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Summary of research carried out under Interagency Agreement DE-AI02-07ER64355 with the USDA Forest Service at the Howland Forest AmeriFlux site in central Maine. Includes a list of publications resulting in part or whole from this support.
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Attempts to improve the handling of satellite temperature and cloud-derived data during the FGGE experiment are compared with results gained during the trials. The satellite data were edited by assigning quality indicators to temperature soundings by means of the IR TV camera on the Tiros-N spacecraft, and to cloud-tracked wind data from GEO satellites. The data quality were assayed on the basis of horizontal, vertical, and temporal consistency of observed synoptic conditions. The data interpreter-operator retrieved all available data for an area, determined which regions were data-sparse, then used data-rich areas nearby to supply smoothed gradients into the zones with insufficient data. Results are presented for measurements taken during Jan.-Feb., and May 1979 over Alaska. It was found that enhanced and operational IR soundings were mostly equivalent. Some improvements were implemented in the 1000-300 mb layer thickness and intensification of atmospheric thermal gradients. Interactive processing was concluded to be an aid to processing Tiros-N data. The data-improvements treatment was found to significantly modify large scale analyses.
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Model calculations and analyses have been carried out to compare with several sets of data (dose, induced radioactivity in various experiment samples and spacecraft components, fission foil measurements, and LET spectra) from passive radiation dosimetry on the Long Duration Exposure Facility (LDEF) satellite, which was recovered after almost six years in space. The calculations and data comparisons are used to estimate the accuracy of current models and methods for predicting the ionizing radiation environment in low earth orbit. The emphasis is on checking the accuracy of trapped proton flux and anisotropy models.
The Finite Element Structural Optimization Program's (FESOP) ability to perform minimum weight optimization using two different finite element analyses and models is discussed. FESOP uses the ADS optimizer developed by Dr. Garret Vanderplaats to solve the nonlinear constrained optimization problem. The design optimization problem requires a response spectrum analysis and model to evaluate the stress and displacement constraints. However, the problem needs a frequency analysis and model to calculate the natural frequencies used to evaluate the frequency range constraints. The results of both the successful and unsuccessful approaches used to solve this difficult weight minimization problem are summarized. The results show that no one ADS optimization algorithm worked in all cases. However, the Sequential Convex Programming and Modified Method of Feasible Directions algorithms were the most successful.
A continuous simulation watershed model has been used to perform sensitivity analyses that provide guidance in defining remote sensing requirements for the monitoring of watershed features and processes. The results show that out of 26 input parameters having meaningful effects on simulated runoff, 6 appear to be obtainable with existing remote sensing techniques. Of these six parameters, 3 require the measurement of the areal extent of surface features (impervious areas, water bodies, and the extent of forested area), two require the descrimination of land use that can be related to overland flow roughness coefficient or the density of vegetation so as to estimate the magnitude of precipitation interception, and one parameter requires the measurement of distance to get the length over which overland flow typically occurs. Observational goals are also suggested for monitoring such fundamental watershed processes as precipitation, soil moisture, and evapotranspiration. A case study on the Patuxent River in Maryland shows that runoff simulation is improved if recent satellite land use observations are used as model inputs as opposed to less timely topographic map information.
The International Space Station (ISS) will provide long-term missions which will enable the astronauts to live and work, as well as, conduct research in a microgravity environment. The dominant factor in space affecting the crew is "weightlessness" which creates a challenge for establishing workstation microgravity design requirements. The crewmembers will work at various workstations such as Human Research Facility (HRF), Microgravity Sciences Glovebox (MSG) and Life Sciences Glovebox (LSG). Since the crew will spend considerable amount of time at these workstations, it is critical that ergonomic design requirements are integral part of design and development effort. In order to achieve this goal, the Space Human Factors Laboratory in the Johnson Space Center Flight Crew Support Division has been tasked to conduct integrated evaluations of workstations and associated crew restraints. Thus, a two-phase approach was used: 1) ground and microgravity evaluations of the physical dimensions and layout of the workstation components, and 2) human modeling analyses of the user interface. Computer-based human modeling evaluations were an important part of the approach throughout the design and development process. Human modeling during the conceptual design phase included crew reach and accessibility of individual equipment, as well as, crew restraint needs. During later design phases, human modeling has been used in conjunction with ground reviews and microgravity evaluations of the mock-ups in order to verify the human factors requirements. (Specific examples will be discussed.) This two-phase approach was the most efficient method to determine ergonomic design characteristics for workstations and restraints. The real-time evaluations provided a hands-on implementation in a microgravity environment. On the other hand, only a limited number of participants could be tested. The human modeling evaluations provided a more detailed analysis of the setup. The issues identified during the real-time testing were investigated in the human modeling analyses. In some cases, the opposite was true where preliminary human modeling analyses provided the design engineers with critical issues that needed to be addressed further. This extensive approach provided an effective means to fully address ergonomic design considerations and accurately identify critical issues.
Typically environmental management problems require analysis of large and complex data sets originating from concurrent data streams with different data collection frequencies and pedigree. These big data sets require on-the-fly integration into a series of models with different complexity for various types of model analyses where the data are applied as soft and hard model constraints. This is needed to provide fast iterative model analyses based on the latest available data to guide decision-making. Furthermore, the data and model are associated with uncertainties. The uncertainties are probabilistic (e.g. measurement errors) and non-probabilistic (unknowns, e.g. alternative conceptual models characterizing site conditions). To address all of these issues, we have developed an integrated framework for real-time data and model analyses for environmental decision-making called ZEM. The framework allows for seamless and on-the-fly integration of data and modeling results for robust and scientifically-defensible decision-making applying advanced decision analyses tools such as Bayesian- Information-Gap Decision Theory (BIG-DT). The framework also includes advanced methods for optimization that are capable of dealing with a large number of unknown model parameters, and surrogate (reduced order) modeling capabilities based on support vector regression techniques. The framework is coded in Julia, a state-of-the-art high-performance programing language (http://julialang.org). The ZEM framework is open-source and can be applied to any environmental management site. The framework will be open-source and released under GPL V3 license.
Analyses of Mars spectra reveal that primary minerals may be more iron rich than average basalts on Earth, and the oxidation state of iron in the pyroxines suggests equally high or higher oxygen fugacities on Mars than Earth. Analysis of Mercury spectra reveal that silicate iron contents are substantially lower than those on Mars. Mercury, however, probably has a substantial iron core. This is consistent with a lower oxidation state of iron on Mercury than on Mars. These findings are consistent with predictions of models of equilibrium condensation and homogeneous accretion. Those models predict that Mercury would have negligible Fe(2+) in silicates (Fe/Fe+Mg approx. 0.5). For Mercury iron should be virtually all metallic, while for Mars the iron would be all oxidized as FeS and silicate. Surface measurements of Fe/Fe+Mg on Venus, Earth, and Mars further support the predicted relative increase in Fe/Fe+Mg ratio (increased oxidation state) with distance from the Sun. The implied high oxygen fugacities on Mars (Fe(3+) in silicates) provide additional consistence with the model predictions.
Building on our prior research with a national survey sample of 5385 US participants, the Pooled Rideshare Acceptance Model (PRAM) was built upon two factor analyses. This exploratory study extends the PRAM framework using the Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMA) to examine how 16 demographic variables influence and interact with the acceptance of Pooled Rideshare (PR), filling a gap in understanding user segmentation and personalization. Using a national sample of 5385 US participants, this methodological approach allowed for the evaluation of how PRAM variables such as safety, privacy, service experience, and environmental impact vary across diverse groups, including gender, generation, driver’s license, rideshare experience, education level, employment status, household size, number of children, income, vehicle ownership, and typical commuting practices. Factors such as convenience, comfort, and passenger safety did not show significant differences across the moderators, suggesting their universal importance across all demographics. Furthermore, geographical differences did not significantly impact the relationships within the model, suggesting consistent relationships across different regions. The findings highlight the need to move beyond a “one size fits all” approach, demonstrating that tailored strategies may be crucial for enhancing the adoption and satisfaction of PR services among various demographic groups. The analyses provide valuable insight for policymakers and rideshare companies looking to optimize their services and increase user engagement in PR.
Analyses were performed on a high-speed composite blade set for the Department of Defense Propfan Missile Interactions Project. The final design iteration, which resulted in the CM2D-2 blade design, is described in this report. Mode shapes, integral order excitation, and stress margins were examined. In addition, geometric corrections were performed to compensate for blade deflection under operating conditions with respect to the aerodynamic design shape.
Simple climate models (SCMs) are frequently used in research and decision-making communities because of their flexibility, tractability, and low computational cost. SCMs can be idealized, flexibly representing major climate dynamics as impulse response functions, or process-based, using explicit equations to model possibly nonlinear climate and Earth system dynamics. Each of these approaches has strengths and limitations. Here we present and test a hybrid impulse response modeling framework (HIRM) that combines the strengths of process-based SCMs in an idealized impulse response model, with HIRM's input derived from the output of a process-based model. This structure enables the model to capture some of the major nonlinear dynamics that occur in complex climate models as greenhouse gas emissions transform to atmospheric concentration to radiative forcing to climate change. As a test, the HIRM framework was configured to emulate the total temperature of the simple climate model Hector 2.0 under the four Representative Concentration Pathways and the temperature response of an abrupt 4 times CO 2 concentration step. HIRM was able to reproduce near-term and long-term Hector global temperature with a high degree of fidelity. Additionally, we conducted two case studies to demonstrate potential applications for this hybrid model: examining the effect of aerosol forcing uncertainty on global temperature and incorporating more process-based representations of black carbon into a SCM. The open-source HIRM framework has a range of applications including complex climate model emulation, uncertainty analyses of radiative forcing, attribution studies, and climate model development.
This report summarizes the SASSI analyses of a deeply embedded reactor model performed by BNL and CJC and Associates, as part of the seismic soil-structure interaction (SSI) simulation capability project for the NEAMS (Nuclear Energy Advanced Modeling and Simulation) Program of the Department of Energy. The SASSI analyses included three cases: 0.2 g, 0.5 g, and 0.9g, all of which refer to nominal peak accelerations at the top of the bedrock. The analyses utilized the modified subtraction method (MSM) for performing the seismic SSI evaluations. Each case consisted of two analyses: input motion in one horizontal direction (X) and input motion in the vertical direction (Z), both of which utilized the same in-column input motion. Besides providing SASSI results for use in comparison with the time domain SSI results obtained using the DIABLO computer code, this study also leads to the recognition that the frequency-domain method should be modernized so that it can better serve its mission-critical role for analysis and design of nuclear power plants.
A model-independent treatment of dark-matter particle elastic scattering has been developed, yielding the most general interaction for WIMP-nucleon low-energy scattering, and the resulting amplitude has been embedded into the nucleus, taking into account the selection rules imposed by parity and time-reversal. One finds that, in contrast to the usual spin-independent/spin-dependent (SI/SD) formulation, the resulting cross section contains six independent nuclear response functions, three of which are associated with possible velocity-dependent interactions. We find that current experiments are four orders of magnitude more sensitive to derivative couplings than is apparent in the standard SI/SD treatment, which necessarily associated such interactions with cross sections proportional to v 2 T ∼ 10 −6 , where v T is the WIMP velocity relative to the center of mass of the nuclear target.
TIROS-N and NOAA-6 temperature soundings over North America during three days in January 1980, and synoptic analyses and numerical-model forecasts derived from them, are compared with conventional data and analyses from NMC's limited-area fine-mesh model (LFM). The collocated sounding comparison revealed significant errors, especially near the surface and the tropopause. Satellite-derived thermal gradients were found to be weak, and thickness-analysis difference fields to propagate eastward, suggesting that sounding errors are correlated with synoptic patterns. The same pattern of anomalies is seen in the model forecasts. More detailed determinations of the correlation detected here could be used to optimize the assimilation of satellite soundings to conventional data.