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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Double copy for massive scalar field theories

We explore extensions of the double copy to massive theories and find a new cubic theory with a local double copy. We consider the nonlinear sigma model and the special galileon theory, massless versions of which are known to be related through the double copy. We show that by performing a Kaluza-Klein reduction of these theories from five dimensions down to four, a double copy relation exists between the resulting massive four-dimensional scalar field theories. This requires the vanishing contribution of new galileon terms arising in high dimensions. We further explore if other interactions that do not arise from a dimensional reduction of the nonlinear sigma model could be double copied and find a new cubic interaction which satisfies the BCJ relations up to 5-point amplitudes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Contaminant Migration Modeling to Support the In Situ Decommissioning of Hardened Nuclear Facilities - 20215

The decommissioning of hardened nuclear facilities provides a unique challenge in balancing current worker dose with exposure to future receptors and media. In situ decommissioning (ISD) is a cost-effective and safe option for the closure of such facilities but requires a detailed understanding of the threat that radioactive and hazardous constituents remaining in the facilities pose to groundwater and surrounding surface water. The Savannah River Site (SRS) extensively employs contaminant migration models within the decommissioning process to develop site-specific removal, grouting, and monitoring strategies in support of safe and effective final end states of nuclear facilities. This work discusses the use of contaminant migration modeling in the ISD process at SRS, including specific examples from the closure of P-Reactor and R-Reactor, Building 235-F, F-Canyon and F/H Laboratory Complex. Migration models developed during the closure of P-Reactor and R-Reactor were divided into four source areas: the reactor vessel, the process area, the disassembly basin, and the purification wing. Each source area was assigned a specific inventory and migration pathway and was then subject to varying hypothetical removal, capping, and grouting schemes. Modeling indicated that groundwater Maximum Concentration Limits (MCLs) might be exceeded if no action was taken for eleven and ten constituents of concern (COCs) at P-Reactor and R-Reactor, respectively. These exceedances could occur in as few as 200 to 500 years. Alternatively, the migration modeling demonstrated that the selected ISD actions reduced contaminant mobility which allowed for significant radioactive decay and resulted in fewer predicted exceedances of groundwater MCLs (five COCs for P-Reactor; eight COCs for R-Reactor). In response to the modeling results for P-Reactor and R-Reactor, effectiveness monitoring programs were developed to target contaminants, specific to each reactor, that may migrate to groundwater. Contaminant migration modeling also revealed that roof collapse was a large factor in the release of COCs to the environment, giving rise to roof improvements, and an inspection and vegetation control program to ensure roof stability over time. Contaminant migration modeling is also aiding in the closure planning for hardened facilities in F Area. Building 235-F housed the Actinide Billet Line, which produced Np-237 billets for irradiation in SRS reactors, and the Plutonium Fuel Form (PuFF) facility that produced Pu-238 heat sources for the space program. As a result of these missions, areas within Building 235-F contain considerable residual amounts of both Pu-238 and Np-237. Contaminant migration modeling of Building 235-F was originally performed in 2012 to identify the feasibility of ISD and the amount of radioactive material removal required to prevent the exceedance of groundwater MCLs. The original model indicated that a 60% reduction in the PuFF facility Pu-238 inventory could keep groundwater concentrations below standards, while Np-237 did not pose a threat to groundwater. However, updates to the model with an emphasis on source impact pathways revealed that, due to the orientation of the source areas relative to groundwater flow, no amount of reasonable removal of Pu-238 would keep groundwater concentrations below MCLs and that Np-237 could be a large contributor to localized MCL exceedances. With this insight, the refined 2019 model is being used to assist in the development of grouting plans specific to each facility source area, where bentonite may be utilized to slow the migration of Pu-238 and its daughter products from the PuFF facility and a reducing grout may decrease Np-237 transport by ensuring the nuclide remains in the less mobile +IV oxidation state. The beginning phases of contaminant migration modeling are underway for F-Canyon and associated facilities using lessons learned from the Reactors and Building 235-F. A contaminant migration pathway, similar to the pathway used for the reactor vessels, is being developed for the hot and warm canyons. The F-Canyon inventories are being spatially refined to identify specific and localized source zones, comparable to Building 235-F, that may impact groundwater. Contaminant migration modeling provides vital input within the ISD process, from facility investigation to post closure effectiveness monitoring, making it a valuable tool in the development of safe and effective end states for hardened nuclear facilities at SRS. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Modeling the Air Quality Impacts of Future Energy Scenarios

Many greenhouse gas (GHG) emission reduction measures achieve simultaneous reductions in air pollutants. Human-Earth system models can estimate such emission changes in the energy system but using them in chemistry-transport models (CTMs) to study their air quality impacts involves resource-intensive emissions processing. This is greatly simplified by an emissions scaling approach linking state-level emissions estimated by a human-Earth system model to a CTM. A scenario continuing pre-2022 energy policy in the U.S. to 2050 shows widespread air quality improvements over the 2015 baseline from SO 2 and NO x emission reductions of 50–80% from electricity generation and light-duty vehicles. Scenarios of GHG mitigation and vehicle electrification at the state and national level add further benefits. However, PM 2.5 increases from increased use of wood heating and bioenergy suggest that additional PM 2.5 management may be needed when using biofuels. In conclusion, this approach helps assess multiple future energy scenarios efficiently without sacrificing chemical detail in the air quality simulations.

air quality↗
DOE OSTI2025

Understanding the Competition between Alcohol Formation and Dimerization during Electrochemical Reduction of Aromatic Carbonyl Compounds

The electrochemical reductive dimerization of small aromatic carbonyl compounds derived from lignocellulosic biomass is a crucial C−C coupling reaction for upgrading small molecules to longchain hydrocarbons, particularly in the synthesis of drop-in sustainable aviation fuels. Although other electrochemical reduction reactions of these reactants (i.e., hydrogenation and hydrogenolysis) have undergone extensive mechanistic investigation, the understanding of dimerization remains relatively underdeveloped. Most importantly, there is a lack of understanding of the selectivity-determining step between dimerization and monomer reduction and critical factors that can affect this step. In this study, we provide a comprehensive mechanistic model to explain the competition between dimerization and monomer reduction of benzaldehyde under various conditions. Our model proposes that the selectivity between dimerization and monomer reduction depends on the competition between desorption of a ketyl radical from the electrode, necessary for dimerization, and further reduction of the ketyl radical to an alcohol on the electrode by proton-coupled electron transfer (PCET). Computationally comparing the adsorption/desorption energy and PCET activation barrier energy is challenging because conventional DFT calculations substantially underestimate the PCET kinetic barriers. In this study, we employed constrained DFTbased configuration interaction (CDFT-CI) to obtain a reliable comparison of these energies. Our mechanistic model was tested and supported by experimental results obtained with four electrodes (Cu, Pb, Bi, graphite), three pH conditions (acidic, neutral, basic), and three potentials. Our study offers a coherent mechanistic foundation that can explain how each of these conditions impacts the desorption and PCET processes and the selectivities for dimerization and alcohol production.

09 BIOMASS FUELS↗
NASA NTRS1988

Analytical and experimental investigation of the notched strength of thick laminates with surface notches

Experimental and analytical investigations of the fracture of a graphite/epoxy laminate with part-through semielliptic surface notches have been conducted. Experimental values of notched strength were determined for a variety of notch aspect ratios and notch depths. Analytical predictions of laminate failure were obtained from three different models. The three models were equally successful in predicting the fracture of laminates with deep notches. The experimental results of laminates with shallow notches indicated more notch sensitivity (that is greater strength reduction) than did the analytical models.

Harris, Charles E.↗
DOE OSTI2019

Reduction Mechanism of Iron Oxide Briquettes by Carbonaceous Materials Extracted from Blast Furnace Dust

The reducibility of carbonaceous powder extracted from blast furnace dust was investigated. In this study, pickling treatment was used for BF bag dust and BF gravitational dust to extract the carbonaceous material. The structural characteristics of carbonaceous material were studied by X-ray diffraction, scanning electron microscope, and energy-dispersive spectrometer. The reduction of ferric oxide and carbon gasification experiments were researched by thermogravimetry. The results show that the pickled raw coal gives the highest reducibility, which is followed by BF bag dust and BF gravitational dust. The reason for this is that the higher disordered crystalline structure leads to stronger gasification reactivity, and further results in stronger reduction reactivity. Based on the randomized nucleation model, the kinetic analysis shows that the activation energies for the reduction reaction of BF gravitational dust, BF bag dust, and raw coal after pickling are 300.14, 180.43, and 124.62 kJ mol{sup −1}, respectively.

36 MATERIALS SCIENCE↗
NASA NTRS1984

Proton damage in GaAs solar cells

A simplified model for the short-circuit current reduction caused by proton-induced radiation damage is described. The model accounts for the nonuniformity of defect production within heteroface GaAs shallow junction solar cells. The results from the model show agreement with the strong energy dependence observed in proton radiation damage experiments.

Wilson, J. W.↗
NASA NTRS1994

Interpretation of satellite airglow observations during the March 22, 1979, magnetic storm, using the coupled ionosphere-thermosphere model developed at University College, London

The University of California, Berkeley, extreme ultraviolet spectrometer aboard the U.S. Air Force STP 78-1 satellite measured emission features in the Earth's dayglow due to neutral and ionized species in the atmosphere, in the 35 to 140-nm range. The spectrometer was operating between March 1979 and March 1980, including the period of the magnetic storm on March 22, 1979. Some of these measurements are interpreted using the predictions of the three-dimensional time-dependent coupled ionosphere-thermosphere model developed at University College, London. The observations show a reduction in the atomic oxygen 130.4-nm airglow emission at high northern latitudes following the storm. Model simulations show that this reduction in 130.4-nm emission is associated with an increase in the O2/O ratio. Analysis of model results using electron transport and radiative transport codes show that the brightness of 130.4-nm emission at high latitudes due to resonantly scattered sunlight is approximately twice that due to photoelectron impact excitation. However, the observed decrease in the brightness at high northern latitudes is mainly due to a change in the photoelectron impact source, which contributes approximately 75% of the total, as well as its multiple scattering component; for the photoelectron impact source at 70 deg latitude and 200 km altitude, the reduction in multiple scattering is 1.5 times greater than the reduction in the initial excitation. The reduction in the airglow emission is visible only in the norther n hemisphere because the south pole was not sunlit over the storm period. The comparison of model results with observations suggests that 130.4-nm emission may be useful as a tracer for global changes in the concentration of atomic energy.

Parish, H. F.↗
DOE OSTI2014

Analysis and modeling of Nannochloropsis growth in lab, greenhouse, and raceway experiments

Efficient production of algal biofuels could reduce dependence on foreign oil by providing a domestic renewable energy source. Moreover, algae-based biofuels are attractive for their large oil yield potential despite decreased land use and natural resource (e.g., water and nutrients) requirements compared to terrestrial energy crops. Important factors controlling algal lipid productivity include temperature, nutrient availability, salinity, pH, and the light-to-biomass conversion rate. Here, computational approaches allow for inexpensive predictions of algae growth kinetics for various bioreactor sizes and geometries without the need for multiple, expensive measurement systems. Parametric studies of algal species include serial experiments that use off-line monitoring of growth and lipid levels. Such approaches are time consuming and usually incomplete, and studies on the effect of the interaction between various parameters on algal growth are currently lacking. However, these are the necessary precursors for computational models, which currently lack the data necessary to accurately simulate and predict algae growth. In this work, we conduct a lab-scale parametric study of the marine alga Nannochloropsis salina and apply the findings to our physics-based computational algae growth model. We then compare results from the model with experiments conducted in a greenhouse tank and an outdoor, open-channel raceway pond. Results show that the computational model effectively predicts algae growth in systems across varying scale and identifies the causes for reductions in algal productivities. Applying the model facilitates optimization of pond designs and improvements in strain selection.

09 BIOMASS FUELS↗
DOE OSTI2023

An automated and portable method for selecting an optimal GPU frequency

Power consumption poses a significant challenge in current and emerging graphics processing unit (GPU) enabled high-performance computing systems. In modern GPUs, dynamic voltage frequency scaling (DVFS) appears to be a reliable control to regulate power consumption and performance. However, the DVFS design space is large - hence, brute-force approaches are infeasible to select the optimal frequency. Furthermore, no single frequency can be universally optimal for applications with varying computational intensities. Thus, the application's complexity and the availability of a wide range of frequency settings are a challenge in selecting the optimal frequency configuration for a given GPU workload. To that end, this paper proposes a systematic approach that consists of three steps. The feature characterization study identifies the fine-grain GPU utilization metrics that influence the power consumption and execution time of a given workload. To understand the performance, power, and energy consumption behaviors of a workload across GPU's DVFS design space, we derived analytical power and performance models using the identified fine-grain features. Here, it is shown that the same set of GPU utilization metrics can estimate both the power consumption and execution time while being agnostic of changes to frequency and input sizes. Applying a power control with the single objective of reducing power may cause performance degradation, leading to more energy consumption. A multi-objective approach is proposed to select the optimal GPU DVFS configuration for a workload that reduces power consumption with negligible degradation in performance. The evaluation was conducted using SPEC ACCEL benchmarks and three real applications - NAMD LAMMPS, and LSTM on NVIDIA GV100, GA100, and AMD MI210 GPUs. On average, real applications showed 29.6% energy savings with a performance loss of 5.2% on GA100 and 22.6% energy savings with a performance loss of 4.7% on GV100. Moreover, the proposed models are portable to real applications, GPU architectures, and vendors, and require metric collection at only the default frequency rather than all supported DVFS configurations. Additionally, we conducted a comparison between our models and the GPU assembly instructions (PTX)-based static models. The results revealed a significant reduction in the average error rates, with a decrease from 19.7% to 3.1% for power models and from 29.4% to 5.2% for performance models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

SU-F-T-144: Analytical Closed Form Approximation for Carbon Ion Bragg Curves in Water

Purpose: Semi-empirical modeling is a powerful computational method in radiation dosimetry. A set of approximations exist for proton ion depth dose distribution (DDD) in water. However, the modeling is more complicated for carbon ions due to fragmentation. This study addresses this by providing and evaluating a new methodology for DDD modeling of carbon ions in water. Methods: The FLUKA, Monte Carlo (MC) general-purpose transport code was used for simulation of carbon DDDs for energies of 100–400 MeV in water as reference data model benchmarking. Based on Thomas Bortfeld’s closed form equation approximating proton Bragg Curves as a basis, we derived the critical constants for a beam of Carbon ions by applying models of radiation transport by Lee et. al. and Geiger to our simulated Carbon curves. We hypothesized that including a new exponential (κ) residual distance parameter to Bortfeld’s fluence reduction relation would improve DDD modeling for carbon ions. We are introducing an additional term to be added to Bortfeld’s equation to describe fragmentation tail. This term accounts for the pre-peak dose from nuclear fragments (NF). In the post peak region, the NF transport will be treated as new beams utilizing the Glauber model for interaction cross sections and the Abrasion- Ablation fragmentation model. Results: The carbon beam specific constants in the developed model were determined to be : p= 1.75, β=0.008 cm-1, γ=0.6, α=0.0007 cm MeV, σmono=0.08, and the new exponential parameter κ=0.55. This produced a close match for the plateau part of the curve (max deviation 6.37%). Conclusion: The derived semi-empirical model provides an accurate approximation of the MC simulated clinical carbon DDDs. This is the first direct semi-empirical simulation for the dosimetry of therapeutic carbon ions. The accurate modeling of the NF tail in the carbon DDD will provide key insight into distal edge dose deposition formation.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2021

CNN-Encoder-Decoder Model

Code and data for training CNN-Encoder-Decoder model described in the publication 'Noise reduction in X-ray photon correlation spectroscopy with convolutional neural networks encoder-decoder models.'

Konstantinova, Tatiana [Brookhaven National Lab. (↗
DOE OSTI2015

Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®

Ever-tightening regulations on fuel economy, and the likely future regulation of carbon emissions, demand persistent innovation in vehicle design to reduce vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials, by adding material diversity and composite materials, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing plate thickness while retaining sufficient strength and ductility required for durability and safety. A project to develop computational material models for advanced high strength steel is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the US Department of Energy. Under this program, new Third Generation Advanced High Strength Steel (i.e., 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. The objectives of the project are to integrate atomistic, microstructural, forming and performance models to create an integrated computational materials engineering (ICME) toolkit for 3GAHSS. The mechanical properties of Advanced High Strength Steels (AHSS) are controlled by many factors, including phase composition and distribution in the overall microstructure, volume fraction, size and morphology of phase constituents as well as stability of the metastable retained austenite phase. The complex phase transformation and deformation mechanisms in these steels make the well-established traditional techniques obsolete, and a multi-scale microstructure-based modeling approach following the ICME [0]strategy was therefore chosen in this project. Multi-scale modeling as a major area of research and development is an outgrowth of the Comprehensive Test Ban Treaty of 1996 which banned surface testing of nuclear devices [1]. This had the effect that experimental work was reduced from large scale tests to multiscale experiments to provide material models with validation at different length scales. In the subsequent years industry realized that multi-scale modeling and simulation-based design were transferable to the design optimization of any structural system. Horstemeyer [1] lists a number of advantages of the use of multiscale modeling. Among these are: the reduction of product development time by alleviating costly trial-and-error iterations as well as the reduction of product costs through innovations in material, product and process designs. Multi-scale modeling can reduce the number of costly large scale experiments and can increase product quality by providing more accurate predictions. Research tends to be focussed on each particular length scale, which enhances accuracy in the long term. This paper serves as an introduction to the LS-OPT and LS-DYNA methodology for multi-scale modeling. It mainly focuses on an approach to integrate material identification using material models of different length scales. As an example, a multi-scale material identification strategy, consisting of a Crystal Plasticity (CP) material model and a homogenized State Variable (SV) model, is discussed and the parameter identification of the individual material models of different length scales is demonstrated. The paper concludes with thoughts on integrating the multi-scale methodology into the overall vehicle design.

Stander, Nielen↗
NASA NTRS1976

The formulation of simulation models of aeronautical systems

Recent developments in formula-manipulation compilers have led to a significant reduction in the time spent in formulating models of complex multi-degrees-of-freedom dynamical systems. MACSYMA, a computer system that can be used to perform symbolic manipulations in an interactive mode, is applied to the problem of formulating models of aeronautical systems for simulation studies. An example demonstrates that once the procedure is established, the formulation and modification of the models can be reduced to a series of routine computer operations.

Howard, J. C.↗
NASA NTRS1996

Drag Reduction Devices for Aircraft (Latest Citations from the Aerospace Database)

The bibliography contains citations concerning the modeling, application, testing, and development of drag reduction devices for aircraft. Slots, flaps, fences, large-eddy breakup (LEBU) devices, vortex generators and turbines, Helmholtz resonators, and winglets are among the devices discussed. Contour shaping to ensure laminar flow, control boundary layer transition, or minimize turbulence is also covered. Applications include the wings, nacelles, fuselage, empennage, and externals of aircraft designed for high-lift, subsonic, or supersonic operation. The design, testing, and development of directional grooves, commonly called riblets, are covered in a separate bibliography.(Contains 50-250 citations and includes a subject term index and title list.)

AIRCRAFT DESIGN↗
DOE OSTI2015

Oxygen reduction reaction induced pH-responsive chemo-mechanical hydrogel actuators

We describe and characterize elementary designs for electrochemical micro- and macro-scale chemomechanical hydrogel actuators. The actuation of a pH-sensitive cross-linked polyacrylic acid (PAA) hydrogel is driven in the model devices through the oxygen reduction reaction (ORR) occurring at the electrodes of an embedded Au mesh micro-electrochemical array. Proton consumption by the ORR at the cathode of the embedded electrochemical cell leads to the formation of a localized pH gradient that in turn drives the strain response in the composite actuators. The dynamics result from the ionization of the carboxylic acid moieties of the PAA network in the high pH region, yielding an osmotic pressure that drives a volumetric expansion due to water imbibition. This system actuates both stably and reversibly; when the electrochemically-induced ORR is halted, the localized pH gradient dissipates due to diffusive mixing, which in turn relaxes the induced strains. Two approaches to the fabrication of hydrogel actuators were examined in this work. The first method adopted a design based on small flagella (~0.2 mm × 1.5 mm × 60 μm, width × length × height) in which the actuating PAA structures are molded atop a set of fixed electrodes mounted on a supporting substrate. These hydrogel actuators show fast, large-amplitude, and largely reversible responses in the ORR mediated chemomechanical dynamics. We also investigated larger hydrogel actuators (~4.5 mm × 11 mm × 1 mm, width × length × height), based on an autonomous design that embeds an open mesh stretchable micro-electrode array within the hydrogel. Furthermore, the significant and design-dependent impacts of mass transfer on the chemomechanical dynamics are evidenced in each case, a feature examined to elucidate more efficient mesoscopic design rules for actuators of this form.

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

The Energy Modeling Forum (EMF)-30 Study on Short-Lived Climate Forcers: Introduction and Overview

The Energy Modeling Forum (EMF)-30 inter-comparison study on short-lived climate forcers (SLCFs) focuses on black carbon (BC) and methane, two of the most important warming SLCFs. The potential impact on climate change of methane and BC-focused emission reductions in the transport and residential sectors were quantified using nine integrated assessment models and a simple climate model. These SLCF reductions reduced global temperatures by 0.18–0.26 °C in 2050 across the models for central climate parameters, with methane being the dominant contributor. The incremental impact of SLCF-focused reductions is much smaller when combined with a broader climate policy. Individual modeling groups examined the health benefits of air pollutant reductions, climate policy co-benefits, and quantified market impacts from air pollutant damages. Model structure and set-up impact on results are discussed along with areas for future work.

Smith, Steven J.↗
DOE OSTI2016

The environmental and public health benefits of achieving high penetrations of solar energy in the United States

Here, we estimate the environmental and public health benefits that may be realized if solar energy cost reductions continue until solar power is competitive across the U.S. without subsidies. Specifically, we model, from 2015 to 2050, solar power–induced reductions to greenhouse gas (GHG) emissions, air pollutant emissions, and water usage. To find the incremental benefits of new solar deployment, we compare the difference between two scenarios, one where solar costs have fallen such that solar supplies 14% of the nation's electricity by 2030 and 27% by 2050, and a baseline scenario in which no solar is added after 2014. We monetize benefits, where credible methods exist to do so. We find that under these scenarios, solar power reduces GHG and air pollutants by ~10%, from 2015 to 2050, providing a discounted present value of 56–789 billion USD (central value of ~250 billion USD, equivalent to ~2 ¢/kWh-solar) in climate benefits and 77–298 billion USD (central value of 167 billion USD, or ~1.4 ¢/kWh-solar) in air quality and public health benefits. The ranges reflect uncertainty within the literature about the marginal impact of emissions of GHG and air pollutants. Solar power is also found to reduce water withdrawals and consumption by 4% and 9%, respectively, including in many drought-prone states.

14 SOLAR ENERGY↗