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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Hydrotreatment of Nylon 66 and Amide Model Compounds Over Sulfided NiMo Catalysts

Molybdenum sulfide-based catalysts, such as nickel–molybdenum on alumina (NiMoS x /Al 2 O 3 ), are widely used in hydrotreating and have potential for catalyzing waste plastic conversion via hydrogenolysis, yet their performance, such as reaction kinetics and network, for amide-rich polymer feeds is poorly defined. Here we combine Nylon 66 with the amide model compound, N,N-dibutylhexanediamide (DBDAD), to quantify hydrodeoxygenation (HDO) and hydrodenitrogenation (HDN) chemistry in a stirred batch reactor (53 bar H 2 , 280–320°C). DBDAD conversion is near-linear with time, indicating strong adsorption of the substrates on the active sites. Time-resolved product identification indicates parallel C─O first-cleavagedeoxygenation (DO) and C─N first-cleavagedenitrogenation (DN) sequences proceeding through amine and diol intermediates, respectively, to C 4 ─C 6 alkanes. Increasing temperature shifts selectivity toward DN, decreasing the initial r(DO)/r(DN) from 1.38 (280°C) to 0.69 (320°C), with an apparent activation energy of 173 kJ mol −1 for DBDAD conversion. At 300°C, nylon 66 converts faster than DBDAD, producing a complex mixture of oxygen- and nitrogen-containing species and an initial rate ratio r(DO)/r(DN) of 1.6. No heteroaromatic nitrogen products are detected by the method used. These results provide reaction pathways and product signatures relevant to hydro-processing catalysts exposed to polyamide-derived streams.

Nylon 66↗
DOE OSTI2024

Single-Shot Decoding of Good Quantum LDPC Codes

Abstract Quantum Tanner codes constitute a family of quantum low-density parity-check codes with good parameters, i.e., constant encoding rate and relative distance. In this article, we prove that quantum Tanner codes also facilitate single-shot quantum error correction (QEC) of adversarial noise, where one measurement round (consisting of constant-weight parity checks) suffices to perform reliable QEC even in the presence of measurement errors. We establish this result for both the sequential and parallel decoding algorithms introduced by Leverrier and Zémor. Furthermore, we show that in order to suppress errors over multiple repeated rounds of QEC, it suffices to run the parallel decoding algorithm for constant time in each round. Combined with good code parameters, the resulting constant-time overhead of QEC and robustness to (possibly time-correlated) adversarial noise make quantum Tanner codes alluring from the perspective of quantum fault-tolerant protocols.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

DECA: Discrete Event inspired Cellular Automata for grain structure prediction in additive manufacturing

Microstructure largely dictates macroscopic material properties and is strongly affected by processing. Therefore, the simulation of microstructure evolution in response to thermal fields during processing is of significant interest within the computational materials science community. Additive manufacturing (AM) has emerged as a technique for producing complex geometries and unique microstructures. Yet, complex and rapid thermal cycles in AM pose computational challenges for existing microstructure models. This work proposes a discrete event inspired cellular automata (CA) approach, titled DECA, to accelerate simulation of grain structure evolution in AM. In contrast to conventional time-stepped CA models, this model directly solves the times capture events would take place allowing for stepping in events rather than time (a technique also found in the field of discrete-event simulation). In comparison to purely serial discrete-event models, DECA allows for temporary violation of the causality constraint, but detects and corrects these violations, leading to an emergent phenomenon dubbed causality rippling, in which previously calculated capture events are overwritten. The amount of repeated calculations, defined by the capture ratio, is taken as a measure of computational inefficiency, and the model parameters that affect this ratio are evaluated. The new DECA approach was found to be more computationally efficient than conventional time-stepped CA models while guaranteeing an accurate solution, which can only be achieved in the conventional models for vanishingly small time steps. Finally, opportunities for parallelization and scaling of the new approach are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2020

NESSi : The N on- E quilibrium S ystems S imulation package

The nonequilibrium dynamics of correlated many-particle systems is of interest in connection with pump–probe experiments on molecular systems and solids, as well as theoretical investigations of transport properties and relaxation processes. Nonequilibrium Green’s functions are a powerful tool to study interaction effects in quantum many-particle systems out of equilibrium, and to extract physically relevant information for the interpretation of experiments. Here, we present the open-source software package NESSi (The Non-Equilibrium Systems Simulation package) which allows to perform many-body dynamics simulations based on Green’s functions on the L-shaped Kadanoff–Baym contour. NESSi contains the library libcntr which implements tools for basic operations on these nonequilibrium Green’s functions, for constructing Feynman diagrams, and for the solution of integral and integro-differential equations involving contour Green’s functions. The library employs a discretization of the Kadanoff–Baym contour into time points and a high-order implementation of integration routines. The total integrated error scales up to $\mathcal{O}(N^{-7})$, which is important since the numerical effort increases at least cubically with the simulation time. A distributed-memory parallelization over reciprocal space allows large-scale simulations of lattice systems. We provide a collection of example programs ranging from dynamics in simple two-level systems to problems relevant in contemporary condensed matter physics, including Hubbard clusters and Hubbard or Holstein lattice models. The libcntr library is the basis of a follow-up software package for nonequilibrium dynamical mean-field theory calculations based on strong-coupling perturbative impurity solvers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

HiPACE++: A portable, 3D quasi-static particle-in-cell code

Modeling plasma accelerators is a computationally challenging task and the quasi-static particle-in-cell algorithm is a method of choice in a wide range of situations. In this work, we present the first performance-portable, quasi-static, three-dimensional particle-in-cell code HiPACE++. By decomposing all the computation of a 3D domain in successive 2D transverse operations and choosing appropriate memory management, HiPACE++ demonstrates orders-of-magnitude speedups on modern scientific GPUs over CPU-only implementations. The 2D transverse operations are performed on a single GPU, avoiding time-consuming communications. The longitudinal parallelization is done through temporal domain decomposition, enabling near-optimal strong scaling from 1 to 512 GPUs. HiPACE++ is a modular, open-source code enabling efficient modeling of plasma accelerators from laptops to state-of-the-art supercomputers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Space–time reduced order model for large-scale linear dynamical systems with application to Boltzmann transport problems

A classical reduced order model for dynamical problems involves spatial reduction of the problem size. However, temporal reduction accompanied by the spatial reduction can further reduce the problem size without losing much accuracy, which results in a considerably more speed-up than the spatial reduction only. Recently, a novel space–time reduced order model for dynamical problems has been developed [17], where the space–time reduced order model shows an order of a hundred speed-up with a relative error of 10 –4 for small academic problems. However, in order for the method to be applicable to a large-scale problem, an efficient space–time reduced basis construction algorithm needs to be developed. Here we present the incremental space–time reduced basis construction algorithm. The incremental algorithm is fully parallel and scalable. Additionally, the block structure in the space–time reduced basis is exploited, which enables the avoidance of constructing the reduced space–time basis. These novel techniques are applied to a large-scale particle transport simulation with million and billion degrees of freedom. The numerical example shows that the algorithm is scalable and practical. Also, it achieves a tremendous speed-up, maintaining a good accuracy. Finally, error bounds for space-only and space–time reduced order models are derived.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Coping with silent and fail-stop errors at scale by combining replication and checkpointing

This paper provides a model and an analytical study of replication as a technique to cope with silent errors, as well as a mixture of both silent and fail-stop errors on large-scale platforms. Compared with fail-stop errors that are immediately detected when they occur, silent errors require a detection mechanism. To detect silent errors, many application-specific techniques are available, either based on algorithms (e.g., ABFT), invariant preservation or data analytics, but replication remains the most transparent and least intrusive technique. We explore the right level (duplication, triplication or more) of replication for two frameworks: (i) when the platform is subject to only silent errors, and (ii) when the platform is subject to both silent and fail-stop errors. A higher level of replication is more expensive in terms of resource usage but enables to tolerate more errors and to even correct some errors, hence there is a trade-off to be found. Replication is combined with checkpointing and comes with two flavors: process replication and group replication. Process replication applies to message-passing applications with communicating processes. Each process is replicated, and the platform is composed of process pairs, or triplets. Group replication applies to black-box applications, whose parallel execution is replicated several times. The platform is partitioned into two halves (or three thirds). In both scenarios, results are compared before each checkpoint, which is taken only when both results (duplication) or two out of three results (triplication) coincide. Otherwise, one or more silent errors have been detected, and the application rolls back to the last checkpoint, as well as when fail-stop errors have struck. We provide a detailed analytical study for all of these scenarios, with formulas to decide, for each scenario, the optimal parameters as a function of the error rate, checkpoint cost, and platform size. We also report a set of extensive simulation results that nicely corroborates the analytical model.

Checkpointing↗
DOE OSTI2023

Near-continuum, hypersonic oxygen flow over a double cone simulated by direct simulation Monte Carlo informed from quantum chemistry

A large-scale, fully resolved direct simulation Monte Carlo (DSMC) computation of a non-equilibrium, reactive flow of pure oxygen over a double cone is presented. Under the simulated near-continuum conditions, the computational demands are shown to be significant because of the wide range of length scales that must be resolved. Therefore, robust grid adaption capabilities and efficient parallelization of the Stochastic PArallel Rarefied-gas Time-accurate Analyzer (SPARTA) code that is utilized in this work are essential. The thermochemical and transport collision models were selected for efficiency and simplicity. First-principles data, obtained from the highly accurate direct molecular simulation method, were used to inform the collision models’ parameters. Importantly, because SPARTA implements molecular collision models using collision-specific energies, the resulting macroscopic relaxation rates were evaluated a posteriori via zero-dimensional heat bath simulations. The comparisons of surface properties, namely heat flux and pressure, show very close agreement with previous computational fluid dynamics (CFD) results. Differences with the measurements were found to be similar to the CFD simulations. The unresolved discrepancy with the measurements could be due to inconsistent free stream conditions with the actual experimental data or missing physical phenomena altogether, for example atomic and molecular oxygen electronically excited states, three-dimensional effects, or more complex gas–surface interactions. As shown in this work, the advantages of obtaining a DSMC particle solution for these flows reside in the method's ability to be directly informed from first principles and to seamlessly describe internal energy non-equilibrium for all modes. With the advent of exascale computing and beyond, particle methods will be an increasingly important tool to verify the validity of physical assumptions in reduced-order models via fully resolved, experimental-scale simulations, down to the level of molecular-level distributions.

Mechanics↗
DOE OSTI2022

Fe Oxidation and Species Distribution at the Rock–Fluid Interface of Marcellus Shale Reacted with Hydraulic Fracturing Fluid

Hydraulic fracturing of shale reservoirs resulted in significant opportunity for increased oil and gas production in the United States. Rock-fluid interactions can cause mineral dissolution and precipitation reactions that lead to permeability changes in the shale matrix, which ultimately may affect transport pathways and hydrocarbon production. Understanding the distribution of secondary precipitates, such as barite and Fe(III) (hydro)oxides, and cation leaching at the rock-fluid interface is an important step to further investigate how these geochemical processes can change permeability and transport pathways. In this study, thin sections of the fracture-matrix interface were made from reacted Marcellus shale cores. The thin sections were characterized using synchrotron X-ray fluorescence imaging and synchrotron X-ray absorption spectroscopy. Fe species with different oxidation states were identified in the maps, together with barite and Ca distribution. The results show that ferrihydrite, as newly formed Fe(III)-bearing precipitates, aligned well with the border of the Ca (e.g., calcite) leaching region in the reaction front. Some Fe-containing clay also dissolved, but the dissolution region for the clay was not as deep as the calcite. Further, the reaction front is about three times deeper in the direction parallel to the shale bedding than that perpendicular to the bedding. The Ca leaching region can be an index for reaction front detection for Marcellus shale. Reactive transport modeling was conducted and the predicted Ca leaching boarder align well with ferrihydrite precipitation, consistent with the experimental observation. The carbonate mineral dissolution can be crucial to promote fluid access into the shale matrix. Together with our previous study on the shale reactive surface, this follow-up study showed similar Ca leaching region and Fe(III) precipitates distribution in the reaction front regardless of barite precipitation on the surface, indicating that the barite coatings on the surface may not pose a significant impact on reactive transport at the shale-fluid interface.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2026

Interfacial Inversion of Stealth Surfactants

Amphiphilic macromolecular surfactants segregate to liquid–liquid interfaces, thereby reducing the interfacial tension and free energy. Here, we investigated “stealth surfactants” in the form of core–shell bottlebrush polymers comprised of pH-responsive diblock copolymer side chains forming a hydrophilic core and a hydrophobic shell, enabling solubility in oil. At liquid–liquid interfaces, these polymers undergo a structural “inversion”, with hydrophilic blocks segregating into the aqueous phase and hydrophobic blocks residing in the oil phase. The reconfiguration kinetics and surfactant properties are influenced by multiple factors, including the molecular weights of the backbone and side chain components, the hydrophilic-to-hydrophobic balance of the side chains, and the pH of the aqueous phase. An observed nonmonotonic dependence of interfacial tension with time is attributed to a progressive structural inversion, where the projected area of the macromolecule onto the interface decreases. To validate this inversion hypothesis, interfacial properties were characterized by sum-frequency generation vibrational spectroscopy, which revealed configurational changes of the core–shell bottlebrush polymers at the fluid interface and revealed a pH-dependent interfacial coverage. Coarse-grained molecular dynamics simulations supported these experimental findings, showing that the pH-responsive core and hydrophobic shell assume a time-averaged configuration with orientations parallel and perpendicular to the plane of the interface, respectively. These findings open routes to design multistimuli-responsive polymeric surfactants and compatibilizers, expanding their potential applications in advanced interfacial systems.

Stealth surfactants↗
DOE OSTI2017

The structure of bow shocks formed by the interaction of pulsed-power driven magnetised plasma flows with conducting obstacles

We present an experimental study of the development and structure of bow shocks produced by the interaction of a magnetised, collisional, super-Alfvénic plasma flow with conducting cylindrical obstacles. The plasma flow with an embedded, frozen-in magnetic field (Re M ~ 20) is produced by the current-driven ablation of fine aluminium wires in an inverse, exploding wire array z-pinch. We show that the orientation of the embedded field with respect to the obstacles has a dramatic effect on the bow shock structure. When the field is aligned with the obstacle, a sharp bow shock is formed with a global structure that is determined simply by the fast magneto-sonic Mach number. When the field is orthogonal to the obstacle, magnetic draping occurs. This leads to the growth of a magnetic precursor and the subsequent development of a magnetised bow shock that is mediated by two-fluid effects, with an opening angle and a stand-off distance, that are both many times larger than in the parallel geometry. By changing the field orientation, we change the fluid regime and physical mechanisms that are responsible for the development of the bow shocks. MHD simulations show good agreement with the structure of well-developed bow shocks. However, collisionless, two-fluid effects will need to be included within models to accurately reproduce the development of the shock with an orthogonal B-field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Drive-pressure optimization in ramp-wave compression experiments through differential evolution

Ramp-wave dynamic-compression experiments are used to examine quasi-isentropic loading paths in materials. The gradual and continuous increase in pressure created by ramp waves make these types of experiments ideal for studying nonequilibrium material behavior, such as solidification kinetics. In ramp-wave compression experiments, the input drive pressure to the experimental setup may be exerted through one of a number of different mechanisms (e.g., magnetic fields, gas-gun-driven impactors, or high-energy lasers) and is generally required for simulating such experiments. Yet, regardless of the specific mechanism, this drive pressure cannot be measured directly (measurements are generally taken at a location near the back of the experimental setup through a transparent window), leading to an inverse problem where one must determine the drive pressure at the front of the experimental setup (i.e., the input) that corresponds to the particle velocity (the output) measured near the back of the experimental setup. Furthermore, we solve this inverse problem using a heuristic optimization algorithm, known as differential evolution, coupled with a multiphysics, hydrodynamics code that simulates the compression of the experimental setup. By running many rounds of forward simulations of the experimental setup, our optimization process iteratively searches for a drive pressure that is optimized to closely reproduce the experimentally measured particle velocity near the back of the experimental setup. While our optimization methodology requires a significant number of hydrodynamics simulations to be conducted, many of these can be performed in parallel, which greatly reduces the time cost of our methodology. One novel aspect of our method for determining the drive pressure is that it does not require physical modeling of the drive mechanism and can thus be broadly applied to many types of ramp-compression experiments, regardless of the drive mechanism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

GPU-accelerated dislocation dynamics using subcycling time-integration

Discrete dislocation dynamics (DDD) simulations are being increasingly employed to investigate metal plasticity at the mesoscale. However, in spite of its ability to access beyond the length and time limits of atomistic methods, the DDD model is still limited by its high computational cost, with ranges of achievable strains too low and strain rates too high by several orders of magnitude compared with typical experimental conditions. By combining the efficiency of the recently developed subcycling time-integrator with the highly parallel architecture of graphics processing unit (GPU) devices, we developed a DDD model that provides significant acceleration compared to existing implementations. Our GPU-accelerated implementation enables large-scale DDD simulations that can reach relevant levels of strain using a moderate amount of computational resources.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hvac: Removing I/O Bottleneck for Large-Scale Deep Learning Applications

Scientific communities are increasingly adopting deep learning (DL) models in their applications to accelerate scientific discovery processes. However, with rapid growth in the computing capabilities of HPC supercomputers, large-scale DL applications have to spend a significant portion of training time performing I/O to a parallel storage system. Previous research works have investigated optimization techniques such as prefetching and caching. Unfortunately, there exist non-trivial challenges to adopting the existing solutions on HPC supercomputers for large-scale DL training applications, which include non-performance and/or failures at extreme scale, lack of portability and generality in design, complex deployment methodology, and being limited to a specific application or dataset. To address these challenges, we propose High-Velocity AI Cache (HVAC), a distributed read-cache layer that targets and fully exploits the node-local storage or near node-local storage technology. HVAC seamlessly accelerates read I/O by aggregating node-local or near node-local storage, avoiding metadata lookups and file locking while preserving portability in the application code. We deploy and evaluate HVAC on 1,024 nodes (with over 6000 NVIDIA V100 GPUS) of the Summit supercomputer. In particular, we evaluate the scalability, efficiency, accuracy, and load distribution of HVAC compared to GPFS and XFS-on-NVMe. With four different DL applications, we observe an average 25 % performance improvement atop GPFS and 9% drop against XFS-on-NVMe, which scale linearly and are considered the performance upper bound. We envision HVAC as an important caching library for upcoming HPC supercomputers such as Frontier.

Khan, Awais↗
DOE OSTI2020

2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)

Recent proliferation of distributed energy sources in distribution or sub-transmission systems necessitates close monitoring of these three-phase power grids which typically operate under unbalanced loading conditions. Unlike the transmission systems where the network equations are commonly based on the positive sequence component models, a detailed three phase model will have to be used in implementing network applications for these systems. In the specific case of the state estimator, where measurement and parameter errors may bias the solution, bad data and parameter error detection algorithms should also be incorporated. Implementing the state estimator and error detection algorithms for three-phase systems impose additional computational burden and modifications to the state estimation code. This paper proposes a practical solution to avoid these issues by using synchronized phasor measurements and modal decoupling. The previously developed parameter error detection algorithm based on the normalized Lagrange multipliers (NLM) test is applied to the measurements independently in each mode in parallel, not only saving CPU time but also avoiding new code development for a three-phase estimator. Different parameter error scenarios are created and tested to verify the effectiveness of the proposed error detection approach.

Khalili, Ramtin↗
DOE OSTI2018

Physics-Dynamics Coupling in Weather, Climate, and Earth System Models: Challenges and Recent Progress

Geophysical models of the atmosphere and ocean invariably involve parameterizations. These represent two distinct areas: a) Subgrid processes which the model cannot (yet) resolve, due to its discrete resolution, and b) sources in the equation, due to radiation for example. Hence coupling between these physics parameterizations and the resolved fluid dynamics and also between the dynamics of the different fluids in the system (air and water) is necessary. This coupling is an important aspect of geophysical models. However, often model development is strictly segregated into either physics or dynamics. Hence, this area has many more unanswered questions than in-depth understanding. Furthermore, recent developments in the design of dynamical cores (significant increase of resolution, move to non-hydrostatic equation sets etc), extended process physics (prognostic micro physics, 3D turbulence, non-vertical radiation etc) and predicted future changes of the computational infrastructure (Exascale with its need for task parallelism, data locality and asynchronous time stepping for example) is adding even more complexity and new questions.

Gross, Markus↗
DOE OSTI2021

Dynamic Ride-Matching for Large-Scale Transportation Systems

Efficient dynamic ride-matching (DRM) in large-scale transportation systems is a key driver in transport simulations to yield answers to challenging problems. Although the DRM problem is simple to solve, it quickly becomes a computationally challenging problem in large-scale transportation system simulations. Therefore, this study thoroughly examines the DRM problem dynamics and proposes an optimization-based solution framework to solve the problem efficiently. To benefit from parallel computing and reduce computational times, the problem’s network is divided into clusters utilizing a commonly used unsupervised machine learning algorithm along with a linear programming model. Then, these sub-problems are solved using another linear program to finalize the ride-matching. At the clustering level, the framework allows users adjusting cluster sizes to balance the trade-off between the computational time savings and the solution quality deviation. A case study in the Chicago Metropolitan Area, U.S., illustrates that the framework can reduce the average computational time by 58% at the cost of increasing the average pick up time by 26% compared with a system optimum, that is, non-clustered, approach. Another case study in a relatively small city, Bloomington, Illinois, U.S., shows that the framework provides quite similar results to the system-optimum approach in approximately 62% less computational time.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Automatic identification and classification of Palomar Transient Factory astrophysical objects in GLADE

Palomar Transient Factory (PTF) is a comprehensive detection system for the identification and classification of transient astrophysical objects. In this paper, we make two significant contributions to the PTF pipeline. First, we present an experimental study that evaluates a novel implementation of the real-time classifier in GLADE - a parallel data processing system that combines the efficiency of a database with the extensibility of map-reduce. We show how each stage in the classifier maps optimally into GLADE tasks by taking advantage of the unique features of the system - range-based data partitioning, columnar storage, multi-query execution, and in-database support for complex aggregate computation. Second, we introduce a novel parallel similarity join algorithm for advanced transient classification. In conclusion, we implement this algorithm in GLADE and execute it on a massive supercomputer with more than 3,000 threads, achieving more than three orders of magnitude improvement over the PostgreSQL solution.

79 ASTRONOMY AND ASTROPHYSICS↗