Results for “expanded analysis” — Page 56

DOE OSTI2018

Techno-Economic Renewable Energy Potential on Tribal Lands

Renewable energy technologies provide opportunities for diversification, energy independence, environmental sustainability, and new revenue streams for Native American Indian tribes and Alaska Native villages. Many of these lands are in areas with that have abundant renewable energy, such as wind, solar, and biomass. This study estimates the technical and economic potential for renewable energy development on tribal lands. It aims to support tribes in decision-making as they evaluate technologies, potential scales of development, and economic viability. The resources analyzed here include wind, solar photovoltaics (PV) and concentrating solar power (CSP), woody biomass, biogas, geothermal, and hydropower. The study provides updated information to a previous renewable energy technical potential analysis on tribal lands, Geospatial Analysis of Renewable Energy Technical Potential on Tribal Lands (Doris et al. 2013). It includes current information, refined data, additional locations (in Alaska, for distributed generation only), and an expanded scope expansion that includes an economic evaluation of the renewable energy potential.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2016

High-energy synchrotron study of in-pile-irradiated U–Mo fuels

Here synchrotron scattering analysis results on U–7wt.%Mo fuel specimens irradiated in the Advanced Test Reactor to three burnup levels (3.0, 5.2, and 6.3 × 1021 fission/cm3) are reported. Mature fission gas bubble superlattice was observed to form at intermediate burnup. The superlattice constant was determined to be 11.7 and 12.0 nm by wide-angle and small-angle scattering respectively. Grain sub-division takes place throughout the irradiation and causes the collapse of the superlattice at high burnup. The bubble superlattice expands the U–Mo lattice and acts as strong sink for radiation-induced defects. The evolution of dislocation loops was, therefore, suppressed until the bubble superlattice collapsed.

metallic nuclear fuel↗

NASA NTRS1993

Cosmic physics data analysis program

A data analysis program was carried out to investigate the intensity, propagation, and origin of primary Cosmic Ray Galactic electrons. Scanning was carried out on two new balloon flight experiments as well as the border area of previous experiments. The identification and evaluation of the energies of the primary electrons were carried out. A new analysis of these data were incorporated into an overall evaluation of the roll of electrons in the problem of the origin of cosmic rays. Recent measurements indicate that the earth may be within the expanding Geminga supernova shock wave which is expected to have a major effect upon the propagation and the energy spectrum of galactic electrons. Calculations with the Geminga model indicate that the cut-off energy may be very close to the observed highest energy electrons in our analysis.

Wilkes, R. Jeffrey↗

NASA NTRS1989

A linear shock cell model for jets of arbitrary exit geometry

The shock cell structures of single supersonic non-ideally expanded jets with arbitrary exit geometry are studied. Both vortex sheets and realistic mean profiles are considered for the jet shear layer. The boundary element method is used to predict the shock spacing and screech tones in a vortex sheet model of a single jet. This formulation enables the calculations to be performed only on the vortex sheet. This permits the efficient and convenient study of complicated jet geometries. Results are given for circular, elliptic and rectangular jets and the results are compared with analysis and experiment. The agreement between the predictions and measurements is very good but depends on the assumptions made to predict the geometry of the fully expanded jet. A finite diffference technique is used to examine the effect of finite mixing layer thickness for a single jet. The finite thickness of the mixing layer is found to decrease the shock spacing by approximately 20 percent over the length of the jet potential core.

Morris, P. J.↗

DOE OSTI2020

Description and Use of SCALE Sampler Parametric Capability for Engineering Analysis and Optimization

The Sampler sequence was introduced into the SCALE nuclear modeling and simulation suite in SCALE 6.2 to perform uncertainty quantification via random sampling of nuclear data, material number densities, and dimensions. Sampler was expanded with the introduction of a parametric capability in SCALE 6.2.2. This paper discusses input for the Sampler parametric sequence and presents two case studies of analyses performed using the sequence. These case studies include preconceptual design of a package for transporting high assay low-enriched uranium (HALEU) oxide and scoping calculations to support subcritical limit development for a future update of the ANSI/ANS-8.1 (ANS-8.1) standard. The parametric capability within Sampler provides many benefits to analysts. For instance, parametric sweeps are frequently used to identify optimum parameter values as part of safety analysis or system design, but such sweeps can require substantial engineering time or may rely on custom-written scripts or scripts such as Write One, Run Many (or WORM) developed outside of any software quality assurance program. With the parametric capabilities in Sampler, however, a large number of inputs can be generated automatically without recourse to scripting by individual analysts. The parametric capability can also be used in lieu of the CSAS5S search sequence to identify optimum parameters more simply with straightforward inputs and outputs. Sampler can also be used to calculate input parameters from engineering specifications. For example, diameters can be converted to radii, or masses can be used to calculate number densities. Overall, the Sampler parametric capability provides a robust feature within SCALE, eliminating the need for user-developed scripting.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Industry Facing PV Degradation Prediction Tool and Database to Enable a 50-Year Life Module

The Photovoltaic (PV) industry constantly aims for lower costs, higher-efficiency cells, and improved module designs. These trends lead to using new materials, designs, and manufacturing processes, resulting in a continually changing technological landscape. These changes can potentially introduce new, unknown degradation mechanisms and failure modes that are difficult to diagnose, analyze, test, and model. This introduces uncertainty into the expected lifetime of PV modules of 25 years. Furthermore, research efforts aim for up to 50 years of service life while keeping performance degradation at a minimum for decades of outdoor weathering - putting additional pressure on improving the accuracy of long-term durability and reliability assessments. Here there is a need to organize the existing degradation data into an accessible format and to provide industry relevant tools for extrapolation from laboratory to field conditions. Because the core of this type of analysis involves calculations that are complicated but ubiquitous for many degradation processes, an enhanced predictive modeling framework will facilitate the analysis to help researchers keep up with the rapid pace of technological changes. In this work, we present an online tool that can be used to search for and analyze degradation information and extrapolate PV module performance and durability to field exposure. A graphical user interface will aid in the understanding of the results. The prediction tool will be built modular and published as open source, enabling users to expand on the existing framework. We use an integration pipeline approach that allows us to leverage weather data from the National Solar Radiation Database to perform geospatial degradation analysis in the US and worldwide. Our repository will contain various degradation models and material parameters suitable for the reliability and durability assessment of materials and components deployed outdoors. We hope to become a repository that can be used for weathering and degradation analysis for various applications beyond the PV industry.

degradation↗

DOE OSTI2024

3D Lead-Organoselenide-Halide Perovskites and their Mixed-Chalcogenide and Mixed-Halide Alloys

Here, we incorporate Se into the 3D halide perovskite framework using the zwitterionic ligand: SeCYS ( + NH 3 (CH 2 ) 2 Se - ), which occupies both the X - and A + sites in the prototypical ABX 3 perovskite. The new organoselenide-halide perovskites: (SeCYS)PbX 2 (X=Cl, Br) expand upon the recently discovered organosulfide-halide perovskites. Single-crystal X-ray diffraction and pair distribution function analysis reveal the average structures of the organoselenide-halide perovskites, whereas the local lead coordination environments and their distributions were probed through solid-state 77 Se and 207 Pb NMR, complemented by theoretical simulations. Density functional theory calculations illustrate that the band structures of (SeCYS)PbX 2 largely resemble those of their S analogs, with similar band dispersion patterns, yet with a considerable band gap decrease. Optical absorbance measurements indeed show band gaps of 2.07 and 1.86 eV for (SeCYS)PbX 2 with X=Cl and Br, respectively. We further demonstrate routes to alloying the halides (Cl, Br) and chalcogenides (S, Se) continuously tuning the band gap from 1.86 to 2.31 eV–straddling the ideal range for tandem solar cells or visible-light photocatalysis. The comprehensive description of the average and local structures, and how they can fine-tune the band gap and potential trap states, respectively, establishes the foundation for understanding this new perovskite family, which combines solid-state and organo-main-group chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Thermodynamic control on the decomposition of organic matter across different electron acceptors

The increasing availability of high-resolution characterization of natural organic matter (OM) data has shifted the paradigm of lumped descriptions of OM components and potential microbial activities. Our recent development of a substrate-explicit thermodynamic model uniquely enables incorporating complex OM pools to formulate biogeochemical reaction models based on their elemental compositions. While this previous work facilitates prediction of aerobic respiration of complex OM, it is equally imperative to consider the role of non-oxygenic electron acceptors in regulating OM turnover and the fate of carbon. In this study, we significantly expand our previous model by flexibly incorporating both detailed OM chemistry and electron acceptors other than oxygen. Here, our modeling analysis has revealed substantial variations in the energy status of OM molecules across different soils, which drive the co-occurrence of different electron-accepting processes. We demonstrated the effectiveness of the proposed model using a consistency check with experimental data. Through systematic evaluation of the impact of diverse chemical inputs (both electron donors and acceptors) on OM decomposition, the new model also revealed how key microbial growth parameters such as carbon use efficiency (CUE) and reaction rates vary across different electron-accepting processes. Our model provides a unified framework integrating thermodynamic and kinetic constraints on microbial metabolic activities. It complements traditional kinetic models, which are often designed solely to capture mass fluxes. We conclude that thermodynamic modeling emerges as a powerful tool for describing the mechanisms underlying the interplay between microbial growth and OM chemistry and cycling across different electron acceptors, enhancing our ability to project complex ecosystem behaviors in dynamic environments.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Understanding Fragmentation of Organic Small Molecules in Atom Probe Tomography

In atom probe tomography of molecular organic materials, field ionization of either entire molecules or molecular fragments can occur, but the mechanism governing this behavior was not previously understood. This work explains when a doubly ionized small molecule organic material is expected to undergo fragmentation. Here, we find that multiple detection events arising from post-ionization fragmentation of a parent molecular dication into two daughter ions is well explained by the free energy and geometries of the molecules computed using density functional theory. Of the systems studied, exergonic free energies for formation of the daughter ions, smaller activation energies for dissociation, and increases in bond length are all found to be quantitative predictors for ion fragmentation. This work expands the applicability of atom probe tomography to organic materials by increasing the fundamental understanding of processes occurring during this analysis technique.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Sensor Fusion: Comprehensive Real-Time, On-Line Monitoring for Process Control via Visible, Near-Infrared, and Raman Spectroscopy

On-line monitoring based on optical spectroscopy provides unprecedented insight into the chemical composition of process streams or batches. Amplifying this approach through utilizing multiple forms of optical spectroscopy in sensor fusion can greatly expand the number and type of chemical species that can be identified and quantified. This is demonstrated herein, on the analysis of used nuclear fuel recycling streams: highly complex processes with multiple target and interfering analytes. The optical techniques of visible absorbance, near infrared absorbance, and Raman spectroscopy were combined to quantify plutonium (III, IV, VI), uranium (IV, VI), neptunium (IV, V, VI), and nitric acid. Chemometric modeling was used to quantify analytes in process streams in real-time and results were successfully used to enable immediate process control and generation of a product stream at a set composition ratio. This represents a significant step forward in the ability to monitor and control complex chemical processes occurring in harsh chemical environments.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Structure of an RNA G-quadruplex from the West Nile virus genome

Potential G-quadruplex sites have been identified in the genomes of DNA and RNA viruses and proposed as regulatory elements. The genus Orthoflavivirus contains arthropod-transmitted, positive-sense, single-stranded RNA viruses that cause significant human disease globally. Computational studies have identified multiple potential G-quadruplex sites that are conserved across members of this genus. Subsequent biophysical studies established that some G-quadruplexes predicted in Zika and tickborne encephalitis virus genomes can form and known quadruplex binders reduced viral yields from cells infected with these viruses. The susceptibility of RNA to degradation and the variability of loop regions have made structure determination challenging. Despite these difficulties, we report a high-resolution structure of the NS5-B quadruplex from the West Nile virus genome. Analysis reveals two stacked tetrads that are further stabilized by a stacked triad and transient noncanonical base pairing. This structure expands the landscape of solved RNA quadruplex structures and demonstrates the diversity and complexity of biological quadruplexes. We anticipate that the availability of this structure will assist in solving further viral RNA quadruplexes and provides a model for a conserved antiviral target in Orthoflavivirus genomes.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Charting the chemical space of Zintl phases with graph neural networks and bonding insights

A large number of Zintl phases have been discovered by solid-state chemists driven by empirical knowledge, chemical intuition and in some cases, through serendipitous accidents. These discoveries have only scratched the surface, given the vast compositional and structural diversity that Zintl phases can accommodate. The large chemical space of Zintl phases, as well as intermetallic compounds in general, remain under-explored. Here, we use graph neural networks and the upper bound energy minimization approach to efficiently scan a large chemical space of >90 000 hypothetical Zintl phases and accurately discover 1810 new thermodynamically stable phases with 90% precision, as validated with first-principles calculations. We show that our approach is more than 2× more accurate in predicting DFT stability than M3GNet (40% precision) on the same dataset. Using a random forest model and SHAP analysis, we demonstrate the critical role of ionic bonding in the thermodynamic stability of Zintl phases. Our results not only expand the known chemical landscape of Zintl phases but also highlight the efficacy of machine learning frameworks combined with domain knowledge in uncovering chemically meaningful insights across complex intermetallics.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2020 .Net)

To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.

Wang, Michael↗

DOE OSTI2021

Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2021 .Net)

To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.

Wang, Michael↗

DOE OSTI2022

Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2022 .Net)

To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.

Wang, Michael↗

DOE OSTI2023

Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2023 .Net)

To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.

Wang, Michael↗

DOE OSTI2015

Search for Low-Mass Dark Matter wtih SuperCDMS Soudan and Study of Shorted Electric Field Configurations in CDMS Detectors

The area of dark matter is one of the most interesting and exciting topics in physics today. Existing at the intersection of particle physics and astrophysics, the existence of a new dark matter particle can be used to explain many astrophysical and cosmological observations, as well as to reconcile outstanding issues in the standard model of particle physics. Experiments such as SuperCDMS are built to detect dark matter in the lab by looking for low-energy nuclear recoils produced by collisions between dark matter particles and atoms in terrestrial detectors. SuperCDMS Soudan is particularly well-suited to follow up on possible hints of low-mass dark matter seen by other recent experiments because of its low thresholds and excellent background discrimination. Analyzing SuperCDMS Soudan data to look for low-mass dark matter comes with particular challenges because of the low signal-to-noise very near threshold. However, with a detailed background model developed by scaling high-energy events down into the low-energy signal region, SuperCDMS Soudan produced worldleading limits on the existence of low-mass dark matter. In addition, a few SuperCDMS Soudan detectors experienced cold hardware problems that can affect the data collected. Of particular interest is one detector considered for the low-mass WIMP search that has one of its charge electrodes shorted to chassis ground. Three events were observed in this detector upon unblinding the SuperCDMS Soudan low-energy data, even though <1 event was expected based on pre-unblinding calulations. However, the data collected by the shorted detector may have been compromised since an electrode shorted to ground will modify the electric field in the detector. The SuperCDMS Detector Monte Carlo (DMC) provides an excellent way to model the effects of the modified electric field, so a new model of the expected backgrounds in the low-mass WIMP search is developed using the DMC to try to explain how the short may have affected the data collected. This thesis is organized as follows: Chapter 1 gives a broad introduction to dark matter, discussing the astrophysical and cosmological evidence for its existence, listing several possible particle physics candidates, and outlining several experimental strategies to look for dark matter. Chapter 2 is an overview of CDMS detector technology and the experimental setup at the Soudan Underground Laboratory, with a focus on how data coming out of Soudan is analyzed. Chapter 3 presents results from a search for low-mass dark matter at SuperCDMS Soudan and discusses the interpretation of the results. Chapter 4 contains follow-up work that uses the CDMS Detector Monte Carlo (DMC) to understand the possible systematics associated with a detector that had one of its charge electrodes shorted to ground. This chapter represents the first time the DMC has been used to inform ongoing CDMS analysis. Chapter 5 takes a brief detour into the world of effective field theory (EFT), examining the consequences of an expanded set of possible WIMP-nucleon interactions in the EFT framework. Finally, Chapter 6 wraps up the material of the previous chapters and discusses how the research presented in this thesis can be applied as CDMS moves toward SuperCDMS SNOLAB.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

Organic Rankine Cycle Integration and Optimization for High Efficiency CHP Genset Systems (Final Technical Report)

This project successfully advanced the integration of Organic Rankine Cycle (ORC) technology with reciprocating engine–based combined heat and power (CHP) systems to improve electrical efficiency, total CHP efficiency, and grid-responsive operation. Over three budget periods, the work progressed from high-temperature ORC component development and thermodynamic model validation to next-generation system design, working fluid transition, and techno-economic analysis. Key technical accomplishments include development and validation of a thermodynamic model capable of accurately predicting ORC performance across an expanded temperature and pressure envelope; successful identification and validation of low-global-warming-potential (GWP) working fluids—most notably R1233zd(E)—as viable replacements for R245fa; and demonstration of scalable ORC architectures suitable for integration with 1–20 MW class reciprocating engines. These advances enable flexible CHP configurations that can increase electrical output while maintaining high overall utilization of available thermal energy. The project also produced a clean-sheet design for a next-generation ORC system targeting substantially higher power output per unit, supported by detailed component selection, heat exchanger evaluation, and system-level modeling. Techno-economic analyses indicate that ORC-enabled flexible CHP systems can meet or exceed Department of Energy (DOE) efficiency targets while providing value to both facility operators and the electric grid.. Late-stage testing of the largest next-generation ORC prototype identified limitations related to pump net positive suction head (NPSH) requirements and condenser flooding under certain operating conditions. Although these issues constrained full validation of that configuration within the project timeframe, they provided clear and actionable design guidance for future system refinements. Importantly, validated modeling, smaller-scale testing, and working fluid evaluations confirmed the technical viability of the overall approach. In aggregate, this project met its core objectives by establishing validated design tools, de-risking key ORC technologies for CHP applications, and defining a credible pathway toward commercialization of flexible, high-efficiency CHP systems. The results form a strong foundation for continued development and deployment beyond the conclusion of the DOE-funded effort.

20 FOSSIL-FUELED POWER PLANTS↗