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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Repairable and Reconfigurable Structured Liquid Circuits

The advance of printed electronics is significantly bolstered by the development of liquid-state electronics that overcome the inherent limitations in flexibility and reconfigurability of solid-state electronics. By integrating the biocompatibility and conductivity of sulfonated polyaniline (S-PANI) and phytic acid (PA) with the reconfigurability of structured liquids, highly conductive all-liquid threads are developed. The dense packing and overlap of PA/S-PANI complexes at an oil/water interface promotes in-plane electron transport, and standard four-point probe measurements of PA/S-PANI interfacial assemblies demonstrate enhanced electrical properties. Notably, the rapid jetting of the ink phase into the matrix phase allows for liquid threads to be printed, enabling the fabrication of large-scale, conductive pathways between two electrodes and liquid circuits. Upon mechanical cleavage of the liquid wires, circuits can be broken, but will easily self-repair using an electric field, making this motif useful in the design of switches as well as restoring conductive pathways in series or in parallel. In conclusion, the demonstrated flexibility and reconfigurability these PA/S-PANI wires possess hold significant promise for their practical use in the design of flexible and adaptive bioelectronics that can be repaired on demand, signifying a transformative step in the evolution of liquid electronic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Resonant acoustic monitoring of damage in plug‐screw feeders

Abstract Plug‐screw feeders are critical in many industrial processes for compressing slurry materials via a rotating plug‐screw feeder. Over time, increasing plug‐screw feeder wear will eventually lead to catastrophic mechanical failure. Early detection of the wear state can prevent unplanned catastrophic failures resulting in operational shut‐downs, costly repairs, and most importantly the health and safety of workers. We present a theoretical basis for a noninvasive, in operando acoustic resonant technique to monitor the wear state of plug‐screw feeders. The technique is based on tracking the resonant acoustic modes of the plug‐screw feeder, which are sensitive to the plug‐screw feeder geometry, material, and operating conditions. We implemented a multivariate polynomial model to estimate the plug‐screw feeder wear state using multiple acoustic resonances by simulating the acoustic resonant modes for two categories of wear (tip and thread damage) that are common in plug‐screw feeders. Fitting multiple resonances to the polynomial model, we demonstrate accurate estimation of the total mass loss, as well as characterization of the type of damage (i.e., tip vs. thread). Current approaches for monitoring plug‐screw feeder wear rely on shutting down the operation and visually inspecting the plug‐screw feeder. The presented acoustic technique offers a noninvasive, in operando measurement approach that mitigates unplanned catastrophic failures. The acoustic resonance technique presented in the paper has a broad range of industrial applications including the Pharmaceutical, Mining, Integrated Biorefineries (IBR), and Additive Manufacturing industries, to name a few.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Large language model evaluation for high–performance computing software development

We apply AI-assisted large language model (LLM) capabilities of GPT-3 targeting high-performance computing (HPC) kernels for (i) code generation, and (ii) auto-parallelization of serial code in C ++, Fortran, Python and Julia. Our scope includes the following fundamental numerical kernels: AXPY, GEMV, GEMM, SpMV, Jacobi Stencil, and CG, and language/programming models: (1) C++ (e.g., OpenMP [including offload], OpenACC, Kokkos, SyCL, CUDA, and HIP), (2) Fortran (e.g., OpenMP [including offload] and OpenACC), (3) Python (e.g., numpy, Numba, cuPy, and pyCUDA), and (4) Julia (e.g., Threads, CUDA.jl, AMDGPU.jl, and KernelAbstractions.jl). Kernel implementations are generated using GitHub Copilot capabilities powered by the GPT-based OpenAI Codex available in Visual Studio Code given simple + + prompt variants. To quantify and compare the generated results, we propose a proficiency metric around the initial 10 suggestions given for each prompt. For auto-parallelization, we use ChatGPT interactively giving simple prompts as in a dialogue with another human including simple “prompt engineering” follow ups. Results suggest that correct outputs for C++ correlate with the adoption and maturity of programming models. For example, OpenMP and CUDA score really high, whereas HIP is still lacking. We found that prompts from either a targeted language such as Fortran or the more general-purpose Python can benefit from adding language keywords, while Julia prompts perform acceptably well for its Threads and CUDA.jl programming models. Finally, we expect to provide an initial quantifiable point of reference for code generation in each programming model using a state-of-the-art LLM. Overall, understanding the convergence of LLMs, AI, and HPC is crucial due to its rapidly evolving nature and how it is redefining human-computer interactions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Porting DMRG++ Scientific Application to OpenPOWER

With the rapidly changing microprocessor designs and architectural diversity (multi-cores, many-cores, accelerators) for the next generation HPC systems, scientific applications must adapt to the hardware, to exploit the different types of parallelism and resources available in the architecture. To get the benefit of all the in-node hardware threads, it is important to use a single programming model to map and coordinate the available work to the different heterogeneous execution units in the node (e.g., multi-core hardware threads (latency optimized), accelerators (bandwidth optimized), etc.).Our goal is to show that we can manage the node complexity of these systems by using OpenMP for in-node parallelization by exploiting different “programming styles” supported by OpenMP 4.5 to program CPU cores and accelerators. Finding out the suitable programming-style (e.g., SPMD style, multi-level tasks, accelerator programming, nested parallelism, or a combination of these) using the latest features of OpenMP to maximize performance and achieve performance portability across heterogeneous and homogeneous systems is still an open research problem.We developed a mini-application, Kronecker Product (KP), from the original DMRG++ application (sparse matrix algebra) computational motif to experiment with different OpenMP programming styles on an OpenPOWER architecture and present their results in this paper.

Chatterjee, Ronnie↗
DOE OSTI2019

Optimization of Condensed Matter Physics Application with OpenMP Tasking Model

The Density Matrix Renormalization Group (DMRG++) is a condensed matter physics application used to study superconductivity properties of materials. It’s main computations consist of calculating hamiltonian matrix which requires sparse matrix-vector multiplications. This paper presents task-based parallelization and optimization strategies of the Hamiltonian algorithm. The algorithm is implemented as a mini-application in C++ and parallelized with OpenMP. The optimization leverages tasking features, such as dependencies or priorities included in the OpenMP standard 4.5. The code refactoring targets performance as much as programmability. The optimized version achieves a speedup of 8.0× with 8 threads and 20.5× with 40 threads on a Power9 computing node while reducing the memory consumption to 90 MB with respect to the original code, by adding less than ten OpenMP directives.

Criado, Joel↗
DOE OSTI2024

GraphTango: A Hybrid Representation Format for Efficient Streaming Graph Updates and Analysis

Abstract Streaming graph processing performs batched updates and analytics on a time-evolving graph. The underlying representation format of the graph largely determines the throughputs of these updates and analytics phases. Existing representation formats usually employ variations of hash tables or adjacency lists. However, a recent study showed that the adjacency-list-based approaches perform poorly on heavy-tailed graphs, and the hash table-based approaches suffer on short-tailed graphs. We propose GraphTango, a hybrid representation format that provides excellent update and analytics throughput regardless of the graph’s degree distribution. GraphTango dynamically switches among three different formats based on a vertex’s degree: (i) Low-degree vertices store the edges directly with the neighborhood metadata, confining accesses to a single cache line, (2) Medium-degree vertices use adjacency lists, and (3) High-degree vertices use hash tables as well as adjacency lists. In this case, the adjacency list provides fast traversal during the analytics phase, while the hash table provides constant-time lookups during the update phase. We further optimized the performance by designing an open-addressing-based hash table that fully utilizes every fetched cache line. In addition, we developed a thread-local lock-free memory pool that allows fast growing/shrinking of the adjacency lists and hash tables in a multi-threaded environment. We evaluated GraphTango with the help of the SAGA-Bench framework and compared it with four other representation formats: Stinger, Degree-aware Robin Hood Hashing, and two adjacency list-based formats with different workload balancing scheme. On average, GraphTango provides 4.5x higher insertion throughput, 3.2x higher deletion throughput, and 1.1x higher analytics throughput over the next best format. Furthermore, we integrated GraphTango with the state-of-the-art graph processing frameworks DZiG and RisGraph. Compared to the vanilla DZiG and vanilla RisGraph , [ GraphTango + DZiG ] and [ GraphTango + RisGraph ] reduces the average batch processing time by 2.3x and 1.5x, respectively.

Ahmed, Alif↗
DOE OSTI2022

A Common Tracking Software Project

Abstract The reconstruction of the trajectories of charged particles, or track reconstruction, is a key computational challenge for particle and nuclear physics experiments. While the tuning of track reconstruction algorithms can depend strongly on details of the detector geometry, the algorithms currently in use by experiments share many common features. At the same time, the intense environment of the High-Luminosity LHC accelerator and other future experiments is expected to put even greater computational stress on track reconstruction software, motivating the development of more performant algorithms. We present here A Common Tracking Software (ACTS) toolkit, which draws on the experience with track reconstruction algorithms in the ATLAS experiment and presents them in an experiment-independent and framework-independent toolkit. It provides a set of high-level track reconstruction tools which are agnostic to the details of the detection technologies and magnetic field configuration and tested for strict thread-safety to support multi-threaded event processing. We discuss the conceptual design and technical implementation of ACTS, selected applications and performance of ACTS, and the lessons learned.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

High compressive energy absorption and shape recovery behavior of additively manufactured textile-inspired cylindrical braided metamaterials

Mechanical metamaterials (MMs) are engineered structures with unique mechanical properties that arise from their unique spatial arrangement or lattice-like structure. The most commonly designed MMs such as honeycomb and re-entrant auxetics are prone to failure at the sharp corners and weak joints due to the increased stress concentration under deformation. To mitigate this challenge, braided MM structures involving intertwining threads of nylon—forming curved unit cells—have been studied. These textile-inspired cylindrical braided metamaterials (CBMMs) with contrasting unit cells, namely diamond and regular CBMMs, were fabricated by 3D printing. The layer-by-layer deposited structure built by fused filament fabrication delivered an assembly of overlapped threads that are fused at the contact point. To understand deformation behavior of these MMs, finite element models were developed for various load scenarios including quasi-static compression, cyclic and creep loads at room temperature. Stress distribution, deformation mechanisms, and failure modes were analyzed and validated by experiments to analyze the geometries and associated performance. The diamond CBMMs showed stress softening at 30 % compressive strain, withstanding a load of ∼440 N, whereas the regular CBMMs at 50 % strain experienced ∼250 N. The diamond CBMMs delivered higher creep resistance under sustained load and better energy absorption under cyclic loading than the regular CBMMs. The latter, however, exhibited 94 % shape recovery in contrast to 88 % recovery in former prototype during their first cyclic load. In conclusion, this study helps design mechanical lightweight devices that endure significant sustained load and exhibit enhanced energy absorption and shape recovery characteristics in cyclic loading.

Creep↗
DOE OSTI2025

Myna: Connecting powder bed fusion build data to simulation tools for digital twin applications

Additive manufacturing (AM), as a digital process, can generate a detailed digital thread linking a part’s design and manufacturing to its operational performance. As AM systems advance, an increasing amount of process data is stored in manufacturing databases. In principle, this data can be utilized by simulation-based digital twin approaches, such as real-time process control and asynchronous post-processing guidance. However, few tools currently exist for systematically integrating digital thread data with computational tools. Here, in this study, we propose a software package, called Myna, for connecting data from powder bed fusion processes to simulation tools. The utility of such a platform is demonstrated using build data from the Oak Ridge National Laboratory Manufacturing Demonstration Facility “Peregrine v2023-10” public dataset to automatically configure and run 54 semi-analytical 3DThesis melt pool simulations, 78 numerical Additive FOAM melt pool simulations, and 3 ExaCA microstructure simulations. The simulated, spatially registered microstructures are then compared directly with electron backscatter diffraction characterization of the corresponding as-built part locations. The resulting simulated microstructure showed variation as a function of process parameters, particularly stripe width; however, the experimental data had little variation between the microstructure texture and grain size resulting from different processing conditions. Analysis of the discrepancies suggest that it is possible a two-phase ferritic-austenitic solidification model is needed to accurately predict grain size and texture for certain stainless steel 316L feedstock compositions under powder bed fusion conditions, providing direction for future research. As illustrated here, due to the number and complexity of the simulations involved in AM process-structure–property predictions, automated methods to connect process data and simulations will remain necessary tools for testing hypotheses and implementing digital twin applications.

Knapp, Gerald L. [Oak Ridge National Laboratory (O↗
DOE OSTI2023

Highly-scalable GPU-accelerated compressible reacting flow solver for modeling high-speed flows

Emerging supercomputing systems utilize a combination of central processing units (CPUs) and graphics processing units (GPUs) in an effort to reach exascale capabilities while minimizing the energy footprint of operating such systems. Such heterogeneous machines introduce new challenges for fluids solvers because the hardware architecture and operation of a GPU are fundamentally different from conventional CPUs. In this work, a general approach for efficient implementation of finite-volume based reacting flow solvers on such heterogeneous systems is presented. Three main challenges, namely, data access pattern, thread divergence, and thread safety, are addressed. Since compressible reacting flows require special methods to deal with chemical reactions, hyperbolic and nonlinear convection terms, and the presence of turbulence, specific algorithms that ensure GPU-based efficiency are developed. The approach is demonstrated on the widely available OpenFOAM open source software by modifying core algorithms for GPU accessibility. The scalability of the resulting solver, is demonstrated using practical test cases, including flow through a scramjet engine and the dynamics of a rotating detonation engine. Here, the solver provides near-ideal scaleup on a large number of GPUs (>3000), and extremely efficient use of the GPUs, with throughput nearly a constant even when processing a large number of control volumes.

42 ENGINEERING↗
DOE OSTI2026

Parallelized real-time physics codes for plasma control on DIII-D

A real-time safe multi-threading library was developed on the DIII-D plasma control system to optimize the real-time TORBEAM and real-time STRIDE physics codes. These physics codes are crucial for future fusion power plant operation as they provide information about electron cyclotron wave propagation and heating as well as inform about ideal plasma stability limits. The real-time TORBEAM code executed consistently in under 20 ms while the real-time STRIDE code computes in 100 ms. The multi-threading library developed in this work can be applied to other real-time physics-based codes that will be crucial for the next generation of fusion devices.

DIII-D↗
DOE OSTI2018

Single- and dual-variant atomic ordering in GaAsP compositionally graded buffers on GaP and Si substrates

Here, we investigate the material properties of GaAsP graded buffers on both GaP and Si substrates in order to determine limitations to dislocation glide in GaAsP. Phase separation is not observed in these GaAsP buffers, but CuPt B atomic ordering is present, and has an impact on the Burgers vector distribution of gliding dislocations. Tellurium surfactant eliminates ordering in GaAsP, allowing control over the glide plane distribution while highlighting the importance of the growth surface and choice of dopant. The impact of single-variant CuPtB ordering of GaAsP buffers grown on GaP substrates is investigated by monitoring the threading dislocation density throughout the buffer in sequential steps. The dislocation density rises steadily throughout the graded buffer, implying that factors other than ordering-induced glide plane switches play a dominant role in the final dislocation density. We observe an increase in surface roughness throughout the buffer and speculate that a dislocation nucleation source on the surface has a low activation energy and may lead to increased threading dislocation density. On Si substrates, the GaAsP buffer displays dual-variant CuPt B ordering rather than single-variant ordering due to the surface step geometry. We discuss how dual-variant ordering leads to a variable glide force, and thus has a different impact on dislocation dynamics than single-variant ordering. Because the III-V on Si nucleation procedure determines the step geometry, it also influences the dislocation dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Influence of trimethylaluminum predoses on the growth morphology, film-substrate interface, and microstructure of MOCVD-grown AlN on (1 1 1)Si

Aluminum nitride (AlN) was deposited on (1 1 1) silicon by metalorganic chemical vapor deposition after varied trimethylaluminum “predoses”. Growth morphologies, film-substrate interfaces, and film microstructures were examined using scanning electron microscopy, atomic force microscopy, X-ray diffraction, and transmission electron microscopy. In samples grown with predoses, lateral growth was observed over faceted “patches” formed during the predose. Three-dimensional growth was observed to seed from small islands on the surface of these patches and eventually overgrow them. The three-dimensional growth mode was similar to that observed when AlN was grown without a predose, resulting in similar morphologies in all films, regardless of predose, after the islands coalesced. The AlN-silicon interface was found to be predominantly amorphous when no predose was used. However, narrow regions were observed over which the film was in atomic registry with the substrate. This indicates AlN nucleates in epitaxy with the substrate and amorphous silicon nitride forms between nucleation sites due to ammonia exposure. Films grown with predoses had structurally abrupt interfaces, suggesting aluminum within the observed patch features inhibits the reaction between ammonia and silicon at the onset of growth. A structure distinct from both wurtzite AlN and diamond cubic silicon was observed at the substrate interface in films grown with a predose, consistent with either zinc blende AlN or a strained Si/Al alloy. A mosaic microstructure was observed in all films, grown with or without predoses, which consisted of sub-boundaries formed by clusters of threading dislocations. Finally, threading dislocations, separated by hundreds of nanometers, were found to be tilted along common directions, providing evidence for a dislocation bending mechanism possibly enhanced by the predose.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Role of V-defect density on the performance of III-nitride green LEDs on sapphire substrates

In this paper, we experimentally investigated the role of V-defect density on the performance of green III-nitride LEDs grown on sapphire substrates by metalorganic chemical vapor deposition. We systematically varied the threading dislocation (TD) density from 4 × 10 8 to 1 × 10 9 cm -2 by changing the V/III ratio during initial high temperature GaN growth. A 30-period InGaN/GaN superlattice promoted V-defect formation and growth at TDs, where the density of V-defects was correlated to the TD density. By interrupting the LED growth and examining the surface of the active region, we quantified the average size and density of V-defects. In a series of LEDs, we measured a systematic decrease in forward voltage (V F ) with V-defect density. At a V-defect density of 5.0 × 10 8 cm -2 and TD density of 1 × 10 9 cm -2 , green LED devices were demonstrated with λ = 523 nm and V F = 2.94 V at 20 A cm -2 . These results highlight the potential of using V-defect engineering to achieve low V F long wavelength LEDs on sapphire substrates, where opening of remaining threading dislocations into V-defects presents an opportunity for further V F reduction.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Correlation of Early-Stage Growth Process Conditions with Dislocation Evolution in MOCVD-Based GaP/Si Heteroepitaxy

To identify the complex relationships between early-stage growth processes and the resultant defect microstructure in GaP/Si heteroepitaxy, a holistic study of several key metal-organic chemical vapor deposition (MOCVD) parameters was conducted, focusing on Si surface preparation and GaP atomic layer epitaxy (ALE) based nucleation processes. Here, crystalline defects related to the lattice mismatch and/or interfacial heterovalency, namely misfit dislocations (MD), threading dislocations (TD), and stacking fault pyramids (SFP), were quantitatively characterized via electron channeling contrast imaging (ECCI) and correlated against the different process variations. Choice of Si surface preparation method between the two examined (dilute SiH4 annealing versus Si2H6 based homoepitaxy) had little impact on resultant GaP film morphology and defect content, whereas differing GaP ALE nucleation conditions produced much more substantial changes. In particular, the initial precursor species (tert-butylphosphine versus triethygallium) and ALE cycle purge times both yielded significant influence over threading dislocation densities (TDD) in thin (100 nm), post-critical thickness GaP/Si films, with TDD spanning two orders of magnitude, from 6.7×10 7 cm -2 to 7.1×10 5 cm -2 , depending on the specific process conditions employed. SFP densities were also found to follow a similar trend, ranging from 2.0×10 7 cm -2 to 1.8×10 5 cm -2 , but with no apparent causal relationship between SFP density and TDD. To help explain the dramatic differences observed, detailed, large-area MD network characterization was used to provide statistically-relevant quantitative analyses of the critical dislocation dynamics (introduction rates and glide velocities) associated with the different process variants. These extracted values are then correlated against the ALE process variants to provide insight into the potential mechanistic roles of the different growth processes.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Optimizing the hypre solver for manycore and GPU architectures

The solution of large-scale combustion problems with codes such as Uintah on modern computer architectures requires the use of multithreading and GPUs to achieve performance. Uintah uses a low-Mach number approximation that requires iteratively solving a large system of linear equations. The Hypre iterative solver has solved such systems in a scalable way for Uintah, but the use of OpenMP with Hypre leads to at least slowdown due to OpenMP overheads. The proposed solution uses the MPI Endpoints within Hypre, where each team of threads acts as a different MPI rank. This approach minimizes OpenMP synchronization overhead and performs as fast or (up to 1.44) faster than Hypre's MPI-only version, and allows the rest of Uintah to be optimized using OpenMP. The profiling of the GPU version of Hypre shows the bottleneck to be the launch overhead of thousands of micro-kernels. The GPU performance was improved by fusing these micro-kernels and was further optimized by using Cuda-aware MPI, resulting in an overall speedup of 1.16—1.44 compared to the baseline GPU implementation. The above optimization strategies were published in the International Conference on Computational Science 2020 [1]. This work extends the previously published research by carrying out the second phase of communication-centered optimizations in Hypre to improve its scalability on large-scale supercomputers. Additionally, this includes an efficient non-blocking inter-thread communication scheme, communication-reducing patch assignment, and expression of logical communication parallelism to a new version of the MPICH library that utilizes the underlying network parallelism [2]. The above optimizations avoid communication bottlenecks previously observed during strong scaling and improve performance by up to 2 on 256 nodes of Intel Knight's Landing processor.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A microbenchmark characterization of the Emu chick

The Emu Chick is a prototype system designed around the concept of migratory memory-side processing. Rather than transferring large amounts of data across power-hungry, high-latency interconnects, the Emu Chick moves lightweight thread contexts to near-memory cores before the beginning of each memory read. The current prototype hardware uses FPGAs to implement cache-less “Gossamer” cores for computational work and rely on a typical stationary core (PowerPC) to run basic operating system functions and migrate threads between nodes. In this multi-node characterization of the Emu Chick, we extend an earlier single-node investigation of the the memory bandwidth characteristics of the system through benchmarks like STREAM, pointer chasing, and sparse matrix-vector multiplication. Here, we compare the Emu Chick hardware to architectural simulation and an Intel Xeon-based platform. Our results demonstrate that for many basic operations the Emu Chick can use available memory bandwidth more efficiently than a more traditional, cache-based architecture although bandwidth usage suffers for computationally intensive workloads like SpMV. Moreover, the Emu Chick provides stable, predictable performance with up to 65% of the peak bandwidth utilization on a random-access pointer chasing benchmark with weak locality.

97 MATHEMATICS AND COMPUTING↗