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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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Comparative evaluation of deep learning workloads for leadership-class systems
Deep learning (DL) workloads and their performance at scale are becoming important factors to consider as we design, develop and deploy next-generation high-performance computing systems. Since DL applications rely heavily on DL frameworks and underlying compute (CPU/GPU) stacks, it is essential to gain a holistic understanding from compute kernels, models, and frameworks of popular DL stacks, and to assess their impact on science-driven, mission-critical applications. At Oak Ridge Leadership Computing Facility (OLCF), we employ a set of micro and macro DL benchmarks established through the Collaboration of Oak Ridge, Argonne, and Livermore (CORAL) to evaluate the AI readiness of our next-generation supercomputers. In this paper, we present our early observations and performance benchmark comparisons between the Nvidia V100 based Summit system with its CUDA stack and an AMD MI100 based testbed system with its ROCm stack. We take a layered perspective on DL benchmarking and point to opportunities for future optimizations in the technologies that we consider.
Comparative Analysis of Corrinoid Profiles across Host-Associated and Environmental Samples
Vitamin B 12 (the cyanated form of cobalamin cofactors) is best known for its essential role in human health. In addition to its function in human metabolism, cobalamin also plays important roles in microbial metabolism and can impact microbial community function. Cobalamin is a member of the structurally diverse family of cofactors known as cobamides that are produced exclusively by certain prokaryotes. Cobamides are considered shared nutrients in microbial communities because the majority of bacteria that possess cobamide-dependent enzymes cannot synthesize cobamides de novo. Furthermore, different microbes have evolved metabolic specificity for particular cobamides, and therefore, the availability of cobamides in the environment is important for cobamide-dependent microbes. Determining the cobamides present in an environment of interest is essential for understanding microbial metabolic interactions. By examining the abundances of different cobamides in diverse environments, including 10 obtained in this study, we find that, contrary to its preeminence in human metabolism, cobalamin is relatively rare in many microbial habitats. Comparison of cobamide profiles of mammalian gastrointestinal samples and wood-feeding insects reveals that host-associated cobamide abundances vary and that fecal cobamide profiles differ from those of their host gastrointestinal tracts. Environmental cobamide profiles obtained from aquatic, soil, and contaminated groundwater samples reveal that the cobamide compositions of environmental samples are highly variable. As the only commercially available cobamide, cobalamin is routinely supplied during microbial culturing efforts. Furthermore, these findings suggest that cobamides specific to a given microbiome may yield greater insight into nutrient utilization and physiological processes that occur in these habitats.
Comparing coordination uranyl( vi ) complexes with 2-(1 H -imidazo[4,5- b ]phenazin-2-yl)phenol and derivatives
The synthesis, characterization, emission, and electronic spectroscopy for complexes of derivatives of 2-(1 H -imidazo[4,5- b ]phenazin-2-yl)phenol with uranyl (UO 2 2+ ) and copper (Cu 2+ ) are detailed.
Comparing reproduced cyber experimentation studies across different emulation testbeds.
Abstract not provided.
Comparative PV LCOE Calculator (Comparative Photovoltaic Levelized Cost of Energy Calculator) [SWR-20-86]
The calculator calculates levelized cost of energy (LCOE) for photovoltaic (PV) systems based on cost, performance, and reliability inputs for a baseline and a proposed technology. The user can choose inputs and watch the effect on LCOE to determine whether a proposed technology is cost-effective, perform trade-off analysis among different technology options, and do break-even analysis of cost or performance.
Off-spec fly ash-based lightweight aggregate properties and their influence on the fresh, mechanical, and hydration properties of lightweight concrete: A comparative study
An off-spec fly ash-based spherical lightweight aggregate (LWA), designated as Spherical Porous Reactive Aggregate (SPoRA), was manufactured through a lab pilot-scale production and its engineering properties, including specific gravity, dry rodded unit weight, water absorption, mechanical performance, and pore structure, were evaluated. Using SPoRA, lightweight concrete (LWC) samples were made and their fresh, mechanical, and hydration properties were assessed and compared with LWC samples made using two commercial LWA available in the US market. The results indicated that fine and coarse SPoRA had 72 h water absorption capacities of 16.4 % and 20.9 %, respectively, which were higher than that of the two commercial LWAs. Higher saturated surface dry specific gravity of SPoRA compared to commercial LWAs led to a higher fresh density for the corresponding LWC. Using X-ray computed tomography, large spherical type pores were observed in SPoRA similar to those in the commercial slate-based LWA. Additionally, the pore size distribution of SPoRA, characterized by a dynamic vapor sorption analyzer, indicated that more than 97 % of the pores had diameters greater than 50 nm. SPoRA’s average bulk crushing strength was 6.8 MPa which was smaller than commercial LWA and was potentially attributed to the differences in manufacturing processes. Nonetheless, SPoRA LWC with 28 days compressive strength of 29 MPa passed the ASTM C330 requirement and had a comparable strength with LWC prepared with the commercial LWAs indicating lesser importance for the LWA strength. SPoRA LWC had a flowability of 5 % compared to LWC prepared with commercial LWAs having flowability of 18 %. This observation was potentially related to the fluxing agent used in the SPoRA production. SPoRA had a 70 % degree of hydration at 12 days which was comparable with that of LWC prepared with commercial LWA.
Low-carbon fuels for spark-ignited engines: A comparative study of compressed natural gas and liquefied petroleum gas on a CFR engine with exhaust gas recirculation
Decades of work on low-carbon fuels have established their potential for substantial emissions reductions; however, their adoption is still limited by infrastructure concerns and engine efficiency deficits. As infrastructures have begun to evolve, research on strategies that maximize engine efficiency through interactions with fuel properties must also now take center place. This paper compares the performance, emissions, and combustion characteristics of two forefront low-carbon fuels: compressed natural gas (CNG) and liquefied petroleum gas (LPG) in a cooperative fuel research (CFR) engine over a range of compression ratios and engine loads. The effects of exhaust gas recirculation (EGR), end-gas auto-ignition, and a novel combustion control tool, the combustion intensity metric (CIM), were also evaluated at different stoichiometric engine operating conditions. In comparison to LPG, CNG operation demonstrated an extended knock-free regime, allowing engine operation at higher engine loads and compression ratios, but LPG operation exhibited enhanced combustion characteristics with higher peak pressures and faster apparent heat release rates (AHRR). LPG operation achieved higher brake thermal efficiencies and lower equivalent CO 2 emissions compared to CNG operation at the tested engine loads and compression ratios. LPG demonstrated significantly higher EGR tolerance limits compared to CNG, with a maximum of 28% EGR rate, compared to 23% for CNG. This improved EGR dilution tolerance was responsible for a 90% reduction in NOx emissions for LPG compared to a maximum of 70% with CNG. EGR dilution also exhibited more effective knock mitigation potential with LPG, suppressing knock intensity values by up to 98% and transitioning the engine operation towards normal combustion from heavy knocking conditions. As a result, the CIM was found to decrease burn durations and improve the quality of combustion by controlling the desired fraction of end-gas auto-ignition.
Comparability of Liquid Chromatography Tandem Mass Spectrometry Analysis of Dissolved Organic Matter across Laboratories
Non-targeted liquid chromatography tandem highresolution mass spectrometry (LC−MS/MS) is increasingly applied for the structure-resolved chemical analysis of dissolved organic matter (DOM). With new developments in MS instrumentation and analysis software, the approach has gained substantial momentum over the past decade. However, achieving high-quality analytical data that is reproducible and comparable across laboratories can be a bottleneck in non-targeted metabolomics and organic matter chemical analysis, especially for data reuse in repository-scale analyses. Understanding the capabilities as well as challenges of comparing LC−MS/MS data from different laboratories is necessary for inferring global trends from public data sets. To illuminate instrumentation factors that drive differences and variability, we used a standardized data analysis pipeline, including classical (CMN) and featurebased molecular networking (FBMN), to analyze data from a ring trial by 24 laboratories on identical sample sets of algal and DOM extracts that were mixed in predefined concentrations and spiked with standards. Our results showed that data sets from similar mass spectrometer types with unified instrument parameters were qualitatively comparable, resolving the same general trends and shared mass spectral features. Interlaboratory comparability was best for high-intensity features, while low-intensity features showed greater detection variability. Our analysis also highlights challenges when comparing data from instruments with different acquisition rates or operating with less standardized methods. Lastly, we provide recommendations for data integration, public data sharing, standardization, and best practices for standardized LC−MS/MS data acquisition, which will be critical for long-term time series and intercomparability of DOM chemical analyses.
Comparing event generator predictions and ab initio calculations of ν- 12 C neutral-current quasielastic scattering at 1 GeV
The measurement of neutrino oscillations and exotic physics searches are important parts of the physics program in the near future, with new state-of-the-art experiments planned within the next decade. Future and modern experiments in these fields will make use of nuclear targets. Event generators (EGs) are software used in the analysis of neutrino oscillation experiments. EGs are used to predict kinematic observables for a range of neutrino energies. These simulations make use of simple models of nucleon dynamics. As such, they may fail to capture features of more rigorous theoretical calculations. This work compares EG performance to nuclear theory calculations by comparing observables generated in the two frameworks. We provide a common set of definitions between theory and experiment and assess the adequacy of the implementation of two nuclear physics models in EG simulations. Neutral-current quasielastic (NCQE) scattering events for neutrinos and antineutrinos on a 12 C target are simulated with a specific EG, NEUT, used by the T2K experiment for its analysis. The simulated cross sections are compared to analytic calculations from nuclear theory within the factorization scheme. We compare the NEUT implementation of two different models on nuclear spectral functions: the relativistic Fermi gas (RFG) and the correlated basis spectral function (CBF) to analytic calculations of the same models in the factorization scheme. For both nuclear physics models, we compare the appearance of features in the distributions relevant to experimental analyses. The peak of the cross section dσ/(dΩ dω) is consistent in energy transfer, ω, for RFG and CBF simulations. Qualitatively, the shape of the simulated distribution is similar to the one obtained through theory calculations; however, there are some discrepancies between the theory calculations and the NEUT simulation. While the EG simulations and analytic calculations with the same model of nuclear dynamics show similar overall features, there are still differences between the two. These results demonstrate the importance of benchmarking EGs so their nuclear physics implementations can be improved for the analysis of future experiments.
Impact of 12-nm FinFET Technology Variations on TID Effects: A Comparative Study of GF 12LP and 12LP+ at the Transistor Level
Here, this article presents a comparative analysis of total ionizing dose (TID) response in GlobalFoundries’ (GF) 12 low-power (LP) and 12LP+12-nm bulk fin field effect transistor (FinFET) technologies using 10-keV X-rays. Our findings show that 12LP+ n-type transistors demonstrate higher sensitivity to TID degradation of the off-state leakage drain current compared to 12LP. Data indicate that for both 12LP and 12LP+, transistors with higher threshold voltages (VTs) exhibit lower off-state drain-source leakage postirradiation compared to transistors with lower VTs. Data consistently show that transistors with fewer fins per transistor show superior TID tolerance, in both 12LP and 12LP+ technologies. Lower VT transistors in both technologies display similar preirradiation leakage currents. On the other hand, higher VT transistors in 12LP+ show lower preirradiation leakage currents than those in 12LP, highlighting that the front-end-of-line of 12LP+ technology has been modified compared to 12LP. p-type devices in 12LP+ presented negligible degradation. Larger TID sensitivity in 12LP+ might be attributed to the implementation of dual-metal gate work functions, reduced halo doping, deeper source/drain (S/D) doping profiles, and/or 12LP+ having narrower fins compared to 12LP.
Graph-Based Similarity Metrics for Comparing Simulation Model Causal Structures
The causal structure of a simulation is a major determinant of both its character and behavior, yet most methods we use to compare simulations focus only on simulation outputs. We introduce a method that combines graphical representation with information theoretic metrics to quantitatively compare the causal structures of models. The method applies to agent-based simulations as well as system dynamics models and facilitates comparison within and between types. Comparing models based on their causal structures can illuminate differences in assumptions made by the models, allowing modelers to (1) better situate their models in the context of existing work, including highlighting novelty, (2) explicitly compare conceptual theory and assumptions to simulated theory and assumptions, and (3) investigate potential causal drivers of divergent behavior between models. We demonstrate the method by comparing two epidemiology models at different levels of aggregation.
Performance Monitoring Program: Developing Comparative Metrics for Fitness-for-Duty Programs
To comply with U.S. Nuclear Regulatory Commission (NRC) regulations, licensees and entities authorized under Title 10 of the Code of Federal Regulations (CFR) Part 26 Section 26.3 (§ 26.3) are required to have fitness-for-duty (FFD) programs. Under § 26.3, the expectation of these FFD programs is to provide reasonable assurance that individuals who are granted unescorted access to nuclear power reactor protected areas and Category I fuel cycle facility material control areas are trustworthy, will perform their tasks in a reliable manner, are not under the influence of any substance, legal or illegal, that may impair their ability to perform their duties, and are not mentally or physically impaired from any cause that can adversely affect their ability to safely and competently perform their duties. Pacific Northwest National Laboratory (PNNL) was tasked with developing a performance monitoring program to risk inform NRC inspection and policy regarding quantitative FFD performance data. To meet this need, PNNL developed methodologies that could be implemented within a performance monitoring program. Throughout this report, these methodologies are referred to as comparative metrics. The NRC provided PNNL with 2016–2019 data from annual reporting forms and single positive test forms provided by licensees and other entities. For most of the comparative metrics, the analyses required customized processing, such as creating filtering fields, adding data fields and summaries, and joining datasets. The comparative metrics developed include: random testing rate, random policy violation rate, pre-access policy violation rate, subversion attempt rate, and number of policy violations by labor category. The comparative metrics can be used for parsing and visualizing FFD program data and monitoring FFD performance at the labor category, facility, licensee, and industry levels to risk inform NRC inspection and policy with regard to the FFD data currently collected from licensees and other entities that implement Part 26 requirements. Furthermore, these developed comparative metrics allow a more in-depth look at the FFD programs for the industry to discern trends and patterns that may warrant changes at an industry level and to inform policy decisions. These analyses should be refreshed as new FFD data become available.
Comparing event generator predictions and ab-initio calculations of $\nu$-$^{12}$C neutral current quasi-elastic scattering at 1 GeV
The measurement of neutrino oscillations and exotic physics searches are important parts of the physics program in the near future, with new state-of-the-art experiments planned within the next decade. Future and modern experiments in these fields will make use of nuclear targets. Event Generators (EGs) are software used in the analysis of neutrino oscillation experiments. EGs use to predict kinematic observables for a range of neutrino energies. These simulations may lack physics captured by more rigorous theoretical calculations. This work compares EG performance to nuclear theory calculations by comparing observables generated in the two frameworks. We provide a common set of definitions between theory and experiment and assess the physics contained in EG simulations. Neutral current quasi-elastic (NCQE) scattering events for neutrinos and anti-neutrinos on a $^{12}$C target are simulated with a specific EG, NEUT, used by the T2K experiment for its analysis. The simulated cross sections are compared to analytic calculations from nuclear theory within the factorization scheme. We compare the NEUT implementation of two different models on nuclear spectral functions: the Relativistic Fermi Gas (RFG) and the correlated basis spectral function (CBF) to analytic calculations of the same models in the factorization scheme. For both nuclear physics models, we compare the appearance of features in the distributions relevant to experimental analyses. Qualitatively, the shape of the simulated distribution is similar to the one obtained through theory calculations; however, there are some discrepancies between the theory calculations and the NEUT simulation. While the EG simulations and analytic calculations with the same model of nuclear dynamics show similar overall features, there are still differences between the two.
Gene expression of functionally-related genes coevolves across fungal species: detecting coevolution of gene expression using phylogenetic comparative methods
Researchers often measure changes in gene expression across conditions to better understand the shared functional roles and regulatory mechanisms of different genes. Analogous to this is comparing gene expression across species, which can improve our understanding of the evolutionary processes shaping the evolution of both individual genes and functional pathways. One area of interest is determining genes showing signals of coevolution, which can also indicate potential functional similarity, analogous to co-expression analysis often performed across conditions for a single species. However, as with any trait, comparing gene expression across species can be confounded by the non-independence of species due to shared ancestry, making standard hypothesis testing inappropriate. We compared RNA-Seq data across 18 fungal species using a multivariate Brownian Motion phylogenetic comparative method (PCM), which allowed us to quantify coevolution between protein pairs while directly accounting for the shared ancestry of the species. Our work indicates proteins which physically-interact show stronger signals of coevolution than randomly-generated pairs. Interactions with stronger empirical and computational evidence also showing stronger signals of coevolution. We examined the effects of number of protein interactions and gene expression levels on coevolution, finding both factors are overall poor predictors of the strength of coevolution between a protein pair. Simulations further demonstrate the potential issues of analyzing gene expression coevolution without accounting for shared ancestry in a standard hypothesis testing framework. Furthermore, our simulations indicate the use of a randomly-generated null distribution as a means of determining statistical significance for detecting coevolving genes with phylogenetically-uncorrected correlations, as has previously been done, is less accurate than PCMs, although is a significant improvement over standard hypothesis testing. These methods are further improved by using a phylogenetically-corrected correlation metric. Our work highlights potential benefits of using PCMs to detect gene expression coevolution from high-throughput omics scale data. This framework can be built upon to investigate other evolutionary hypotheses, such as changes in transcription regulatory mechanisms across species.
Comparative performance of PETase as a function of reaction conditions, substrate properties, and product accumulation
There is keen interest to develop new technologies to recycle the plastic poly(ethylene terephthalate) (PET). To this end, the use of PET-hydrolyzing enzymes has shown promise for PET deconstruction to its monomers, terephthalate (TPA) and ethylene glycol (EG). Here, we compare the Ideonella sakaiensis PETase wild-type enzyme to a previously reported improved variant (W159H/S238F). We compare the thermostability of each enzyme and describe a 1.45 Å resolution structure of the mutant, highlighting changes in the substrate binding cleft compared to the wild-type enzyme. Subsequently, the performance of the wild-type and variant enzyme was compared as a function of temperature, substrate morphology, and reaction mixture composition. These studies show that reaction temperature has the strongest influence on performance between the two enzymes. We also show that both enzymes achieve higher levels of PET conversion for substrates with moderate crystallinity relative to amorphous substrates. Finally, we assess the impact of product accumulation on reaction progress for the hydrolysis of both PET and bis(2-hydroxyethyl) terephthalate (BHET). Each enzyme displays different inhibition profiles to mono(2-hydroxyethyl) terephthalate (MHET) and TPA, while both are sensitive to inhibition by EG. Overall, this work highlights the importance of reaction conditions, substrate selection, and product accumulation for catalytic performance of PET-hydrolyzing enzymes, which have implications for enzyme screening in the development of enzyme-based polyester recycling.
Comparing field data using Alpert multi-wavelets
In this paper we introduce a method to compare sets of full-field data using Alpert tree-wavelet transforms. The Alpert tree-wavelet methods transform the data into a spectral space allowing the comparison of all points in the fields by comparing spectral amplitudes. The methods are insensitive to translation, scale and discretization and can be applied to arbitrary geometries. This makes them especially well suited for comparison of field data sets coming from two different sources such as when comparing simulation field data to experimental field data. We have developed both global and local error metrics to quantify the error between two fields. Additionally, we verify the methods on two-dimensional and three-dimensional discretizations of analytical functions. Furthermore, we then deploy the methods to compare full-field strain data from a simulation of elastomeric syntactic foam.