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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Numerical investigation of a fueled pre-chamber spark-ignition natural gas engine

Pre-chamber spark-ignition (PCSI) is a leading advanced ignition concept for internal combustion engines with the potential to enable diesel-like efficiency in medium-duty/heavy-duty (MD/HD) natural gas (NG) engines. By leveraging distributed ignition sources from multiple turbulent jets, the PCSI technology can deliver extremely short combustion duration in ultra-lean mixtures and significantly improve the engine thermal efficiency. However, in the automotive industry there is a lack of adequate science base and predictive simulation tools required for commercial development of PCSI engines. Here, in this study, Reynolds-Average Navier-Stokes simulations are carried out to describe the combustion process in lean-burn NG engines, focusing on the combustion modeling approach. Two combustion models, multi-zone well-stirred reactor (MZ-WSR) and G-equation, are used to simulate the combustion process in an MD NG engine equipped with a fueled-PCSI system for four operating conditions close to the lean operating limit. A skeletal chemical mechanism and a laminar flame speed tabulation are used to compute the combustion accurately. Simulation results are compared with experimental data regarding measured cylinder pressure, heat release rate, and combustion duration. By dividing the PCSI combustion process into four distinct phases, the difference between the two models’ results for each phase is analyzed in detail. The MZ-WSR model overestimates the combustion duration for early flame kernel growth in the pre-chamber due to the lack of a specific formulation to take turbulence-chemistry interaction into account. Despite the prolonged combustion duration and low pressure built-up inside the pre-chamber, the model matches the combustion rate in the main-chamber. In contrast, the G-equation model delivers good agreements for the pre-chamber combustion and turbulent jet-driven combustion processes. However, the model starts to underestimate the combustion rate in the main-chamber, especially under ultra-lean mixture conditions. Finally, improvements are needed for both models to simulate the later combustion stage that occurred in the near-wall regions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Dynamic energy system modeling using hybrid physics-based and machine learning encoder–decoder models

Three model configurations are presented for multi-step time series predictions of the heat absorbed by the water and steam in a thermal power plant. The models predict over horizons of 2, 4, and 6 steps into the future, where each step is a 5-minute increment. The evaluated models are a pure machine learning model, a novel hybrid machine learning and physics-based model, and the hybrid model with an incomplete dataset. The hybrid model deconstructs the machine learning into individual boiler heat absorption units: economizer, water wall, superheater, and reheater. Each configuration uses a gated recurrent unit (GRU) or a GRU-based encoder–decoder as the deep learning architecture. Mean squared error is used to evaluate the models compared to target values. The encoder–decoder architecture is over 11% more accurate than the GRU only models. The hybrid model with the incomplete dataset highlights the importance of the manipulated variables to the system. The hybrid model, compared to the pure machine learning model, is over 10% more accurate on average over 20 iterations of each model. Automatic differentiation is applied to the hybrid model to perform a local sensitivity analysis to identify the most impactful of the 72 manipulated variables on the heat absorbed in the boiler. The models and sensitivity analyses are used in a discussion about optimizing the thermal power plant.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Deformation and Fracture Behaviors of Cylindrical Battery Shell During Thermal Runaway

Thermal runaway is one of the catastrophic failure modes of lithium-ion cells. During thermal runaway in cylindrical cells, sidewall shell rupture has been identified as a contributing factor for thermal runaway propagation in battery packs. Herein, the deformation and fracture behaviors of the battery shell during thermal runaway are investigated based on in-situ and ex-situ characterization as well as physics-based modeling. The deformation and fracture modes of the battery shell with/without Carbon Fiber Reinforced Polymer (CFRP) sleeves are identified. In the simulation, the strain introduced by thermal expansion of the system is considered, as well as the thermal and strain rate effects on the plastic stage. The final cell shell modeling is validated by cell thermal runaway tests. Results reveal the quantitative relation between shell deformation behaviors and the pressure and temperature distribution. Both the experiment and model demonstrate the effectiveness of adding a tight-fitting CFRP sleeve around the cell in limiting the side-wall rupture of the shell. The use of CFRP tubes introduces a novel phenomenon in the context of uneven temperature distribution. Results shed light on the mechanistic analysis of a cell side-wall rupture during thermal runaway and provide essential guidance for the next-generation safe battery design.

battery casing↗
DOE OSTI2021

An efficient numerical model for predicting residual stress and strain in parts manufactured by laser powder bed fusion

Abstract Computational modeling of additively manufactured structures plays an increasingly important role in product design and optimization. For laser powder bed fusion processes, the accurate modeling of stress and distortion requires large amount of computational cost due to very localized heat input and evolving complex geometries. The current study takes advantage of a graphics processing unit accelerated explicit finite element analysis code and approximated heat conduction analysis to predict the macroscopic thermo-mechanical behavior in laser selective melting. Adjacent layers and tracks were lumped to reduce the number of time steps and elements in the finite element model. The effects of track and layer grouping on prediction accuracy and solution efficiency are investigated to provide a guidance for a cost-effective simulation. Thin-wall builds from Inconel alloy 625 (IN625) powders were simulated by applying the developed modeling approach to get the detailed residual stress and distortion at a computational speed 50 times higher than conventional approach. Under repeated heating and cooling cycles, a high tensile stress was produced near surfaces of a build due to a larger shrinkage on surface than that in central area. It is also shown that horizontal stresses concentrate near the root and top layers of the IN625 build. The predicted residual elastic strain distribution was validated by the experimental measurement using x-ray synchrotron diffraction.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A reduced-order modeling of a tubular solar reactor for long duration thermochemical energy storage

The storage of solar energy in a solid form, referred to as a “solar fuel”, can be achieved through a process known as endothermic solar thermochemistry. This process transforms the absorbed solar energy into a stable and retrievable form that can be stored for extended periods of time. This paper presents a low–order heat transfer model of a counter–current tubular falling bed reactor designed to produce thermally reduced magnesium manganese oxide pellets for long duration thermochemical energy storage. The energy required for the endothermic reduction was supplied by concentrated solar energy or renewable electricity via indirect heating of the gas and solid reactants flowing in a ceramic tube. The counter-current gas flow enhances the mixing of the solid particles with the heat recuperation zone, allowing the gas and particles to enter and exit the tubular reactor close to room temperature. Further, the reactor was vertically oriented and was heated circumferentially by an adjustable level heat flux along a finite segment of its length. The temperature distribution of the reactor in response to transient changes along the tube was modeled by considering conduction, convection, and radiation heat transfer. Governing equations for the heat transfer model were solved by discretizing the reactor tube into a finite number of control volumes and using an energy balance for the heat exchange between the reactor wall, gas, and particles within the control volume. The energy absorbed during this endothermic reaction was modeled numerically by fitting the data of the chemical conversion rate with the corresponding temperature of particles in the heating zone. The numerical model has been experimentally validated using a reactor prototype made of a 121.92 cm alumina tube heated by a 7kW electric tube–furnace. The alumina tube receives magnesium manganese oxide pellets of 3.66±0.516 mm in diameter from the top, and a counter–current gas flow from the bottom. The reactor wall temperature was monitored by six thermocouples installed along the reactor tube length. The experimental procedure was numerically simulated, and the temperature variation along the reactor tube was compared with a matrix of experimental runs for a range of particles mass flowrates (0.75–1.25g/s) and corresponding gas flowrates (36–65 SLPM). The reactor system was heated gradually from room temperature to a steady state temperature of 1673K, and then cooled down to room temperature. The heating and cooling processes were simulated, and the numerical and experimental results were compared throughout processes. The numerical model showed similar trends to the experimental results, with an error of 0.69 to 7.9% for the particle inlet and 0.7 to 7.9% for the gas inlet during steady-state operation. The proposed numerical model can be implemented as a simplified physical model to design a feedback control system to regulate reactor temperature.

14 SOLAR ENERGY↗
DOE OSTI2020

Tritium Pressure Enhancement on the TPBAR Cladding by Physical Processes at the Getter

Tritium for the U.S. nuclear weapon stockpile is produced in tritium producing burnable absorber rods (TPBARs) inserted into Tennessee Valley Authoritys (TVA) light-water nuclear reactors. The rods are stainless steel tubes with a permeation barrier coating and internal components that generate and contain the tritium. The TPBAR incorporates a Ni-plated Zircoloy getter tube to capture tritium and prevent it from reaching the rod cladding and permeating into the environment. Under the conventional view of getter behavior, the tritium pressure outside the getter tube is expected to be limited to the equilibrium vapor pressure of Zr hydride at the temperature of the rod as long as the total hydrogen concentration remains below the capacity of the hydride. Since the tritium pressure is higher within the rod core, this behavior relies on the thin getters ability to hold off a differential tritium pressure. The effective tritium pressure on the cladding can also be enhanced by isotope exchange. Hydrogen ingress through the cladding from the reactor coolant creates a hydrogen pressure on the outer surface of the getter that can exchange with tritium, allowing the tritium partial pressure to increase toward this hydrogen gettering pressure. The goal of this work was to use laboratory-scale experiments to examine these mechanisms and create a model of getter behavior that describes tritium transport within the TPBAR. A third mechanism wherein the concentration at the outer surface of the getter is increased by the temperature gradient within the getter tube wall (the Soret effect) is not experimentally tested but is captured in the model. While not conclusively demonstrated by the experiments due to low pressure, high temperature, and small gap volume conditions, the model shows that when combined, the three mechanisms can explain both the magnitude and time dependence of the tritium release observed for reactor fuel assemblies with TPBARs. The model also shows how various modifications of the TPBAR design can reduce this tritium release into the environment.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

First lithium experiments in HIDRA and evidence of helium retention during quasi-steady-state stellarator plasma operations

Recent experiments in Hybrid Illinois Device for Research and Applications (HIDRA) have had operational discharges between t discharge = 60 and 1000 s using electron cyclotron resonant heating (ECRH) of the plasma. This means that quasi-steady-state plasma discharges reach conditions to study long-pulse plasma material interactions (PMIs). The newly commissioned HIDRA-Material Analysis Test-stand PMI diagnostic is used to place a drop of lithium onto a heated tungsten surface, transfer the sample in-vacuo and expose it in a helium plasma. Helium is of interest as there is an open question to whether lithium will be able to remove helium ash in real fusion devices. The introduction of the W-Li sample in HIDRA resulted in evaporation of lithium into the helium plasma during a 600 s pulse and caused a reduction of over 90% in neutral pressure during the discharge. It was also observed that the plasma density and temperature increased by over 2.5 times. Using spectroscopy and a helium collisional radiative model, the peak temperature and density of the helium plasma can be monitored during the discharge. During lithium evaporation, as significant lithium ionization occurs, there is a 85% drop in the HIDRA vessel neutral pressure, despite a constant flow rate of He gas. This reduction in neutral pressure is supported by spectroscopy data with corresponding reductions in He I line intensities (587 nm, 667 nm, 706 nm, and 728 nm), as well as those of other impurities. At one point in the discharge a lithium plasma is created, as indicated by an increase in Li + emission and a complete reduction in He + emission, but the electron density jumps from ne = 3 × 10 18 m –3 to over ne = 8 × 10 18 m –3 while the core temperature stays relatively constant between Te = 16 eV and 20 eV. Once lithium has completely evaporated from the sample and the majority of the ionized lithium has diffused from the plasma to the vessel walls, pressure and spectroscopy data paired with He collisional radiative model calculations shows a re-establishment of a helium plasma in a low recycling regime. In this regime, the density drops down to ne = 2 × 10 18 m –3 and the electron temperature increases from T e = 20 eV to over T e = 50 eV indicating an increase in helium heating efficiency. This is also indicated by the He+ emission re-establishing and having a higher intensity. Here, we show the results from the first lithium campaign in HIDRA. In the presence of lithium, and in particular when lithium ions are present, the helium disappears from the plasma via an as of yet unknown complex relationship that needs to be further studied. The most likely explanation is that the lithium ions are distributed around the vessel and able to trap helium to the surface turning HIDRA into a large gettering surface. These results have potential implications on future plasma facing component design using liquid lithium for impurity and recycling control using limiters and divertors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Towards fast and accurate predictions of radio frequency power deposition and current profile via data-driven modelling: applications to lower hybrid current drive

Three machine learning techniques (multilayer perceptron, random forest and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. A single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time to complete, which is acceptable for many purposes, but too slow for integrated modelling and real-time control applications. The machine learning models use a database of more than 16 000 GENRAY/CQL3D simulations for training, validation and testing. Latin hypercube sampling methods ensure that the database covers the range of nine input parameters ( $n_{e0}$ , $T_{e0}$ , $I_p$ , $B_t$ , $R_0$ , $n_{\|}$ , $Z_{{\rm eff}}$ , $V_{{\rm loop}}$ and $P_{{\rm LHCD}}$ ) with sufficient density in all regions of parameter space. The surrogate models reduce the inference time from minutes to $\sim$ ms with high accuracy across the input parameter space.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Towards fast, accurate predictions of RF simulations via data-driven modeling: Forward and lateral models

Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. A single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time to complete, which is acceptable for many purposes, but too slow for integrated modeling and real-time control applications. More accurate simulations with fast electron diffusion are even slower, requiring multiple hours of run time with parallel processing. The machine learning models use a database of 16,000+ GEN-RAY/CQL3D simulations for training, validation, and testing. Latin hypercube sampling methods implemented in πScope ensure that the database covers the range of 9 input parameters (n e0 , T e0 , I p , B t , R 0 , n ∥︀ , Z e f f , V loop , P LHCD ) with sufficient density in all regions of parameter space. The surrogate models reduce the computation time from minutes-hours to ms with high accuracy across the input parameter space. Data-driven surrogate models also allow for solving inverse and “lateral” problems. A surrogate model for the inverse problem maps from a desired current drive or power deposition profile to a set of input parameters that would result in such a profile, while a surrogate model for the lateral problem maps from a measured experimental quantity such as hard x-ray emission to a current drive or power deposition profile. In conclusion, the πScope database creation workflow is flexible and applicable to other RF simulation codes such as TORIC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Towards Fast and Accurate Predictions of Radio Frequency Power Deposition and Current Profile via Data-driven Modeling

Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. A single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time to complete, which is acceptable for many purposes, but too slow for integrated modeling and real-time control applications. The machine learning models use a database of 16,000+ GENRAY/CQL3D simulations for training, validation, and testing. Latin hypercube sampling methods ensure that the database covers the range of 9 input parameters ($n_{e0}$, $T_{e0}$, $I_p$, $B_t$, $R_0$, $n_{||}$, $Z_{eff}$, $V_{loop}$, $P_{LHCD}$) with sufficient density in all regions of parameter space. The surrogate models reduce the inference time from minutes to ~ms with high accuracy across the input parameter space.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Domain Dynamics under Ultrafast Electric-Field Pulses

Exploring the dynamic responses of a material is of importance to both understanding its fundamental physics at high frequencies and potential device applications. Here we develop a phase-field model for predicting the dynamics of ferroelectric materials and study the dynamic responses of ferroelectric domains and domain walls subjected to an ultrafast electric field pulse. We discover a transition of domain evolution mechanisms from pure domain growth at a relatively low field to combined nucleation and growth of domains at a high field. We derive analytical models for the two regimes which allow us to extract the effective mass and damping coefficient of ferroelectric domain walls. The exhibition of two regimes for the ferroelectric domain dynamics at low and high electric fields is expected to be a general phenomenon that would appear for ferroic domains under other ultrafast stimuli. Finally, the present work also offers a general framework for studying domain dynamics and obtaining fundamental properties of domain walls and thus for manipulating the dynamic functionalities of ferroelectric materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Self-consistent modeling of tokamak edge plasma transport with lithium sources

Magnetic confinement fusion devices require effective heat and particle exhaust solutions on the divertor plates to operate sustainably, especially under reactor-relevant conditions. Liquid lithium divertors have been proposed to address two major challenges: control of excessive heat flux to plasma-facing components through vapor shielding and minimization of core plasma contamination from impurities. The National Spherical Torus Experiment-Upgrade (NSTX-U) will explore lithium as a divertor material due to its potential to meet both objectives. We present a self-consistent coupling framework between the plasma boundary transport code UEDGE and the lithium wall transport code Wall–Li to evaluate the feasibility and operational limits of lithium-based divertors. The model aims to optimize lithium sourcing levels to prevent core plasma contamination via fuel dilution while ensuring divertor protection through vapor shielding. This integrated framework, applicable to any tokamak with lithium sources, dynamically adjusts lithium sourcing based on local plasma conditions and surface temperature. The coupled model is tested using NSTX-like geometry and plasma conditions to assess its performance and reliability. Wall–Li calculates lithium fluxes from plasma-facing components, incorporating physical sputtering, thermally enhanced sputtering, and evaporation driven by surface temperature and ion flux. These fluxes are reintroduced into UEDGE as neutral lithium atoms, enabling simulation of their transport and distribution within the plasma. UEDGE computes plasma and neutral transport, surface heat flux, and iteratively feeds this information back to Wall–Li. A small time step is employed to ensure numerical stability and convergence, enabling accurate simulations over typical tokamak discharge durations. This integrated modeling approach provides a robust tool for identifying operational regimes that balance effective lithium sourcing with minimal core plasma contamination, offering critical insights for optimizing lithium-based divertor systems in current and future fusion devices.

Magnetic confinement fusion↗
DOE OSTI2026

ResStock Measure Documentation: Advanced Air Sealing, Attic Floor Insulation, Duct Sealing and Insulation, and Drill-and-Fill Wall Insulation

This report is part of a series describing different ResStock measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Advanced Air Sealing, Attic Floor Insulation, Duct Sealing and Insulation, and Drill-and-Fill Wall Insulation" measure upgrade methodology and briefly discusses key results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Center for Tokamak Transients Simulations

The major goals for the Center for Tokamak Transients Simulations (CTTS) were to develop detailed numerical simulations of disruptive transients in tokamak experiments and to use them in theoretical studies of the thermal-quench (TQ) and current-quench (CQ) phases of disruption. The University of Wisconsin-Madison component of CTTS contributed relevant development for the NIMROD code (https://nimrodteam.org) and applied it to disruptions that involve global vertical displacement. Code-development contributions include boundary conditions that represent sheath effects which occur when tokamak plasma is in contact with the surrounding vessel wall during vertical displacement events (VDEs). We also implemented a reduced model of energetic runaway electrons (REs) to simulate the effect of these energetic electrons on the CQ phase of tokamak disruptions. Our computations of VDEs include 2D and 3D verification through benchmarks with two other widely used macroscale plasma simulation codes, M3D-C1 and JOREK. Over nonlinear evolution to the final termination of plasma current, the 2D simulation results on magnetic axis location, toroidal current, and halo current track each other well. With the 3D benchmark computation, all three codes found the same qualitative behavior of the asymmetric instabilities having increasing growth rate after contact with the wall, followed by nonlinear excitation of other toroidal harmonics. Our NIMROD computations for an idealized configuration show agreement with an analytical assessment by V. D. Pustovitov [Nucl. Fusion 55, 113032 (2015)] that the plasma and non-ideal wall remain in force-balance such that net forces only result from magnetic stresses over the outer surface of the wall. Our study of the influence of boundary conditions on VDEs shows that extended-MHD simulations of VDEs are sensitive to electron energy transport to the wall and that boundary conditions on flow are only significant to the extent that they influence the electron energy transport. Resistive-MHD NIMROD simulations of the tokamak discharges in the Madison Symmetric Torus show that magnetic perturbations of poloidal wavenumber m=3 lead to chaotic magnetic topology over the edge region, which helps deconfine energetic electrons. A second area of RE study shows that the coupled resistive MHD/reduced RE model reproduces the resistive-hose particle-beam instability. With respect to educational opportunities, this effort involved and supported four graduate students at the University of Wisconsin-Madison and one postdoctoral associate. The results of this study have been disseminated through journal publications, conference presentations, technical reports, and PhD dissertations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

CFD modeling and simulation for corrosive wear of refractory in molten slag

The development of high-wear resistant refractories having minimal production costs is facilitated by characterizing the wear mechanisms associated with their corrosive wear. Static cup testing is a commonly used method for comparing the corrosion resistance performance of two or more refractory materials. Although the static cup test conditions are not as severe as dynamic tests, this study shows that the thermal gradient present within the system during heating and cooling stages serves to generate movement of the slag leading to mechanical wear. The thermal gradient within the refractory, and between the slag and the refractory, occurs during the ramp stage of the test and lasts until the soaking stage is reached bringing the system to a thermal equilibrium. Using computational fluid dynamics (CFD) capabilities embedded within ANSYS software, this study modelled and quantified the convection currents within the slag and associated shear stresses generated on the refractory walls due to the thermal gradient. A traditional ladle furnace was employed as a case study to verify the results of the studied CFD model. The corrosion rate of the refractory lining was found to depend on the mass transfer coefficient of the refractory dissolution into the slag, and a velocity term which governs the extent of corrosion at any given location. This velocity term is a function of slag viscosity, as well as the concentration gradient and/or temperature gradient at the triple points. In this study, wall shear stress was used as a reliable proxy for identifying high-velocity regions prone to excessive corrosive wear. Elevated wall shear stress near the slag/air and slag/molten steel interfaces align with observed corrosion grooves, which reflects the intensified corrosive wear at these locations.

Ramteke, Rajat Rajat Durgesh Ramteke [University o↗
DOE OSTI2022

Characterizing W sources in the all-W wall, all-RF WEST tokamak environment

In this work, experimental data, together with interpretive modeling tools, are examined to study trends in the tungsten (W) source in the all-W environment of the WEST tokamak, both from the divertor and from the main chamber. In particular, a poloidal limiter protecting an ion cyclotron resonance heating (ICRH) antenna is used as proxy for main chamber sourcing. The key study is carried out by stepping up lower hybrid current drive (LHCD) power, as the only auxiliary power source. Limiter and divertor W sources exhibit a qualitatively similar proportionality to the total power crossing the separatrix, P SEP , although the main chamber source remains substantially lower than the divertor source, for the range of P SEP accessible in the experiments. Intepretive modeling of the limiter source is carried out with a particle-in-cell (PIC) sheath model coupled to a surface sputtering model. Oxygen is used as a proxy for all light impurity species allowing for characterization of the critical W erosion regions. To get a good quantitative match to the data, it is necessary to assume that the oxygen arrives at the surface mostly at high ionization stages (4+ and above). A separate simulation with SOLEDGE-EIRENE, constrained to measured upstream scrape-off-layer plasma profiles, gives oxygen fractional abundances that are compatible with the PIC simulation result. This is understood to arise from transport processes that dominate over recombination. Substituting the LHCD by ICRH, in an equivalent experiment, the local W source exhibits a 3× enhancement. This can be matched by the simulation, by assuming local RF electric field rectification, based on ~100 eV peak-to-peak, near-antennna electric field. This work has highlighted the particular importance of understanding the ion charge state balance of light impurities as these are most likely the dominant sputtering species in fusion devices with high-Z walls.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Quantifying Message Aggregation Optimisations for Energy Savings in PGAS Models

Upon breaking past the exascale barrier, HPC systems are facing their greatest challenge yet - a power wall that must be addressed through new methods in both hardware and software. While energy costs are becoming a major issue at all levels, of particular concern is that of the network, as the relative cost of moving data is increasing faster than ever. The partitioned global address space (PGAS) model is critical within certain HPC domains, but is known to suffer from the small message problem, where irregular many-to-many access patterns result in congesting the network with excessive numbers of small messages. To address this, the conveyor aggregation library was developed to defer individual messages and group them for subsequent bulk processing. In this paper, we investigate its impact on energy use related to the network, with a focus on the Slingshot 11 interconnect. We will demonstrate that this strategy is not only highly performant, but also crucial to reducing energy footprints to remain within target power envelopes.

Welch, Aaron [ORNL]↗