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All sources NASA NTRS DOE OSTI

DOE OSTI2019

Updraft Constraints on Entrainment: Insights from Amazonian Deep Convection

Abstract Mixing of environmental air into clouds, or entrainment, has been identified as a major contributor to erroneous climate predictions made by modern comprehensive climate and numerical weather prediction models. Despite receiving extensive attention, the ad hoc treatment of this convective-scale process in global models remains poor. On the other hand, while limited-area high-resolution nonhydrostatic models can directly resolve entrainment, their sensitivity to model resolution, especially with the lack of benchmark mass flux observations, limits their applicability. Here, the dataset from the Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) campaign focusing on radar retrievals of convective updraft vertical velocities is used with the aid of cloud-resolving model simulations of four deep convective events over the Amazon to provide insights into entrainment. Entrainment and detrainment are diagnosed from the model simulations by applying the mass continuity equation over cloud volumes, in which grid cells are identified by some thresholds of updraft vertical velocity and cloud condensates, and accounting for the sources and sinks of the air mass. Entrainment is then defined as the environmental air intruding into convective cores causing cloud volume to shrink, while detrainment is defined as cloudy grid cells departing the convective core and causing cloud volume to expand. It is found that the diagnosed entrainment from the simulated convective events is strongly correlated to the inverse of the updraft vertical velocities in convective cores, which enables a more robust estimation of the mixing time scale. This highlights the need for improved observational capabilities for sampling updraft velocities across diverse geographic and cloud conditions. Evaluation of a number of assumptions used to represent entrainment in parameterization schemes is also presented, as contrasted against the diagnosed one.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Tracking studies in eRHIC energy-recovery recirculator

Beam and polarization tracking studies in eRHIC energy recovery electron recirculator are presented, based on a very preliminary design of the FFAG lattice. These simulations provide examples of some of the beam and spin optics aspects of the linear FFAG lattice concept and its application in eRHIC, they provide code benchmarking for synchrotron radiation and spin diffusion in addition, and pave the way towards end-to-end 6-D(phasespace)+3D(spin) tracking simulations.

43 PARTICLE ACCELERATORS↗

DOE OSTI2017

Clean Energy Manufacturing Analysis Center Benchmark Report: Framework and Methodologies

This report documents the CEMAC methodologies for developing and reporting annual global clean energy manufacturing benchmarks. The report reviews previously published manufacturing benchmark reports and foundational data, establishes a framework for benchmarking clean energy technologies, describes the CEMAC benchmark analysis methodologies, and describes the application of the methodologies to the manufacturing of four specific clean energy technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2016

Reactivity Insertion Accident (RIA) Capability Status in the BISON Fuel Performance Code

One of the Challenge Problems being considered within CASL relates to modelling and simulation of Light Water Reactor LWR) fuel under Reactivity Insertion Accident (RIA) conditions. BISON is the fuel performance code used within CASL for LWR fuel under both normal operating and accident conditions, and thus must be capable of addressing the RIA challenge problem. This report outlines required BISON capabilities for RIAs and describes the current status of the code. Information on recent accident capability enhancements, application of BISON to a RIA benchmark exercise, and plans for validation to RIA behavior are included.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

Sensitivity/Uncertainty Comparison Study: Oak Ridge National Laboratory Results [Slides]

Various methods and sensitivity/uncertainty tools have been developed over the years to assist in determining upper subcritical limits (USLs). The task is to compare calculated USLs from various methods on a small set of benchmark problems. The benchmark experiments selected are the following applications: HEU-MET-FAST-013-001, HEU-SOL-THERM-001-008, PU-MET-FAST-022-001, and PU-SOL-THERM-001-001.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Multifidelity Monte Carlo estimation for efficient uncertainty quantification in climate-related modeling

Abstract. Uncertainties in an output of interest that depends on the solution of a complex system (e.g., of partial differential equations with random inputs) are often, if not nearly ubiquitously, determined in practice using Monte Carlo (MC) estimation. While simple to implement, MC estimation fails to provide reliable information about statistical quantities (such as the expected value of the output of interest) in application settings such as climate modeling, for which obtaining a single realization of the output of interest is a costly endeavor. Specifically, the dilemma encountered is that many samples of the output of interest have to be collected in order to obtain an MC estimator that has sufficient accuracy – so many, in fact, that the available computational budget is not large enough to effect the number of samples needed. To circumvent this dilemma, we consider using multifidelity Monte Carlo (MFMC) estimation which leverages the use of less costly and less accurate surrogate models (such as coarser grids, reduced-order models, simplified physics, and/or interpolants) to achieve, for the same computational budget, higher accuracy compared to that obtained by an MC estimator – or, looking at it another way, an MFMC estimator obtains the same accuracy as the MC estimator at lower computational cost. The key to the efficacy of MFMC estimation is the fact that most of the required computational budget is loaded onto the less costly surrogate models so that very few samples are taken of the more expensive model of interest. We first provide a more detailed discussion about the need to consider an alternative to MC estimation for uncertainty quantification. Subsequently, we present a review, in an abstract setting, of the MFMC approach along with its application to three climate-related benchmark problems as a proof-of-concept exercise.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2005

Bayesian Retrieval of Complete Posterior PDFs of Oceanic Rain Rate From Microwave Observations

This paper presents a new Bayesian algorithm for retrieving surface rain rate from Tropical Rainfall Measurements Mission (TRMM) Microwave Imager (TMI) over the ocean, along with validations against estimates from the TRMM Precipitation Radar (PR). The Bayesian approach offers a rigorous basis for optimally combining multichannel observations with prior knowledge. While other rain rate algorithms have been published that are based at least partly on Bayesian reasoning, this is believed to be the first self-contained algorithm that fully exploits Bayes Theorem to yield not just a single rain rate, but rather a continuous posterior probability distribution of rain rate. To advance our understanding of theoretical benefits of the Bayesian approach, we have conducted sensitivity analyses based on two synthetic datasets for which the true conditional and prior distribution are known. Results demonstrate that even when the prior and conditional likelihoods are specified perfectly, biased retrievals may occur at high rain rates. This bias is not the result of a defect of the Bayesian formalism but rather represents the expected outcome when the physical constraint imposed by the radiometric observations is weak, due to saturation effects. It is also suggested that the choice of the estimators and the prior information are both crucial to the retrieval. In addition, the performance of our Bayesian algorithm is found to be comparable to that of other benchmark algorithms in real-world applications, while having the additional advantage of providing a complete continuous posterior probability distribution of surface rain rate.

Chiu, J. Christine↗

NASA NTRS2013

Application of Statistically Derived CPAS Parachute Parameters

The Capsule Parachute Assembly System (CPAS) Analysis Team is responsible for determining parachute inflation parameters and dispersions that are ultimately used in verifying system requirements. A model memo is internally released semi-annually documenting parachute inflation and other key parameters reconstructed from flight test data. Dispersion probability distributions published in previous versions of the model memo were uniform because insufficient data were available for determination of statistical based distributions. Uniform distributions do not accurately represent the expected distributions since extreme parameter values are just as likely to occur as the nominal value. CPAS has taken incremental steps to move away from uniform distributions. Model Memo version 9 (MMv9) made the first use of non-uniform dispersions, but only for the reefing cutter timing, for which a large number of sample was available. In order to maximize the utility of the available flight test data, clusters of parachutes were reconstructed individually starting with Model Memo version 10. This allowed for statistical assessment for steady-state drag area (CDS) and parachute inflation parameters such as the canopy fill distance (n), profile shape exponent (expopen), over-inflation factor (C(sub k)), and ramp-down time (t(sub k)) distributions. Built-in MATLAB distributions were applied to the histograms, and parameters such as scale (sigma) and location (mu) were output. Engineering judgment was used to determine the "best fit" distribution based on the test data. Results include normal, log normal, and uniform (where available data remains insufficient) fits of nominal and failure (loss of parachute and skipped stage) cases for all CPAS parachutes. This paper discusses the uniform methodology that was previously used, the process and result of the statistical assessment, how the dispersions were incorporated into Monte Carlo analyses, and the application of the distributions in trajectory benchmark testing assessments with parachute inflation parameters, drag area, and reefing cutter timing used by CPAS.

Romero, Leah M.↗

NASA NTRSDate not supplied

A Study of Parallel Scalability and Dynamic Workload Balancing in GlennICE

The Glenn Icing Computational Environment (GlennICE) is a computational tool designed to calculate ice growth on complex three-dimensional geometries. It utilizes user-supplied computational fluid dynamics solutions for the geometry of interest. Key developments include advancements in convergence of collection efficiency, trajectory optimization, and refinement methodology. These improvements have significantly enhanced GlennICE’s efficiency for practical engineering applications. A recent study focused on benchmarking GlennICE’s scalability in a parallel environment using static scheduling. Findings indicated a potential twofold increase in efficiency through workload balance enhancements. This paper presents an analysis of the solver’s new workload balancing improvements, incorporating shared memory and dynamic scheduling routines. Results demonstrate a highly efficient and consistent algorithm across high-performance computing clusters.

Computational Icing↗

NASA NTRSDate not supplied

A Study of Parallel Scalability and Dynamic Workload Balancing in GlennICE

Computational Icing↗

DOE OSTI2011

Dynamic Time-Variant Connection Management for PGAS Models on InfiniBand

InfiniBand (IB) has established itself as a promising network infrastructure for high-end cluster computing systems as evidenced by its usage in the Top500 supercomputers today. While the IB standard describes multiple communication models (including reliable-connection (RC), and unreliable datagram (UD)), most of its promising features such as remote direct memory access (RDMA), hardware atomics and network fault tolerance are only available for the RC model which requires connections between communicating process pairs. In the past, several researchers have proposed on-demand connection management techniques that establish connections when there is a need to communicate, and not before. While such techniques work well for algorithms and applications that only communicate with a small set of processes in their life-time, there exists a broad set of applications that do not follow this trend. For example, applications that perform dynamic load balancing and adaptive work stealing have a small set of communicating neighbors at any given time, but over time the total number of neighbors can be very high; in some cases, equal to the entire system size. In this paper, we present a dynamic time-variant connection management approach that establishes connections on-demand like previous approaches, but further intelligently tears down some of the unused connections as well. While connection tear-down itself is relevant for any programming model, different models have different complexities. In this paper, we study the Global Arrays (GA) PGAS model for two reasons: (1) the simple one-sided communication primitives provided by GA and other PGAS models ensure that connection requests are always initiated by the origin process without explicit synchronization with the target process---this makes connection tear-down simpler to handle; and (2) GA supports several applications that demonstrate this behavior making it an obvious first target for the proposed enhancements. We evaluate our proposed approach using several micro-benchmarks as well as the NWChem computational chemistry application on more than 6000 processes, and show that our approach can significantly reduce the memory requirements of the communication library while maintaining its performance. To the best of our knowledge, this is the first design, implementation and evaluation of connection tear-down protocols over InfiniBand.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2011

An Expanded Criticality Validation Suite for MCNP [Slides]

The Expanded Validation Suite provides a significant advance in the quality assurance and verification/ validation of MCNP for criticality problems. The careful selection of Handbook benchmark problems that span the expected application space provides the required broad coverage of code applicability. For validation purposes, it is expected that the suite will be used with different cross section libraries, e.g., ENDF/B-VII.1, to broadly assess the impact of library improvements. For practitioners, the suite may also serve as a starting point for validating MCNP and its data libraries for their specific applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2013

Efficiency and accuracy of the perturbation response coefficient generation method for whole core comet calculations in BWR and CANDU configurations

The coarse mesh transport method (COMET) is a highly accurate and efficient computational tool which predicts whole-core neutronics behaviors for heterogeneous reactor cores via a pre-computed eigenvalue-dependent response coefficient (function) library. Recently, a high order perturbation method was developed to significantly improve the efficiency of the library generation method. In that work, the method's accuracy and efficiency was tested in a small PWR benchmark problem. This paper extends the application of the perturbation method to include problems typical of the other water reactor cores such as BWR and CANDU bundles. It is found that the response coefficients predicted by the perturbation method for typical BWR bundles agree very well with those directly computed by the Monte Carlo method. The average and maximum relative errors in the surface-to-surface response coefficients are 0.02%-0.05% and 0.06%-0.25%, respectively. For CANDU bundles, the corresponding quantities are 0.01%-0.05% and 0.04% -0.15%. It is concluded that the perturbation method is highly accurate and efficient with a wide range of applicability. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2014

Application of the Hybrid Diffusion-Transport Spatial Homogenization Method to a Pressurized Water Reactor Benchmark Problem - Paper 70

The recently developed Hybrid Diffusion-Transport Spatial Homogenization (DTH) method was previously tested on a benchmark problem typical of a boiling water reactor. In this summary, the DTH method is tested in a 1-D benchmark problem typical of a pressurized water reactor. The method recreates the heterogeneous flux to within 1% average flux error and 34 pcm eigenvalue error in half the time as a heterogeneous transport calculation. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2013

Copper doped TiO2 nanoparticles characterized by X-ray absorption spectroscopy, total scattering, and powder diffraction – a benchmark structure–property study

Metal functionalized nanoparticles potentially have improved properties e.g. in catalytic applications, but their precise structures are often very challenging to determine. Here we report a structural benchmark study based on tetragonal anatase TiO 2 nanoparticles containing 0–2 wt% copper. The particles were synthesized by continuous flow synthesis under supercritical water–isopropanol conditions. Size determination using synchrotron PXRD, TEM, and X-ray total scattering reveals 5–7 nm monodisperse particles. The precise dopant structure and thermal stability of the highly crystalline powders were characterized by X-ray absorption spectroscopy and multi-temperature synchrotron PXRD (300–1000 K). The combined evidence reveals that copper is present as a dopant on the particle surfaces, most likely in an amorphous oxide or hydroxide shell. UV-VIS spectroscopy shows that copper presence at concentrations higher than 0.3 wt% lowers the band gap energy. The particles are unaffected by heating to 600 K, while growth and partial transformation to rutile TiO 2 occur at higher temperatures. Anisotropic unit cell behavior of anatase is observed as a consequence of the particle growth (a decreases and c increases).

Lock, Nina↗

DOE OSTI2024

Object Proxy Patterns for Accelerating Distributed Applications

Workflow and serverless frameworks have empowered new approaches to distributed application design by abstracting compute resources. However, their typically limited or one-size-fits-all support for advanced data flow patterns leaves optimization to the application programmer—optimization that becomes more difficult as data become larger. The transparent object proxy, which provides wide-area references that can resolve to data regardless of location, has been demonstrated as an effective low-level building block in such situations. Here we propose three high-level proxy-based programming patterns—distributed futures, streaming, and ownership—that make the power of the proxy pattern usable for more complex and dynamic distributed program structures. We motivate these patterns via careful review of application requirements and describe implementations of each pattern. As a result, we evaluate our implementations through a suite of benchmarks and by applying them in three meaningful scientific applications, in which we demonstrate substantial improvements in runtime, throughput, and memory usage.

Distributed Computing↗

DOE OSTI2014

Reactive transport codes for subsurface environmental simulation

A general description of the mathematical and numerical formulations used in modern numerical reactive transport codes relevant for subsurface environmental simulations is presented. The formulations are followed by short descriptions of commonly used and available subsurface simulators that consider continuum representations of flow, transport, and reactions in porous media. These formulations are applicable to most of the subsurface environmental benchmark problems included in this special issue. The list of codes described briefly here includes PHREEQC, HPx, PHT3D, OpenGeoSys (OGS), HYTEC, ORCHESTRA, TOUGHREACT, eSTOMP, HYDROGEOCHEM, CrunchFlow, MIN3P, and PFLOTRAN. The descriptions include a high-level list of capabilities for each of the codes, along with a selective list of applications that highlight their capabilities and historical development.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Can I/O Variability Be Reduced on QoS-Less HPC Storage Systems?

For a production high-performance computing (HPC) system, where storage devices are shared between multiple applications and managed in a best effort manner, I/O contention is often a major problem. In this paper, we propose a balanced messaging-based re-routing in conjunction with throttling at the middleware level. This work tackles two key challenges that have not been fully resolved in the past: whether I/O variability can be reduced on a QoS-less HPC storage system, and how to design a runtime scheduling system that can scale up to a large amount of cores. The proposed scheme uses a two-level messaging system to re-route I/O requests to a less congested storage location so that write performance is improved, while limiting the impact on read by throttling re-routing. An analytical model is derived to guide the setup of optimal throttling factor. We thoroughly analyze the virtual messaging layer overhead and explore whether the in-transit buffering is effective in managing I/O variability. Contrary to the intuition, in-transit buffer cannot completely solve the problem. It can reduce the absolute variability but not the relative variability. The proposed scheme is verified against a synthetic benchmark as well as being used by production applications.

Huang, Dan↗