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Understanding Material Property Impacts on Co-Current Flame Spread: Improving Understanding Crucial for Fire Safety
The prospect of long-term manned space flight brings fresh urgency to the development of an integrated and fundamental approach to the study of material flammability. Currently, NASA uses two tests, the upward flame propagation test and heat and visible smoke release rate test, to assess the flammability properties of materials to be used in space under microgravity conditions. The upward flame propagation test can be considered in the context of the 2-D analysis of Emmons. This solution incorporates material properties by a "mass transfer number", B in the boundary conditions.
Heliophysics 2009 Roadmap and Global Change: Possibilities for Improved Understanding of the Connection
Heliophysics is the science that includes all aspects of the research needed to understand the Sun and its effects on the Earth and the solar system. Six science targets: 1. Origins of Near-Earth Plasma - to understand the origin and transport of terrestrial plasma from its source to the magnetosphere and solar wind. 2. Solar Energetic Particle Acceleration and Transport - to understand how and where solar eruptions accelerate energetic particles that reach Earth. 3. Ion-Neutral Coupling in the Atmosphere - to understand how neutral winds control ionospheric variability. 4. Climate Impacts of Space Radiation - to understand our atmosphere s response to auroral, radiation belt, and solar energetic particles, and the associated effects on nitric oxide (NO) and ozone. 5. Dynamic Geospace Coupling - to understand how magnetospheric dynamics provides energy into the coupled ionosphere-magnetosphere system. 6. Heliospheric Magnetics - to understand the flow and dynamics of transient magnetic structures form the solar interior to Earth.
Understanding of catalytic transformation of shale gas and development of catalysts with high activity and selectivity through experimental exploration and theoretical simulation
Catalysis on transition metal oxides is equivalently important in contrast to that on metal catalysts in chemical and energy transformations. Understanding of catalytic reactions on early transition metal oxide catalysts is fundamentally intriguing and of great practical interest in efficient production of chemical and fuel feedstocks. Fundamental understanding of catalysis on transition metal oxide-based catalysts has been lagged behind catalysis on metals due to the complexity of chemistry and structure of surface and bulk of oxide catalysts and their structural flexibility in reactive environment at high temperatures. The funded DOE project explored surface chemistry of a few reducible oxides including CeO 2 - based, Co 3 O 4 -based, and CoO-based which are significant for heterogeneous catalysis. Through in-situ studies using ambient pressure X-ray photoelectron spectroscopy and high pressure scanning tunneling microscopy, we revealed phase transformation, the accompanying changes of surface chemistry and structure, and uncovered their correlations with catalytic activity and selectivity in catalytic reactions including reduction of NO with CO, water-gas shift, and chemical transformations of methane to methanol and acetic acid under mild conditions. Driven by the following two facts, we propose to pursue fundamental understanding of oxidative dehydrogenation of ethane and oxidative coupling of methane on oxide catalysts through both in-situ studies of catalyst surfaces during catalysis and computational studies in the renewal proposal. One driving force is the significance of oxidative dehydrogenation of ethane and oxidative coupling of methane for utilization of earth-abundant, relatively inexpensive energy resource and the urgent needs of efficient chemical processes to generate ethylene from shale gas. The other is that exploration of surface chemistry of oxide catalysts during catalysis has remained challenging though it is critical in deeply understanding catalysis on oxide catalysts and developing oxide-based catalysts toward high selectivity and activity. Therefore, the overall objective of the renewal proposal is to mechanistically understand the oxidative dehydrogenation of ethane and oxidative coupling of methane at a molecular level through building correlations between surface chemistry of catalysts during catalysis and the corresponding catalytic performances, and thus design catalysts with high selectivity and activity for production of ethylene with the guidance achieved from these fundamental studies. Experiments were designed to explore the influences of electronic states of cations supported on substrate oxides, cations of surface of the substrate oxides, and surface lattice oxygen atoms of the substrate oxides on their catalytic selectivity and activity. Surface chemistry, including oxidation state of the surface monomers and cations of substrate oxides and density of oxygen vacancies during catalysis, will be tracked with AP-XPS during catalysis. A correlation between surface chemistry of these catalysts at different temperatures and their corresponding catalytic selectivity for production of ethylene and activity will be built. Computational studies will calculate adsorption energies of reactant molecules and their dissociated species and intermediates on the catalyst surface, search transition states, and simulate reaction pathway close to experimental studies. By integrating the computational studies into these correlations to be built from experimental studies, fundamental understanding of the catalytic mechanisms of oxidative dehydrogenation of ethane and oxidative coupling of methane at a molecular level will be achieved. With these insights, new catalysts with high selectivity and activity will be developed.
Limitations on the Use of Eye-Tracking Data to Understand Operator Awareness
In the last 20 years, a number of accidents and incidents in commercial aviation have pointed to poor flight crew awareness of basic flight path parameters (e.g., airspeed, bank, pitch). As a result, there is a desire to improve pilot situation awareness and how attention is allocated. Eye-tracking has been a commonly used measure of awareness; it can aid in understanding whether specific indications were fixated, and perhaps how a pilot gathered information (that is, which indications in which sequence). In this paper, we discuss limitations on what eye-tracking data can reveal about pilot awareness and understanding. First, previous studies (e.g., Sarter et al., 2007) have shown that fixation on an indication may not ensure awareness or understanding. Further, an operator may have awareness of information not fixated. Additional measures—such as self-report or control inputs—can help to better establish the extent of pilot awareness and understanding. Second, sequences of fixations (scan patterns) have also become a performance measure. While a small number of recognized scan patterns have been validated for a small set of parameters on the Primary Flight Display (PFD), scan patterns have not been identified to support the broader context of flight path management or flight operations. More important is to understand the full set of drivers underlying the larger pattern of eye fixations; this approach moves away from the idea of well-established scan patterns as a marker of skilled performance and gives a larger role to pilot cognition. Pilots have various reasons to direct attention to specific elements on the interface, such as: - feedback tied to control inputs - a check on compliance with flight path targets - a reaction to an alert or a call out - attempt to understand an unexpected indication - assess progress toward a flight path target The importance of cognition is further implicated in the finding that pilot interviews show that fixating typically is accompanied by expectation; generally, pilots have a strong expectation of what value or indication they will see, which allows more efficient integration of information and an ability to identify indications that suggest an alternative account of the current system state. We will describe a range of eye-tracking measures and how they should and should not be used.
Model Hierarchies for Understanding Atmospheric Circulation
In this review, we highlight the complementary relationship between simple and comprehensive models in addressing key scientific questions to describe Earth's atmospheric circulation. The systematic representation of models in steps, or hierarchies, connects our understanding from idealized systems to comprehensive models and ultimately the observed atmosphere. First, we define three interconnected principles that can be used to characterize the model hierarchies of the atmosphere. We explore the rich diversity within the governing equations in the dynamical hierarchy, the ability to isolate and understand atmospheric processes in the process hierarchy, and the importance of the physical domain and resolution in the hierarchy of scale. We center our discussion on the large-scale circulation of the atmosphere and its interaction with clouds and convection, focusing on areas where simple models have had a significant impact. Our confidence in climate model projections of the future is based on our efforts to ground the climate predictions in fundamental physical understanding. This understanding is, in part, possible due to the hierarchies of idealized models that afford the simplicity required for understanding complex systems.
Soil Aggregate Microbial Communities: Towards Understanding Microbiome Interactions at Biologically Relevant Scales
Soils contain a tangle of minerals, water, nutrients, gases, plant roots, decaying organic matter, and microorganisms which work together to cycle nutrients and support terrestrial plant growth. Most soil microorganisms live in periodically interconnected communities closely associated with soil aggregates, i.e., small (<2 mm), strongly bound clusters of minerals and organic carbon that persist through mechanical disruptions and wetting events. Their spatial structure is important for biogeochemical cycling, and we cannot reliably predict soil biological activities and variability by studying bulk soils alone. To fully understand the biogeochemical processes at work in soils, it is necessary to understand the micrometer-scale interactions that occur between soil particles and their microbial inhabitants. Here, we review the current state of knowledge regarding soil aggregate microbial communities and identify areas of opportunity to study soil ecosystems at a scale relevant to individual cells. We present a framework for understanding aggregate communities as “microbial villages” that are periodically connected through wetting events, allowing for the transfer of genetic material, metabolites, and viruses. Here, we describe both top-down (whole community) and bottom-up (reductionist) strategies for studying these communities. Understanding this requires combining “model system” approaches (e.g., developing mock community artificial aggregates), field observations of natural communities, and broader study of community interactions to include understudied community members, like viruses. Initial studies suggest that aggregate-based approaches are a critical next step for developing a predictive understanding of how geochemical and community interactions govern microbial community structure and nutrient cycling in soil.
Understanding the engines and progenitors of gamma-ray bursts
Our understanding of the engines and progenitors of gamma-ray bursts has expanded through the ages as a broader set of diagnostics has allowed us to test our understanding of these objects. In this work, we review the history of the growth in our understanding, focusing on 3 leading engines and 9 potential progenitors. The first gravitational wave detection of a short burst is the latest in a series of breakthrough observations shaping this understanding and we study the importance of multi-diagnostic, multi-messenger observations on these engines and their progenitors. Our understanding based on a detailed study of nearby bursts can be applied to make predictions for the trends expected as we begin to observe high redshift bursts and we discuss these trends.
Understanding and Constraining the Midlatitude Cloud Optical Depth Feedback in Climate Models (Final Report)
The objectives of this investigation are to provide a deeper understanding of the brightening of middle and high latitude clouds that occurs in many climate models as the climate warms, and to better understand why models give varying estimates of the strength of this negative feedback. The investigation may also provide new information on why models are deficient in their simulation of the present day clouds in these regions. The analysis will reveal which models simulate current clouds most realistically in the regions of interest, and relate this to the strength of the cloud feedbacks in the models. This will improve the uncertainty quantification of climate simulations and will provide theoretical understanding potentially leading to increased reliability of climate change projections. This will enhance the predictive understanding of the Earth system by analyzing the natural and anthropogenic components of global climate change in models. The primary methods involve the study of the clouds in the suite of CMIP5 model climate simulations and comparison of clouds in climate simulations with data from satellite measurement systems, with a particular emphasis on mixed-phase cloud physics, for which ice and water are present simultaneously. State-of-the-art climate model feedback analysis will be combined with new and more comprehensive observations of clouds available from modern measurement systems. Novel use of model simulations in combination with observations enables a deeper understanding of the role of clouds in climate change. Metrics that facilitate model-to-model and model-to-observation comparisons related to mixed-phase cloud physics will be developed and used to highlight challenges and opportunities for improving the state-of-the-science models. This investigation is a collaboration between the University of Washington, where the data work is concentrated and LLNL where the model data and the tools and expertise to do cloud feedback analysis are located. The grant supported the work of 3 different graduate students at different times (McCoy, Wall and Berry) Post-doctoral researcher Blaž Gasparini was also partially supported on this grant and led our collaboration with PNNL scientists. PNNL scientists also collaborated in the work of graduate student Wall (Po-Lun Ma). The main results of our research efforts are reported in 6 papers and 1 book chapter that were supported by this grant.
Understanding and Predictability of Integrated Mountain Hydroclimate (Workshop Report)
Mountainous systems cover approximately 23% of Earth’s land and are distributed across all continents. They can capture and store atmospheric moisture that is then cycled through the terrestrial surface and subsurface system, released to downstream communities, and cycled back to the atmosphere. Mountain hydroclimate—characterized by steep gradients, geological, ecological, and biogeochemical diversity—is influenced by topographic forcing and elevated warming and susceptible to large subseasonal to multidecadal variability and rapid changes. Terrestrial hydrological and biogeochemical cycles also experience cascading effects from global warming impacts, such as multidecadal declines in mountain snowpack, longer growing seasons, and increased frequency and severity of extreme events like droughts and wildfires. However, little is known about the effects of these impacts and their feedbacks on climate systems and surface-subsurface compartments. Also unknown are the full implications of changing hydroclimate and extreme events on hydro biogeochemical cycles across atmosphere, terrestrial, and human systems in mountain regions and beyond. This knowledge gap is critical, given human reliance on mountain systems for stable water supply and quality. Mountain systems’ increasing vulnerability to climate change and human perturbations motivates the need to improve understanding of integrated mountain hydroclimate (IMHC) systems and their feedbacks and impacts on humans across scales. However, due to large heterogeneity and strong gradients, coupled natural-human processes in mountain regions present significant challenges for observations, modeling, predictions, and projections. Motivated by gaps in mountain hydroclimate understanding, observations, and modeling and the need for credible projections of future changes, the U.S. Department of Energy’s (DOE) Biological and Environmental Research (BER) program organized a virtual workshop on “Understanding and Predictability of Integrated Mountain Hydroclimate.” Sponsored by BER’s Earth and Environmental Systems Sciences Division (EESSD), the workshop aimed to inform and catalyze EESSD’s growing interests in enhancing predictive understanding of IMHC. Organizers structured the workshop to identify (1) knowledge gaps, (2) observational and modeling challenges, (3) short-term (1 to 3 years) and long-term (10 years and beyond) research opportunities, and (4) strategies for fostering collaboration and coordination. To address the outstanding challenges of IMHC, the workshop included two sessions organized by disciplinary, cross-disciplinary, and crosscutting science topics. The disciplinary and cross-disciplinary topics focused on essential IMHC elements: atmosphere, terrestrial, and human systems and their interactions. Breakout sessions on disciplinary and cross-disciplinary topics facilitated identification of crosscutting topics and central emerging themes. Session 1 focused on connecting existing DOE investments to accelerate progress related to scientific challenges in understanding mountain hydroclimate. In Session 2, participants further explored key Session 1 takeaways through the lens of multiagency collaborations and coordination.
Understanding and Tailoring Diffusion and Co-Adsorption Inside the Confined Pores of Metal-Organic Frameworks (Final Scientific/Technical Report for Award DE-SC0019902)
The aim of this program was to gain a fundamental understanding of the behavior of various guest molecules in nano-confined environments, such as metal organic frameworks (MOFs), using a combination of novel synthesis, ab initio modeling, and in situ characterization. Through this project, we developed a concise understanding of the mechanisms that control adsorption/desorption of gaseous molecules and their mixtures, leading to design/synthesis guidelines for MOFs with desired functionality. We further developed methods to disentangle kinetic from thermodynamic effects during adsorption, as well as to characterize the interactions at play. In the first funding cycle, the focus was on the unambiguously characterization of co-adsorption and diffusion of gasses/vapors and their mixtures. In the second funding cycle, the focus was on characterizing the effects of the nano-confinement on the kinetics and thermodynamics of adsorption processes inside MOFs, again with an emphasis on mixtures of gasses and vapors. The nano-confinement can tip the thermodynamic vs. kinetic balance, and current understanding and theory based on single-component analysis can lead to incorrect predictions for mixtures. This is of particular interest in real-world applications, where gasses/vapors are typically mixed, contain impurities, or are often exposed to humid conditions. Our main findings were: (i) within confined environments the adsorption behavior of mixed gasses/vapors can be drastically different from the “sum” of the corresponding single phases; (ii) co-adsorption is often competitive and detrimental to performance, but it can also be cooperative and beneficial; (iii) in some co-adsorbed gasses/vapors, molecules that are strongly bound in the single-component phase can be replaced by molecules that are nominally weaker bound (molecular exchange) due to guest-guest interactions that lower the kinetic barriers and favor the final adsorption state; (iv) kinetic and thermodynamic effects can be precisely controlled through pore-size engineering and synthesis; and, (v) kinetic effects can be identified and disentangled from thermodynamic effects during adsorption through a series of sequential and simultaneous gas loading measurements. The short-term goal of this program was the controlling and understanding of common MOF systems in real-world situations where gasses/vapors are mixed, which will have an important impact on industrial processes and applications from gas storage and sequestration to catalysis and sensors. The long-term goals include the development of theoretical and experimental methods for gaining a fundamental understanding of adsorption/reaction processes within MOFs, as well as new guidelines for synthesizing MOFs with tailored physical and chemical properties.
Bringing Climate Scientist's Tools into Classrooms to Improve Conceptual Understandings
Efforts to address anthropogenic global climate change (AGCC) require public understanding of Earth and climate science. To meet this need, educational reforms and prominent scientists have called for instructional approaches that teach students how climate scientists examine AGCC. Yet, only a few educational studies have reported clear empirical results on what instructional approaches and climate education technologies best accomplish this goal. This manuscript presents detailed analysis and statistically significant results on the educational impact pre to post of students learning to use a National Aeronautics and Space Administration (NASA) global climate model (GCM). This series of case studies demonstrates that differing instructional approaches and climate education technologies result in differing levels of understanding of AGCC and ability to engage with policies addressing it. Students who learned the scientific process of climate modeling scored significantly higher pre to post on exams (quantitatively) and gained more complete conceptual understandings of the issue (qualitatively). Yet, teaching students to conduct research with complex technology can be difficult. This study also found lecture-based learning better improved recall of facts about GCMs tested by multiple-choice questions. Our findings indicate what educational systems and related technologies might provide the public with the conceptual understandings necessary to engage in the political debate over AGCC.
Virtual texture analysis to understand microstructure effects on deformation twinning and detwinning behavior in BCC metals
Understanding and predicting deformation twinning contributions to plastic deformation in BCC metals has been a long-standing challenge due to the interplay with dislocation slip and non-Schmid effects that render an asymmetry under tension and compression. This paper uses molecular dynamics simulations to understand the effect of unloading and grain orientation on deformation twinning in a nanocrystalline Fe (nc-Fe) system as a model BCC metal. The nc-Fe system is loaded under uniaxial stress tension and compression to understand the effect of grain orientation (Schmid effects) on deformation twinning behavior and the tension/compression asymmetry (non-Schmid effects). A new virtual texture analysis “VirTex” tool is used to understand the role of grain orientation on the nucleation of twins and their contributions to the observed stress–strain response. For certain grain orientations, the twinnability is observed to be different in tension and compression. In addition, the flow stress accommodation from twins in certain grains is observed to be different in tension and compression and different from that for the grains. Subsequent unloading leads to detwinning in the deformed microstructures, where the extent of detwinning depends on the strain from which the system is unloaded and on the morphology of the twin. Lastly, the simulations are carried out to analyze the role of the Schmid factor on the twinnability and asymmetry in tension and compression.
Astrovirology: how viruses enhance our understanding of life in the Universe
Abstract Viruses are the most numerically abundant biological entities on Earth. As ubiquitous replicators of molecular information and agents of community change, viruses have potent effects on the life on Earth, and may play a critical role in human spaceflight, for life-detection missions to other planetary bodies and planetary protection. However, major knowledge gaps constrain our understanding of the Earth's virosphere: (1) the role viruses play in biogeochemical cycles, (2) the origin(s) of viruses and (3) the involvement of viruses in the evolution, distribution and persistence of life. As viruses are the only replicators that span all known types of nucleic acids, an expanded experimental and theoretical toolbox built for Earth's viruses will be pivotal for detecting and understanding life on Earth and beyond. Only by filling in these knowledge and technical gaps we will obtain an inclusive assessment of how to distinguish and detect life on other planetary surfaces. Meanwhile, space exploration requires life-support systems for the needs of humans, plants and their microbial inhabitants. Viral effects on microbes and plants are essential for Earth's biosphere and human health, but virus–host interactions in spaceflight are poorly understood. Viral relationships with their hosts respond to environmental changes in complex ways which are difficult to predict by extrapolating from Earth-based proxies. These relationships should be studied in space to fully understand how spaceflight will modulate viral impacts on human health and life-support systems, including microbiomes. In this review, we address key questions that must be examined to incorporate viruses into Earth system models, life-support systems and life detection. Tackling these questions will benefit our efforts to develop planetary protection protocols and further our understanding of viruses in astrobiology.
Understanding Impacts of Frequency Calculations on Underfrequency Load Shedding
Power system fundamental frequency-dependent protection decisions and control decisions are increasingly common in the distribution system space. Understanding the algorithms used in frequency measurements is critical to understanding the decisions made by the many intelligent electronic devices in the power system. These decisions are critically important for reliability analysis for interconnected power systems as they bear directly on resource planning to mitigate under-frequency conditions that would result in under-frequency load shedding (UFLS). This work aims to improve the understanding of frequency measurement algorithms, evaluate the intelligent electronic devices that use frequency measurements for decision making, and understand the algorithms' direct impact on frequency related decision making. First, this work presents background information on the use of frequency measurements in protection logic, specifically UFLS. Second, the paper presents a relay hardware evaluation test bed used to detect and protect systems from under-frequency events. Finally, the paper presents the dynamic events used to evaluate commercially available, off-the-shelf relay equipment and the results from the relay evaluation.
SUNSet: The Software Understanding for National Security Dataset Repo
SAND2025-00511O SUNSet: The Software Understanding for National Security Dataset Repo serves as a repository for software understanding researchers to conduct systematic research in the field. It provides a platform for storing questions, answers, and scripts related to software programs, supporting research in software understanding. The repository is a nascent effort aimed at exploring the support needed by researchers and documenting how software understanding questions can be addressed using existing tools. The software consists of a simple database and front end interface for easy access and management of the stored information. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Breaking the Bottleneck of Genomes: Understanding Gene Function Across Taxa Workshop Report
In the last few decades, high-throughput technologies using various “omics” have enabled unprecedented views of biological systems at the molecular level. In parallel, the integration of omic datasets using computational modeling has provided new understanding of biological processes in organisms relevant to the U.S. Department of Energy’s (DOE) missions in energy and the environment. Collectively, these developments have spearheaded the advancement of systems biology, which can be viewed as a holistic approach for deciphering the complexity of biological systems. However, as high-throughput omic technologies and integrative systems biology efforts have improved our understanding of some biological systems, analyzing and finding meaningful answers within these massive datasets remain extremely challenging, in large part due to the lack of fundamental knowledge of gene function. Indeed, all sequenced genomes, both microbes and plants, contain large numbers of genes of “unknown function” that significantly limit scientists’ ability to model, predict, and engineer organisms with enhanced functions relevant to DOE. Current methodologies can be employed to decipher gene function, but they are typically slow, laborious, inefficient, and not scalable. This “bottleneck” in genome understanding could be broken with new, innovative, and transformative experimental tools, datasets, and computation that can define gene function on a massive and high-throughput scale compatible with the pace of DNA sequencing. In light of this grand challenge, DOE’s Office of Biological and Environmental Research (BER) convened the Breaking the Bottleneck of Genomes: Understanding Gene Function Across Taxa workshop on November 1–2, 2018. This workshop brought together leaders in microbiology, plant sciences, technology, and computation, who collectively identified the experimental and data analysis gaps preventing large-scale gene function determination as well as opportunities for overcoming these gaps.
First-Principles Understanding of Optical Excitations within Low-Dimensional Materials
The objective of this project is to utilize first-principles computational approaches to understand optical excitations within two-dimensional monolayers and heterostructures, with the ultimate goal of designing new materials by modifying the chemical and physical structure on the nanoscale. In 2D heterostructures, the nature and movement of the exciton is determined to a large extent by the electron-electron and electron-phonon strengths within individual monolayers, as well as the coupling between layers, all of which in turn depend on chemistry, solid-state screening properties, and quantum confinement. Controlling the nature and migration properties of excitons requires an understanding of the complex relationship between electrons, phonons, defects, disorder, and dynamics. The aim of this project is to determine, by analysis of highly accurate density functional theory (DFT) and many-body perturbation theory (MBPT) calculations, how these complexities can be decomposed into simple, tunable parameters. The specific goals of this project are to 1) understand electron conductivity, absorption and transparency of monolayer semiconductors and metals; 2) develop a theory of excitons near defects in low dimensions; and 3) understand the influence of inter-layer interactions in heterostructures.