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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 109 records · Page 6

Microscale Mechanical‐Chemical Modeling of Granular Salt: Insights for Creep

Abstract Microscale numerical modeling is potentially an effective approach for understanding salt creep, but it is quite challenging because natural salt grain boundaries can have complex and evolving geometry, and because contacts between these deformable salt mineral grains are dynamic as a result of compaction, chemical reaction, fluid flow, and heat transfer. In this study, we have overcome these challenges and developed a new microscale mechanical‐chemical (MC) model to analyze creep of salt at the microscale, accounting for coupled deformation, dynamic contacts, and chemical reaction in granular systems with realistic geometric representations. The MC model was realized by linking a new microscale mechanical code based on the numerical manifold method (NMM) to a reactive transport code named Crunch. We simulated the processes of reorganization of the salt grains, microfracturing, and pressure solution that contribute to creep at larger scales. Based on this first quantitative microscale model, we found that sharp corners of mineral grains can dominate the contact dynamics, microfracturing, and pressure solution when salt is compacted, thus governing the structural changes and porosity loss of the system. We found that pressure solution, which preferentially dissolves sharp corners and edges, can lead to relatively high porosity loss in the system, thus playing an important role in the creep of salt. Our analysis shows that the dynamic changes of salt granular systems involving grain relocation and pressure solution can occur repeatedly and continuously, thus contributing to longer‐term creep of salt at larger scales.

58 GEOSCIENCES↗

A proposed origin for palimpsests and anomalous pit craters on Ganymede and Callisto

The hypothesis that palimpsests and anomalous pit craters are essentially pristine crater forms derived from high-velocity impacts and/or impacts into an ice crust with preimpact temperatures near melting is explored. The observational data are briefly reviewed, and an impact model is proposed for the direct formation of a palimpsest from an impact when the modification flow which produces the final crater is dominated by 'wet' fluid flow, as opposed to the 'dry' granular flow which produces normal craters. Conditions of 'wet' modification occur when the volume of impact melt remaining in the transient crater attains a volume comparable to the transient crater. The normal crater-palimpsest transition is found to occur for sufficiently large impacts or sufficiently fast impactors. The range of crater diameters and morphological characteristics inferred from the impact model is consistent with the observed characteristics of palimpsests and anomalous pit craters.

Croft, S. K.↗

Correction to: Investigating the rheology of fluidized and non-fluidized gas-particle beds: implications for the dynamics of geophysical flows and substrate entrainment

We report natural geophysical mass flows are among the most complex granular systems and their dynamics are often modified by the presence of an interstitial fluid. Prediction of their runout requires the development of models estimating the solid stresses in these hazardous currents wherein excess pore-fluid pressure can develop. We use discrete element modelling (DEM-CFD) with a Coarse-Graining post-processing technique (CG) to investigate the rheology of unsteady gas-particle fluidized to non-fluidized granular beds placed on horizontal and inclined planes. Similar to fluidized beds immersed in viscous fluids, the effective friction coefficient of air-fluidized beds can be defined as a function of the classic μ(I)-rheology and the non-dimensional fluid or solid pressure to explain the failure and dynamics of granular flows with excess pore pressure on inclines. However, dilation imposed by fluid drag and particle collisions in gas-particle fluidized beds can drastically change its effective frictional properties. In contrast with the common assumption in water-particle flows that granular temperature is negligible, in our gas-particle simulations, the contribution of the velocity fluctuations to the stress tensor is significant. Hence, the shear stress is found to be non-zero even when the flow is fully fluidized in the inertial regime. These results suggest the need to better understand velocity fluctuations to predict the effective viscosity of sheared fluidized mixtures and are relevant for many applications. Notably, a unified approach is useful for many geophysical flows that encompass a range of fluidization conditions in a single flow such as pyroclastic density currents and snow avalanches.

58 GEOSCIENCES↗

LC-Opt: Benchmarking Reinforcement Learning and Agentic AI for End-to-End Liquid Cooling Optimization in Data Centers

Liquid cooling is critical for thermal management in high-density data centers with the rising AI workloads. However, machine learning-based controllers are essential to unlock greater energy efficiency and reliability, promoting sustainability. We present LC-Opt, a Sustainable Liquid Cooling (LC) benchmark environment, for reinforcement learning (RL) control strategies in energy-efficient liquid cooling of high-performance computing (HPC) systems. Built on the baseline of a high-fidelity digital twin of Oak Ridge National Lab's Frontier Supercomputer cooling system, LC-Opt provides detailed Modelica-based end-to-end models spanning site-level cooling towers to data center cabinets and server blade groups. RL agents optimize critical thermal controls like liquid supply temperature, flow rate, and granular valve actuation at the IT cabinet level, as well as cooling tower (CT) setpoints through a Gymnasium interface, with dynamic changes in workloads. This environment creates a multi-objective real-time optimization challenge balancing local thermal regulation and global energy efficiency, and also supports additional components like a heat recovery unit (HRU). We benchmark centralized and decentralized multi-agent RL approaches, demonstrate policy distillation into decision and regression trees for interpretable control, and explore LLM-based methods that explain control actions in natural language through an agentic mesh architecture designed to foster user trust and simplify system management. LC-Opt democratizes access to detailed, customizable liquid cooling models, enabling the ML community, operators, and vendors to develop sustainable data center liquid cooling control solutions.

Naug, Avisek [Hewlett Packard Enterprise]↗

Cooperative Merging via Online Speed Replanning: A Model-Free Approach With Vehicle-to-Vehicle Communication Packet Drop Compensation

On-ramp merging is a critical bottleneck in freeway traffic flow, contributing to congestion, accidents, and excessive fuel consumption. Although traditional ramp metering provides macroscopic control, it lacks the granularity for optimizing an individual vehicle’s trajectory. Cooperative merging, enabled by connected and automated vehicles, can potentially enhance traffic efficiency, safety, and fuel economy. However, existing research often neglects the influence of heterogeneous vehicle dynamics, unreliable vehicle-to-vehicle (V2V) communication, and real-time implementation challenges. Here, this paper introduces novel model-free online speed planners for cooperative on-ramp merging. The planners address these limitations by being agnostic to vehicle dynamics, effectively compensating for V2V communication packet drops and incurring only a light computational burden. Comprehensive evaluation, conducted on a real-time traffic-vehicle-communication co-simulation platform integrating high-fidelity vehicle dynamics, a traffic simulator, and recorded V2V communication footprints, demonstrates the effectiveness of the proposed speed planners. Simulation results reveal that the proposed method yields accurate tracking of desired speed and inter-vehicle distance, maintaining low fuel consumption even under high packet drop ratios, and demonstrating real-time implementation efficiency.

Wang, Zejiang [Univ. of Texas at Dallas, Richardso↗

An Open-Source Framework for the Computational Analysis and Design of Autothermal Chemical Processes

The main project object was to develop software tools for simulating non-equilibrium autothermal processes, improving the prospects for identifying and designing such systems. The project demonstrates the use of these tools to simulate autothermal pyrolysis, a process recently developed at the pilot-plant scale at Iowa State University. In such process, instead of externally heating a reactor to pro-vide the enthalpy of pyrolysis, sufficient oxygen in the form of air is introduced into the reactor to support partial oxidation of reactants and products with the exothermic energy released supporting endothermic pyrolysis reactions. A fluidized bed is used to assure good mixing of biomass and oxidant and provide an isothermal reaction environment. The amount of oxygen required depends upon the kind of biomass being pyrolyzed and parasitic heat losses from the reactor. For example, for woody biomass pyrolyzed under conditions that simulate adiabatic operation, equivalence ratios can be as low as 0.06, compared to 0.20 or higher for autothermal gasifiers. By removing the heat transfer bottleneck of conventional pyrolysis, operation in autothermal mode allowed a significant increase in reactor throughput process, approaching five times the throughput of the conventionally operated pyrolyzer. Different simulation strategies were considered and developed: a zero-dimensional chemistry model was used to verify the applicability of kinetic schemes to predict biomass fast pyrolysis in autothermal conditions. Conventional chemical reactor models such as the plug flow reactor and the partially stirred reactor were used to investigate the role of mixing in the fluidized bed pyrolyzer and to establish the impact of mixing time on the gas-phase reactions. A comprehensive multiphase computational fluid dynamics (mCFD) framework, including polydisperse granular phase modeling and detailed chemical kinetics was formulated and used to model the experimental setup for autothermal biomass fast pyrolysis at ISU. Multiphase CFD was also used to investigate the role of biomass feed positioning on the mixing of biomass in the pyrolizer. Finally, a reduced order model (ROM), suitable to be implemented in process simulators was obtained. Both the mCFD and the ROM were validated against experiments.

09 BIOMASS FUELS↗

pnnl/OpenCGRA

OpenCGRA is an open-source framework for modeling, testing, and evaluating CGRAs. The first open-source integrated framework able to support the full top-to-bottom design flow for specializing and implementing CGRAs: modeling at different abstraction levels (functional level, cycle level, register-transfer level) with compiler support, verification at different granularities (unit testing, integration testing, property-based testing), simulation, generation of synthesizable Verilog, and characterization (area, power, and timing).

Cheng, Tan↗

OpenCGRA: An Open-Source Unified Framework for Modeling,Testing, and Evaluating CGRAs

Coarse-grained reconfigurable arrays (CGRAs),loosely defined as arrays of functional units (e.g, adder, sub-tractor, multiplier, divider, or larger multi-operation units, butsmaller than a general-purpose core) interconnected through aNetwork-on-Chip, provide higher flexibility than domain-specificASIC accelerators while offering increased hardware efficiencywith respect to fine-grained reconfigurable devices, such as FieldProgrammable Gate Arrays (FPGAs). The fast evolving fieldsof machine learning and edge computing, which are seeing acontinuous flow of novel algorithms and larger models, makeCGRAs ideal target architectures to allow domain specializationwithout loosing too much generality. They also generally offerquicker and more effective reconfigurability than FPGAs, po-tentially allowing adaptation during actual algorithm execution,and implement a dataflow programming paradigm that adaptswell to these emerging workloads. Designing and generating aCGRA, however, still requires to define the type and number ofthe specific functional units, implement their interconnect andthe network topology, and perform its simulation and validation,given a variety of workloads of interest.In this paper, we propose OpenCGRA, a Python-based unifiedframework that integrates generation, modeling, testing and eval-uation for CGRAs. OpenCGRA is the first open-source integratedframework able to support the full top-to-bottom design flow forspecializing and implementing CGRAs: modeling at different ab-straction levels (functional level, cycle level, register-transfer level),generation, simulation, testing at different granularities (unit test-ing, integration testing, property-based testing), and characteriza-tion (area, power, and timing). OpenCGRAs will be made availableon GitHub.

CGRA, synthesis↗

Impact of Janssen effect on thermal transport in granular flow

Using a modulated photothermal radiometry (MPR) technique capable of measuring thermal transport in particle beds, we find asymptotically increasing effective thermal conductivity and decreasing near-wall thermal resistance along gravity-driven downward granular flows through a 1-meter-long narrow vertical channel owing to the Janssen effect. The Janssen effect is confirmed by similar asymptotic trends from particle bed apparent mass measurements as well as separate MPR heat transfer measurements on stationary particle beds under compression at different heights of the channel with and without pressure screening. Furthermore, local heat transfer coefficient along the 1-meter-long channel was modeled based on measured spatially resolved thermal conductivity and near-wall thermal resistance due to the Janssen effect. This work reveals for the first time the impact of the over century-old Janssen effect on heat transfer in granular media. Furthermore, the results from this work can lead to a better understanding of heat transfer in granular flow.

14 SOLAR ENERGY↗

Discrete-Element and Material-Point Method (DEM and MPM) Based Solvers for Sustainable Technologies

We present the use of discrete element method (DEM) and material point method (MPM) in three relevant green technology applications that include biomass feedstock handling, lithium-ion battery manufacturing, and high-pressure reverse osmosis. Our open-source DEM and MPM solvers are developed using performance portable grid and particle management library, AMReX, thus enabling superior performance on NVIDIA and AMD GPUs with > 100 million particles. Our DEM solver resolves the motion of individual particles in a granular system and includes a bonded sphere method for modeling non-spherical particles along with Hertzian and liquid bridge-based contact models. We simulate highly variable biomass feedstock flows in large-scale hoppers for biofuel production and electrode calendering in battery manufacturing using DEM. Our simulations predict flow blockage in large scale biomass hoppers and electrode microstructure variations, thus providing valuable information for biofuel and battery manufacturers, respectively. The second half of the talk will be on MPM and its application towards pore resolved simulations of reverse osmosis membranes under compressive loads. We present a validation study of our MPM simulations with membrane microscopy imaging thus providing useful insights on membrane stability under high pressure conditions. We also present a spectral stability analysis of using linear hat, quadratic and cubic spline basis in MPM indicating regions of numerical stability.

BIOMASS FUELS,MATHEMATICS AND COMPUTING↗

Shear Is Not Always Simple: Rate-Dependent Effects of Flow Type on Granular Rheology

we report that despite there being an infinite variety of types of flow, most rheological studies focus on a single type such as simple shear. Using discrete element simulations, we explore bulk granular systems in a wide range of flow types at large strains and characterize invariants of the stress tensor for different inertial numbers and interparticle friction coefficients. We identify a strong dependence on the type of flow, which grows with increasing inertial number or friction. Standard models of yielding, repurposed to describe the dependence of the stress on flow type in steady-state flow and at finite rates, are compared with data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A High-Performance Discrete-Element Framework for Simulating Flow and Jamming of Moisture Bearing Biomass Feedstocks

We developed and verified a high-performance open-source discrete element method (DEM) solver with simultaneously-supported feedstock-specific interaction models, including bonded-sphere, liquid bridge, cohesion, and non-linear contact models. Our solver uses parallel data structures on hybrid central and graphics processing unit (CPU/GPU) architectures, with favorable strong scaling performance observed for large problem sizes comprised of (100 M particles), and 4X single-node GPU speedup. The particles for corn stover feedstock were conceptualized and calibrated based on experimental measurements and results. Sensitivity analyses demonstrate that the mass flow rate from a wedge hopper is governed primarily by moisture content, friction coefficient, and cohesion energy density. The model is used to reproduce experimentally observed hopper jamming results, highlighting that the experimental no-flow trends can only be achieved by using non-spherical particles, liquid bridge and cohesion models, highlighting the importance of using concurrent feedstock specialized models for the effective representation of biomass material handling problems.

bioenergy↗

Using Solid Particles as Heat Transfer Fluid-Use in CSP Plants (CRADA Final Report)

NREL assisted the BRIDGE project led by the University of Colorado (CU), Boulder, on developing granular flow and heat transfer simulation tool to serve for an enclosed particle-receiver design. NREL will provide the particle receiver design configuration and operating condition to assist the model setup and may provide certain testing results for model verifications. NREL will attend project reviewing meeting and provide application back-ground including concentrating solar energy technology to collaborate with CU researchers.

14 SOLAR ENERGY↗

Thermal conductivity of heterogeneous mixtures and lunar soils

The theoretical evaluation of the effective thermal conductivity of granular materials is discussed with emphasis upon the heat transport properties of lunar soil. The following types of models are compared: probabilistic, parallel isotherm, stochastic, lunar, and a model based on nonlinear heat flow system synthesis.

Vachon, R. I.↗

Imaging Spectroscopy of Sunspots using IBIS

We use the Interferometric BIdimensional Spectrometer (IBIS) of the INAF/Arcetri Astrophysical Observatory and installed at the National Solar Observatory (NSO) Dunn Solar Telescope, to understand the structure of sunspots. These high resolution observations were acquired on 2004 July 30-31, of active region NOAA 10654, using the high order NSO adaptive optics system. We map the spatio-temporal variation of the penumbral Doppler signatures in three spectral lines, FeI 6301.5\AA, FeII 7224.4\AA, and CaII 8542.6\AA, from the photosphere to the chromosphere. From a 70-minute temporal average of individual 32-second cadence Doppler observations we find that the averaged velocities decrease with height, about 3.5 times larger in the deeper photosphere (FeII 7224.4\AA; height-of-formation $\approx$\50 km) than in the upper photosphere FeI 6301.5\AA; height-of-formation $\approx$\350 km), There is a remarkable coherence of Doppler signals over the height difference of 300 km. From a highspeed animation of the Doppler sequence we find evidence for what appears to be ejection of high speed gas concentrations from edges of penumbral filaments into the surrounding granular photosphere. The Evershed flow persists a few arcseconds beyond the traditionally demarcated penumbra-granulation boundary. We present these and other results and discuss the implications of these measurements for sunspot models

Balasubramaniam, K. S.↗

3-D Structure of Sunspots using Imaging Spectroscopy

We use the Interferometric BIdimensional Spectrometer (IBIS) of the INAF/Arcetri Astrophysical Observatory and installed at the National Solar Observatory (NSO) Dunn Solar Telescope, to understand the structure of sunspots. Using the spectral lines FeI 6301.5 A, FeII 7224.4 A, and CaII 8542.6 A, we examine the spectroscopic variation of sunspot penumbral and umbral structures at the heights of formation of these lines. These high resolution observations were acquired on 2004 July 30-31, of active region NOAA 10654, using the high order NSO adaptive optics system. We map the spatio-temporal variation of Doppler signatures in these spectral lines, from the photosphere to the chromosphere. From a 70-minute temporal average of individual 32-second cadence Doppler observations we find that the averaged velocities decrease with height, about 3.5 times larger in the deeper photosphere (FeII 7224.4 A; height-of-formation approx. 50 km) than in the upper photosphere FeI 6301.5 A; height-of-formation approx. 350 km), There is a remarkable coherence of Doppler signals over the height difference of 300 km. From a high-speed animation of the Doppler sequence we find evidence for what appears to be ejection of high speed gas concentrations from edges of penumbral filaments into the surrounding granular photosphere. The Evershed flow persists a few arcseconds beyond the traditionally demarcated penumbra-granulation boundary. We present these and other results and discuss the implications of these measurements for sunspot models.

Balasubramaniam, K. S.↗

A Modification and Analysis of Lagrangian Trajectory Modeling and Granular Dynamics of Lunar Dust Particles

A previously developed mathematical model is amended to more accurately incorporate the effects of lift and drag on single dust particles in order to predict their behavior in the wake of high velocity gas flow. The model utilizes output from a CFD or DSMC simulation of exhaust from a rocket nozzle hot gas jet. An extension of the Saffman equation for lift based on the research of McLaughlin (1991) and Mei (1992) is used, while an equation for the Magnus force modeled after the work of Oesterle (1994) and Tsuji et al (1985) is applied. A relationship for drag utilizing a particle shape factor (phi = 0.8) is taken from the work of Haider and Levenspiel (1989) for application to non-spherical particle dynamics. The drag equation is further adjusted to account for rarefaction and compressibility effects in rarefied and high Mach number flows according to the work of Davies (1945) and Loth (2007) respectively. Simulations using a more accurate model with the correction factor (Epsilon = 0.8 in a 20% particle concentration gas flow) given by Richardson and Zaki (1954) and Rowe (1961) show that particles have lower ejection angles than those that were previously calculated. This is more prevalent in smaller particles, which are shown through velocity and trajectory comparison to be more influenced by the flow of the surrounding gas. It is shown that particles are more affected by minor changes to drag forces than larger adjustments to lift forces, demanding a closer analysis of the shape and behavior of lunar dust particles and the composition of the surrounding gas flow.

Long, Jason M.↗

Particle size and shape effect of Crumbler® rotary shear-milled granular woody biomass on the performance of Acrison® screw feeder: A computational and experimental investigation

Physical experiments and discrete element model (DEM) simulations are conducted to evaluate particle characteristics and operation parameter effects on screw feeding performance for rotary shear-milled Douglas fir. Three performance metrics are used: mass flow rate, shaft driving torque, and specific energy consumption. The impact of particle size, particle size distribution (PSD), shaft rotational speed (rpm), and hopper dimensions on the performance are investigated. All employed performance metrics reveal the superior flowability of the 2-mm particles in contrast to the larger 6-mm counterpart. Remarkably, wider PSD results in poorer flowability than the two mono-sized particles, proving the flowability enhancement achieved by narrower PSD of the woody feedstock. More importantly, DEM simulations unveil PSD-induced degradation in flowability is attributed to mechanical interlocking and particle segregation effects. Furthermore, higher shaft rpm causes higher mass flow rate at the cost of higher specific energy consumption due to viscous dissipation and changes in flow pattern.

09 BIOMASS FUELS↗