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At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Premixed flames subjected to extreme turbulence: Some questions and recent answers

It has been predicted that several changes will occur when premixed flames are subjected to the extreme levels of turbulence that can be found in practical combustors. Our report is a review of recent experimental and DNS results that have been obtained for the range of extreme turbulence, and it includes a discussion of cases that agree or disagree with predictions. “Extreme turbulence” is defined to correspond to a turbulent Reynolds number (Re Τ , based on integral scale) that exceeds 2800 or a turbulent Karlovitz number that exceeds 100, for reasons that are discussed in Section 2.1. Several data bases are described that include measurements made at Lund University, the University of Sydney, the University of Michigan and the U.S. Air Force Research Lab. The data bases also include DNS results from Sandia National Laboratory, the University of New South Wales, Newcastle University, the California Institute of Technology and the University of Cambridge. Several major observations are: (a) DNS now can be achieved for a realistic geometry (of the Lund University jet burner) even for extreme turbulence levels, (b) state relations (conditional mean profiles) from DNS and experiments do tend to agree with laminar profiles, at least for methane-air and hydrogen-air reactants that are not preheated, and (c) regime boundaries have been measured and they do not agree with predicted boundaries. Results indicate that the range of conditions for which flamelet models should be valid is larger than what was previously believed. Additional parameters have been shown to be important; for example, broken reactions occur if the “back-support” is insufficient due to the entrainment of cold gas into the product gas. Turbulent burning velocity measurements have been extended from the previous normalized turbulence levels (u’/S L ) of 24 up to a value of 163. Turbulent burning velocities no longer follow the trend predicted by Shchelkin but they tend to follow the trend predicted by Damköhler. The boundary where flamelet broadening begins was measured to occur at Re Taylor = 13.8, which corresponds to an integral scale Reynolds number (Re T ) of 2800. This measured regime boundary can be explained by the idea that flame structure is altered when the turbulent diffusivity at the Taylor scale exceeds a critical value, rather than the idea that changes occur when Kolmogorov eddies just fit inside a flamelet. A roadmap to extend DNS to complex chemistry and to higher Reynolds numbers is discussed. Exascale computers, machine learning, adaptive mesh refinement and embedded DNS show promise. Some advances are reviewed that have extended the use of line and planar PLIF and CARS laser diagnostics to studies that consider complex hydrocarbon fuels and harsh environments.

42 ENGINEERING↗
DOE OSTI2021

Towards grounding nuclear physics in QCD

Exascale computing could soon enable a predictive theory of nuclear structure and reactions rooted in the Standard Model, with quantifiable and systematically improvable uncertainties. Such a predictive theory will help exploit experiments that use nucleons and nuclei as laboratories for testing the Standard Model and its limitations. Examples include direct dark matter detection, neutrinoless double beta decay, and searches for permanent electric dipole moments of the neutron and atoms. It will also help connect QCD to the properties of cold neutron stars and hot supernova cores. We discuss how a quantitative bridge between QCD and the properties of nuclei and nuclear matter will require a synthesis of lattice QCD (especially as applied to two- and three- nucleon interactions), effective field theory, and ab initio methods for solving the nuclear many-body problem. While there are significant challenges that must be addressed in developing this triad of theoretical tools, the rapid advance of computing is accelerating progress. In particular, we focus this review on the anticipated advances from lattice QCD and how these advances will impact few-body effective theories of nuclear physics by providing critical input, such as constraints on unknown low-energy constants of the effective (field) theories. We also review particular challenges that must be overcome for the successful application of lattice QCD for low-energy nuclear physics. We describe progress in developing few-body effective (field) theories of nuclear physics, with an emphasis on HOBET, a non-relativistic effective theory of nuclear physics, which is less common in the literature. We use the examples of neutrinoless double beta decay and the nuclear-matter equation of state to illustrate how the coupling of lattice QCD to effective theory might impact our understanding of symmetries and exotic astrophysical environments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Programming approaches for scalability, performance, and portability of combustion physics codes

Here, this paper presents the process, strategy, and results associated with porting a typical combustion physics flow solver to current state-of-the-art and future massively-parallel computer architectures. Major focus is placed on the distinct algorithmic structure of these types of codes and how it can be integrated with modern programming paradigms for heterogeneous platforms (i.e., distributed many-core systems with accelerators). An end-to-end case study is presented that exemplifies the process in a generic manner, which then serves as a clear guide with respect to the strategy and best practices leading to a robust and adaptable framework that performs well, is durable over time, is portable, and requires minimal human-effort. This end is accomplished beginning with the use of a mature, validated, structured, multiblock code framework optimized for application of both Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS). This code has been ported to a variety of platforms over the past decade, including most recently the Oak Ridge Leadership Computing Facility’s “Summit” Platform. The experience gained on these multiple platforms provides general insights and thus the results presented are not specific to any one code or platform other than the overarching trend toward distributed many-core systems with accelerators in order to move toward exascale performance. The resultant performance and scalability of the ported code is demonstrated on a real-world application; a state-of-the-art rotating detonation rocket engine simulation that matches the complex geometry and boundary conditions imposed as part of a companion experimental campaign.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Mining Software Usage with the Automatic Library Tracking Database (ALTD)

Tracking software usage is important for HPC centers, computer vendors, code developers and funding agencies to provide more efficient and targeted software support, and to forecast needs and guide HPC software effort towards the Exascale era. However, accurately tracking software usage on HPC systems has been a challenging task. In this paper, we present a tool called Automatic Library Tracking Database (ALTD) that has been developed and put in production on several Cray systems. The ALTD infrastructure prototype automatically and transparently stores information about libraries linked into an application at compilation time and also the executables launched in a batch job. We will illustrate the usage of libraries, compilers and third party software applications on a system managed by the National Institute for Computational Sciences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

High-Order/Low-Order methods for ocean modeling

We examine a High Order/Low Order (HOLO) approach for a z-level ocean model and show that the traditional semi-implicit and split-explicit methods, as well as a recent preconditioning strategy, can easily be cast in the framework of HOLO methods. The HOLO formulation admits an implicit-explicit method that is algorithmically scalable and second-order accurate, allowing timesteps much larger than the barotropic time scale. We demonstrate how HOLO approaches, in particular the implicit-explicit method, can provide a solid route for ocean simulation to heterogeneous computing and exascale environments.

16 TIDAL AND WAVE POWER↗
DOE OSTI2018

Exploring the capabilities of support vector machines in detecting silent data corruptions

As the exascale era approaches, the increasing capacity of high-performance computing (HPC) systems with targeted power and energy budget goals introduces significant challenges in reliability. Silent data corruptions (SDCs), or silent errors, are one of the major sources that corrupt the execution results of HPC applications without being detected. Here in this paper, we explore a set of novel SDC detectors – by leveraging epsilon-insensitive support vector machine regression – to detect SDCs that occur in HPC applications. The key contributions are threefold. (1) Our exploration takes temporal, spatial, and spatiotemporal features into account and analyzes different detectors based on different features. (2) We provide an in-depth study on the detection ability and performance with different parameters, and we optimize the detection range carefully. (3) Experiments with eight real-world HPC applications show that support-vector-machine-based detectors can achieve detection sensitivity (i.e., recall) up to 99% yet suffer a less than 1% false positive rate for most cases. Our detectors incur low performance overhead, 5% on average, for all benchmarks studied in this work.

97 MATHEMATICS AND COMPUTING↗
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 OSTI2021

From NWChem to NWChemEx: Evolving with the Computational Chemistry Landscape

Since the advent of the first computers, chemists have been at the forefront of using computers to understand and solve complex chemical problems. As the hardware and software have evolved, so have the theoretical and computational chemistry methods and algorithms. Parallel computers clearly changed the common computing paradigm in the late 1970s and 80s, and the field has again seen a paradigm shift with the advent of graphical processing units. This review explores the challenges and some of the solutions in transforming software from the terascale to the petascale and now to the upcoming exascale computers. While discussing the field in general, NWChem and its redesign, NWChemEx, will be highlighted as one of the early codesign projects to take advantage of massively parallel computers and emerging software standards to enable large scientific challenges to be tackled.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Assembly and Analysis of Cell-Scale Membrane Envelopes

The march toward exascale computing will enable routine molecular simulation of larger and more complex systems, for example, simulation of entire viral particles, on the scale of approximately billions of atoms-a simulation size commensurate with a small bacterial cell. Anticipating the future hardware capabilities that will enable this type of research and paralleling advances in experimental structural biology, efforts are currently underway to develop software tools, procedures, and workflows for constructing cell-scale structures. Herein, we describe our efforts in developing and implementing an efficient and robust workflow for construction of cell-scale membrane envelopes and embedding membrane proteins into them. A new approach for construction of massive membrane structures that are stable during the simulations is built on implementing a subtractive assembly technique coupled with the development of a structure concatenation tool (fastmerge), which eliminates overlapping elements based on volumetric criteria rather than adding successive molecules to the simulation system. Using this approach, we have constructed two "protocells" consisting of MARTINI coarse-grained beads to represent cellular membranes, one the size of a cellular organelle and another the size of a small bacterial cell. The membrane envelopes constructed here remain whole during the molecular dynamics simulations performed and exhibit water flux only through specific proteins, demonstrating the success of our methodology in creating tight cell-like membrane compartments. Extended simulations of these cell-scale structures highlight the propensity for nonspecific interactions between adjacent membrane proteins leading to the formation of protein microclusters on the cell surface, an insight uniquely enabled by the scale of the simulations. We anticipate that the experiences and best practices presented here will form the basis for the next generation of cell-scale models, which will begin to address the addition of soluble proteins, nucleic acids, and small molecules essential to the function of a cell.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Enabling Multireference Calculations on Multimetallic Systems with Graphic Processing Units

Modeling multimetallic systems efficiently enables faster prediction of desirable chemical properties and the design of new materials. This work describes an initial implementation for performing multireference wave function method localized active-space self-consistent field (LASSCF) calculations through the use of multiple graphics processing units (GPUs) to accelerate time-to-solution. Density fitting is leveraged to reduce memory requirements, and we demonstrate the ability to fully utilize multi-GPU compute nodes. Performance improvements of 5–10x in total application runtime were observed in LASSCF calculations for multimetallic catalyst systems up to 1200 AOs and an active space of (22e,40o) using up to four NVIDIA A100 GPUs. Furthermore, written with performance portability in mind, a comparable performance is also observed in early runs on the Aurora exascale system using Intel Max Series GPUs.

Algorithms↗
DOE OSTI2019

Heterogeneous CPU+GPU-Enabled Simulations for DFTB Molecular Dynamics of Large Chemical and Biological Systems

We introduce a new heterogeneous CPU+GPU-enhanced DFTB approach for the routine and efficient simulation of large chemical and biological systems. Here, compared to homogenous computing with conventional CPUs, heterogeneous computing approaches exhibit substantial performance with only a modest increase in power consumption, both of which are essential to upcoming exascale computing initiatives. We show that DFTB-based molecular dynamics is a natural candidate for heterogeneous computing since the computational bottleneck in these simulations is the diagonalization of the Hamiltonian matrix, which is performed several times during a single molecular dynamics trajectory. To thoroughly test and understand the performance of our heterogeneous CPU+GPU approach, we examine a variety of algorithmic implementations, benchmarks of different hardware configurations, and applications of this methodology on several large chemical and biological systems. Finally, to demonstrate the capability of our implementation, we conclude with a large-scale DFTB MD simulation of explicitly solvated HIV protease (3,974 atoms total) as a proof-of-concept example of an extremely large/complex system which, to the best of our knowledge, is the first time that an entire explicitly-solvated protein has been treated at a quantum-based MD level of detail.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Field Programmable Gate Arrays for Enhancing the Speed and Energy Efficiency of Quantum Dynamics Simulations

We present the first application of field programmable gate arrays (FPGAs) as new, customizable hardware architectures for carrying out fast and energy-efficient quantum dynamics simulations of large chemical/material systems. Instead of tailoring the software to fixed hardware, which is the typical case for writing quantum chemistry code for central processing units (CPUs) and graphics processing units (GPUs), FPGAs allow us to directly customize the underlying hardware (even at the level of specific electrical signals in the circuit) to give a truly optimized computational performance for quantum dynamics calculations. By offloading the most intensive and repetitive calculations onto an FPGA, we show that the computational performance of our real-time electron dynamics calculations can even exceed that of optimized commercial mathematical libraries running on high-performance GPUs. In addition to this impressive computational speedup, we show that FPGAs are immensely energy-efficient and consume 4 times less energy than modern GPU or CPU architectures. These energy savings are a practical and important metric for supercomputing centers (many of which exceed over $1 million in power costs alone), as exascale computing capabilities become more widespread and commonplace. Taken together, the implementation techniques and performance metrics of our study demonstrate that FPGAs could play a promising role in upcoming quantum chemistry and materials science applications, particularly for the acceleration and energy-efficient execution of quantum dynamics calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Using Deep Neural Networks as Cost-Effective Surrogate Models for Super-Parameterized E3SM Radiative Transfer

Deep neural networks (DNNs) are implemented in Super-Parameterized Energy Exascale Earth System Model (SP-E3SM) to imitate the shortwave and longwave radiative transfer calculations. These DNNs were able to emulate the radiation parameters with an accuracy of 90–95% at a cost of 8–10 times cheaper than the original radiation parameterization. Here, a comparison of time-averaged radiative fluxes and the prognostic variables manifested qualitative and quantitative similarity between the DNN emulation and the original parameterization. It has also been found that the differences between the DNN emulation and the original parameterization are comparable to the internal variability of the original parameterization. Although the DNNs developed in this investigation emulate the radiation parameters for a specific set of initial conditions, the results justify the need of further research to generalize the use of DNNs for the emulations of full model radiation and other parameterization for seasonal predictions and climate simulations.

58 GEOSCIENCES↗
DOE OSTI2018

Model Resolution Sensitivity of the Simulation of North Atlantic Oscillation Teleconnections to Precipitation Extremes

We evaluate a high-resolution (0.25°), four-member ensemble simulation of the global climate (1979–2005) with the U.S. Department of Energy's Energy Exascale Earth System Model v0.3—forced with observed ocean surface temperatures and sea ice extent—for its ability to represent the North Atlantic Oscillation (NAO) teleconnections to winter precipitation extremes over western Europe. As compared to the low-resolution model (1°), it simulates a stronger impact of NAO on daily precipitation extremes over the western slopes of mountain ranges over southwestern Norway, northwestern United Kingdom, and the Western Balkan states. Precipitation extremes and their linear relationship with NAO are quantified using the generalized extreme value distribution. NAO-dependent large-scale (stratiform) precipitation intensity strengthens in the high-resolution model on seasonal time scales and plays a dominant role during simulated daily precipitation extremes. Improvements in the high-resolution model over these varied-topography regions largely appear to be due to finer resolved scales of motion that amplify NAO-dependent seasonal vertical moisture fluxes and enhance stable condensation. However, the high-resolution model simulates a weaker than observed impact of NAO on extratropical cyclone activity and total precipitable water, generally underperforming the low-resolution model These effects possibly offset the impact of enhanced vertical moisture fluxes on NAO-dependent precipitation extremes in the high-resolution model in these regions. Over the southwestern Iberian peninsula, the high-resolution model underperforms the low-resolution model simulating weaker than observed impact of NAO on precipitation extremes. Finally, this appears to be due to the reduction in total precipitable water despite an increase in NAO-dependent extratropical activity there.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Northern Hemisphere Blocking in ~25-km-Resolution E3SM v0.3 Atmosphere-Land Simulations

The fidelity of a prerelease Energy Exascale Earth System Model (E3SM) in reproducing atmospheric blocking is evaluated with ~100- and ~25-km horizontal resolution within ensembles of simulations with Atmospheric Modeling Intercomparison Protocol-type active atmosphere and land surface configurations. Here this evaluation is conducted via a hybrid bidimensional blocking index based on geopotential height. The lower-resolution model correctly reproduces the spatial distribution of blocking frequency maxima over the Northern Hemisphere. However, it overestimates the blocking frequency over western North America, the Pacific Northeast, and Eastern Europe regions and largely underestimates blocking frequency over the North Atlantic. The high-resolution model significantly reduces the bias over the North Pacific region, particularly over western North America, but the biases over the North Atlantic blocking sector mostly persist. A diagnosis of the mean flow reveals that the subtropical jet is displaced poleward in the high-resolution model with a jet core speed that is generally more realistic. A time scale analysis of eddies suggests that synoptic eddies associated with the blocking events are increased in the high-resolution configuration. The discrepancy between the models implies that both synoptic and low-frequency eddies play significant roles in determining North Pacific blocking, whereas North Atlantic blocking is mainly driven by low-frequency eddies. The characteristic time scale associated with blocking events is also investigated, and it shows that both model resolutions produce events that are overly persistent. However, the bias in the high-resolution model is reduced, which reflects more efficient energy dispersion with higher resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

An evaluation of the ocean and sea ice climate of E3SM using MPAS and interannual CORE-II forcing

The Energy Exascale Earth System Model (E3SM) is a new coupled Earth system model sponsored by the US Department of Energy. Here we present E3SM global simulations using active ocean and sea ice that are driven by the CORE–II inter–annual atmospheric forcing data set. The E3SM ocean and sea–ice components are MPAS–Ocean and MPAS–Seaice, which use the Model for Prediction Across Scales (MPAS) framework and run on unstructured horizontal meshes. For this study, grid cells vary from 30 to 60 km for the low resolution mesh and 6 to 18 km at high resolution. The vertical grid is a structured z–star coordinate and uses 60 and 80 layers for low and high resolution, respectively. The lower resolution simulation was run for five CORE cycles (310 years) with little drift in sea surface temperature or heat content. The meridional heat transport is within observational range, while the meridional overturning circulation at 26.5° N is low compared to observations. The largest temperature biases occur in the Labrador Sea and western boundary currents, and the mixed layer is deeper than observations at northern high latitudes in the winter months. In the Antarctic, maximum mixed layer depths (MLD) compare well with observations, but the spatial MLD pattern is shifted relative to observations. Sea–ice extent, volume and concentration agree well with observations. At high resolution, the sea surface height compares well with satellite observations in mean and variability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Improving Representation of Deforestation Effects on Evapotranspiration in the E3SM Land Model

Abstract Evapotranspiration (ET) plays an important role in land‐atmosphere coupling of energy, water, and carbon cycles. Following deforestation, ET is typically observed to decrease substantially as a consequence of decreases in leaf area and roots and increases in runoff. Changes in ET (latent heat flux) revise the surface energy and water budgets, which further affects large‐scale atmospheric dynamics and feeds back positively or negatively to long‐term forest sustainability. In this study, we used observations from a recent synthesis of 29 pairs of adjacent intact and deforested FLUXNET sites to improve model parameterization of stomatal characteristics, photosynthesis, and soil water dynamics in version 1 of the Energy Exascale Earth System Model (E3SM) Land Model (ELMv1). We found that default ELMv1 predicts an increase in ET after deforestation, likely leading to incorrect estimates of the effects of deforestation on land‐atmosphere coupling. The calibrated model accurately represented the FLUXNET observed deforestation effects on ET. Importantly, the search for global optimal parameters converged at values consistent with recent observational syntheses, confirming the reliability of the calibrated physical parameters. Applying this improved model parameterization to the globe scale reduced the bias of annual ET simulation by up to ~600 mm/year. Analysis on the roles of parameters suggested that future model development to improve ET simulation should focus on stomatal resistance and soil water‐related parameterizations. Finally, our predicted differences in seasonal ET changes from deforestation are large enough to substantially affect land‐atmosphere coupling and should be considered in such studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Representing Nitrogen, Phosphorus, and Carbon Interactions in the E3SM Land Model: Development and Global Benchmarking

Over the past several decades, the land modeling community has recognized the importance of nutrient regulation on the global terrestrial carbon cycle. Implementations of nutrient limitation in land models are diverse, varying from applying simple empirical down–regulation of potential gross primary productivity under nutrient deficit conditions to more mechanistic treatments. In this study, we introduce a new approach to model multinutrient (nitrogen [N] and phosphorus [P]) limitations in the Energy Exascale Earth System Model (E3SM) Land Model version 1 (ELMv1–ECA). The development is grounded on (1) advances in representing multiple–consumer, multiple–nutrient competition; (2) a generic dynamic allocation scheme based on water, N, P, and light availability; (3) flexible plant CNP stoichiometry; (4) prognostic treatment of N and P constraints on several carbon cycle processes; and (5) global data sets of plant physiological traits. Through benchmarking the model against best knowledge of global plant and soil carbon pools and fluxes, we show that our implementation of nutrient constraints on the present–day carbon cycle is robust at the global scale. Compared with predecessor versions, ELMv1–ECA better predicts global–scale gross primary productivity, ecosystem respiration, leaf area index, vegetation biomass, soil carbon stocks, evapotranspiration, N2O emissions, and NO3– leaching. Factorial experiments imply that representing the phosphorus cycle improves modeled carbon fluxes, while considering dynamic allocation improves modeled carbon stock density. We also illustrate the value of using the International Land Model Benchmarking (ILAMB) package to evaluate and document performance during model development.

58 GEOSCIENCES↗