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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 649 records · Page 36

Challenges and opportunities in verification and validation of low temperature plasma simulations and experiments

This paper describes the verification and validation (V&V) framework developed for the stochastic Particle-in-Cell, Direct Simulation Monte Carlo code Aleph. An ideal framework for V&V from the viewpoint of the authors is described where a physics problem is defined, and relevant physics models and parameters to the defined problem are assessed and captured in a Phenomena Identification and Ranking Table (PIRT). Furthermore, numerous V&V examples guided by the PIRT for a simple gas discharge are shown to demonstrate the V&V process applied to a real-world simulation tool with the overall goal to demonstrably increase the confidence in the results for the simulation tool and its predictive capability. Although many examples are provided here to demonstrate elements of the framework, the primary goal of this work is to introduce this framework and not to provide a fully complete implementation, which would be a much longer document. Comparisons and contrasts are made to more usual approaches to V&V, and techniques new to the low-temperature plasma community are introduced. Specific challenges relating to the sufficiency of available data (e.g., cross sections), the limits of ad hoc validation approaches, the additional difficulty of utilizing a stochastic simulation tool, and the extreme cost of formal validation are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Electron scattering processes: fundamentals, challenges, advances, and opportunities

Much effort has been devoted to describing qualitatively and quantitatively electron scattering processes due to their ever-increasing importance in many industrial and medical applications. We present achievements made in the last years, focusing on some of the advancements and recent progress in the field. Particular reference is made on concrete case studies to probe the level of accord in cross-section data obtained from experiments and theory, as well as on selected instrumentation developments to probe dynamics of dissociative processes induced by electron impact. We stress that the purpose of this colloquium paper is not to be a comprehensive review but rather to provide a snapshot of different research topics in electron scattering by pointing out certain challenges and, therefore, indicating opportunities to facilitate further experimental and theoretical work.

74 ATOMIC AND MOLECULAR PHYSICS↗

Neural networks for large eddy simulations of wall-bounded turbulence: numerical experiments and challenges

Here, we examine the application of neural network-based methods to improve the accuracy of large eddy simulations of incompressible turbulent flows. The networks are trained to learn a mapping between flow features and the subgrid scales, and applied locally and instantaneously—in the same way as traditional physics-based subgrid closures. Models that use only the local resolved strain rate are poorly correlated with the actual subgrid forces obtained from filtering direct numerical simulation data. We see that highly accurate models in a priori testing are inaccurate in forward calculations, owing to the preponderance of numerical errors in implicitly filtered large eddy simulations. A network that accounts for the discretization errors is trained and found to be unstable in a posteriori testing. We identify a number of challenges that the approach faces, including a distribution shift that affects networks that fail to account for numerical errors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Progress and challenges in small systems

We present a comprehensive review of the theoretical and experimental progress in the investigation of novel high-temperature quantum chromodynamics phenomena in small systems at both the Relativistic Heavy Ion Collider and the Large Hadron Collider. We highlight the challenges and opportunities associated with studying small systems, by which we generally mean collision systems that involve at least one light ion or even a photon projectile. Here, we discuss perspectives on possible future research directions to better understand the underlying physics at work in the collisions of small systems.

collective behavior↗

Progress and challenges in small systems

Here, we present a comprehensive review of the theoretical and experimental progress in the investigation of novel high-temperature quantum chromodynamics phenomena in small systems at both the Relativistic Heavy Ion Collider and the Large Hadron Collider. We highlight the challenges and opportunities associated with studying small systems, by which we generally mean collision systems that involve at least one light ion or even a photon projectile. We discuss perspectives on possible future research directions to better understand the underlying physics at work in the collisions of small systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Generalizable coordination of large multiscale workflows: challenges and learnings at scale

The advancement of machine learning techniques and the heterogeneous architectures of most current supercomputers are propelling the demand for large multiscale simulations that can automatically and autonomously couple diverse components and map them to relevant resources to solve complex problems at multiple scales. Nevertheless, despite the recent progress in workflow technologies, current capabilities are limited to coupling two scales. In the first-ever demonstration of using three scales of resolution, we present a scalable and generalizable framework that couples pairs of models using machine learning and in situ feedback. We expand upon the massively parallel Multiscale Machine-Learned Modeling Infrastructure (MuMMI), a recent, award-winning workflow, and generalize the framework beyond its original design. We discuss the challenges and learnings in executing a massive multiscale simulation campaign that utilized over 600,000 node hours on Summit and achieved more than 98% GPU occupancy for more than 83% of the time. We present innovations to enable several orders of magnitude scaling, including simultaneously coordinating 24,000 jobs, and managing several TBs of new data per day and over a billion files in total. Finally, we describe the generalizability of our framework and, with an upcoming open-source release, discuss how the presented framework may be used for new applications.

Bhatia, Harsh↗

OReole-FM: successes and challenges toward billion-parameter foundation models for high-resolution satellite imagery

While the pretraining of Foundation Models (FMs) for remote sensing (RS) imagery is on the rise, models remain restricted to a few hundred million parameters. Scaling models to billions of parameters has been shown to yield unprecedented benefits including emergent abilities, but requires data scaling and computing resources typically not available outside industry R&D labs. In this work, we pair high-performance computing resources including Frontier supercomputer, America's first exascale system, and high-resolution optical RS data to pretrain billion-scale FMs. Our study assesses performance of different pretrained variants of vision Transformers across image classification, semantic segmentation and object detection benchmarks, which highlight the importance of data scaling for effective model scaling. Moreover, we discuss construction of a novel TIU pretraining dataset, model initialization, with data and pretrained models intended for public release. By discussing technical challenges and details often lacking in the related literature, this work is intended to offer best practices to the geospatial community toward efficient training and benchmarking of larger FMs.

Ambrozio Dias, Philipe↗

Fluid Mechanics Challenges in Direct-Ink-Writing Additive Manufacturing

Direct-ink writing (DIW) has rapidly become a versatile 3D fabrication method due to its ability to deposit a wide range of complex fluids into customizable 3D geometries. This review highlights key fundamental fluid mechanics and soft matter challenges across the different stages of the DIW printing process. The rheology of fluids and suspensions governs the flow behavior through narrow nozzles, posing questions about extrudability, confined flow dynamics, and clogging mechanisms. Downstream, the formation and deposition of extruded filaments involve extensional flows and potential instabilities, while postdeposition dynamics introduces complexities related to yield stress and structural stability. These stages are inherently interdependent, as optimizing material composition without considering filament stability risks compromising the final structure. As DIW applications expand through advanced ink formulations, developing fundamental fluid mechanics frameworks is essential to replace trial-and-error approaches with predictive design methodologies to enable more precise control and improved reliability of the printing process.

3D printing↗

Inertial Confinement Fusion: Status and Challenges

While a variety of laboratory-based fusion schemes have been studied for decades, the only fusion scheme yet to demonstrate fusion ignition and significant energy gain has been X-ray-driven inertially confined fusion. Ignition was demonstrated to occur at the thermodynamic conditions where it had long been expected, but the energy required for the implosion system to reach these conditions was more than projected years ago. This short review gives a status update on the three principal inertial confinement fusion schemes and research challenges going forward.

gain↗

Editors’ Choice—Perspective—Challenges in Moving to Multiscale Battery Models: Where Electrochemistry Meets and Demands More from Math

There has been significant recent interest in studying multiscale characteristics of current and next-generation batteries, including lithium-metal and lithium-sulfur batteries. Advances in computing power make researchers believe that the detailed multiscale models can be efficiently simulated to arrive at the insights for the degradation and performance loss; however, this is not true and special attention needs to be paid to local singularities, boundary layers, moving boundaries, etc. This article presents 2D examples that illustrate the importance of grid convergence studies, provides well-defined detailed models to test the efficiency of numerical schemes, and discusses the associated simulation challenges.

Shah, Krishna (ORCID:0000000278026361)↗

Review—Polymer/Ceramic Interface Barriers: The Fundamental Challenge for Advancing Composite Solid Electrolytes for Li-Ion Batteries

Composite-solid electrolytes, in which ion-conducting polymers are combined with superionic ceramics, could revolutionize electrochemical-energy-storage devices enabling higher energy density, providing greater stability during operation and enhanced safety. However, the interfacial resistance between the ceramic and polymer phases strongly suppresses the ionic conductivity and presents the main obstacle to the use of these materials. Here, we emphasize the need for a distinct focus on reducing energy barriers to interfacial ion transport and improving the cation transference number. To achieve this goal, it is essential to develop a fundamental understanding of the parameters that influence the interfacial barriers to ion transport in composite electrolytes, and to understand the effect of the type of ceramic ("active" and "inert") and its content on ion-transport phenomena. We suggest that adapting the polymer chemistry, mainly directed on polymerized ionic liquids, (PolyILs), and combined with functionalization of the surface of ceramic nanoparticles is a promising route for overcoming the high-energy-barrier challenge. Owing to high content of ion-conducting ceramics and high t+ of PolyILs, the fractional contribution of the migrating cationic species to the total ionic conductivity of polymer-in-ceramic electrolytes via an interfacial percolation path, will be close to unity, thus eliminating complications that might arise from emerging concentration gradients during the operation of solid-state batteries.

25 ENERGY STORAGE↗

Wearable Sensors Measure Ankle Joint Changes of Patients with Parkinson’s Disease before and after Acute Levodopa Challenge

Background . Previous studies found levodopa could improve the activity of the ankle joints of patients with Parkinson’s disease (PD). But ankle joint movement is composed of four motion ranges. The specific changes of four motion ranges in PD remain unknown. Objective . The purpose of this study was to decompose the complex ankle joint movement, measure ankle joint changes before and after the acute levodopa challenge test (ALCT), and investigate the effects of these parameters on gait performance. Methods . 29 PD patients and 30 healthy control subjects (HC) completed the Instrumented Stand and Walk (ISAW) test and gait parameters were collected by the JiBuEn gait analysis system. The percentage of improvement of gait data and the UPDRS III in the on-drug condition (ON) were determined with respect to the off-drug condition (OFF). Results . We observed a reduction in the heel strike angle (HS), 3-plantarflexion (3-PF) angle, and 4-dorsiflexion (4-DF) angle of ankle joints. We did not find significant difference in the toe-off angle (TO), 1-plantarflexion (1-PF) angle, and 2-dorsiflexion (2-DF) angle among three groups. Stride length improvement rate was significantly correlated with HS ( r s = 0.616, P < 0.001 ) and 3-PF ( r s = 0.639, P < 0.001 ) improvement rates. The improvement in the sum of rigidity items (UPDRS motor subsection item 22) was also correlated with HS ( r s = 0.389, P = 0.037 ) and 3-PF ( r s = 0.373, P = 0.046 ) improvement rates. Conclusions . Exogenous levodopa supplementation can significantly reduce the rigidity of patients with PD, improve their 3-PF and 4-DF of ankle joint kinematic parameters, and ultimately enhance their gait.

Wu, Zhuang↗

Opportunities for and challenges to further reductions in the “specific power” rating of wind turbines installed in the United States

A wind turbine’s “specific power” rating relates its capacity to the swept area of its rotor in terms of Watt per square meter. For a given generator capacity, specific power declines as rotor size increases. In land-rich but capacity-constrained wind power markets, such as the United States, developers have an economic incentive to maximize megawatt-hours per constrained megawatt, and so have favored turbines with ever-lower specific power. To date, this trend toward lower specific power has pushed capacity factors higher while reducing the levelized cost of energy. We employ geospatial levelized cost of energy analysis across the United States to explore whether this trend is likely to continue. We find that under reasonable cost scenarios (i.e. presuming that logistical challenges from very large blades are surmountable), low-specific-power turbines could continue to be in demand going forward. Beyond levelized cost of energy, the boost in market value that low-specific-power turbines provide could become increasingly important as wind penetration grows.

geospatial modeling↗

Asynchronous-many-task systems: Challenges and opportunities - Scaling an AMR astrophysics code on exascale machines using Kokkos and HPX

Dynamic and adaptive mesh refinement is pivotal in high-resolution, multi-physics, multi-model simulations, necessitating precise physics resolution in localized areas across expansive domains. Today’s supercomputers’ extreme heterogeneity presents a significant challenge for dynamically adaptive codes, highlighting the importance of achieving performance portability at scale. Our research focuses on astrophysical simulations, particularly stellar mergers, to elucidate early universe dynamics. Here, we present Octo-Tiger, leveraging Kokkos, HPX, and SIMD for portable performance at scale in complex, massively parallel adaptive multi-physics simulations. Octo-Tiger supports diverse processors, accelerators, and network backends. Experiments demonstrate exceptional scalability across several heterogeneous supercomputers including Perlmutter, Frontier, and Fugaku, encompassing major GPU architectures and x86, ARM, and RISC-V CPUs. Parallel efficiency of 47.59% (110,080 cores and 6880 hybrid A100 GPUs) on a full-system run on Perlmutter (26% HPCG peak performance) and 51.37% (using 32,768 cores and 2048 MI250X) on Frontier are achieved.

97 MATHEMATICS AND COMPUTING↗

Challenges in Clinical Trial Implementation: Results from a Survey of the National Accreditation Program of Breast Centers (NAPBC)

Background: Although the results of clinical trials often guide best practices, changing clinical practice based on clinical trial results can be challenging. The objective of this study was to examine provider-reported barriers to adopting best clinical practices according to clinical trial data. Methods: A cross-sectional survey was conducted of providers from the National Accreditation Program for Breast Centers about barriers that prevent the incorporation of trial findings. Descriptive analyses and multivariable analyses were performed to determine provider characteristics that were significantly associated with reported barriers. Results: Overall, 383 institutions participated (63.5% response rate), with a total of 1226 physicians responding to the survey (80% response rate). Providers identified national guidelines and meetings as the most compelling way to receive practice-changing information. They reported the following internal barriers to trial implementation: patient preference (45%), strongly held beliefs by partners/colleagues (37%), and insufficient time to discuss new practices (30%). External barriers preventing trial implementation included a lack of agreement from multidisciplinary tumor boards (32%), fear of reimbursement loss (23%), and resistance from clinical staff (20%). Reported barriers differed by provider specialty, with plastic surgeons and radiation oncologists reporting that strongly held beliefs by partners/colleagues and disagreement from multidisciplinary tumor boards were the most significant factors preventing clinical trial implementation. Conclusions: Physician beliefs and patient preferences are the most frequently reported barriers to clinical trial implementation. Tactics to better educate providers about how to explain new clinical trial data to their patients and colleagues are needed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Recent Developments in Security-Constrained AC Optimal Power Flow: Overview of Challenge 1 in the ARPA-E Grid Optimization Competition

In “Recent Developments in Security-Constrained AC Optimal Power Flow: Overview of Challenge 1 in the ARPA-E Grid Optimization Competition,” we review the state of the art in practical algorithms for scheduling power-systems operations in the short term and the results of the recent competition organized by the U.S. Advanced Research Projects Agency–Energy. We explain the mixed-integer nonlinear formulation used in the competition for nonspecialists in electrical engineering, the context and organization of the competition, and the performance of competitors. We find that the collective approaches and results of competitors provide support for efforts to move nonlinear optimization techniques into industrial applications, as they have proven to be a robust and efficient alternative to current linear approximation techniques.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NOMAD total scattering dataset for SMC data challenge

The data provided for this challenge was measured using the Nanoscale-Ordered Materials Diffractometer (NOMAD) at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory. The data is stored in a hdf5 file following the NeXus standard and can be read with tools built for either. While the NeXus format is self-describing, there is benefit to explaining some details. The data is stored in 4 NXentries in the file. The NXentries that begin with 'amorphous_SiO2' are for the amorphous data, and the NXentries that begin with 'crystalbolite_SiO2' are for the crystalline material. Solutions that were produced by the scientist are in the entries that end with '_byhand'. Each of the NXdata groups are the plottable data with the 'signal', axes, and (in the case of by-hand components) 'auxiliary_signals' describing which fields should be used. The by-hand component ranges are listed in a 'component' attribute of the various signals. The filtered Sr data is the Fourier transform of the combined components. The data can be quickly viewed using tools such as Nexpy or HDFview. Most languages have libraries that can work with HDF5 (eg. H5py for python) a partial list is provided at https://manual.nexusformat.org/utilities.html The data can be quickly viewed using tools such as Nexpy or HDFview. https://neutrons.ornl.gov/nomad https://www.hdfgroup.org/solutions/hdf5 https://www.nexusformat.org/

36 MATERIALS SCIENCE↗

SNAP diffraction dataset for 2023 SMC data challenge

The data provided this challenge is ice under high pressure measured using the Spallation Neutrons and Pressure Diffractometer (SNAP) at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory. The data is stored in a hdf5 file following the NeXus standard and can be read with tools built for either. While the NeXus format is self-describing, there is benefit to explaining some details. The data is stored in a single NXdata entry within a single NXentry. The NXdata has several fields denoting the 3-dimensional data (signal), the axes (D0 is the Qx axis, D1 is the Qy axis, and D2 is the Qz axis), and fields for the uncertainties and masking information. The data can be quickly viewed using the LoadMD algorithm and slice viewer in the Mantid workbench https://www.mantidproject.org.

36 MATERIALS SCIENCE↗