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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Generalization of Threshold-Based and Probability-Based Models of Information Diffusion

Diffusion of information through complex networks is of interest in studies such as propagation prediction and influence maximization, both of which have applications in viral marketing and rumor controlling. There are a variety of information diffusion models, all of which simulate the adoption and spread of information over time. However, there is a lack of understanding of whether, despite their conceptual differences, these models represent the same underlying generative structures. For instance, if two different models utilize different conceptual mechanisms, but generate the same results, does the choice of model matter? A classification of diffusion of information models is developed based on the neighbor knowledge of the model infection requirement and the stochasticity of the model. This classification allows for the identification of models that fall into each respective category. The study involves the analysis of the following agent-based models on directed scale-free networks: (1) a linear absolute threshold model (LATM), (2) a linear fractional threshold model (LTFM), (3) the independent cascade model (ICM), (4) Bass-Rand-Rust model (BRRM) (5) a stochastic linear absolute threshold model (SLATM) (6) a stochastic fractional threshold model (SLFTM), and (7) Dodds–Watts model (DWM). Through the execution of simulations and analysis of the experimental results, the distinctive properties of each model are identified. Our analysis reveals that similarity in conceptual design does not imply similarity in behavior concerning speed, final state of nodes and edges, and sensitivity to parameters. Therefore, we highlight the importance of considering the unique behavioral characteristics of each model when selecting a suitable information diffusion model for a particular application.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

Conceptual design and analysis of a dynamic scale model of the Space Station Freedom

This report documents the conceptual design study performed to evaluate design options for a subscale dynamic test model which could be used to investigate the expected on-orbit structural dynamic characteristics of the Space Station Freedom early build configurations. The baseline option was a 'near-replica' model of the SSF SC-7 pre-integrated truss configuration. The approach used to develop conceptual design options involved three sets of studies: evaluation of the full-scale design and analysis databases, conducting scale factor trade studies, and performing design sensitivity studies. The scale factor trade study was conducted to develop a fundamental understanding of the key scaling parameters that drive design, performance and cost of a SSF dynamic scale model. Four scale model options were estimated: 1/4, 1/5, 1/7, and 1/10 scale. Prototype hardware was fabricated to assess producibility issues. Based on the results of the study, a 1/4-scale size is recommended based on the increased model fidelity associated with a larger scale factor. A design sensitivity study was performed to identify critical hardware component properties that drive dynamic performance. A total of 118 component properties were identified which require high-fidelity replication. Lower fidelity dynamic similarity scaling can be used for non-critical components.

Davis, D. A.↗
NASA NTRS1995

Enhanced analysis and users manual for radial-inflow turbine conceptual design code RTD

Modeling enhancements made to a radial-inflow turbine conceptual design code are documented in this report. A stator-endwall clearance-flow model was added for use with pivoting vanes. The rotor calculations were modified to account for swept blades and splitter blades. Stator and rotor trailing-edge losses and a vaneless-space loss were added to the loss model. Changes were made to the disk-friction and rotor-clearance loss calculations. The loss model was then calibrated based on experimental turbine performance. A complete description of code input and output along with sample cases are included in the report.

Glassman, Arthur J.↗
DOE OSTI2022

Simulation of high-frequency dissolved oxygen dynamics in a shallow estuary, the Corsica River, Chesapeake Bay

Understanding shallow water biogeochemical dynamics is a challenge in coastal regions, due to the presence of highly variable land-water interface fluxes, tight coupling with sediment processes, tidal dynamics, and diurnal variability in biogeochemical processes. While the deployment of continuous monitoring devices has improved our understanding of high-frequency (12 - 24 hours) variability and spatial heterogeneity in shallow regions, mechanistic modeling of these dynamics has lagged behind conceptual and empirical models. The inherent complexity of shallow water systems is represented in the Corsica River estuary, a small basin within the Chesapeake Bay ecosystem, where abundant monitoring data have been collected from long-term monitoring stations, continuous monitoring sensors, synoptic sensor surveys, and measurements of sediment-water fluxes. A state-of-the-art modeling system, the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM), was applied to the Corsica domain with a high-resolution grid and nutrient loads from the most recent version of the Chesapeake Bay watershed model. The Corsica SCHISM model reproduced observed high-frequency variability in dissolved oxygen, as well as seasonal variability in chlorophyll-a and sediment-water fluxes. Time-series signal analyses using Empirical Model Decomposition and spectral analysis revealed that the diurnal and M2 tide frequencies are the dominant high-frequency modes and physical transport contributes a larger share to dissolved oxygen budgets than biogeochemical processes on an hourly time scale. Heterogeneity and patchiness in dissolved oxygen resulting from phytoplankton distributions and geometry-driven eddies amplify the physical transport effect, and on longer time scales oxygen is controlled more by photosynthesis and respiration. Our simulation demonstrates that interactions among physical and biological dynamics generate complex high-frequency variability in water quality and non-linear reposes to nutrient loading and environmental forcing in shallow water systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Independent Review of Groundwater Remediation Strategy for Hexavalent Chromium and RDX Groundwater Plumes at Los Alamos National Laboratory (Rev. 1)

Site operations at the Los Alamos National Laboratory (LANL) resulted in the release of oxidized chromium, Cr(VI), into Sandia Canyon from cooling tower effluent from 1956 until 1972. The chromium traveled with the surface water approximately 3 miles downstream before migrating below ground surface. Chromium concentrations exceed 50 μg/L in the upper portion of the aquifer. Another LANL groundwater plume of concern is associated with RDX (Royal Demolition Explosives, 1,3,5-trinitro-1,3,5-triazine). Between 1951 and 1996, RDX was released to the mesa-top facilities' process water outfall, adjacent and underlying soils, and alluvial sediments, along with surface water in Cañon de Valle. Between 2000 and 2010, two remedial actions were deployed, removing much of the near-surface RDX, however, recharge due to precipitation has transported RDX into the perched-intermediate zone and into the regional aquifer. The report documents an independent technical review by scientists from the Department of Energy (DOE) Network of National Laboratories for Environmental Management and Stewardship (NNLEMS) to provide recommendations for potential near term actions to address and optimize remediation for both the Cr(VI) and RDX plumes. The proposed near-term remedial actions include design of pump and treat systems for Cr(VI) and monitoring and study for natural attenuation for RDX. The review assesses existing data, conceptual and numerical modeling, and it recommends a technical integration process to support identifying and implementing strategic, effective and efficient remedies. The DOE Environmental Management Los Alamos Field Office (EM-LA) and their cleanup contractor Newport News Nuclear-BWTX, LLC Los Alamos (N3B) provided the information required for the review. Interviews were also conducted with regulators to obtain the full spectrum of technical, regulatory and scientific perspectives. The independent review team was impressed by the capabilities, experiences, innovativeness, and insightfulness of the technical representatives from both the regulator, the New Mexico Environment Department (NMED) and N3B. Incorporation of vadose zone flow pathways in the conceptual site model (CSM) and configuring the numerical modeling for the site was generally state-of-the-practice (or better). This could be considered state-of-the-art by addressing uncertainties related to spatial extent of hydraulic windows. The reviews from the regulators were thorough and often provided useful concepts for consideration and future/study resolutions. The overarching consensus recommendation of independent review team is that the LANL groundwater plumes should be addressed in context of the emerging "management of complex sites" paradigm.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Conceptual Basis and Techno-Economic Modeling for Integrated Algal Biorefinery Conversion of Microalgae to Fuels and Products (2019 NREL TEA Update: Highlighting Paths to Future Cost Goals via a New Pathway for Combined Algal Processing)

The report documents the conceptual basis for a new potential Combined Algal Processing design strategy which may allow more flexibility in accommodating different algal biomass feedstock compositions, by enabling upgrading of both protein and carbohydrates in a single step, without a strict requirement for either component to be in soluble or monomeric form, while maintaining effective wet lipid extraction techniques to enable high lipid recoveries. In light of previously-established constraints around algal biomass costs (which are significantly higher than lignocellulosic terrestrial biomass), the present CAP processing strategy reflects an integrated biorefinery concept producing both fuels and value-added chemical coproducts as a means to improve profitability and generate coproduct revenues to help drive down the minimum fuel selling price (MFSP) towards economically viable levels. Namely, this report highlights an integrated CAP biorefinery process and associated technical targets that would be required to achieve U.S. Department of Energy target MFSP goals of $2.5/gallon gasoline equivalent by 2030. This is accomplished by a process involving low-cost seasonal storage of algal biomass during high-growth seasons, rapid flash hydrolysis pretreatment of the biomass, solvent extraction of pretreated biomass, cleanup and fractionation of lipids into triglyceride and free fatty acid fractions, and a series of thermochemical conversion steps to upgrade carbohydrates and protein to hydrocarbon fuels. These steps include mild oxidative treatment (MOT), a process originally investigated at NREL for upgrading lignin, followed by catalytic ketonization and hydrotreating of MOT products to fuels. Isolated triglycerides are sent to a coproduct train, with the base case focused on upgrading to polyurethane foams as a high-value, high-market-volume coproduct.

09 BIOMASS FUELS↗
DOE OSTI2023

Impacts of climate change on subannual hydropower generation: a multi-model assessment of the United States federal hydropower plant

Abstract Hydropower is a low-carbon emission renewable energy source that provides competitive and flexible electricity generation and is essential to the evolving power grid in the context of decarbonization. Assessing hydropower availability in a changing climate is technically challenging because there is a lack of consensus in the modeling representation of key dynamics across scales and processes. Focusing on 132 US federal hydropower plants, in this study we evaluate the compounded impact of climate and reservoir-hydropower models’ structural uncertainties on monthly hydropower projections. In particular, instead of relying on one single regression-based hydropower model, we introduce another conceptual reservoir operations-hydropower model in the assessment framework. This multi-model assessment approach allows us to partition uncertainties associated with both climate and hydropower models for better clarity. Results suggest that while at least 70% of the uncertainties at the annual scale and 50% at the seasonal scale can be attributed to the choice of climate models, up to 50% of seasonal variability can be attributed to the choice of hydropower models, particularly in regions over the western US where the reservoir storage is substantial. The analysis identifies regions where multi-model assessments are needed and presents a novel approach to partition uncertainties in hydropower projections. Another outcome includes an updated evaluation of Coupled Model Intercomparison Project Phase 5 (CMIP5)-based federal hydropower projection, at the monthly scale and with a larger ensemble, which can provide a baseline for understanding future assessments based on CMIP6 and beyond.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Evidential Deep Learning: Enhancing Predictive Uncertainty Estimation for Earth System Science Applications

Abstract Robust quantification of predictive uncertainty is a critical addition needed for machine learning applied to weather and climate problems to improve the understanding of what is driving prediction sensitivity. Ensembles of machine learning models provide predictive uncertainty estimates in a conceptually simple way but require multiple models for training and prediction, increasing computational cost and latency. Parametric deep learning can estimate uncertainty with one model by predicting the parameters of a probability distribution but does not account for epistemic uncertainty. Evidential deep learning, a technique that extends parametric deep learning to higher-order distributions, can account for both aleatoric and epistemic uncertainties with one model. This study compares the uncertainty derived from evidential neural networks to that obtained from ensembles. Through applications of the classification of winter precipitation type and regression of surface-layer fluxes, we show evidential deep learning models attaining predictive accuracy rivaling standard methods while robustly quantifying both sources of uncertainty. We evaluate the uncertainty in terms of how well the predictions are calibrated and how well the uncertainty correlates with prediction error. Analyses of uncertainty in the context of the inputs reveal sensitivities to underlying meteorological processes, facilitating interpretation of the models. The conceptual simplicity, interpretability, and computational efficiency of evidential neural networks make them highly extensible, offering a promising approach for reliable and practical uncertainty quantification in Earth system science modeling. To encourage broader adoption of evidential deep learning, we have developed a new Python package, Machine Integration and Learning for Earth Systems (MILES) group Generalized Uncertainty for Earth System Science (GUESS) (MILES-GUESS) ( https://github.com/ai2es/miles-guess ), that enables users to train and evaluate both evidential and ensemble deep learning. Significance Statement This study demonstrates a new technique, evidential deep learning, for robust and computationally efficient uncertainty quantification in modeling the Earth system. The method integrates probabilistic principles into deep neural networks, enabling the estimation of both aleatoric uncertainty from noisy data and epistemic uncertainty from model limitations using a single model. Our analyses reveal how decomposing these uncertainties provides valuable insights into reliability, accuracy, and model shortcomings. We show that the approach can rival standard methods in classification and regression tasks within atmospheric science while offering practical advantages such as computational efficiency. With further advances, evidential networks have the potential to enhance risk assessment and decision-making across meteorology by improving uncertainty quantification, a longstanding challenge. This work establishes a strong foundation and motivation for the broader adoption of evidential learning, where properly quantifying uncertainties is critical yet lacking.

Schreck, John S.↗
NASA NTRS1973

Modeling and measuring limb fine-motor unsteadiness

Fine-motor unsteadiness its properties, conceptual and analytical models, and experimental measurements is examined. Based on a data review, the tentative model derived includes: neuromuscular system, grip interface, and control system dynamic elements. The properties of this model change with muscle tension and match a wide group of extant data. A simple experiment was performed to investigate the amplitude/force relationships of the tremor mode. As the finger-pull force increased from 5 to 20 Newtons, the tremor mode frequency for a given individual stayed within roughly + or - 1 Hz over a range from 9-12 Hz, while the average magnitude of the rms tremor acceleration increased tenfold. A standardized test for making such measurements is given and applications in the fields of psychophysiological stress and strain measurements are mentioned.

Magdaleno, R. E.↗
NASA NTRS1992

Space Station Furnace Facility. Volume 2: Requirements definition and conceptual design study

The Space Station Freedom Furnace (SSFF) Project is divided into two phases: phase 1, a definition study phase, and phase 2, a design and development phase. TBE was awarded a research study entitled, 'Space Station Furnace Facility Requirements Definition and Conceptual Design Study' on June 2, 1989. This report addresses the definition study phase only. Phase 2 is to be complete after completion of phase 1. The contract encompassed a requirements definition study and culminated in hardware/facility conceptual designs and hardware demonstration development models to test these conceptual designs. The study was divided into two parts. Part 1 (the basic part of the effort) encompassed preliminary requirements definition and assessment; conceptional design of the SSFF Core; fabrication of mockups; and preparation for the support of a conceptional design review (CoDR). Part 2 (the optional part of the effort) included detailed definition of the engineering and design requirements, as derived from the science requirements; refinement of the conceptual design of the SSFF Core; fabrication and testing of the 'breadboards' or development models; and preparation for and support of a requirements definition review.

Source record↗
DOE OSTI2022

Model quantification of the effect of coproducts and refinery co-hydrotreating on the economics and greenhouse gas emissions of a conceptual biomass catalytic fast pyrolysis process

Here we present model results for a scaled-up conceptual process informed by bench scale biomass catalytic fast pyrolysis (CFP) and hydrotreating experimental data. This process uses a Pt/TiO 2 catalyst during CFP, which produces a partially deoxygenated organic biocrude intermediate that is then hydroprocessed to a hydrocarbon fuel blendstock; the catalyst also enables high yields of acetone and methyl-ethyl-ketone (MEK) coproducts. Two options for hydroprocessing were modeled: (A) co-hydrotreating at a petroleum refinery using hydrogen sourced from steam reforming of natural gas and (B) standalone hydrotreating at a biorefinery using hydrogen sourced from CFP off gases. The results revealed that Case A was economically advantageous with a modeled minimum fuel selling price (MFSP) of $\$$2.83/GGE or gallon gasoline equivalent (in 2016 US dollars), while the additional cost of standalone hydrotreating facilities in Case B increased the MFSP to $3.13/GGE. Conversely, greenhouse gas (GHG) emissions were lower for Case B (3.9 g CO 2 e/MJ) compared to Case A (21.5 g CO 2 e/MJ) due to the use of biogenic (Case B) and fossil-derived (Case A) hydrogen. In a third option (Case C), the requirements for separation and purification of acetone and MEK were removed from the refinery co-processing scenario (Case A) to evaluate the impacts of this process simplification. Elimination of these coproducts increased the MFSP to $3.21/GGE and GHG emissions to 35 g CO 2 e/MJ. These comparisons based on our detailed conceptual models provide economic and sustainability guidance regarding processing choices for future biorefineries. While refinery coprocessing using existing equipment and the production of relatively valuable coproducts can benefit the economics, the hydrogen-source and biogenic coproducts can have significant impacts on the sustainability of the process, and feasibility to use CFP off-gases or other renewable sources for hydrogen production can help lower GHG emissions.

09 BIOMASS FUELS↗
NASA NTRS2007

Automatic Conversion of Conceptual Geometry to CFD Geometry for Aircraft Design

Conceptual aircraft design is usually based on simple analysis codes. Its objective is to provide an overall system performance of the developed concept, while preliminary aircraft design uses high-fidelity analysis tools such as computational fluid dynamics (CFD) analysis codes or finite element structural analysis codes. In some applications, such as low-boom supersonic concept development, it is important to be able to explore a variety of drastically different configurations while using CFD analysis to check whether a given configuration can be tailored to have a low-boom ground signature. It poses an extremely challenging problem of integrating CFD analysis in conceptual design. This presentation will discuss a computer code, called iPatch, for automatic conversion of conceptual geometry to CFD geometry. In general, conceptual aircraft geometry is not as well-defined as a CAD geometry model. In particular, a conceptual aircraft geometry model usually does not define the intersection curves for the connecting surfaces. The computer code iPatch eliminates the gap between conceptual geometry and CFD geometry by accomplishing the following three tasks automatically: (1) use bicubic B-splines to extrapolate (if necessary) each surface in a conceptual geometry so that all the independently defined geometry components (such as wing and fuselage) can be intersected to form a watertight CFD geometry, (2) compute the intersection curves of surface patches at any resolution (up to 10-7 accuracy) specified by users, and (3) write the B-spline surface patches and the corresponding boundary points for the watertight CFD geometry in the format that can be directly exported to the meshing tool VGRID in the CFD software TetrUSS. As a result, conceptual designers can get quick feedback on the aerodynamic characteristics of their concepts, which will allow them to understand some subtlety in their concepts and to be able to assess their concepts with a higher degree of confidence. This integration of CFD analysis in conceptual aircraft design will greatly eliminate some uncertainty due to simple analysis codes used to develop the concepts and improve the feasibility/credibility of the final concept. The presentation will highlight the mathematical challenges of accomplishing the aforementioned three tasks and the computational algorithms used by iPatch.

Li, Wu↗
DOE OSTI2021

Modeling the effect of habitat availability and quality on endangered winter-run Chinook salmon ( Oncorhynchus tshawytscha ) production in the Sacramento Valley

Reconciliation between water uses and sustaining aquatic species populations requires an effort to identify and quantify essential habitat characteristics for ecosystem health and valuation methods to predict ecosystem response to restoration actions. This process is particularly challenging for anadromous fish species such as California's Sacramento River winter-run Chinook salmon, due to their limited geographic range and diverse life history habitat requirements. Tools, such as life-cycle models, are needed to manage population dynamics and quantify the composite effects of processes across space and time. Nevertheless, complex institutions can hinder result interpretation and communication, and limit model use in decision-making. This paper focuses on the federally endangered and endemic Sacramento River winter-run Chinook (Oncorhynchus tshawytscha) by developing a Winter-Run Habitat-based Population Model (WRHAP). Additionally, WRHAP is a conceptual, freshwater rearing stage model that includes alternative rearing habitats reported in the literature (e.g., floodplains, off-channel and tributaries), defines rules of habitat use based on instream conditions, and incorporates a juvenile growth module that combines bioenergetics modeling with empirical growth rates. Model outputs reasonably follow observed out-migration patterns and provide a realistic smolt size distribution arriving at the San Francisco Bay. This effort demonstrates the importance of currently “non-critical” habitats (as defined by the Endangered Species Act) for juvenile development, with floodplain habitat contributing to a quarter of out-migrating biomass (despite < 18% availability and <10% of total rearing days), and off-channel growth being one of the most sensitive parameters (explaining ~13% of average juvenile weight variance). The model shows the utility of a simple population model to explore relationships between habitat quality/quantity and juvenile development, and to assist water/environmental management and decision-making processes focused on species recovery.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

WaterTAP v1.0.0

WaterTAP is a new open source library of water-specific models built on the IDAES Integrated Platform to support the design and optimization of integrated water treatment systems, improve existing systems and enable the analysis of new designs incorporating emerging technologies. WaterTAP enables advanced modeling and optimization for: conceptual and multiscale design, dynamics and model predictive control of water systems and networks.

Beattie, KeithS↗
NASA NTRS1985

Application of CFD techniques toward the validation of nonlinear aerodynamic models

Applications of Computational fluid dynamics (CFD) methods to determine the regimes of applicability of nonlinear models describing the unsteady aerodynamic responses to aircraft flight motions are described. The potential advantages of computational methods over experimental methods are discussed and the concepts underlying mathematical modeling are reviewed. The economic and conceptual advantages of the modeling procedure over coupled, simultaneous solutions of the gasdynamic equations and the vehicle's kinematic equations of motion are discussed. The modeling approach, when valid, eliminates the need for costly repetitive computation of flow field solutions. For the test cases considered, the aerodynamic modeling approach is shown to be valid.

Schiff, L. B.↗
NASA NTRS1985

Application of CFD techniques toward the validation of nonlinear aerodynamic models

Applications of computational fluid dynamics (CFD) methods to determine the regimes of applicability of nonlinear models describing the unsteady aerodynamic responses to aircraft flight motions are described. The potential advantages of computational methods over experimental methods are discussed and the concepts underlying mathematical modeling are reviewed. The economic and conceptual advantages of the modeling procedure over coupled, simultaneous solutions of the gas dynamic equations and the vehicle's kinematic equations of motion are discussed. The modeling approach, when valid, eliminates the need for costly repetitive computation of flow field solutions. For the test cases considered, the aerodynamic modeling approach is shown to be valid.

Schiff, L. B.↗
NASA NTRS2005

Conceptual Design and Dynamics Testing and Modeling of a Mars Tumbleweed Rover

The NASA Langley Research Center has been developing a novel concept for a Mars planetary rover called the Mars Tumbleweed. This concept utilizes the wind to propel the rover along the Mars surface, bringing it the potential to cover vast distances not possible with current Mars rover technology. This vehicle, in its deployed configuration, must be large and lightweight to provide the ratio of drag force to rolling resistance necessary to initiate motion from rest on the Mars surface. One Tumbleweed design concept that satisfies these considerations is called the Eggbeater-Dandelion. This paper describes the basic design considerations and a proposed dynamics model of the concept for use in simulation studies. It includes a summary of rolling/bouncing dynamics tests that used videogrammetry to better understand, characterize, and validate the dynamics model assumptions, especially the effective rolling resistance in bouncing/rolling dynamic conditions. The dynamics test used cameras to capture the motion of 32 targets affixed to a test article s outer structure. Proper placement of the cameras and alignment of their respective fields of view provided adequate image resolution of multiple targets along the trajectory as the test article proceeded down the ramp. Image processing of the frames from multiple cameras was used to determine the target positions. Position data from a set of these test runs was compared with results of a three dimensional, flexible dynamics model. Model input parameters were adjusted to match the test data for runs conducted. This process presented herein provided the means to characterize the dynamics and validate the simulation of the Eggbeater-Dandelion concept. The simulation model was used to demonstrate full scale Tumbleweed motion from a stationary condition on a flat-sloped terrain using representative Mars environment parameters.

Calhoun Philip C.↗