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At least 1,387 records · Page 77

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DOE OSTI2023

DUET - Distribution of Understory using Elliptical Transport: A mechanistic model of leaf litter and herbaceous spatial distribution based on tree canopy structure

Heterogeneity in surface fuels produced by overstory trees and understory vegetation is a major driver of fire behavior and ecosystem dynamics. Previous attempts at predicting tree leaf and needle litter accumulation over time have been constrained in scope to probabilistic models that consider a limited number of key factors influencing tree litter dispersal patterns and decomposition processes. Here we present a mechanistic model for estimating variation in surface fuels called the Distribution of Understory using Elliptical Transport (DUET). DUET uses a pre-generated voxelated canopy array and distributes the leaf litter from the trees in an elliptical shape based on tree species characteristics, wind data, and location-specific features. DUET then calculates grass growth between trees and around the litter patterns and sets moisture levels based on relative humidity. In this study, we use DUET to simulate spatial distributions of leaf litter and illustrate model sensitivity to several parameters, providing inputs for testing fuel spatial heterogeneity impacts on fire behavior using process-based models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

A generalized Flory-Stockmayer kinetic theory of connectivity percolation and rigidity percolation of cytoskeletal networks

Actin networks are essential for living cells to move, reproduce, and sense their environments. The dynamic and rheological behavior of actin networks is modulated by actin-binding proteins such as α-actinin, Arp2/3, and myosin. There is experimental evidence that actin-binding proteins modulate the cooperation of myosin motors by connecting the actin network. In this work, we present an analytical mean field model, using the Flory-Stockmayer theory of gelation, to understand how different actin-binding proteins change the connectivity of the actin filaments as the networks are formed. We follow the kinetics of the networks and estimate the concentrations of actin-binding proteins that are needed to reach connectivity percolation as well as to reach rigidity percolation. We find that Arp2/3 increases the actomyosin connectivity in the network in a non-monotonic way. We also describe how changing the connectivity of actomyosin networks modulates the ability of motors to exert forces, leading to three possible phases of the networks with distinctive dynamical characteristics: a sol phase, a gel phase, and an active phase. Thus, changes in the concentration and activity of actin-binding proteins in cells lead to a phase transition of the actin network, allowing the cells to perform active contraction and change their rheological properties.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1996

Droplet Deformation in an Extensional Flow: The Role of Surfactant Physical Chemistry

Surfactant-induced Marangoni effects strongly alter the stresses exerted along fluid particle interfaces. In low gravity processes, these stresses can dictate the system behavior. The dependence of Marangoni effects on surfactant physical chemistry is not understood, severely impacting our ability to predict and control fluid particle flows. A droplet in an extensional flow allows the controlled study of stretching and deforming interfaces. The deformations of the drop allow both Marangoni stresses, which resist tangential shear, and Marangoni elasticities, which resist surface dilatation, to develop. This flow presents an ideal model system for studying these effects. Prior surfactant-related work in this flow considered a linear dependence of the surface tension on the surface concentration, valid only at dilute surface concentrations, or a non-linear framework at concentrations sufficiently dilute that the linear approximation was valid. The linear framework becomes inadequate for several reasons. The finite dimensions of surfactant molecules must be taken into account with a model that includes surfaces saturation. Nonideal interactions between adsorbed surfactant molecules alter the partitioning of surfactant between the bulk and the interface, the dynamics of surfactant adsorptive/desorptive exchange, and the sensitivity of the surface tension to adsorbed surfactant. For example, cohesion between hydrocarbon chains favors strong adsorption. Cohesion also slows the rate of desorption from interfaces, and decreases the sensitivity of the surface tension to adsorbed surfactant. Strong cohesive interactions result in first order surface phase changes with a plateau in the surface tension vs surface concentration. Within this surface concentration range, the surface tension is decoupled from surface concentration gradients. We are engaged in the study of the role of surfactant physical chemistry in determining the Marangoni stresses on a drop in an extensional flow in a numerical and experimental program. Using surfactants whose dynamics and equilibrium behavior have been characterized in our laboratory, drop deformation will be studied in ground-based experiment. In an accompanying numerical study, predictive drop deformations will be determined based on the isotherm and equation of state determined in our laboratory. This work will improve our abilities to predict and control all fluid particle flows.

Stebe, Kathleen J.↗

NASA NTRS1991

System monitoring and diagnosis with qualitative models

A substantial foundation of tools for model-based reasoning with incomplete knowledge was developed: QSIM (a qualitative simulation program) and its extensions for qualitative simulation; Q2, Q3 and their successors for quantitative reasoning on a qualitative framework; and the CC (component-connection) and QPC (Qualitative Process Theory) model compilers for building QSIM QDE (qualitative differential equation) models starting from different ontological assumptions. Other model-compilers for QDE's, e.g., using bond graphs or compartmental models, have been developed elsewhere. These model-building tools will support automatic construction of qualitative models from physical specifications, and further research into selection of appropriate modeling viewpoints. For monitoring and diagnosis, plausible hypotheses are unified against observations to strengthen or refute the predicted behaviors. In MIMIC (Model Integration via Mesh Interpolation Coefficients), multiple hypothesized models of the system are tracked in parallel in order to reduce the 'missing model' problem. Each model begins as a qualitative model, and is unified with a priori quantitative knowledge and with the stream of incoming observational data. When the model/data unification yields a contradiction, the model is refuted. When there is no contradiction, the predictions of the model are progressively strengthened, for use in procedure planning and differential diagnosis. Only under a qualitative level of description can a finite set of models guarantee the complete coverage necessary for this performance. The results of this research are presented in several publications. Abstracts of these published papers are presented along with abtracts of papers representing work that was synergistic with the NASA grant but funded otherwise. These 28 papers include but are not limited to: 'Combined qualitative and numerical simulation with Q3'; 'Comparative analysis and qualitative integral representations'; 'Model-based monitoring of dynamic systems'; 'Numerical behavior envelopes for qualitative models'; 'Higher-order derivative constraints in qualitative simulation'; and 'Non-intersection of trajectories in qualitative phase space: a global constraint for qualitative simulation.'

Kuipers, Benjamin↗

NASA NTRS1997

Observational Search for Cometary Aging Processes

The scientific objectives of this study were (i) to search for physical differences in the behavior of the dynamically new comets (those which are entering the solar system for the first time from the Oort cloud) and the periodic comets, and (ii) to interpret these differences, if any, in terms of the physical and chemical nature of the comets and the evolutionary histories of the two comet groups. Because outer solar system comets may be direct remnants of the planetary formation processes, it is clear that the understanding of both the physical characteristics of these bodies at the edge of the planet forming zone and of their activity at large heliocentric distances, r, will ultimately provide constraints on the planetary formation process both in our Solar System and in extra-solar planetary systems. A combination of new solar system models which suggest that the protoplanetary disk was relatively massive and as a consequence comets could form at large distances from the sun (e.g. from the Uranus-Neptune region to the vicinity of the Kuiper belt), observations of activity in comets at large r, and laboratory experiments on low temperature volatile condensation, are dramatically changing our understanding of the chemical'and physical conditions in the early solar nebula. In order to understand the physical processes driving the apparent large r activity, and to address the question of possible physical and chemical differences between periodic, non-periodic and Oort comets, the PI has been undertaking a long-term study of the behavior of a significant sample of these comets (approximately 50) over a wide range of r to watch the development, disappearance and changing morphology of the dust coma. The ultimate goal is to search for systematic physical differences between the comet classes by modelling the coma growth in terms of volatile-driven activity. The systematic observations for this have been ongoing since 1986, and have been obtained over the course of approximately 300 nights using the telescopes on Mauna Kea, Kitt Peak, Cerro Tololo, the European Southern Observatory, and several other large aperture facilities. A greater than 2 TB database of broad band comet images has been obtained which follows the systematic development and fading of the cometary coma for the comets in the database. The results to date, indicate that there is a substantial difference in the brightness and the amount of dust as a function of r between the two comet classes. In addition to this major finding, the program has been responsible for several exciting discoveries, including: the P/Halley outburst at r = 14.3 AU, the discovery of Chiron's coma and modelling and observations of the gravitationally bound component, observational evidence that activity continues out beyond r = 17 AU for many dynamically new comets

Meech, Karen J.↗

NASA NTRS2018

Molecular Dynamics Simulations of Liquid and Polymer Electrolytes for Energy Storage Devices

Advancing beyond current lithium-ion technology is necessary in order to enable energy storage devices for electric airplanes. Electrolyte stability is a key limiting factor, yet the design of improved electrolytes remains a formidable challenge. Molecular dynamics (MD) simulations are a powerful tool for studying electrolytes, since they can be used to evaluate structural, thermodynamic, and transport properties, and can provide molecular-level detail often inaccessible to experimental techniques. Our computational materials groups at the NASA Ames Research Center has developed models and methods to accurately simulate both liquid and polymer electrolytes.We report the results from atomistic MD simulations of several electrolyte materials, with lithium salts dissolved in ionic liquids, dimethoxyethane (DME), and polyethylene oxide (PEO). For improved accuracy, we employ polarizable models, where each atom is given an environment-dependent atomic dipole. The simulations accurately predict bulk transport properties, including viscosity, diffusion, and ionic conductivity, in quantitative agreement with available experimental data. Moreover, the simulations provide important insights into the solvation structure of the lithium ions.We also report the results from coarse-grained MD simulations of polyanion electrolytes. In order to more efficiently capture the longer length- and time-scales of these systems, we employ a generic bead-spring model. These simulations provide important insight into how the polymer chain architecture and ionic interaction strengths affect the ionic aggregation behavior and cation dynamics. Despite the simplicity of the model, the simulations yield qualitative agreement with experimental data for similar systems.

Abbott, Lauren J.↗

DOE OSTI2022

Hydro-mechanical behavior of heated bentonite buffer for geologic disposal of high-level radioactive waste: A bench-scale X-ray computed tomography investigation

The behavior of heated bentonite buffer is critical for the security and long-term performance of a geological repository for high-level radioactive waste (HLW). While laboratory column experiments have been conducted to investigate compacted bentonite and coupled THMC (thermal-hydro-mechanical and chemical) processes for a moderate temperature range of up to 100 °C, data for a higher temperature range are limited. Understanding bentonite behavior and coupled THMC processes under higher temperatures (e.g., up to 200 °C) could allow for a more economic repository design and would expand the data and knowledge base for more reliable modeling. In this study, a bench-scale experiment was conducted in a compacted bentonite column experiencing both heating up to 200 °C in the center and hydration from a sand-clay boundary surrounding the column. During the experiment run for 1.5 years, frequent X-ray computed tomography (CT) scanning of bentonite provided insights into the spatiotemporal evolution of (1) hydration/dehydration, (2) clay swelling/shrinkage, (3) displacement, and (4) mineral precipitation. After the experiment, a comprehensive post-dismantling characterization of bentonite samples was conducted. Results showed that the bentonite hydration was axi-symmetrical despite the initial heterogeneity due to packing, confirming the ability of bentonite to seal fast flow/transport paths. Further, compared to a non-heated control experiment, the heated column showed greater CT density variations along the radial distance, indicating that homogenization of bentonite might be more difficult if a temperature gradient is maintained in the repository. Precipitation of an anhydrite layer occurred in the inner hot zone, pointing to potential concerns about salt precipitation causing canister corrosion. Ultimately, the experiments provided a high-resolution window into the strongly dynamic and coupled behavior of bentonite exposed to heating, hydration and swelling, which will be valuable for improving modeling of coupled processes, especially for the early state of a HLW repository.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

PyZebrascope: An Open-Source Platform for Brain-Wide Neural Activity Imaging in Zebrafish

Understanding how neurons interact across the brain to control animal behaviors is one of the central goals in neuroscience. Recent developments in fluorescent microscopy and genetically-encoded calcium indicators led to the establishment of whole-brain imaging methods in zebrafish, which record neural activity across a brain-wide volume with single-cell resolution. Pioneering studies of whole-brain imaging used custom light-sheet microscopes, and their operation relied on commercially developed and maintained software not available globally. Hence it has been challenging to disseminate and develop the technology in the research community. Here, we present PyZebrascope, an open-source Python platform designed for neural activity imaging in zebrafish using light-sheet microscopy. PyZebrascope has intuitive user interfaces and supports essential features for whole-brain imaging, such as two orthogonal excitation beams and eye damage prevention. Its camera module can handle image data throughput of up to 800 MB/s from camera acquisition to file writing while maintaining stable CPU and memory usage. Its modular architecture allows the inclusion of advanced algorithms for microscope control and image processing. As a proof of concept, we implemented a novel automatic algorithm for maximizing the image resolution in the brain by precisely aligning the excitation beams to the image focal plane. PyZebrascope enables whole-brain neural activity imaging in fish behaving in a virtual reality environment. Thus, PyZebrascope will help disseminate and develop light-sheet microscopy techniques in the neuroscience community and advance our understanding of whole-brain neural dynamics during animal behaviors.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1999

Stability Limits and Dynamics of Nonaxisymmetric Liquid Bridges

Liquid bridges have been the focus of numerous theoretical and experimental investigations since the early work by Plateau more than a century ago. More recently, motivated by interest in their physical behavior and their occurrence in a variety of technological situations, there has been a resurgence of interest in the static and dynamic behavior of liquid bridges. Furthermore, opportunities to carry out experiments in the near weightless environment of a low-Earth-orbit spacecraft have also led to a number of low-gravity experiments involving large liquid bridges. In this paper, we present selected results from our work concerning the stability of nonaxisymmetric liquid bridges, the bifurcation of weightless bridges in the neighborhood of the maximum volume stability limit, isorotating axisymmetric bridges contained between equidimensional disks, and bridges contained between unequal disks. For the latter, we discuss both theoretical and experimental results. Finally, we present results concerning the stability of axisymmetric equilibrium configurations for a capillary liquid partly contained in a closed circular cylinder.

Alexander, J. Iwan D.↗

DOE OSTI2024

Autonomous thermal tracking reveals spatiotemporal patterns of seabird activity relevant to interactions with floating offshore wind facilities

Planning is underway for placement of infrastructure needed to begin offshore wind (OSW) energy generation along the West Coast of the United States and elsewhere in the Pacific Ocean. In contrast to the primarily nearshore windfarms currently in the North Atlantic, the seabird communities inhabiting Pacific Wind Energy Areas (WEAs) include significant populations of species that fly by dynamic soaring, a behavior dependent on wind and in which flight height increases steeply with wind speed. Therefore, a more precise and detailed assessment of their 3D airspace use is needed to better understand the potential collision risks that OSW turbines may present to these seabirds. Toward this end, a novel technology called the ThermalTracker-3D (TT3D), which uses thermal imaging and stereo vision, was developed to render high-resolution (on average within ±5 m) flight tracks and related behavior of seabirds. The technology was developed and deployed on a wind-profiling LiDAR buoy in the Humboldt WEA, located 34 to 57 km off California’s coast. During the at-sea deployment between 24 May and 13 August 2021, the TT3D successfully tracked birds moving between 10 and 500 m from the device, around the clock, and in all weather conditions; a total of 1407 detections and their corresponding 3D flight trajectories were recorded. Mean altitudes of detections ranged 6-295 m above sea level (asl). Considering the degree of overlap with anticipated rotor swept zones (RSZ), which extend 25-260 m asl, 79% of detected birds (per m 3 of airspace) moved below the RSZ, 21% moved at heights overlapping the RSZ, and another 0.04% occurred at heights exceeding the RSZ. The high-resolution tracks provided valuable insight into seabird space use, especially at heights that make them vulnerable to collision during various environmental conditions (e.g., darkness, strong winds). Observations made by the TT3D will be useful in filling critical knowledge gaps related to estimating collision and avoidance between seabirds and OSW facilities in the Pacific and elsewhere. Future research will focus on enhancing the TT3D’s identification capabilities to the lowest taxon through validation studies and artificial intelligence, further contributing to seabird conservation efforts associated with OSW.

17 WIND ENERGY↗

NASA NTRS1973

Landing performance of an air cushion landing system installed on a 1/10-scale dynamic model on the C-8 Buffalo airplane

An experimental study was conducted to evaluate the landing behavior of a 1/10-scale dynamic model of the C-8 Buffalo airplane equipped with an air-cushion landing system (ACLS) on a variety of surfaces including both calm and rough water and a smooth hard surface. Taxi runs were made on the hard surface over several obstacles. Landings were made with the model at various pitch and roll attitudes and vertical velocities and at one nominal horizontal velocity. Data from the landings include time histories of the trunk and air-cushion pressures and accelerations at selected locations on the model.

Thompson, W. C.↗

NASA NTRS1990

Behavior of composite/metal aircraft structural elements and components under crash type loads: What are they telling us

Failure behavior results are presented from crash dynamics research using concepts of aircraft elements and substructure not necessarily designed or optimized for energy absorption or crash loading considerations. To achieve desired new designs which incorporate improved energy absorption capabilities often requires an understanding of how more conventional designs behave under crash loadings. Experimental and analytical data are presented which indicate some general trends in the failure behavior of a class of composite structures which include individual fuselage frames, skeleton subfloors with stringers and floor beams but without skin covering, and subfloors with skin added to the frame-stringer arrangement. Although the behavior is complex, a strong similarity in the static and dynamic failure behavior among these structures is illustrated through photographs of the experimental results and through analytical data of generic composite structural models. It is believed that the similarity in behavior is giving the designer and dynamists much information about what to expect in the crash behavior of these structures and can guide designs for improving the energy absorption and crash behavior of such structures.

Carden, Huey D.↗

NASA NTRS1990

Behavior of composite/metal aircraft structural elements and components under crash type loads - What are they telling us?

Carden, Huey D.↗

DOE OSTI2023

Synergizing Electron and Heat Flows in Photocatalyst for Direct Conversion of Captured CO 2

Abstract We report a ternary hybrid photocatalyst architecture with tailored interfaces that boost the utilization of solar energy for photochemical CO 2 reduction by synergizing electron and heat flows in the photocatalyst. The photocatalyst comprises cobalt phthalocyanine (CoPc) molecules assembled on multiwalled carbon nanotubes (CNTs) that are decorated with nearly monodispersed cadmium sulfide quantum dots (CdS QDs). The CdS QDs absorb visible light and generate electron‐hole pairs. The CNTs rapidly transfer the photogenerated electrons from CdS to CoPc. The CoPc molecules then selectively reduce CO 2 to CO. The interfacial dynamics and catalytic behavior are clearly revealed by time‐resolved and in situ vibrational spectroscopies. In addition to serving as electron highways, the black body property of the CNT component can create local photothermal heating to activate amine‐captured CO 2 , namely carbamates, for direct photochemical conversion without additional energy input.

Choi, Chungseok↗

DOE OSTI2023

Synergizing Electron and Heat Flows in Photocatalyst for Direct Conversion of Captured CO 2

We report a ternary hybrid photocatalyst architecture with tailored interfaces that boost the utilization of solar energy for photochemical CO 2 reduction by synergizing electron and heat flows in the photocatalyst. The photocatalyst comprises cobalt phthalocyanine (CoPc) molecules assembled on multiwalled carbon nanotubes (CNTs) that are decorated with nearly monodispersed cadmium sulfide quantum dots (CdS QDs). The CdS QDs absorb visible light and generate electron-hole pairs. The CNTs rapidly transfer the photogenerated electrons from CdS to CoPc. The CoPc molecules then selectively reduce CO 2 to CO. Here, the interfacial dynamics and catalytic behavior are clearly revealed by time-resolved and in situ vibrational spectroscopies. In addition to serving as electron highways, the black body property of the CNT component can create local photothermal heating to activate amine-captured CO 2 , namely carbamates, for direct photochemical conversion without additional energy input.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

A multiscale cohesive law for carbon fiber networks

Better predictive models of mechanical failure in low-weight heat shield composites would aid material certification for missions with aggressive atmospheric entry conditions. In this study, we develop such a model for the rapid engineering analysis of the failure limits of phenolic impregnated carbon ablator (PICA) - a leading heat shield material whose structural component is a carbon fiber network. We hypothesize inelastic deformation failure mechanisms and model their behavior using molecular dynamics simulations to calculate the binding energy. We then upscale this binding energy to the macroscale using a renormalization argument. The approach delivers insightful and reasonably accurate macroscale predictions that compare favorably to experiments. In application, the model is validated for a particular variety of PICA by comparison to experiment and would then be used to study design scenarios in different entry conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Generating realistic building electrical load profiles through the Generative Adversarial Network (GAN)

Building electrical load profiles can improve understanding of building energy efficiency, demand flexibility, and building-grid interactions. Current approaches to generating load profiles are time-consuming and not capable of reflecting the dynamic and stochastic behaviors of real buildings; some approaches also trigger data privacy concerns. In this study, we proposed a novel approach for generating realistic electrical load profiles of buildings through the Generative Adversarial Network (GAN), a machine learning technique that is capable of revealing an unknown probability distribution purely from data. The proposed approach has three main steps: (1) normalizing the daily 24-hour load profiles, (2) clustering the daily load profiles with the k-means algorithm, and (3) using GAN to generate daily load profiles for each cluster. The approach was tested with an open-source database – the Building Data Genome Project. We validated the proposed method by comparing the mean, standard deviation, and distribution of key parameters of the generated load profiles with those of the real ones. The KL divergence of the generated and real load profiles are within 0.3 for majority of parameters and clusters. Additionally, results showed the load profiles generated by GAN can capture not only the general trend but also the random variations of the actual electrical loads in buildings. We report the proposed GAN approach can be used to generate building electrical load profiles, verify other load profile generation models, detect changes to load profiles, and more importantly, anonymize smart meter data for sharing, to support research and applications of grid-interactive efficient buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Estimating the population level impact of a gonococcal vaccine candidate: Predictions from a simple mathematical model

Neisseria gonorrhoeae cross-protection was suggested in a New Zealand meningitis B vaccine. We modeled the potential impact of similar vaccines on gonorrhea prevalence in heterosexuals in the United States. Here, our mathematical model incorporated infection, behavior, and vaccination dynamics. Approximate Bayesian Computation calibrated our model to US prevalence. Primary analyses assumed New Zealand vaccine characteristics: 30% efficacy and 2-year duration of protection. We estimated impact under two vaccine coverages (20%, 50%). Reduction in gonorrhea prevalence ranged from 4.8 to 39.4%, depending on vaccine coverage. Vaccine impact was correlated with both size of the highly sexually active subpopulation and sexual mixing between high and low activity subpopulations. A meningitis vaccine providing low efficacy cross-protection against gonorrhea acquisition and short duration of protection could result in a large reduction in gonorrhea prevalence in the United States. Potential dual protective effects can be considered when making vaccine recommendations.

60 APPLIED LIFE SCIENCES↗