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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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At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Longitudinal Assessment of Lung Cancer Progression in Mice Using the Sodium Iodide Symporter Reporter Gene and SPECT/CT Imaging

Lung cancer has the highest mortality rate of any tissue-specific cancer in both men and women. Research continues to investigate novel drugs and therapies to mitigate poor treatment efficacy, but the lack of a good descriptive lung cancer animal model for preclinical drug evaluation remains an obstacle. Here we describe the development of an orthotopic lung cancer animal model which utilizes the human sodium iodide symporter gene (hNIS; SLC5A5) as an imaging reporter gene for the purpose of non-invasive, longitudinal tumor quantification. hNIS is a glycoprotein that naturally transports iodide (I- ) into thyroid cells and has the ability to symport the radiotracer 99mTc-pertechnetate ( 99mTcO4 - ). A549 lung adenocarcinoma cells were genetically modified with plasmid or lentiviral vectors to express hNIS. Modified cells were implanted into athymic nude mice to develop two tumor models: a subcutaneous and an orthotopic xenograft tumor model. Tumor progression was longitudinally imaged using SPECT/CT and quantified by SPECT voxel analysis. hNIS expression in lung tumors was analyzed by quantitative real-time PCR. Additionally, hematoxylin and eosin staining and visual inspection of pulmonary tumors was performed. We observed that lentiviral transduction provided enhanced and stable hNIS expression in A549 cells. Furthermore, 99mTcO4 - uptake and accumulation was observed within lung tumors allowing for imaging and quantification of tumor mass at twotime points. This study illustrates the development of an orthotopic lung cancer model that can be longitudinally imaged throughout the experimental timeline thus avoiding inter-animal variability and leading to a reduction in total animal numbers. Furthermore, our orthotopic lung cancer animal model is clinically relevant and the genetic modification of cells for SPECT/CT imaging can be translated to other tissue-specific tumor animal models.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Extending JuTrack’s capabilities to the FRIB accelerator to enhance online modeling

JuTrack is a Julia-based accelerator modeling and tracking package that utilizes compiler-level automatic differentiation (AD) to enable fast and accurate derivative calculations. While JuTrack provides a solid foundation for beam dynamics simulations, its capabilities must be extended to support the Facility for Rare Isotopes (FRIB) linac. This includes modeling heavy-ion linac accelerator components such as the liquid-lithium charge stripper, which facilitates efficient acceleration by remove electrons from heavy isotopes, and incorporating multi-charge state acceleration tracking, which allows for charge-dependent beam dynamics. These extensions address challenges such as the beam matching and optimization of multi charge state through various accelerating structures and beam-material interaction modeling while maintaining the auto differentiation capability. This work focuses on adapting JuTrack to incorporate these elements, enhancing its online modeling abilities. We present modifications to JuTrack’s framework and demonstrate their performance in FRIB simulations.

Accelerator Physics↗
DOE OSTI2020

New opportunities at the next-generation neutrino experiments I: BSM neutrino physics and dark matter

The combination of the high intensity proton beam facilities and massive detectors for precision measurements of neutrino oscillation parameters including the charge-parity violating (CPV) phase will open the door to help make beyond the standard model (BSM) physics reachable even in low energy regimes in the accelerator-based experiments. Large-mass detectors with highly precise tracking and energy measurements, excellent timing resolution, and low energy thresholds will enable the searches for BSM phenomena from cosmogenic origin, as well. Therefore, it is also conceivable that BSM topics in the next-generation neutrino experiments could be the dominant physics topics in the foreseeable future, as the precision of the neutrino oscillation parameter and CPV measurements continue to improve. This paper reviews the current landscape of BSM theory in neutrino experiments in two selected areas of the BSM topics-dark matter and neutrino related BSM-and summarizes the current results from existing neutrino experiments to set benchmarks for both theory and experiment. This paper then provides a review of upcoming neutrino experiments throughout the next 10 to 15 year time scale and their capabilities to set the foundation for potential reach in BSM physics in the two aforementioned themes. An important outcome of this paper is to ensure theoretical and simulation tools exist to carry out studies of these new areas of physics, from the first day of the experiments, such as Deep Underground Neutrino Experiment in the U.S. and Hyper-Kamiokande Experiment in Japan.

dark sector↗
DOE OSTI2015

Preface: Special Topic on Coarse Graining of Macromolecules, Biopolymers, and Membranes

This special issue highlights new developments in theory and coarse-graining in biological and synthetic macromolecules and membranes. Such approaches give unique insights into the principles and design of the structures, dynamics, and assembly processes of these complex fluids and soft materials, where the length and time scales are often prohibitively long for fully atomistic modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Combustion chemistry in the twenty-first century: Developing theory-informed chemical kinetics models

Over the past 20 to 25 years theoretical chemistry (particularly theoretical chemical kinetics) has played an increasingly important role in developing chemical kinetics models for combustion. Theoretical methods of obtaining rate parameters are now competitive in accuracy with experiment, particularly for small molecules. Moreover, theoretical methods can deal with conditions that experiments frequently cannot. In addition to increased accuracy, theory has rejuvenated methods and discovered phenomena that were completely unappreciated, or at least underappreciated, in the 20th century. Our primary interest here is in molecular-level issues, i.e. in calculating rate and transport parameters. However, dealing with kinetics models that involve thousands of reactions and hundreds of species is important for practical applications and is relatively new to the 21st century. Theory, in a general sense, and theoretical methods development have a role to play here too. We discuss in this review all these topics in some detail with an emphasis on issues and methods that have emerged in the last 20 years or so. Even so, our review is selective, rather than comprehensive, out of necessity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Beam Dynamics in g-2 Storage Ring

The muon anomalous magnetic moment has played an important role in constraining physics beyond the Standard Model. The Fermilab Muon g-2 Experiment has a goal to measure it to unprecedented precision: 0.14 ppm. To achieve this goal, we must understand the beam dynamics systematic effects in the muon storage ring. We will present the muon beam dynamics and discuss two specific topics here: the beam resonance which is related to the muon loss and the fast rotation analysis to determine the muon momentum distribution.

43 PARTICLE ACCELERATORS↗
DOE OSTI2013

Annual Energy Outlook 2013 With Projections to 2040

The Annual Energy Outlook 2013 (AEO2013), prepared by the U.S. Energy Information Administration (EIA), presents long-term projections of energy supply, demand, and prices through 2040, based on results from EIA’s National Energy Modeling System. The report begins with an “Executive summary” that highlights key aspects of the projections. It is followed by a “Legislation and regulations” section that discusses evolving legislative and regulatory issues, including a summary of recently enacted legislation and regulations, such as: Updated handling of the U.S. Environmental Protection Agency’s (EPA) National Emissions Standards for Hazardous Air Pollutants for industrial boilers and process heaters; New light-duty vehicle (LDV) greenhouse gas (GHG) and corporate average fuel economy (CAFE) standards for model years 2017 to 2025; Reinstatement of the Clean Air Interstate Rule (CAIR) after the court’s announcement of intent to vacate the Cross-State Air Pollution Rule (CSAPR); and Modeling of California’s Assembly Bill 32, the Global Warming Solutions Act (AB 32), which allows for representation of a cap-and-trade program developed as part of California’s GHG reduction goals for 2020. The “Issues in focus” section contains discussions of selected energy topics, including a discussion of the results in two cases that adopt different assumptions about the future course of existing policies, with one case assuming the elimination of sunset provisions in existing policies and the other case assuming the elimination of the sunset provisions and the extension of a selected group of existing public policies—CAFE standards, appliance standards, and production tax credits. Other discussions include: oil price and production trends in AEO2013; U.S. reliance on imported liquids under a range of cases; competition between coal and natural gas in electric power generation; high and low nuclear scenarios through 2040; and the impact of growth in natural gas liquids production. The “Market trends” section summarizes the projections for energy markets. The analysis in AEO2013 focuses primarily on a Reference case, Low and High Economic Growth cases, and Low and High Oil Price cases. Results from a number of other alternative cases also are presented, illustrating uncertainties associated with the Reference case projections for energy demand, supply, and prices. Complete tables for the five primary cases are provided in Appendixes A through C. Major results from many of the alternative cases are provided in Appendix D. Complete tables for all the alternative cases are available on EIA’s website in a table browser at http://www.eia.gov/oiaf/aeo/tablebrowser. AEO2013 projections are based generally on federal, state, and local laws and regulations in effect as of the end of September 2012. The potential impacts of pending or proposed legislation, regulations, and standards (and sections of existing legislation that require implementing regulations or funds that have not been appropriated) are not reflected in the projections. In certain situations, however, where it is clear that a law or regulation will take effect shortly after the Annual Energy Outlook (AEO) is completed, it may be considered in the projection.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Overview of Algorithms for Using Particle Morphology in Pre-Detonation Nuclear Forensics

A major goal in pre-detonation nuclear forensics is to infer the processing conditions and/or facility type that produced radiological material. This review paper focuses on analyses of particle size, shape, texture (“morphology”) signatures that could provide information on the provenance of interdicted materials. For example, uranium ore concentrates (UOC or yellowcake) include ammonium diuranate (ADU), ammonium uranyl carbonate (AUC), sodium diuranate (SDU), magnesium diuranate (MDU), and others, each prepared using different salts to precipitate U from solution. Once precipitated, UOCs are often dried and calcined to remove adsorbed water. The products can be allowed to react further, forming uranium oxides UO3, U3O8, or UO2 powders, whose surface morphology can be indicative of precipitation and/or calcination conditions used in their production. This review paper describes statistical issues and approaches in using quantitative analyses of measurements such as particle size and shape to infer production conditions. Statistical topics include multivariate t tests (Hotelling’s T 2 ), design of experiments, and several machine learning (ML) options including decision trees, learning vector quantization neural networks, mixture discriminant analysis, and approximate Bayesian computation (ABC). ABC is emphasized as an attractive option to include the effects of model uncertainty in the selected and fitted forward model used for inferring processing conditions.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

Hadronic uncertainties versus new physics for the W boson mass and Muon g – 2 anomalies

There are now two single measurements of precision observables that have major anomalies in the Standard Model: the recent CDF measurement of the W mass shows a 7σ deviation and the Muon g – 2 experiment at FNAL confirmed a long-standing anomaly, implying a 4.2σ deviation. Doubts regarding new physics interpretations of these anomalies could stem from uncertainties in the common hadronic contributions. We demonstrate that these two anomalies pull the hadronic contributions in opposite directions by performing electroweak fits in which the hadronic contribution was allowed to float. The fits show that including the g – 2 measurement worsens the tension with the CDF measurement and conversely that adjustments that alleviate the CDF tension worsen the g – 2 tension beyond 5σ. This means that if we adopt the CDF W mass measurement, the case for new physics in either the W mass or muon g – 2 is inescapable regardless of the size of the SM hadronic contributions. Lastly, we demonstrate that a mixed scalar leptoquark extension of the Standard Model could explain both anomalies simultaneously.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

HP-LSP: A reference of land surface phenology from fused Harmonized Landsat and Sentinel-2 with PhenoCam data

Abstract Land surface phenology (LSP) products are currently of large uncertainties due to cloud contaminations and other impacts in temporal satellite observations and they have been poorly validated because of the lack of spatially comparable ground measurements. This study provided a reference dataset of gap-free time series and phenological dates by fusing the Harmonized Landsat 8 and Sentinel-2 (HLS) observations with near-surface PhenoCam time series for 78 regions of 10 × 10 km 2 across ecosystems in North America during 2019 and 2020. The HLS-PhenoCam LSP (HP-LSP) reference dataset at 30 m pixels is composed of: (1) 3-day synthetic gap-free EVI2 (two-band Enhanced Vegetation Index) time series that are physically meaningful to monitor the vegetation development across heterogeneous levels, train models (e.g., machine learning) for land surface mapping, and extract phenometrics from various methods; and (2) four key phenological dates (accuracy ≤5 days) that are spatially continuous and scalable, which are applicable to validate various satellite-based phenology products (e.g., global MODIS/VIIRS LSP), develop phenological models, and analyze climate impacts on terrestrial ecosystems.

Science & Technology - Other Topics↗
DOE OSTI2019

Quantitative impacts of incubation phase transmission of foot-and-mouth disease virus

The current investigation applied a Bayesian modeling approach to a unique experimental transmission study to estimate the occurrence of transmission of foot-and-mouth disease (FMD) during the incubation phase amongst group-housed pigs. The primary outcome was that transmission occurred approximately one day prior to development of visible signs of disease (posterior median 21hours, 95% CI: 1.1–45.0). Updated disease state durations were incorporated into a simulation model to examine the importance of addressing preclinical transmission in the face of robust response measures. Simulation of FMD outbreaks in the US pig production sector demonstrated that including a preclinical infectious period of one day would result in a 40% increase in the median number of farms afected (166 additional farms and 664,912 pigs euthanized) compared to the scenario of no preclinical transmission, assuming suboptimal outbreak response. These fndings emphasize the importance of considering transmission of FMD during the incubation phase in modeling and response planning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Data assimilation in operator algebras

We develop an algebraic framework for sequential data assimilation of partially observed dynamical systems. In this framework, Bayesian data assimilation is embedded in a nonabelian operator algebra, which provides a representation of observables by multiplication operators and probability densities by density operators (quantum states). In the algebraic approach, the forecast step of data assimilation is represented by a quantum operation induced by the Koopman operator of the dynamical system. Moreover, the analysis step is described by a quantum effect, which generalizes the Bayesian observational update rule. Projecting this formulation to finite-dimensional matrix algebras leads to computational schemes that are i) automatically positivity-preserving and ii) amenable to consistent data-driven approximation using kernel methods for machine learning. Moreover, these methods are natural candidates for implementation on quantum computers. Applications to the Lorenz 96 multiscale system and the El Niño Southern Oscillation in a climate model show promising results in terms of forecast skill and uncertainty quantification.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

SYMBA: symbolic computation of squared amplitudes in high energy physics with machine learning

The cross section is one of the most important physical quantities in high-energy physics and the most time consuming to compute. While machine learning has proven to be highly successful in numerical calculations in high-energy physics, analytical calculations using machine learning are still in their infancy. In this work, we use a sequence-to-sequence model, specifically, a transformer, to compute a key element of the cross section calculation, namely, the squared amplitude of an interaction. We show that a transformer model is able to predict correctly 97.6% and 99% of squared amplitudes of quantum chromodynamics and quantum electrodynamics processes, respectively, at a speed that is up to orders of magnitude faster than current symbolic computation frameworks. We discuss the performance of the current model, its limitations and possible future directions for this work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Fuel Injection Dynamics and Composition Effects on RDE Performance

Rotating detonation engines (RDEs) provide a promising route to substantially increasing cycle efficiency in stationary gas turbines. Much of this increase relies on the ability to achieve consistent pressure gain within the combustor. In particular, the design of injectors that feed fuel and air into the detonation channel plays a crucial role. Such injectors have to ensure proper mixing of fuel and oxidizer, while minimizing backflow of detonation products into the feed plenums, and reduce susceptibility to the complex wave structures that exist within the combustor. From a practical perspective, such RDEs also need to operate with variable fuel composition. When fuel mixtures with components that possess vastly different oxidation pathways and time-scales are used, there could be additional losses through deflagrative burning instead of detonation-driven heat release. Such sensitivity to the complete flow path is akin to the physics of thermoacoustic instabilities in conventional gas turbines. In this sense, RDEs pose a unique research challenge: the performance of the device relies on the small-scale heat release process, which is highly dependent on the flow interactions within the full-scale system. As a result, canonical flow configurations, instrumented with detailed diagnostics or modeled using high-fidelity tools, but only focus on the small-scale processes will not contain the key system-level interactions. At the same time, macroscopic measurements and models that only capture system-level performance will not provide insight into the key sources of pressure losses. These couplings and sensitivities provide a formidable challenge to both experimental and simulation studies of the effects Thus, a joint experimental/computational program designed specifically to address these challenges was undertaken in this program. The focus of this program was on two key topics: a) the interaction between injector flow and the overall wave dynamics within the combustor, and b) the deflagration/detonation structure in multi-component fuels that are of practical interest. Both topics involve interaction of small-scale heat release processes with the geometry-dependent wave structure. Studies focused on the study of full-scale RDE systems, based on a 6-inch conventional annular geometry. Experimentally RDEs were studied using a combination of diagnostics. A combination of optical diagnostics and aero-thermo-acoustic analysis based on a combination of spectral and mode decomposition analysis was used to identify the dynamics of the detonation wave and other secondary waves that exist in the system. These studies have helped the identification and investigation of injector and detonation dynamics arising from coupling, and how they affect RDE mixing, detonation structure, operability and performance. Performance of RDEs was investigated through thrust stand measurements, which was used to evaluate the effective pressure gain generated by the system through the concept of equivalent available pressure. Optical diagnostics were developed and implemented to investigate the distribution of heat release, across the detonation wave. Novel optical diagnostics of NIR imaging was also developed and applied to investigate the high temperature / high pressure distribution across the detonation wave. In order to complement the experiments, the computational tools were geared to simulate the full experimental setup. GPU-based acceleration of the models and computations were developed to enable rapid simulation of the full system. In addition, the use of adaptive mesh refinement, and unstructured grid formulation, enabled the investigation of realistic geometries studied in the laboratory. The simulations produced a wealth of detail on the structure of the detonation wave under different operating conditions. Emphasis was placed on quantifying mixture pre-burning and the impact on wave propagation and structure.

03 NATURAL GAS↗
DOE OSTI2019

Halide Perovskites: Is It All about the Interfaces?

Design and modification of interfaces, always a critical issue for semiconductor devices, has become a primary tool to harness the full potential of halide perovskite (HaP)-based optoelectronics, including photovoltaics and light-emitting diodes. In particular, the outstanding improvements in HaP solar cell performance and stability can be primarily ascribed to a careful choice of the interfacial layout in the layer stack. In this review, we describe the unique challenges and opportunities of these approaches (section 1). For this purpose, we first elucidate the basic physical and chemical properties of the exposed HaP thin film and crystal surfaces, including topics such as surface termination, surface reactivity, and electronic structure (section 2). This is followed by discussing experimental results on the energetic alignment processes at the interfaces between the HaP and transport and buffer layers. This section includes understandings reached as well as commonly proposed and applied models, especially the often-questionable validity of vacuum level alignment, the importance of interface dipoles, and band bending as the result of interface formation (section 3). We follow this by elaborating on the impact of the interface formation on device performance, considering effects such as chemical reactions and surface passivation on interface energetics and stability. On the basis of these concepts, we propose a roadmap for the next steps in interfacial design for HaP semiconductors (section 4), emphasizing the importance of achieving control over the interface energetics and chemistry (i.e., reactivity) to allow predictive power for tailored interface optimization.

14 SOLAR ENERGY↗