, describes probabilistic knowledge of each file that may be subsequently used for discovery or organization. Skluma's architecture enables it to be deployed both locally and used as an on-demand, cloud-hosted service to create and execute dynamic extraction workflows on massive numbers of files. It is modular and extensible-allowing users to contribute their own specialized metadata extractors. Thus far we have tested Skluma on local filesystems, remote FTP-accessible servers, and publicly-accessible Globus endpoints. We have demonstrated its efficacy by applying it to a scientific environmental data repository of more than 500,000 files. We show that we can extract metadata from those files with modest cloud costs in a few hours.

data swamp↗
DOE OSTI2024

A Roadmap for a Lightning Modeling Grand Challenge

This document is a roadmap for building an interconnected model of the physical processes that produce a lightning discharge, and its observable optical and radio signals. We call this a Lightning Modeling Grand Challenge, recognizing that significant effort and coordination of human and financial resources is required to realize the capability. The roadmap serves to outline the coordination of resources necessary to enable stitching together existing knowledge and model components to make a lightning prediction, and to test these predictions with observations. Such a capability does not currently exist. The roadmap is motivated not only by a spirit of scientific inquiry, but by practical challenges faced by US Federal and societal stakeholders. Advancements in lightning observations have outpaced our tests of integrated understanding, leaving many stakeholders unsure how to design their missions to properly detect and discriminate lightning, and unsure how to apply the sometimes-disagreeing lightning signals from diverse instruments. The time is right to connect existing theories and models to support stakeholders in understanding the signals they observe, for needs as diverse as climate monitoring, national security, weather forecasting, public safety, and protection of natural and built environments. The roadmap’s two main technical sections describe the components of a linked physical model, followed by a description of models of lightning signals and sensors that are driven by outputs from the physical model. The goal is to predict the time-varying physical properties of lightning that are self-consistent with the thunderstorm’s structure and dynamics. These lightning signals then propagate through the storm, with realistic dispersion and attenuation, to receivers on the ground or in space. At a high level, the model begins with weather (cloud) model output, including explicit prediction of the electrification of cloud particles. The cloud’s electrical structure drives a model of lightning physics, from initiation, through channel development, and discharges along those channels. Key lightning parameters, such as the temperature and currents in the channel, and their space and time distribution, are then used to produce optical and electromagnetic signal sources that propagate to modeled receivers. This architecture therefore generates a dataset suitable for comparison to existing and envisioned observing systems. The need for additional measurements and field campaigns to support model development is described. In each model sub-component, inputs, outputs, uncertainties, evaluation methods, and next steps are summarized, interleaved with references to the scientific literature. Identifying boundaries between the model sub-components aids in segmenting an integrated, complex model into practical work packages and system sub-components, allowing a diverse team to contribute and maintain the system. We estimate that at least five years of effort and a $\$$10M initial investment is necessary to make a significant step forward. Mechanisms to facilitate community coordination, including annual workshops and open-source code repositories, are described.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Performance of Vehicle Fuel System Elastomers and Plastics with Test Fuels Representing Gasoline Blended with 10% Ethanol (E10) and 16% Isobutanol (iBu16)

The compatibilities of fuel system elastomers and plastics were evaluated for test fuels containing 16 vol.% isobutanol (iBu16) and 10 vol.% ethanol (E10). Elastomers included two fluorocarbons, four acrylonitrile butadiene rubbers (NBRs), and one type of fluorosilicone, neoprene, and epichlorohydrin/ethylene oxide. Plastic materials included four nylon grades, three polyamides, polytetrafluoroethylene (PTFE), polyvinylidene fluoride (PVDF), ethylene tetrafluoroethylene (ETFE), polyphenylene sulfide (PPS), high-density polyethylene (HDPE), polybutylene terephthalate (PBT), polyoxymethylene (POM), flexible polyvinylchloride (PVC), polyetherimide (PEI), polyetheretherketone (PEEK), and a phenol formaldehyde reinforced with glass fiber (GFPF). For each polymer material, the volume, mass, and hardness were measured before and after drying. Dynamic mechanical analysis (DMA) measurements were also performed on the dried specimens.For the elastomer materials the measured properties were similar for both fuels. The fluorocarbons and fluorosilicone swelled the least (~20%), while more moderate (20-45%) expansion occurred for the two NBR hose grades and (ECO). HNBR, neoprene, and silicone exhibited high swelling and softening, which likely precludes their use in many fuel systems. For the plastic materials, the observed swell was low; Nylon 11 swelled around 15%, but otherwise, their measured swell was <10%. Many of the plastics also showed sensitivity to alcohol type, as the E10 test fuel often imparted appreciably higher swell than iBu16. In general, the plastic materials showed good compatibility with the iBu16 and E10 test fuels. Here, the sole exception was the PVC material, which was structurally degraded from exposure to either fuel type. Compositional analysis showed high fuel retention in Nylon 12 and PVC. PVC also experienced a significant reduction in plasticizer compounds following exposure, which resulted in embrittlement and an increase in the glass-to-rubber transition temperature.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

A new yield and failure theory for composite materials under static and dynamic loading

In order to facilitate and accelerate the process of introducing, evaluating and adopting new material systems, it is important to develop/establish comprehensive and effective procedures of characterization, modeling and failure prediction of composite structures based on the properties of the constituent materials, e. g., fibers, matrix, and the single ply or lamina. A new yield/failure theory is proposed for predicting lamina yielding and failure under multi-axial states of stress including strain rate effects. It is based on the equivalent stress concept derived from energy principles and is expressed in terms of a single criterion. It is presented in the form of master yield and failure envelopes incorporating strain rate effects. The theory can be further adapted and extended to the prediction of in situ first ply yielding and failure (FPY and FPF) and progressive damage of multi-directional laminates under static and dynamic loadings. The significance of this theory is that it allows for rapid screening of new composite materials without extensive testing and offers easily implemented design tools.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Connecting primordial gravitational waves and dark energy

Cosmic acceleration manifested in the early universe as inflation, generating primordial gravitational waves detectable in the cosmic microwave background (CMB) radiation. Cosmic acceleration is occurring again at present as dark energy, detectable in cosmic distance and structure surveys. We explore the intriguing idea of connecting the two occurrences through quintessential inflation by an α-attractor potential without a cosmological constant. For this model we demonstrate robustness of the connection 1 + w 0 ≈ 4/(3N 2 r) between the present day dark energy equation of state parameter w 0 and the primordial tensor to scalar ratio r for a wide range of initial conditions. Analytic and numerical solutions produce current thawing behavior, resulting in a tight relation w a ≈ -1.53(1 + w 0 )≈ -0.2 (4 × 10 -3 /r). Upcoming CMB and galaxy redshift surveys can test this consistency condition. In conclusion, within this model, lack of detection of a dark energy deviation from Λ predicts a higher r, and lack of detection of r predicts greater dark energy dynamics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

The Future Polarized Target Program at Jefferson Lab

Polarized targets have played a crucial role in Jefferson Lab's exploration of nuclear structure over the past four decades. The three original experimental halls have seen 19 separate installations of polarized solid or gas targets for use in the particle physics scattering experiments, and this trend will continue in the next decade. Five polarized target systems are in preparation for use at JLab in the coming years. Hall B will see the use of two solid polarized targets, one longitudinally polarized to the beam, the other transversely, as well as a novel 3He gas polarized target. In Hall C, new experiments will augment the tensor polarization in dynamically polarized solids. Plans are under development to bring a polarized solid target to Jefferson Lab's photon beam hall, Hall D, for the first time. To support these efforts, the JLab polarized target group is building a test laboratory to develop dynamic nuclear polarization techniques, as well as an apparatus to irradiate target material using electrons from JLab's injector test facility. In this talk, we will explore the development progress and plans for each of these efforts.

Maxwell, James [Thomas Jefferson National Accelera↗
DOE OSTI2021

Brought to Light. I. Quantification of Disk Substructure in Dwarf Early-type Galaxies

Dwarf early-type galaxies (ETGs) display a rich diversity in their photometric, structural, and dynamical properties. In this work, we address their structural complexity by studying with deep imaging a sample of nine dwarf ETGs from the Virgo galaxy cluster, characterized by having faint disk features such as bars and spiral arms, that lie mostly hidden within the bright diffuse light of the galaxies. We present a new, robust method that aims to identify and extract the disk substructure embedded in these dwarf ETGs. The method consists in an iterative procedure that gradually separates a galaxy image into two components: the bright, dominant, diffuse component, and the much fainter, underlying disk component. By applying it to the dwarf ETG sample, we quantify their disk substructure and find that its relative contribution to the total galaxy light ranges between 2.2% and 6.4% within two effective radii. We test the reliability of the method, and prove that it is accurate in recovering the disk substructure we introduce in mock galaxy images, even at low disk-to-total light fractions of a few percent. As a potential application of the method, we perform a Fourier analysis on the extracted disk substructures and measure the orientation, length, and strength of the bars, as well as the pitch angle and strength of the spiral arms. We also briefly discuss a scenario based on the numerical simulations presented in our companion paper, Brought to Light II: Smith et al., in which we investigate the origins of the substructure in such dwarf systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Construction of a Cosmic Ray Telescope for the hpDIRC Radiators at the Electron Ion Collider

Nuclear physics pertains to the understanding of the structure and dynamics of the nuclei of atoms, accounting for almost all of the visible matter in the universe. The future Electron-Ion Collider (EIC) will play a crucial role in discovering new laws of Nuclear physics. A pivotal aspect of the EIC is exceptional particle identification (PID). Identifying charged hadrons in their final state can be done with special types of Cherenkov Detectors. One type of detector utilizes the Detection of Internally Reflected Cherenkov radiation (DIRC) phenomena. Able to provide precise PID separation up to relatively high momenta, DIRC radiators, made of synthetic fused silica, produce Cherenkov radiation when hit by high energy electromagnetically charged particles. In this thesis we present details of the construction of a cosmic ray telescope (CRT) to utilize high energy muons from cosmic rays to test DIRC radiators. These types of radiators will be used for the high-performance DIRC (hpDIRC) to be used in the ePIC detector in the future EIC. We go into detail on the DIRC process and the individual pieces of hardware required to make the CRT. Lots of labor was used for certain parts of the CRT, specifically the construction of a dark box for the DIRC radiators. The CRT construction and implementation of all of its components are planned to be completed before 2025.

Shankman, Nathan↗
DOE OSTI2024

Near wake evolution of a tidal stream turbine due to asymmetric sheared turbulent inflow with different integral length scales

Tidal stream turbines deployed at highly energetic open water sites are subjected to sheared inflow in the rotor plane. The inflow shear is expected to cause asymmetric loading on the rotor blades and affect the downstream wake. In the current study, two different turbulent inflow conditions, static-high shear and dynamic shear, were generated via an active-grid turbulence generator. A 1:20 scaled three-bladed horizontal axis tidal turbine model was tested in those conditions. The results were compared to a quasi-laminar case with no imposed turbulence or shear. The results show that the high shear reduces the average performance, with a drop of up to 16% in the optimal power coefficient. Besides, the shear profiles increase torque fluctuations and induce significant differences in wake hydrodynamics between the high-speed (upper) and low-speed (lower) regions. The large integral length scales further enhance the load fluctuations perceived by the rotor but have a negligible effect on the mean wake field quantities and the wake recovery. The lower half region featured a faster breakdown of tip vortex structure and a rapid drop of swirl number, a phenomenon conjectured to be a consequence of the strong turbulence intensities and Reynolds stresses in the lower half region. Furthermore, the sheared turbulent inflow also results in a very intensive energy redistribution process towards large-scale, low-frequency motions, which is important to the downstream turbines.

16 TIDAL AND WAVE POWER↗
DOE OSTI2016

Smart Novel Semi-Active Tuned Mass Damper for Fixed-Bottom and Floating Offshore Wind (Paper)

The intention of this paper is to present the results of a novel smart semi-active tuned mass damper (SA-TMD), which mitigates unwanted loads for both fixed-bottom and floating offshore wind systems. The paper will focus on the most challenging water depths for both fixed-bottom and floating systems. A close to 38m Monopile and 55m Tension Leg Platform (TLP) will be considered. A technical development and trade-off analysis will be presented comparing the new system with existing passive non-linear TMD (N-TMD) technology and semi-active. TheSATMD works passively and activates itself with low power source under unwanted dynamic loading in less than 60msec. It is composed of both variable stiffness and damping elements coupled to a central pendulum mass. The analysis has been done numerically in both FAST(NREL) and Orcaflex (Orcina), and integrated in the Wind Turbine system employing CAD/CAE. The results of this work will pave the way for experimental testing to complete the technology qualification process. The load reductions under extreme and fatigue cases reach up significant levels at tower base, consequently reducing LCOE for fixed-bottom to floating wind solutions. The nacelle acceleration is reduced substantially under severe random wind and sea states, reducing the risks of failure of electromechanical components and blades at the rotor nacelle assembly. The SA-TMD system isa new technology that has not been applied previously in wind solutions. Structural damping devices aim to increase offshore wind turbine system robustness and reliability, which eases multiple substructures installations and global stability.

17 WIND ENERGY↗
DOE OSTI2021

Sulfur-doped graphene anchoring of ultrafine Au 25 nanoclusters for electrocatalysis

The biggest challenge of exploring the catalytic properties of under-coordinated nanoclusters is the issue of stability. We demonstrate herein that chemical dopants on sulfur-doped graphene (S-G) can be utilized to stabilize ultrafine (sub-2 nm) Au 25 (PET)18 clusters to enable stable nitrogen reduction reaction (NRR) without significant structural degradation. The Au 25 @S-G exhibits an ammonia yield rate of 27.5μgNH 3 ∙ mg Au -1 ∙ h -1 at -0.5 V with faradic efficiency of 2.3%. More importantly, the anchored clusters preserve ~ 80% NRR activity after four days of continuous operation, a significant improvement over the 15% remaining ammonia production rate for clusters loaded on undoped graphene tested under the same conditions. Isotope labeling experiments confirmed the ammonia was a direct reaction product of N 2 feeding gas instead of other chemical contaminations. Ex-situ X-ray photoelectron spectroscopy and X-ray absorption near-edge spectroscopy of post-reaction catalysts reveal that the sulfur dopant plays a critical role in stabilizing the chemical state and coordination environment of Au atoms in clusters. Further ReaxFF molecular dynamics (RMD) simulation confirmed the strong interaction between Au nanoclusters (NCs) and S-G. Furthermore, this substrate-anchoring process could serve as an effective strategy to study ultrafine nanoclusters’ electrocatalytic behavior while minimizing the destruction of the under-coordinated surface motif under harsh electrochemical reaction conditions.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

An AFM Dynamic Contact Model with Finite Thickness Correction to Study Micro-Rheology of Biological Cells

One of the major sources of error in Atomic Force Microscopy based Force Spectroscopic studies is bottom substrate effect, which comes due to assumption of infinite sample thickness. In the present work, anew experimentally validated mathematical correction for finite thickness of thesample is incorporated into a dynamic indentation model. This model is an extension of Sneddon’s static indentation contact model developed for conical tip indenters by incorporating the tip geometric effects, correction to hydrodynamic drag, viscoelastic nature of the sample and its finite thickness. The new model is applied to extract the viscoelastic properties of primary mesenchymal stem cells (MSC’s) extracted from human bone marrow and HCT-116 aggressive epithelial colorectal cancer cells. The micro-rheological studies indicated the presence of profound influence of infinite thickness assumption depending upon indentation depth and sample thickness at the point of indentation. The present model nullified this error and provided a better estimate of the rheological properties. The tests were conducted over a wide frequency bandwidth (0.5 to 126 Hz) and frequency dependent material properties were analyzed using power law structural damping model. It was found that MSC’s are stiffer and less viscous in nature compared to cancer cells.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2017

The mimetic finite difference method for the Landau–Lifshitz equation

The Landau–Lifshitz equation describes the dynamics of the magnetization inside ferromagnetic materials. This equation is highly nonlinear and has a non-convex constraint (the magnitude of the magnetization is constant) which poses interesting challenges in developing numerical methods. We develop and analyze explicit and implicit mimetic finite difference schemes for this equation. These schemes work on general polytopal meshes which provide enormous flexibility to model magnetic devices with various shapes. A projection on the unit sphere is used to preserve the magnitude of the magnetization. We also provide a proof that shows the exchange energy is decreasing in certain conditions. The developed schemes are tested on general meshes that include distorted and randomized meshes. As a result, the numerical experiments include a test proposed by the National Institute of Standard and Technology and a test showing formation of domain wall structures in a thin film.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

A sharp interface Lagrangian-Eulerian method for flexible-body fluid-structure interaction

This paper introduces a sharp-interface approach to simulating fluid-structure interaction (FSI) involving flexible bodies described by general nonlinear material models and across a broad range of mass density ratios. This new flexible-body immersed Lagrangian-Eulerian (ILE) scheme extends our prior work on integrating partitioned and immersed approaches to rigid-body FSI. Our numerical approach incorporates the geometrical and domain solution flexibility of the immersed boundary (IB) method with an accuracy comparable to body-fitted approaches that sharply resolve flows and stresses up to the fluid-structure interface. Unlike many IB methods, our ILE formulation uses distinct momentum equations for the fluid and solid subregions with a Dirichlet-Neumann coupling strategy that connects fluid and solid subproblems through simple interface conditions. As in earlier work, we use approximate Lagrange multiplier forces to treat the kinematic interface conditions along the fluid-structure interface. This penalty approach simplifies the linear solvers needed by our formulation by introducing two representations of the fluid-structure interface, one that moves with the fluid and another that moves with the structure, that are connected by stiff springs. This approach also enables the use of multi-rate time stepping, which allows us to use different time step sizes for the fluid and structure subproblems. Our fluid solver relies on an immersed interface method (IIM) for discrete surfaces to impose stress jump conditions along complex interfaces while enabling the use of fast structured-grid solvers for the incompressible Navier-Stokes equations. The dynamics of the volumetric structural mesh are determined using a standard finite element approach to large-deformation nonlinear elasticity via a nearly incompressible solid mechanics formulation. This formulation also readily accommodates compressible structures with a constant total volume, and it can handle fully compressible solid structures for cases in which at least part of the solid boundary does not contact the incompressible fluid. Selected grid convergence studies demonstrate second-order convergence in volume conservation and in the pointwise discrepancies between corresponding positions of the two interface representations as well as between first and second-order convergence in the structural displacements. The time stepping scheme is also demonstrated to yield second-order convergence. To assess and validate the robustness and accuracy of the new algorithm, comparisons are made with computational and experimental FSI benchmarks. Test cases include both smooth and sharp geometries in various flow conditions. Furthermore, we also demonstrate the capabilities of this methodology by applying it to model the transport and capture of a geometrically realistic, deformable blood clot in an inferior vena cava filter.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Development of a Filtered CFD-DEM Drag Model with Multiscale Markers Using an Artificial Neural Network and Nonlinear Regression

Here, the accuracy of coarse-grained Euler-Lagrangian simulations of fluidized beds heavily depends on the mesoscale drag models to account for the influences of the unresolved sub-grid structures. Traditional filtered drag models are regressed with mesoscale markers such as voidage and slip velocities. In this research, a filtered drag was regressed with both mesoscale and macro-scale markers using fine grid Computational Fluid Dynamics - Discrete Element Method (CFD-DEM) simulations. The traditional non-linear regression method was compared with machine learning regression using an Artificial Neural Network (ANN) implemented in PyTorch and coupled with MFiX. The new drag showed higher accuracy than the Wen-Yu drag and another filtered drag derived from the two-fluid model. The nonlinear regression shows slightly better results than ANN regression in cases with similar R 2 values. The utilization of the gas inlet velocity as an additional macro-scale marker reduced the errors by up to 55.3% in the tested cases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗