Search NASA⌕ Search

SEARCH · Search NASA

Results for “coarse-grained”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7

Development of a multiphase PIC model for slurry flow modeling

MFIX-Exa is a recently released multiphase CFD code originally developed for the simulation of particle-laden gas-solid flows. Due to its high-performance computing capabilities, MFIX-Exa is an ideal candidate for scale-up studies of slurry reactors, specifically the coarse-grained particle-in-cell (PIC) model with its statistical treatment of the particle phase. Unfortunately, several physical models that were neglected during original development because they are not relevant for high-density ratio gas-solid flows are important in slurry flows where the particle-to-fluid density ratio is near unity. In this preliminary work we focus on the effective (suspension) viscosity. The models of Brinkman (1952), Krieger and Dougherty (1956), and Cheng and Law (2003) are considered. The impact of the effective viscosity model is studied on horizontal pipe flow. The experimental data of Gillies et al. (2002) is used to assess the pressure drop predictions.

Fullmer, William D.↗

Evaluation of Advanced Phased-Array Techniques: Interim Results [Slides]

Report: “Evaluation of Advanced Phased-Array Techniques: Interim Results”, August 2023 ML23216A009, PNNL-34622 Results showed that detection rate drops as microstructures/materials become more complex Standard PA had the highest detection rates overall Detection rates in the CASS-CASS mockups were lowest overall FMC had the most accurate length sizing in the fine-grained WSS mockups. All methods struggled with length sizing in coarse-grained mockups SNR vs method depended on the specimen type SNR was consistently high with standard PA SNR was consistently the lowest with PWI FMC performed best on fine-grained WSS A lack of data received from some Round Robin participants resulted in low statistics for many of the analyses.

42 ENGINEERING↗

Evaluation of Advanced Phased-Array Techniques: Interim Results [Slides]

Report: “Evaluation of Advanced Phased-Array Techniques: Interim Results”, August 2023 ML23216A009, PNNL-34622 Results showed that detection rate drops as microstructures/materials become more complex Standard PA had the highest detection rates overall Detection rates in the CASS-CASS mockups were lowest overall FMC had the most accurate length sizing in the fine-grained WSS mockups. All methods struggled with length sizing in coarse-grained mockups SNR vs method depended on the specimen type SNR was consistently high with standard PA SNR was consistently the lowest with PWI FMC performed best on fine-grained WSS A lack of data received from some Round Robin participants resulted in low statistics for many of the analyses.

42 ENGINEERING↗

Coarse Graining Discrete Element Method Information in Particle-in-Cell Length Scales Using a Machine Learning Approach

This report details the development of a machine learning (ML)-driven framework to coarse-grain inter-particle collision dynamics from high-fidelity Discrete Element Method (DEM) simulations to Particle-in-Cell (PIC) scales for gas-solid systems. Traditional PIC models, while computationally efficient, rely on empirical granular stress formulations that fail to capture the full complexity of collision physics, particularly the heterogeneity in particle dynamics. This study adopts a bottom-up approach, integrating insights from DEM simulations to improve the physical fidelity and interpretability of PIC-scale models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Expedition UT-GOM2-2 Site H

Pressure and conventional cores were collected at Site H of the Walker Ridge Protracted Area Block 313 in the Terrebonne Basin, deepwater Gulf of America (Gulf of Mexico) during the University of Texas (UT) Deepwater Hydrate Coring Expedition (UT-GOM2-2). Pressure and conventional cores were collected continuously to a depth of 155.1 meters below the seafloor (mbsf). At deeper depths, cores were taken periodically from hydrate-bearing sands and their bounding muds to a total depth of 861.3 mbsf. 162.6 m of conventional core and 54.8 m of pressure core were recovered. Twelve temperature measurements were made between 27.1 and 144.5 mbsf to determine the geothermal gradient. At the seafloor, more than 4 m of sandy silt of unknown origin was encountered. Beneath this sand, to a depth of about 200 mbsf, the section was composed of interbedded mud and biogenic carbonate ooze. The ooze correlated to low density and high porosity intervals observed in the previously acquired logging while drilling (LWD) data and as measured. These ooze intervals also correspond to lighter sediment color, increased Ca content based on X-ray florescence (XRF) core scanning, and increased calcareous nannofossil abundance. Calcareous nannofossil biostratigraphy constrains the entire record to the Pleistocene (< 0.91 million years), with a pronounced increase in sedimentation rate with depth. Below 200 mbsf, the section was predominantly composed of mud with two thicker, hydrate-bearing coarse-grained intervals, which are commonly known as the Blue and Orange sands. The dissolved gas concentration was quantified from pressure cores. In the shallow section, dissolved methane concentration increased below the sulfate-methane transition zone (SMTZ) and reaches saturation (the limit of solubility for methane) at 147 mbsf. Gas expansion was very common in conventional and depressurized pressure (conventionalized) cores below the SMTZ. At deeper depths, the methane concentration within muds bounding the Blue and Orange reservoirs was generally found to be less than saturation. The dissolved and hydrate gas composition is consistent with a microbial source, containing greater than 99.99% methane and only trace concentrations of ethane, propane, and butane. The methane to ethane ratio (C1 /C2 ) and the methane to ethane plus propane (C1 /(C2 +C3 )) decrease with depth down to at least 678 mbsf, mainly driven by the increase in ethane with depth. It is unclear if this trend continues through the Orange sand interval. The δ13C isotopic signature of methane ranges between -69.9 and -78.5 ‰ relative to the Vienna Pee Dee Belemnite (VPDB) standard. Pressure core recovery in sandy intervals was poor. However, pressure core logs of the Orange sand show intervals of low density and high velocity, which are indicative of high hydrate saturation. One pressure core was degassed and the average hydrate saturation in the core was determined to be 24%. One core from within the Orange sand was composed of interbedded graded sandy silt and mud. The sandy silts from this core are composed of mainly quartz and feldspar with some lithics. Most of the recovered pressure core samples are maintained at near in-situ pressure and temperature (within the hydrate stability field) at the University of Texas Pressure Core Center awaiting analysis. In the shallow section, samples will be used to determine the flux of organic carbon through the basin system, find the rate at which that carbon was consumed, and understand the microbial population responsible for these processes. In the deeper section, samples from in and around the hydrate reservoirs will be used to determine the petrophysical properties of the reservoir and bounding seals in these systems.

03 NATURAL GAS↗

Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials: Part II Resveratrol Exemplar

This SAND report summarizes work supported by an Engineering Sciences Research Foundation (ESRF) Lab Directed Research and Development (LDRD) project entitled “Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials.” This SAND report is written in two parts with Part 1 discusses recrystallization of our explosive exemplar and Part 2 summarizing our work with recrystallization of resveratrol. We have studied resveratrol recrystallization with a multiscale approach combining experiments, modeling and simulation. At the single crystal scale, microscopy experiments illuminate crystal time-dependent growth rates using advanced image analysis. Bench scale experiments were carried out to look at growth of multiple particles in a small reactor creating thousands of particles and analyzing the results with microscopy and μCT. For the modeling we combine kinetic Monte Carlo (kMC) models with subscale information from density functional theory (DFT) or molecular dynamics. This work is discussed in Part 1 and can also be found in a paper from the project discussing a coarse-grained kMC model specifically developed for resveratrol. For well-mixed systems, we have population balance equations (PBE) linked with species mass conservation forming a set of ordinary differential equations that can be solved quickly. For more complicated geometries, such as the vat crystallization used throughout the complex, a coupled computational fluid dynamic (CFD)/PBE method was developed to account for gradients in temperature and concentration and differences in crystallization rates throughout the domain. These simulations are more complex and require high performance computing. We present results for two cases: 5% seed fast cool with parameters fit to the well-mixed case and 5% seed slow cool using the same parameters. We show reasonable agreement with experiments though are particles are significantly larger than the experiments.

36 MATERIALS SCIENCE↗

Why Seeding Works When Nucleation Barriers Vanish

This paper explains why seeds can speed up crystallization even when the formation of new crystal nuclei is not the slow step. In zeolite synthesis, local crystalline order can form relatively early, but the material may still appear poorly crystalline by X-ray diffraction because many small crystallites are misoriented and lack long-range coherence. Using coarse-grained molecular simulations, the study showed that seeds help solve this coherence problem. Rather than primarily lowering a nucleation barrier, seeds impose a common orientation on nearby growing crystallites, allowing them to merge into larger, better aligned domains. This accelerates the development of X-ray-detectable crystallinity even if the total amount of locally ordered material has not changed much. The work changes how induction times in zeolite synthesis should be interpreted: the delay before X-ray crystallinity appears can reflect the time needed to build long-range structural coherence, not simply the time needed to form crystalline material. This provides a new explanation for why seeding is effective in growth-limited crystallization and offers design principles for controlling crystallization rate and crystal quality.

36 MATERIALS SCIENCE↗

Evidence for carbon dioxide removal via enhanced rock weathering with steel slag, though not basalt, in a midwestern U.S. field trial

Enhanced weathering is an emergent pathway for permanent atmospheric carbon dioxide removal (CDR). However, despite a dramatic increase in academic and commercial research, there remain relatively few published examples of field evidence demonstrating the effectiveness of enhanced weathering. Here, we present results from a three-year field trial that evaluated steel slag and crushed basalt applied as amendments in a conventional agricultural system in the Midwestern United States. Steel slag applied to initially acidic soil increased porewater pH and alkalinity and increased soil pH and Ca-saturation. Together, changes in porewater chemistry and soil properties provide strong evidence for steel slag weathering and CDR. However, steel slag applied to soils with a neutral initial pH did not generate significant changes in soil or porewater chemistry. In addition, coarse-grained crushed basalt did not generate significant change in any of the soils. Strong acid effects were apparent in all 3 years of monitoring soil porewater chemistry. Overall, our results demonstrate clear evidence of CDR from applying steel slag amendments to acidic cropland soils while also highlighting the difficulty of greenhouse gas reduction accounting from enhanced weathering and the variable outcomes that can occur depending on feedstock and soil type.

Geosciences↗

Unconventional compute methods and future challenges for superconducting digital computing

Superconducting digital computing (SDC) based on Josephson junctions (JJs) offers significant potential for enhancing compute throughput and reducing energy consumption compared to conventional room-temperature CMOS-based approaches. Current superconducting logic families exhibit diverse characteristics in clocking strategies, power management, and information encoding techniques. This paper reviews recent advancements in unconventional computing methods specifically designed for superconducting digital circuits, emphasizing temporal computing and pulse-train representations. Notable techniques include race logic (RL), temporal pulse train computing (U-SFQ), and temporal multipliers, each offering unique performance and area advantages suited to superconducting implementations. Additionally, this paper reviews innovations in superconducting coarse-grain reconfigurable architectures (CGRA), superconducting-specific on-chip communication architectures, cryogenic sensor interfaces, and quantum computing control electronics. Finally, we highlight research challenges that should be addressed to facilitate the widespread adoption of superconducting digital computing.

EDA tools↗

Closed-loop control of active nematic flows

Stabilizing and shaping autonomous flows of active fluids is a fundamental challenge and a prerequisite for applications. We embed a light-responsive microtubule-based nematic in a proportional-integral control loop that adjusts the applied light intensity in response to real-time measurements of the spatially averaged flow speed. The self-regulating hardware/software/wetware system maintains a target flow speed against external or internal perturbations, including protein aging and aggregation, sample-to-sample variability, and temperature variation. Varying the controller’s gains reveals antagonistic roles between feedback and intrinsic processes, leading to nontrivial dynamics observed in fluctuation spectra. In particular, oscillations emerge from the interplay between the controller, motor binding kinetics, and active hydrodynamic relaxation. Accounting for the underlying binding timescale, our coarse-grained model and nematohydrodynamics simulations corroborate these observations. This work provides insight into the coupled dynamics of controlled active matter, laying the foundation for spatiotemporal patterning of active stress to generate and stabilize new dynamical configurations.

Nishiyama, Katsu [Brandeis Univ., Waltham, MA (Uni↗

The Baby Universe is Fine and the CFT Knows It: On Holography for Closed Universes

Big bang/big crunch closed universes can be realized in AdS/CFT, even though they lack asymptotically AdS boundaries. With enough bulk entanglement, the bulk Hilbert space of a closed universe can be holographically encoded in the CFT. We clarify the relation of this encoding to observer-clone proposals and refute recent arguments about the breakdown of semiclassical physics in such spaces. In the limit of no bulk entanglement, the holographic encoding breaks down. The oft-cited one-dimensional nature of the closed universe Hilbert space represents the limitation of the external (CFT) Hilbert space to access the quantum information in the closed universe, similar to the limitations imposed on observers outside a perfectly isolated quantum lab. We advocate that the CFT nevertheless continues to determine the physical properties of the closed universe in this regime, showing how to interpret this relationship in terms of a final state projection in the closed universe. We provide a dictionary between the final state wavefunction and CFT data. We propose a model of the emergence of an arrow of time in the universe with a given initial or final state projection. Finally, we show that the conventional EFT in the closed universe, without any projection, can be recovered as a maximally ignorant description of the final state. This conventional EFT is encoded in CFT data, and it can be probed by computing coarse-grained observables. We provide an example of one such observable. Taken together, these results amount to a clean bill of health for baby universes born of AdS/CFT.

FOS: Physical sciences↗

Holographic codes and bulk RG flows

We consider the coarse-graining of holographic quantum error correcting codes under a generalized notion of bulk renormalization-group flow. In particular, we study the renormalization under this flow of the $A/4G$ term in the Faulkner-Lewkowycz-Maldacena formula and in its Rényi generalization. This provides a general quantum code perspective on the arguments of Susskind and Uglum. Specifically, given a 'UV' code with two-sided recovery and appropriately flat entanglement spectrum together with a set of 'seed' states in the UV code, we explicitly construct an 'IR' code with corresponding properties which contains the given seed states and is of minimal size in a sense we describe.

FOS: Physical sciences↗

Equation-Free Coarse Control of Distributed Parameter Systems via Local Neural Operators

The control of high-dimensional distributed parameter systems (DPS) remains a challenge when explicit coarse-grained equations are unavailable. Classical equation-free (EF) approaches rely on fine-scale simulators treated as black-box timesteppers. However, repeated simulations for steady-state computation, linearization, and control design are often computationally prohibitive, or the microscopic timestepper may not even be available, leaving us with data as the only resource. We propose a data-driven alternative that uses local neural operators, trained on spatiotemporal microscopic/mesoscopic data, to obtain efficient short-time solution operators. These surrogates are employed within Krylov subspace methods to compute coarse steady and unsteady-states, while also providing Jacobian information in a matrix-free manner. Krylov-Arnoldi iterations then approximate the dominant eigenspectrum, yielding reduced models that capture the open-loop slow dynamics without explicit Jacobian assembly. Both discrete-time Linear Quadratic Regulator (dLQR) and pole-placement (PP) controllers are based on this reduced system and lifted back to the full nonlinear dynamics, thereby closing the feedback loop.

93B52, 93C20, 47N70, 65J15, 65M32, 68T07, 68T20, 6↗

Operationally induced preferred basis in unitary quantum mechanics

The preferred-basis problem and the definite-outcome aspect of the measurement problem persist even if the detector is modeled unitarily, because experimental data are necessarily represented in a Boolean event algebra of mutually exclusive records whereas the theoretical description is naturally formulated in a noncommutative operator algebra with continuous unitary symmetry. This change of mathematical type constitutes the core of the 'cut': a structurally necessary interface from group-based kinematics to set-based counting. In the presented view the basis relevant for recorded outcomes is not determined by the system Hamiltonian alone; it is induced by the measurement mapping, i.e., by the detector channel together with the coarse-grained readout that defines an instrument. The probabilistic mapping is anchored in symmetry and measure theory: by Gleason-type uniqueness (Gleason for projections in $d>2$ and Busch's extension for Positive Operator-Valued Measures (POVMs) including $d=2$), the trace rule is the unique probability measure consistent with additivity over exclusive events and basis-independence of the unitary sector. A compact qubit--pointer model yields an induced unsharp POVM $E_\pm=\tfrac12(\id\pm η\,σ_z)$ with $η$ fixed by pointer resolution, displaying explicitly how the detector induces the relevant basis. Finally, nested-observer paradoxes are tightened into a non-composability lemma: joint assignment of outcome propositions is obstructed unless a joint instrument exists. This relocates the origin of randomness to the stochasticity of the transition rules.

Pronskikh, Vitaly [Fermilab] (ORCID:00000002518174↗

Explaining word embeddings with perfect fidelity: a case study in predicting research impact

The best-performing approaches for scholarly document quality prediction are based on embedding models. In addition to their performance when used in classifiers, embedding models can also provide predictions even for words that were not contained in the labelled training data for the classification model, which is important in the context of the ever-evolving research terminology. Although model-agnostic explanation methods, such as Local interpretable model-agnostic explanations, can be applied to explain machine learning classifiers trained on embedding models, these produce results with questionable correspondence to the model. We introduce a new feature importance method, Self-Model Entities Rated (SMER), for logistic regression-based classification models trained on word embeddings. We show that SMER has theoretically perfect fidelity with the explained model, as the average of logits of SMER scores for individual words (SMER explanation) exactly corresponds to the logit of the prediction of the explained model. Quantitative and qualitative evaluation is performed through five diverse experiments conducted on 50,000 research articles (papers) from the CORD-19 corpus. In conclusion, through an AOPC curve analysis, we experimentally demonstrate that SMER produces better explanations than LIME, SHAP and global tree surrogates.

Coarse-grained models↗

Reversible Physical Gelation of Thermotropic Liquid Crystals Driven by Nanoplate Self-Assembly

Physically gelled soft materials, driven by the self-assembly of low-molecular-mass gelators (LMGs), have emerged as a platform for designing advanced gels that exhibit reversible gelation and property tunability. Liquid crystal (LC) gels are of great interest due to their supramolecular orderings as gel hosts and their enhanced electro-optical properties. In this study, we demonstrate the physical gelation of a nematic LC driven by nanoplate self-assembly, expanding the concept of gelators from small molecules to nanoparticles. These nanoplates are functionalized with promesogenic ligands and form a fibrillar network in LCs with face-to-face interplate stacking, resembling LMGs. The critical gelation volume fraction in the tilt test is only 0.14 v %, comparable to values reported for LMGs. Rheological analyses confirm viscoelastic properties characteristic of gelation. In situ small-angle X-ray scattering (SAXS) characterizes the formation of nanoplate networks in the LC with decreasing temperature, wherein LC mesogens become trapped in pores. Molecular dynamics (MD) simulations reveal that the interaction between ligand-coated nanoplates and LC-forming mesogens induces a multidomain LC structure, increasing friction between LC domains and stabilizing the gel. This study establishes direct relationships among molecular interactions, nanostructures, and mechanical properties in physically gelled LCs. In conclusion, the findings inspire the future gelator design of both LMGs and nanoplates, with potential applicability in bioscaffold engineering and liquid crystalline nanocomposites.

36 MATERIALS SCIENCE↗

Anomalous softening of 3D printed elastomeric foam irradiated under compressive strain

Elastomeric foam is an essential component in many industrial and technological settings, primarily as thermal insulators and as positional/mechanical support cushions. In particular, silicone foam is utilized in harsh environments due to exceptional thermal and chemical stability. Under service conditions within certain applications such material gets exposed to a high dosage of gamma radiation, which can permanently alter the material’s structural and mechanical response properties. Most studies on gamma-exposure under inert or oxidative atmosphere indicate hardening of silicone foam, which is attributed to radiation-induced enhancement in chemical cross-linking. Here we report two contrasting effects depending on whether (non-oxidative) radiation exposure is carried out with the foam under zero or finite compressive strain. While in the former case we observe radiation-hardening consistent with previous studies, in the latter case (50% porous foam under 30% uniaxial compression) we see a monotonic decrease in Young’s modulus with increasing dosage, although solvent swelling experiments on the constituent rubber indicate a net increase in cross-link density independent of the state of strain. We quantitatively model all dose-dependent data using the Ogden Hyperfoam strain-energy function within the framework of Tobolsky two-network scheme and attribute the above anomaly to a combined effect of radiation-induced thickness change (compression set) and inherent nonlinearity in the foam’s stress-strain response.

Coarse-grained models↗