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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

RAP: Resource-aware Automated GPU Sharing for Multi-GPU Recommendation Model Training and Input Preprocessing

Ensuring high-quality recommendations for newly onboarded users requires the continuous retraining of Deep Learning Recommendation Models (DLRMs) with freshly generated data. To serve the online DLRM retraining, existing solutions use hundreds of CPU computing nodes designated for input preprocessing, causing significant power consumption that surpasses even the power usage of GPU trainers. To this end, we propose RAP, an end-to-end DLRM training framework that supports Resource-aware Automated GPU sharing for DLRM input Preprocessing and Training. The core idea of RAP is to accurately capture the remaining GPU computing resources during DLRM training for input preprocessing, achieving superior training efficiency without requiring additional resources. Specifically, RAP utilizes a co-running cost model to efficiently assess the costs of various input preprocessing operations, and it implements a resource-aware horizontal fusion technique that adaptively merges smaller kernels according to GPU availability, circumventing any interference with DLRM training. In addition, RAP leverages a heuristic searching algorithm that jointly optimizes both the input preprocessing graph mapping and the co-running schedule to maximize the end-to-end DLRM training throughput. The comprehensive evaluation shows that RAP achieves 78.3× speedup on average over CPU-based DLRM input preprocessing frameworks. In addition, the end-to-end training throughput of RAP is only 2.04% lower than the ideal case, which has no input preprocessing overhead.

Wang, Zheng↗
DOE OSTI2015

An opinion-driven behavioral dynamics model for addictive behaviors

We present a model of behavioral dynamics that combines a social network-based opinion dynamics model with behavioral mapping. The behavioral component is discrete and history-dependent to represent situations in which an individual’s behavior is initially driven by opinion and later constrained by physiological or psychological conditions that serve to maintain the behavior. Additionally, individuals are modeled as nodes in a social network connected by directed edges. Parameter sweeps illustrate model behavior and the effects of individual parameters and parameter interactions on model results. Mapping a continuous opinion variable into a discrete behavioral space induces clustering on directed networks. Clusters provide targets of opportunity for influencing the network state; however, the smaller the network the greater the stochasticity and potential variability in outcomes. Furthermore, this has implications both for behaviors that are influenced by close relationships verses those influenced by societal norms and for the effectiveness of strategies for influencing those behaviors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Godiva-IV Dosimetry Exercise 2022 Preliminary Results

Integral Experiment Request (IER) 538 is part of a series of dose characterization and nuclear accident dosimetry (NAD) exercises performed under the Department of Energy (DOE) Nuclear Criticality Safety Program (NCSP). This is the second NAD exercise using the Godiva-IV critical assembly and the third NAD exercise overall. The participating laboratories provided their own dosimeters that were mounted on the Lawrence Livermore National Laboratory (LLNL) BOttle Manikin ABsorption (BOMAB) phantoms and aluminum plates. The BOMABs and plates were placed at two, three, and four meters away from the center of Godiva. Alongside the NADs, there was a LLNL Passive Neutron Spectrometer (PNS), Atomic Weapons Establishment (AWE) PNS, and Y-12 Sphere present to measure the neutron dose from Godiva. Two irradiations were conducted to test the NAD performance from each laboratory and assesses their performance to the DOE-STD-1098-2017 part 515 criteria. Neutron and gamma doses were measured prior to this exercise. This work presents a model for the neutron and gamma dose respectively to serve as the reference value. A code written in C/C++/ROOT was used to fit the measured neutron and gamma dose with the new models. It was assumed that the neutron and gamma doses are proportional to the change in temperature of Godiva after a burst irradiation. Uncertainties for the reference values were calculated using error propagation of the model’s parameters. Preliminary results (within twenty-four hours) and final results were compared for each laboratory. On average of all the participating laboratories, 32% of neutron doses and 78% of gamma doses were outside the DOE standards. One laboratory did not report their dose readings and were not included in this average. There is a bias for a lower neutron dose and a higher gamma dose based on the distribution of results. In comparison with the past Godiva-IV NAD exercise, there is an improvement in neutron dose readings by 20%.

BOttle Manikin ABsorption (BOMAB)↗
DOE OSTI2016

A PRIMER ON UNIFYING DEBRIS DISK MORPHOLOGIES

A “minimum model” for debris disks consists of a narrow ring of parent bodies, secularly forced by a single planet on a possibly eccentric orbit, colliding to produce dust grains that are perturbed by stellar radiation pressure. We demonstrate how this minimum model can reproduce a wide variety of disk morphologies imaged in scattered starlight. Five broad categories of disk shape can be captured: “rings,” “needles,” “ships-and-wakes,” “bars,” and “moths (a.k.a. fans),” depending on the viewing geometry. Moths can also sport “double wings.” We explain the origin of morphological features from first principles, exploring the dependence on planet eccentricity, disk inclination dispersion, and the parent body orbital phases at which dust grains are born. A key determinant in disk appearance is the degree to which dust grain orbits are apsidally aligned. Our study of a simple steady-state (secularly relaxed) disk should serve as a reference for more detailed models tailored to individual systems. We use the intuition gained from our guidebook of disk morphologies to interpret, informally, the images of a number of real-world debris disks. These interpretations suggest that the farthest reaches of planetary systems are perturbed by eccentric planets, possibly just a few Earth masses each.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Metabolic model guided strain design of cyanobacteria

Cyanobacteria are oxygenic photoautotrophs that serve as potential platforms for the production of biochemicals from cheap and renewable raw materials – sunlight, water, and carbon dioxide. Systems level analysis of the metabolic network of these organisms could enable the successful engineering of these organisms for the enhanced production of target chemicals. Metabolic modeling techniques including both stoichiometric and kinetic modeling with a genome-wide coverage enable a global assessment of metabolic capabilities. Recent studies guided by such modeling techniques have engineered strains for the enhanced production of valuable chemicals such as ethanol, n-butanol, 1,3-propanediol, glycerol, limonene, and isoprene from CO 2 .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

UMo Benchmark Experiment Data Needed to Support Computational and Nuclear Data Validation

Currently there are almost no benchmark experiment data available directly supporting neutronics modeling and simulation of ~20 wt.% 235U, UMo fuel contained within the Organisation for Co-operation and Development Nuclear Energy Agency (OECD NEA) international benchmark handbooks from the International Criticality Safety Benchmark Evaluation Project (ICSBEP) and International Reactor Physics Experiment Evaluation Project (IRPhEP). The benchmarks within these two handbooks represent the international standards used to support computational and nuclear data validation. Recent activities in nuclear data development supporting new neutronics thermal scattering cross sections for UMo fuel indicate the necessity to provide quality benchmark experiment data that can be utilized to support their validation and development. Preparation of high-integrity neutronics benchmarks from UMo experimental data will ensure proper integral testing of these cross sections, as well as serve to support computational validation of contemporary modeling and simulation software.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Modeling to Support the Development of Habitat Targets for Piping Plovers on the Missouri River

This report describes analyses done in support of the establishment of quantitative targets for piping plovers on the Missouri River using predictive numerical models for emergent sandbar habitat and piping plovers developed for the Missouri River Effects Analysis. Several approaches were considered and modeled: current operations of the reservoirs to serve as a reference (Existing Conditions), an unregulated hydrograph to simulate historical conditions (Unregulated), a scenario where dams were present but not operated (No-Operations), and a scenario where the amount of habitat necessary to provide a desired level of population viability (5% risk of extinction in 50 years) was constructed (Calibrated Target). These scenarios were compared in terms of the distribution of standardized habitat produced, the proportion of time available habitat exceeded a given acreage, and the risk of quasi-extinction for plover populations. Sensitivity analyses were also conducted to demonstrate the effects of initial population size and target habitat acreage on extinction risk and the effects of viability criteria on habitat targets. Limitations and uncertainties in the modeling, including caveats on the use of these models to estimate historical conditions and the availability of information to build a metapopulation model are discussed. The challenges inherent in setting population targets and a possible alternative approach to assessing management alternatives in terms of population effects are also included.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Characterizing initial- and final-state effects of relativistic nuclear collisions

Here, the multiphase transport model (AMPT) is used to study the final-state effects on the symmetric correlations (SC), asymmetric correlations (ASC), normalized symmetric correlations (NSC), and normalized asymmetric correlations (NASC) in Au+Au collisions at 200 GeV. The correlators' sensitivity to nonflow effects associated with long- and short-range nonflow correlations are also discussed using the HIJING model. The results indicate that SC, ASC, NSC, and NASC can give accompanying constraints for initial- and final-state effects. In addition, conducting further detailed experimental measurements spanning a broad range of collision systems and beam energies will serve as an additional constraint for the theoretical models' calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Dynamic global vegetation models underestimate net CO 2 flux mean and inter-annual variability in dryland ecosystems

Despite their sparse vegetation, dryland regions exert a huge influence over global biogeochemical cycles because they cover more than 40% of the world surface (Schimel 2010 Science 327 418–9). It is thought that drylands dominate the inter-annual variability (IAV) and long-term trend in the global carbon (C) cycle (Poulter et al 2014 Nature 509 600–3, Ahlstrom et al 2015 Science 348 895–9, Zhang et al 2018 Glob. Change Biol. 24 3954–68). Projections of the global land C sink therefore rely on accurate representation of dryland C cycle processes; however, the dynamic global vegetation models (DGVMs) used in future projections have rarely been evaluated against dryland C flux data. Here, we carried out an evaluation of 14 DGVMs (TRENDY v7) against net ecosystem exchange (NEE) data from 12 dryland flux sites in the southwestern US encompassing a range of ecosystem types (forests, shrub- and grasslands). We find that all the models underestimate both mean annual C uptake/release as well as the magnitude of NEE IAV, suggesting that improvements in representing dryland regions may improve global C cycle projections. Across all models, the sensitivity and timing of ecosystem C uptake to plant available moisture was at fault. Spring biases in gross primary production (GPP) dominate the underestimate of mean annual NEE, whereas models' lack of GPP response to water availability in both spring and summer monsoon are responsible for inability to capture NEE IAV. Errors in GPP moisture sensitivity at high elevation forested sites were more prominent during the spring, while errors at the low elevation shrub and grass-dominated sites were more important during the monsoon. We propose a range of hypotheses for why model GPP does not respond sufficiently to changing water availability that can serve as a guide for future dryland DGVM developments. Our analysis suggests that improvements in modeling C cycle processes across more than a quarter of the Earth's land surface could be achieved by addressing the moisture sensitivity of dryland C uptake.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Comparison of Building Energy Modeling Programs: Building Loads

This technical report presented the methodologies, processes, and results of comparing three Building Energy Modeling Programs (BEMPs) for load calculations: EnergyPlus, DeST and DOE-2.1E. This joint effort, between Lawrence Berkeley National Laboratory, USA and Tsinghua University, China, was part of research projects under the US-China Clean Energy Research Center on Building Energy Efficiency (CERC-BEE). Energy Foundation, an industrial partner of CERC-BEE, was the co-sponsor of this study work. It is widely known that large discrepancies in simulation results can exist between different BEMPs. The result is a lack of confidence in building simulation amongst many users and stakeholders. In the fields of building energy code development and energy labeling programs where building simulation plays a key role, there are also confusing and misleading claims that some BEMPs are better than others. In order to address these problems, it is essential to identify and understand differences between widely-used BEMPs, and the impact of these differences on load simulation results, by detailed comparisons of these BEMPs from source code to results. The primary goal of this work was to research methods and processes that would allow a thorough scientific comparison of the BEMPs. The secondary goal was to provide a list of strengths and weaknesses for each BEMP, based on in-depth understandings of their modeling capabilities, mathematical algorithms, advantages and limitations. This is to guide the use of BEMPs in the design and retrofit of buildings, especially to support China’s building energy standard development and energy labeling program. The research findings could also serve as a good reference to improve the modeling capabilities and applications of the three BEMPs. The methodologies, processes, and analyses employed in the comparison work could also be used to compare other programs. The load calculation method of each program was analyzed and compared to identify the differences in solution algorithms, modeling assumptions and simplifications. Identifying inputs of each program and their default values or algorithms for load simulation was a critical step. These tend to be overlooked by users, but can lead to large discrepancies in simulation results. As weather data was an important input, weather file formats and weather variables used by each program were summarized. Some common mistakes in the weather data conversion process were discussed. ASHRAE Standard 140-2007 tests were carried out to test the fundamental modeling capabilities of the load calculations of the three BEMPs, where inputs for each test case were strictly defined and specified. The tests indicated that the cooling and heating load results of the three BEMPs fell mostly within the range of spread of results from other programs. Based on ASHRAE 140-2007 test results, the finer differences between DeST and EnergyPlus were further analyzed by designing and conducting additional tests. Potential key influencing factors (such as internal gains, air infiltration, convection coefficients of windows and opaque surfaces) were added one at a time to a simple base case with an analytical solution, to compare their relative impacts on load calculation results. Finally, special tests were designed and conducted aiming to ascertain the potential limitations of each program to perform accurate load calculations. The heat balance module was tested for both single and double zone cases. Furthermore, cooling and heating load calculations were compared between the three programs by varying the heat transfer between adjacent zones, the occupancy of the building, and the air-conditioning schedule.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Land Model Testbed: Accelerating Development, Benchmarking and Analysis of Land Surface Models

A Land Model Testbed (LMT), designed to provide a computational framework for systematically assessing model fidelity and supporting rapid development of complex multiscale models, offers a general-purpose workflow for conducting large ensemble simulations of multiple land surface models, post-processing large volumes of model output, and evaluating model results. It leverages existing tools for launching model simulations and the International Land Model Benchmarking (ILAMB) package for assessing model fidelity through comparison with best-available observational datasets. Increased complexity and proliferation of uncertain parameters in process representations in land surface models has driven the need for frequent and intensive testing and evaluating of models to quantify uncertainties and optimize parameters such that results are consistent with observations. The LMT described here meets these needs by providing tools to run thousands of ensemble simulations simultaneously and post-process their output files, by automating execution of an enhanced version of ILAMB with site-specific benchmarks and multivariate functional relationships, and by offering ensemble diagnostics and a customizable dashboard for displaying model performance metrics and associated graphics. We envision the LMT capabilities will serve as a foundational computational resource for a proposed user facility focused on terrestrial multiscale model--data integration.

Sreepathi, Sarat↗
DOE OSTI2021

Development of MCNP Training Modules for Safeguards Practitioners [Abstract]

The Monte-Carlo N-Particle (MCNP) software developed at LANL is the most widely used neutron transport code in the world. It is an essential tool for a variety of applications including detector development and design, nuclear fuel burnup simulation, criticality safety, and nondestructive assay system optimization. For this reason, it is indispensable within the safeguards and materials control & accountability (MC&A) communities. Multiple MCNP training courses have been created and taught over the last several decades by the MCNP development team at LANL, however there are no existing courses that cover specialized topics considered fundamental to NDA and safeguards models. To fill this gap, the MCNP team and Safeguards Science and Technology group at LANL have co-created a set of training modules customized to meet the specialized needs of the safeguards and MC&A communities. The basic modules cover concepts such as NDA system optimization, He-specific and other capture tallies, and tools for improved theoretical understanding. An advanced module was also created to cover topics including variance reduction for active interrogation simulations, use of the LANL MCNPTools post-processor, PTRAC (particle tracking) and list-mode data simulations, and fuel burnup simulations. The training modules teach to the latest and most state-of-the-art MCNP features and tools released by the development team at LANL and are intended to be taught jointly by the developers and safeguards experts. Ultimately, we hope that creation of these modules will serve to capture and convey the safeguards modeling and MCNP expertise at LANL, and that we will be able to share the modules more broadly with the MC&A and safeguards communities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

An electrochemical investigation of interfacial electron uptake by the sulfur oxidizing bacterium Thioclava electrotropha ElOx9

Extracellular electron transfer (EET) allows microbes to acquire energy from solid state electron acceptors and donors, such as environmental minerals. Here, this process can also be harnessed at electrode interfaces in bioelectrochemical technologies including microbial fuel cells, microbial electrosynthesis, bioremediation, and wastewater treatment. Improving the performance of these technologies will benefit from a better fundamental understanding of EET in diverse microbial systems. While the mechanisms of outward (i.e. microbe-to-anode) EET is relatively well characterized, specifically in a few metal-reducing bacteria, the reverse process of inward EET from redox-active minerals or cathodes to bacteria remains poorly understood. This knowledge gap stems, at least partly, from the lack of well-established model organisms and general difficulties associated with laboratory studies in existing model systems. Recently, a sulfur oxidizing marine microbe, Thioclava electrotropha ElOx9, was demonstrated to perform electron uptake from cathodes. However, a detailed analysis of the electron uptake pathways has yet to be established, and electrochemical characterization has been limited to aerobic conditions. Here, we report a detailed amperometric and voltammetric characterization of ElOx9 cells coupling cathodic electron uptake to reduction of nitrate as the sole electron acceptor, even in the absence of any added inorganic carbon source. By comparing this cellular activity to spent media controls and using medium exchange experiments, we demonstrate that one of the pathways by which ElOx9 facilitates inward EET is by a direct-contact mechanism through a redox center with a formal potential of -94 mV vs SHE, rather than soluble intermediate electron carriers. In addition to the implications for understanding microbial sulfur oxidation in marine environments, this study highlights the potential for ElOx9 to serve as a convenient and readily culturable model organism for understanding the molecular mechanisms of inward EET.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Geometric state function for two-fluid flow in porous media

Models that describe two-fluid flow in porous media suffer from a widely recognized problem that the constitutive relationships used to predict capillary pressure as a function of the fluid saturation are nonunique, thus requiring a hysteretic description. As an alternative to the traditional perspective, we consider a geometric description of the capillary pressure, which relates the average mean curvature, the fluid saturation, the interfacial area between fluids, and the Euler characteristic. The state equation is formulated using notions from algebraic topology and cast in terms of measures of the macroscale state. Synchrotron-based x-ray microcomputed tomography and high-resolution pore-scale simulation is applied to examine the uniqueness of the proposed relationship for six different porous media. We show that the geometric state function is able to characterize the microscopic fluid configurations that result from a wide range of simulated flow conditions in an averaged sense. The geometric state function can serve as a closure relationship within macroscale models to effectively remove hysteretic behavior attributed to the arrangement of fluids within a porous medium. As a result, this provides a critical missing component needed to enable a new generation of higher fidelity models to describe two-fluid flow in porous media.

42 ENGINEERING↗
DOE OSTI2026

Quantitative SANS and multi-model analysis of spacer-dependent micellization of urea-based gemini surfactants

The micellization behavior of urea-based cationic gemini surfactants was investigated using small-angle neutron scattering (SANS) with multi-model form factor analysis. A homologous series of surfactants with urea group included in the hydrophobic tail and polymethylene spacers consisting of two to ten methylene units was analyzed using three form factor models: a core–shell ellipsoid and two variants of homogeneous ellipsoids. The results from all models show a consistent trend of the micelle structures, confirming that the spacer length critically influences micellar geometry, aggregation number, and hydration. The surfactant with four CH 2 groups in the spacer formed the largest micelles with the highest aggregation number, while longer spacers led to progressively smaller, more compact aggregates. The shell hydration—quantified as the volume fraction of heavy water within the hydrophilic region—decreased systematically with increasing spacer length due to enhanced hydrophobicity of the headgroup-spacer region. Intermicellar interactions, modeled as screened Coulomb interaction using the rescaled mean spherical approximation (RMSA), revealed the strongest electrostatic repulsion for the case of four methylene groups in the spacer, corresponding to the highest micellar charge and largest interparticle spacing. The observed spacer-dependent trends were robust across all modeling approaches, demonstrating that the spacer length serves as a key structural determinant of self-assembly in this type of urea-based gemini systems. These findings provide insight into the design of gemini surfactants with tailored aggregation behavior for applications in drug delivery, nanostructure templating, and solubilization technologies.

Core–shell ellipsoid model↗
DOE OSTI2011

MONITORING AND MODELLING OF RADIOLYTIC DEGRADATION PRODUCTS OF TBP/n-DODECANE

The Plutonium Uranium Extraction (PUREX) solvent system was developed for the separation of plutonium and uranium from irradiated fuel. Since the implementation of this process, the degradation chemistry associated with the irradiated solvent system, tributyl phosphate (TBP)/n-dodecane/nitric acid has been extensively studied as the integrity of the organic solvent is paramount for reproducible performance of the separation flowsheet (extraction/scrub/strip) during multiple cycles. In PUREX-like processes, the extent of decomposition is dependent not only upon the solvent, but also upon the presence of constituents, such as nitric acid, that interact with TBP and increase its susceptibility to radiolytic degradation. The build-up of degradation products in the organic phase alters process flowsheet performance via modification of the metal ions speciation, loss of solvent components, and enhanced water transport into the organic phase. On-line identification and quantification of the solvent degradation products would provide the necessary information for more detailed process control as well as providing the basis for timing solvent washing or replacement. In our research, we are exploring the potential of on-line monitoring for the PUREX solvent radiolytic degradation products. To identify degradation products, TBP/n-dodecane solvent, contacted with aqueous nitric acid solutions of variable concentrations are subjected to various gamma radiation external doses then analyzed by electro-spray ionization mass spectrometry (ESMS). In addition, vibrational spectroscopy is utilized to monitor and quantify major degradation products including dibutyl phosphoric acid (HDBP) and monobutyl phosphoric acid (H2MBP) in TBP/n-dodecane solvent. The compiled spectroscopic databases serve for developing interpretive and predictive chemometric models for the quantification of the PUREX solvent degradation products.

Peterson, James M.↗
DOE OSTI2024

PIPES (Pipeline for Integrated Projects in Energy Systems) [SWR-24-89]

The Pipeline for Integrated Projects in Energy Systems (PIPES) is a comprehensive project, data, and workflow management tool designed for integrated modeling teams. PIPES facilitates the management of data requirements, tasks, and progress tracking, serving as a higher-level integration layer that works across various data and modeling software. This tool integrates models, data, and tools to perform large-scale, integrated analysis work at scale. PIPES is designed to streamline integrated modeling projects, enhance collaboration, and ensure the quality and efficiency of data management and workflow processes. https://github.com/nrel-pipes/pipes-api https://github.com/nrel-pipes/pipes-web https://github.com/nrel-pipes/nrel-pipes

Gu, Jianli↗
DOE OSTI2025

Pipeline for Integrated Projects in Energy Systems (PIPES): A Tool for Integrated System Planning [Slides]

The Pipeline for Integrated Projects in Energy Systems (PIPES) is a comprehensive project, data, and workflow management tool designed for integrated modeling teams. PIPES facilitates the management of data requirements, tasks, and progress tracking, serving as a higher-level integration layer that works across various data and modeling software. This tool integrates models, data, and tools to perform large-scale, integrated analysis work at scale. PIPES is designed to streamline integrated modeling projects, enhance collaboration, and ensure the quality and efficiency of data management and workflow processes. This presentation introduces PIPES a multi-model tool for integrated system planning; it describes the underlying architecture, deep dives into common user workflows, and outlines the upcoming development roadmap beyond its current alpha state.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗