SEARCH · Engineering Papers

Results for “Compiler Validation”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10

All sources NASA NTRS DOE OSTI

DOE OSTI2014

Toward Understanding the Effect of Low-Activity Waste Glass Composition on Sulfur Solubility

The concentration of sulfur in nuclear waste glass melter feed must be maintained below the point where salt accumulates on the melt surface. The allowable concentrations may range from 0.37 to over 2.05 weight percent (of SO3 on a calcined oxide basis). If the amount of sulfur exceeds its tolerance level a molten salt will accumulate and upset melter operations and potentially shorten melter useful life. Therefore relatively conservative limits have been placed on sulfur loading in melter feed which in-turn significantly impacts the amount of glass that will be produced, in particular at the Hanford site. Crucible-scale sulfur solubility data and scaled melter sulfur tolerance data have been collected on simulated Hanford waste glasses over the last 15 years. These data were compiled and analyzed. A model was developed to predict the solubility of SO3 in glass based on 312 individual glass compositions. This model was shown to well represent the data, accounting for over 80% of the variation in data and was well validated. The model was also found to accurately predict the tolerance for sulfur in melter feed based on 19 scaled melter tests. The model is appropriate for control of waste glass processing which includes uncertainty quantification. The model also gives quantitative estimates of component concentration effects on sulfur solubility. The components that most increase sulfur solubility are Li2O > V2O5 ≈ TiO2 < CaO < P2O5 ≈ ZnO. The components that most decrease sulfur solubility are Cl > Cr2O3 > SiO2 ≈ ZrO2 > Al2O3.

Borosilicate↗

DOE OSTI2018

Development and Rigorous Validation of Modules for Predicting Organic Aerosol CCN Activity from Molecular Properties

The indirect interaction of anthropogenic aerosols with clouds (aerosol indirect forcing) represents one of the main uncertainties in climate projections, and reducing this uncertainty requires improved understanding of the aerosol life cycle, including atmospheric aging and the ability to nucleate cloud droplets or crystals. A key parameter that links the chemical properties of aerosol to its nucleating properties, and ultimately to aerosol indirect forcing, is its hygroscopicity (ability to uptake water). One way to compare and systematize the ability of various chemical compounds or particle types to nucleate cloud drops is via the hygroscopicity parameter κ, which can be used directly in global models to simulate aerosol indirect forcing. In this project we further investigated the relationships between the chemical composition of organic aerosol particles, which are known to be important components of atmospheric particulate matter, and their ability to serve as cloud condensation nuclei (CCN). In particular, we isolated the role of viscosity on κ by applying methods similar to those we used previously in our DOE/ASR research. Our motivation for the focus on viscosity was through its link to particle phase state. Particle phase affects water uptake on timescales relevant to the laboratory and also likely relevant to atmospheric processes, with reduced apparent hygroscopicities for semisolid and solid particles, compared with liquid particles. Water uptake itself affects viscosity, an important feedback that we explored in this project. The objectives of the project were as follows: (1) measure the effects of molecular structure, temperature, and relative humidity on the viscosity of organic aerosol formed via controlled laboratory experiments, (2) measure the effects of organic aerosol viscosity on water uptake and CCN activity above and below water saturation, (3) further develop the κ parameterization of organic aerosol hygroscopicity to include viscosity/phase, and (4) experimentally validate the κ parameterization for organic aerosol with chemical composition ranging from relatively simple to complex. It was proposed that particle viscosity exerts a kinetic control on equilibrium water uptake. High viscosity was expected to delay water uptake based on diffusional limitations. This would manifest itself in reduced observed CCN activity or κ. Understanding the interplay between water content and viscosity (composition control on particle viscosity) and between viscosity and equilibrium water content (diffusional control on water uptake) were the overall science objectives of this grant. Targeted experiments were carried out to test the kinetic control hypothesis. These experiments included studies that explicitly measured the equilibration time scale of water uptake, and experiments that tested the role of viscous particle coatings on the observed CCN activity. From the combined work, it is concluded that mass transfer limitations by glassy organic particles are unlikely to affect cloud droplet activation near laboratory temperatures. This implies that viscosity does not need to be included in parameterizations that link particle chemical composition and κ. A parameterization to predict κ through the UNIFAC group contribution method was developed with previous ASR funding. As planned, this computational module was further developed and validated here through targeted laboratory studies. The computational module has been made available as free software under the GNU public license. A database of κ-values to aid model development has been compiled and is available online via an open access model. In conducting this work, significant effort was made to understand how aerosol composition, including the associated aerosol water content, affects viscosity. This included a study detailing the influence of functional group composition on organic aerosol viscosity. We identified a strong link between volatility and viscosity. Functional groups responsible for low vapor pressure also promote high viscosity. Specifically, carboxylic acid and hydroxyl groups were identified as major contributors to high viscosity. Several studies were carried out to characterize the link between composition and the glass-to-liquid phase transition. Compositions tested include models of organic/inorganic particles and models of complex organic aerosol formed through secondary processes. A simple computational model to predict the amorphous phase diagram was developed and tested. Excellent agreement between model and measurements was obtained for organic/inorganic mixtures. The computational model is simple enough to be included in global model simulations. However, constraints of input parameters such as the Gordon-Taylor constant for binary mixtures for a wide range of complex mixtures have not yet been fully evaluated. Combined, the performed work provides new constraints on the amorphous phase state of organic aerosols.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2014

On Parametric Sensitivity of Reynolds-Averaged Navier-Stokes SST Turbulence Model: 2D Hypersonic Shock-Wave Boundary Layer Interactions

Examined is sensitivity of separation extent, wall pressure and heating to variation of primary input flow parameters, such as Mach and Reynolds numbers and shock strength, for 2D and Axisymmetric Hypersonic Shock Wave Turbulent Boundary Layer interactions obtained by Navier-Stokes methods using the SST turbulence model. Baseline parametric sensitivity response is provided in part by comparison with vetted experiments, and in part through updated correlations based on free interaction theory concepts. A recent database compilation of hypersonic 2D shock-wave/turbulent boundary layer experiments extensively used in a prior related uncertainty analysis provides the foundation for this updated correlation approach, as well as for more conventional validation. The primary CFD method for this work is DPLR, one of NASA's real-gas aerothermodynamic production RANS codes. Comparisons are also made with CFL3D, one of NASA's mature perfect-gas RANS codes. Deficiencies in predicted separation response of RANS/SST solutions to parametric variations of test conditions are summarized, along with recommendations as to future turbulence approach.

Hypersonic↗

DOE OSTI2023

Building a genome-based understanding of bacterial pH preferences

The environmental preferences of many microbes remain undetermined. This is the case for bacterial pH preferences, which can be difficult to predict a priori despite the importance of pH as a factor structuring bacterial communities in many systems. We compiled data on bacterial distributions from five datasets spanning pH gradients in soil and freshwater systems (1470 samples), quantified the pH preferences of bacterial taxa across these datasets, and compiled genomic data from representative bacterial taxa. While taxonomic and phylogenetic information were generally poor predictors of bacterial pH preferences, we identified genes consistently associated with pH preference across environments. We then developed and validated a machine learning model to estimate bacterial pH preferences from genomic information alone, a model that could aid in the selection of microbial inoculants, improve species distribution models, or help design effective cultivation strategies. More generally, we demonstrate the value of combining biogeographic and genomic data to infer and predict the environmental preferences of diverse bacterial taxa.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1989

Void statistics, scaling, and the origins of large-scale structure

The probability that a volume of the universe of given size and shape spaced at random will be void of galaxies is used here to study various models of the origin of cosmological structures. Numerical simulations are conducted on hot-particle and cold-particle-modulated inflationary models with and without biasing, on isothermal or initially Poisson models, and on models where structure is seeded by loops of cosmic string. For the Pisces-Perseus redshift compilation of Giovanelli and Haynes (1985), it is found that hierarchical scaling is obeyed for subsamples constructed with different limiting magnitudes and subsamples taken at random. This result confirms that the hierarchical ansatz holds valid to high order and supports the idea that structure in the observed universe evolves by a regular process from an almost Gaussian primordial state. Neutrino models without biasing show the effect of a strong feature in the initial power spectrum. Cosmic string models do not agree well with the galaxy data.

Fry, J. N.↗

DOE OSTI2017

Probing the distance-duality relation with high- z data

Measurements of strong gravitational lensing jointly with type Ia supernovae (SNe Ia) observations have been used to test the validity of the cosmic distance duality relation (CDDR), D{sub L}( z )/[(1+ z ){sup 2D{sub A}}( z )]=η=1, where D{sub L}(z) and D{sub A}(z) are the luminosity and the angular diameter distances to a given redshift z , respectively. However, several lensing systems lie in the interval 1.4 ≤ z ≤ 3.6 i.e., beyond the redshift range of current SNe Ia compilations ( z ≈ 1.50), which prevents this kind of test to be fully explored. In this paper, we circumvent this problem by testing the CDDR considering observations of strong gravitational lensing along with SNe Ia and (a subsample from) the latest gamma-ray burst distance modulus data, whose redshift range is 0.033 ≤ z ≤ 9.3. We parameterize their luminosity distances with a second degree polynomial function and search for possible deviations from the CDDR validity by using four different η( z ) functions: η( z )=1+η{sub 0z}, η( z )=1+η{sub 0z}/(1+ z ), η( z )=(1+ z ){sup η{sub 0}} and η( z )=1+η{sub 0ln}(1+ z ). Unlike previous tests done at redshifts lower than 1.50, the likelihood for η{sub 0} depends strongly on the η( z ) function considered, but we find no significant deviation from the CDDR validity (η{sub 0}=0). However, our analyses also point to the fact that caution is needed when one fits data in higher redshifts to test the CDDR as well as a better understanding of the mass distribution of lenses also is required for more accurate results.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Supporting multiple hardware architectures at CMS: the integration and validation of POWER9

Computing resources in the Worldwide LHC Computing Grid (WLCG) have been based entirely on the x86 architecture for more than two decades. In the near future, however, heterogeneous non-x86 resources, such as ARM, POWER and Risc-V, will become a substantial fraction of the resources that will be provided to the LHC experiments, due to their presence in existing and planned world-class HPC installations. The CMS experiment, one of the four large detectors at the LHC, has started to prepare for this situation, with the CMS software stack (CMSSW) already compiled for multiple architectures. In order to allow for a production use, the tools for workload management and job distribution need to be extended to be able to exploit heterogeneous architectures. Profiting from the opportunity to exploit the first sizable IBM Power9 allocation available on Marconi100 HPC system at CINECA, CMS developed all the needed modifications to the CMS workload management system. After a successful proof of concept, a full physics validation has been performed in order to bring the system in production. The experiences are of very high value, when it comes to commissioning of the similar (even larger) Summit HPC system at Oak Ridge, where CMS is also expecting a resource allocation. Moreover the compute power of those systems is being provided also via GPUs and this represents an extremely valuable opportunity to exploit the offloading capability already implemented in CMSSW. The status of the current integration including the exploitation of the GPUs, the results of the validation as well as the future plans will be shown and discussed.

Boccali, Tommaso [INFN, Pisa]↗

DOE OSTI2017

Battery Testing FY 2017 Annual Progress Report

Abuse tests are designed to determine the safe operating limits of HEV\PHEV energy storage devices. Testing is intended to achieve certain worst-case scenarios to yield quantitative data on cell\module\pack response, allowing for failure mode determination and guiding developers toward improved materials and designs. Standard abuse tests with defined start and end conditions are performed on all devices to provide comparison between technologies. New tests and protocols are developed and evaluated to more closely simulate real-world failure conditions. When scaling from cell to the battery level, a detailed understanding of cell interactions provides insight on safety performance. Single point failures from a cell or group of cells can be initiated by a number of triggers including internal short circuit, misuse or abuse, or component failure at the battery or system level. Propagation of a single failure event (regardless of the initiation trigger) through an entire battery, system, or vehicle is an unacceptable outcome with regards to EV battery safety. In this FY, our work has focused on evaluating the propagation of a single cell thermal runaway event through a battery using a variety of design considerations with an emphasis on passive thermal management impacts. This has been coupled with thermal modeling by NREL for these testing conditions. In addition, alternative failure initiation methods have been evaluated to provide direct comparisons of possible energy injection between modes. This data was compiled to better identify what propagation test method is appropriate given certain battery designs. Expanding the analysis of short circuit current during failure propagation has been done for EV relevant chemistries. Ongoing test development and validation to obtain these values has been achieved. While robust mechanical models for vehicles and vehicle components exist, there is a gap for mechanical modeling of EV batteries. The challenge with developing a mechanical model for a battery is the heterogeneous nature of the materials and components (polymers, metals, metal oxides, liquids). Our work will provide empirical data on the mechanical behavior of batteries under compressive load to understand how a battery may behave in a vehicle crash scenario. This work is performed in collaboration with the U.S. Council for Automotive Research (USCAR) and Computer Aided Engineering of Batteries (CAEBAT). These programs have supported the design and development of a drop tower testing apparatus to close the gap between cell/string level testing and full scale crash testing with true dynamic rate effects.

25 ENERGY STORAGE↗

DOE OSTI2014

Enhanced HLW Glass Property-Composition Models – Phase 1 (Final Report)

In the present work, the previously compiled glass property-composition database for WTP HLW glasses has been updated with newly available data. The earlier evaluation of the baseline WTP models against the larger data sets, in terms of range of validity and prediction performance, has been used together with a review of the HLW glass data to identify gaps in the composition regions that need to be filled to support the development of expanded models. Subsequently, statistically-designed compositional matrices were developed to begin to fill these composition gaps. Crucible melts have been prepared for the matrix glasses and glass properties have been collected. Finally, preliminary models have been developed that are applicable to the expanded dataset. Additionally, the performance of the preliminary models have been reviewed to assess the relative advantages of developing one set of models for the entire HLW glass composition space or to developing separate models for discrete composition spaces. The longer-term objective of this multi-year task is to develop new glass property-composition models for PCT release, spinel crystallization (T 1% ), nepheline formation on CCC, TCLP Cd response, viscosity, and electrical conductivity to control glass compositions for HLW vitrification at Hanford.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1997

Ion Engine Service Life Validation by Analysis and Testing

Assessment of the NSTAR ion engine service life is being accomplished through a combination of long duration testing and probabilistic analyses of the credible failure modes. A literature review that examined 65 ion engine endurance tests perfromed over the past 35 years was conducted to compile a list of possible ion engine failure modes.

Ion Engine↗

NASA NTRS1996

Ion Engine Service Life Validation by Analysis and Testing

Ion Engine↗

NASA NTRS2009

The 50 Constellation Priority Sites

The Constellation program (CxP) has developed a list of 50 sites of interest on the Moon which will be targeted by the LRO narrow angle camera. The list has also been provided to the M~ team to supplement their targeting list. This list does not represent a "site selection" process; rather the goal was to find "representative" sites and terrains to understand the range of possible surface conditions for human lunar exploration to aid engineering design and operational planning. The list compilers leveraged heavily on past site selection work (e.g. Geoscience and a Lunar Base Workshop - 1988, Site Selection Strategy for a Lunar Outpost - 1990, Exploration Systems Architecture Study (ESAS) - 2005). Considerations included scientific, resource utilization, and operational merits, and a desire to span lunar terrain types. The targets have been organized into two "tiers" of 25 sites each to provide a relative priority ranking in the event of mutual interference. A LEAG SAT (special action team) was established to validate and recommend modifications to the list. This SAT was chaired by Dr. Paul Lucey. They provided their final results to CxP in May. Dr. Wendell Mendell will organize an on-going analysis of the data as they come down to ensure data quality and determine if and when a site has sufficient data to be retired from the list. The list was compiled using the best available data, however, it is understood that with the flood of new lunar data, minor modifications or adjustments may be required.

Noble, S.↗

NASA NTRS1977

As-built design specification for the digital derivation of daily and monthly data bases from synoptic observations of temperature and precipitation for the People's Republic of China

A data base of synoptic meteorological information was compiled for the People's Republic of China, as an integral part of the Large Area Crop Inventory Experiment. A system description is provided, including hardware and software specifications, computation algorithms and an evaluation of output validity. Operations are also outlined, with emphasis placed on least squares interpolation.

Jeun, B. H.↗

DOE OSTI2017

Testing ΛCDM at the lowest redshifts with SN Ia and galaxy velocities

Peculiar velocities of objects in the nearby universe are correlated due to the gravitational pull of large-scale structure. By measuring these velocities, we have a unique opportunity to test the cosmological model at the lowest redshifts. We perform this test, using current data to constrain the amplitude of the "signal" covariance matrix describing the velocities and their correlations. We consider a new, well-calibrated "Supercal" set of low-redshift SNe Ia as well as a set of distances derived from the fundamental plane relation of 6dFGS galaxies. Here, analyzing the SN and galaxy data separately, both results are consistent with the peculiar velocity signal of our fiducial ΛCDM model, ruling out the noise-only model with zero peculiar velocities at greater than 7σ (SNe) and 8σ (galaxies). When the two data sets are combined appropriately, the precision of the test increases slightly, resulting in a constraint on the signal amplitude of A = 1.05 -0.21 +0.25 where A = 1 corresponds to our fiducial model. Equivalently, we report an 11% measurement of the product of the growth rate and amplitude of mass fluctuations evaluated at z eff = 0.02, f σ 8 = 0.428 -0.045 +0.048 , valid for our fiducial ΛCDM model. Here, we explore the robustness of the results to a number of conceivable variations in the analysis and find that individual variations shift the preferred signal amplitude by less than ~0.5σ. We briefly discuss our Supercal SN Ia results in comparison with our previous results using the JLA compilation.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Data Collection Methods for Validation of Advanced Multi-Resolution Fast Reactor Simulations

In pool-type Sodium Fast Reactors (SFR) the regions most susceptible to thermal striping are the upper instrumentation structure (UIS) and the intermediate heat exchanger (IHX). This project experimentally and computationally (CFD) investigated the thermal mixing in the region exiting the reactor core to the UIS. The thermal mixing phenomenon was simulated using two vertical jets at different velocities and temperatures as prototypic of two adjacent channels out of the core. Thermal jet mixing of anticipated flows at different temperatures and velocities were investigated. Velocity profiles are measured throughout the flow region using Ultrasonic Doppler Velocimetry (UDV), and temperatures along the geometric centerline between the jets were recorded using a thermocouple array. CFD simulations, using COMSOL, were used to initially understand the flow, then to design the experimental apparatus and finally to compare simulation results and measurements characterizing the flows. The experimental results and CFD simulations show that the flow field is characterized into three regions with respective transitions, namely, convective mixing, (flow direction) transitional, and post-mixing. Both experiments and CFD simulations support this observation. For the anticipated SFR conditions the flow is momentum dominated and thus thermal mixing is limited due to the short flow length associated from the exit of the core to the bottom of the UIS. This means that there will be thermal striping at any surface where poorly mixed streams impinge; rather unless lateral mixing is ‘actively promoted out of the core, thermal striping will prevail. Furthermore we note that CFD can be considered a ‘separate effects (computational) test’ and is recommended as part of any integral analysis. To this effect, poorly mixed streams then have potential impact on the rest of the SFR design and scaling, especially placement of internal components, such as the IHX that may see poorly mixed streams. Finally, due to lack or infrastructural support for carrying out sodium experiments, only water experiments and CFD studies were realized in, an otherwise sodium approved facility.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2015

EMMA: an adaptive mesh refinement cosmological simulation code with radiative transfer

EMMA is a cosmological simulation code aimed at investigating the reionization epoch. It handles simultaneously collisionless and gas dynamics, as well as radiative transfer physics using a moment-based description with the M1 approximation. Field quantities are stored and computed on an adaptive three-dimensional mesh and the spatial resolution can be dynamically modified based on physically motivated criteria. Physical processes can be coupled at all spatial and temporal scales. We also introduce a new and optional approximation to handle radiation: the light is transported at the resolution of the non-refined grid and only once the dynamics has been fully updated, whereas thermo-chemical processes are still tracked on the refined elements. Such an approximation reduces the overheads induced by the treatment of radiation physics. A suite of standard tests are presented and passed by EMMA, providing a validation for its future use in studies of the reionization epoch. The code is parallel and is able to use graphics processing units (GPUs) to accelerate hydrodynamics and radiative transfer calculations. Depending on the optimizations and the compilers used to generate the CPU reference, global GPU acceleration factors between ×3.9 and ×16.9 can be obtained. As a result, vectorization and transfer operations currently prevent better GPU performance and we expect that future optimizations and hardware evolution will lead to greater accelerations.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

ATR NEXSHARE Fact Sheet

This fact sheet will provide information for the database of experimental facilities supported by the IAEA as outlined below: NEXSHARE: As part of the Nuclear Harmonization and Standardization Initiative (NHSI), the IAEA proposes to establish a Network for global cooperation and resource sharing for experiments and code validation between experimental facilities, SMRs design organizations, International Organizations and Technical Support Organizations (TSOs). The proposed Network, NEXSHARE, will be done in collaboration with the OECD/NEA. EXPERIMENTAL FACILITY DATABASE: As part of this activity, the IAEA is compiling a database of experimental facilities applicable to SMRs (including water cooled, high temperature gas cooled, molten salt and fast neutron spectrum reactors). This database will also form part of NEXSHARE and will be documented in an IAEA publication.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Data‐Driven Insights into Rare Earth Mineralization: Machine Learning Applications Using Functional Material Synthesis Data

Understanding rare‐earth element (REE) mineralization mechanisms is essential for developing efficient separation strategies. Although the geochemical pathways that generate REE deposits are qualitatively known, quantitative links between specific conditions and mineralization outcomes remain limited. Herein, the repurpose laboratory REE hydrothermal synthesis data—originally collected for functional‐materials fabrication—as a surrogate for studying mineralization with data‐driven methods. The compiled 1,200+ hydrothermal reaction records and trained three machine‐learning models—K‐nearest neighbors (KNN), random forest (RF), and extreme gradient boosting (XGB)—to predict product elements and phases from precursors, additives, reaction conditions, and engineered features. Validation shows XGB achieves the highest accuracy. Feature importance indicates thermodynamic properties of cations and anions dominate model decisions. Correlations reveal positive relationships among precursor concentration, reaction time, pH, and temperature, consistent with classical crystallization behavior. XGB‐based regressors are built to predict crystallization temperature and pH from precursor/product attributes. Performance is strongest when similar training examples exist, while accuracy declines for underrepresented reactions, notably REE carbonates and heavy‐REE systems. Overall, the study shows that functional‐materials datasets can illuminate REE mineralization and provide priors for exploration and processing. Expanding datasets with less‐studied chemistries and conditions will improve generality and support deposit discovery and more efficient REE recovery.

feature importance analysis↗