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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Adaptive Algebraic Derivative Estimation for Battery Electric Buses Energy Consumption Forecasting

The limited service life of onboard batteries for EVs is a challenge, underscoring the need for real-time battery usage prediction. This paper proposes an adaptive Algebraic Derivative Estimation (ADE) approach for forecasting the energy consumption of battery electric buses. By dynamically adjusting the sliding window length, the adaptive ADE retains the fixed-length ADE’s key advantage—namely, operating online without reliance on extensive historical datasets—while substantially bolstering forecast accuracy by actively trading estimation bias off estimation variance. Comparative experiments against both the conventional ADE with a fixed length and a representative machine learning algorithm, XGBoost, were conducted, with performance evaluated via root mean square error, mean absolute error, and the coefficient of determination. The results demonstrate that the proposed approach significantly outperforms baseline methods.

Cui, Tianyang [The University of Texas at Dallas]↗
DOE OSTI2020

Atomic resolution convergent beam electron diffraction analysis using convolutional neural networks

Two types of convolutional neural network (CNN) models, a discrete classification network and a continuous regression network, were trained to determine local sample thickness from convergent beam diffraction (CBED) patterns of SrTiO 3 collected in a scanning transmission electron microscope (STEM) at atomic column resolution. Acquisition of atomic resolution CBED patterns for this purpose requires careful balancing of CBED feature size in pixels, acquisition speed, and detector dynamic range. The training datasets were derived from multislice simulations, which must be convolved with incoherent source broadening. Sample thicknesses were also determined using quantitative high-angle annular dark-field (HAADF) STEM images acquired simultaneously. The regression CNN performed well on sample thinner than 35 nm, with 70% of the CNN results within 1 nm of HAADF thickness, and 1.0 nm overall root mean square error between the two measurements. The classification CNN was trained for a thicknesses up to 100 nm and yielded 66% of CNN results within one classification increment of 2 nm of HAADF thickness. Our approach depends on methods from computer vision including transfer learning and image augmentation.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Soil Moisture Buffers the Impact of Precipitation Variability on Ecosystem Productivity

Water availability governs ecosystem productivity, yet estimates of vegetation sensitivity to water can differ greatly depending on whether the sensitivity is examined spatially or temporally. In particular, the spatial sensitivity is often reported to be much stronger than temporal sensitivities, leading to highly uncertain projections of ecosystem responses to future climate change when using space-for-time substitution. The large difference between spatial and temporal sensitivities remains unexplained. Prior research, however, primarily relied on precipitation as the water availability proxy, whereas vegetation responds to soil moisture. Here, we combined satellite estimates of vegetation productivity with soil moisture data across water-limited ecosystems of the continental United States (CONUS) to identify a convergent sensitivity of productivity to water availability. Using precipitation, we show that temporal sensitivity is 66% lower than spatial sensitivity overall. Our analysis identified the cause of the difference to be primarily driven by the seasonal variability of water availability, rooting depth, and soil properties. When using soil moisture instead of precipitation, we observed widespread convergence in the spatial and temporal sensitivities—that is, the two sensitivities became much more similar in magnitude across all water-limited ecosystems within CONUS. These results show that overlooking soil hydrology can inflate perceived discrepancies between spatial and temporal vegetation sensitivities, leading to biased projections of ecosystem dynamics under future hydro-climatic change.

Wang, Huiqi [University of California, Berkeley, C↗
NASA NTRS1992

Numerical methods for the analysis of sampled-data systems and for the computation of system zeros

MARSYAS is a computer-aided control system design package for the simulation and analysis of dynamic systems. In the summer of 1991 MARSYAS was updated to allow for the analysis of sampled-data systems in terms of frequency response, stability, etc. This update was continued during the summer of 1992 in order to extend further MARSYAS commands to the study of sampled-data systems. Further work was done to examine the computation of OPENAT transfer functions, root-locii and w-plane frequency response plots.

Hodel, A. Scottedward↗
NASA NTRS2005

Carbon Dynamics in Vegetation and Soils

The overall goals of CD-08 team in Phase I were to quantify the contributions of different components of the carbon cycle to overall ecosystem carbon balance in Amazonian tropical forests and to undertake process studies at a number of sites along the eastern LBA transect to understand how and why these fluxes vary with site, season, and year. We divided this work into a number of specific tasks: (1) determining the average rate (and variability) of tree growth over the past 3 decades; (2) determining age demographics of tree populations, using radiocarbon to determine tree age; (3) assessing the rate of production and decomposition of dead wood debris; (4) determining turnover rates for organic matter in soils and the mean age of C respired from soil using radiocarbon measurements; and (5) comparing our results with models and constructing models to predict the potential of tropical forests to function as sources or sinks of C. This report summarizes the considerable progress made towards our original goals, which have led to increased understanding of the potential for central Amazon forests to act as sources or sinks of carbon with altered productivity. The overall picture of tropical forest C dynamics emerging from our Phase I studies suggests that the fraction of gross primary production allocated to growth in these forests is only 25-30%, as opposed to the 50% assumed by many ecosystem models. Consequent slow tree growth rates mean greater mean tree age for a given diameter, as reflected in our measurements and models of tree age. Radiocarbon measurements in leaf and root litter suggest that carbon stays in living tree biomass for several years up to a decade before being added to soils, where decomposition is rapid. The time lags predicted from 14C, when coupled with climate variation on similar time scales, can lead to significant interannual variation in net ecosystem C exchange.

Trumbore, Susan↗
NASA NTRS2005

An Improved Analysis of Forest Carbon Dynamics using Data Assimilation

There are two broad approaches to quantifying landscape C dynamics - by measuring changes in C stocks over time, or by measuring fluxes of C directly. However, these data may be patchy, and have gaps or biases. An alternative approach to generating C budgets has been to use process-based models, constructed to simulate the key processes involved in C exchange. However, the process of model building is arguably subjective, and parameters may be poorly defined. This paper demonstrates why data assimilation (DA) techniques - which combine stock and flux observations with a dynamic model - improve estimates of, and provide insights into, ecosystem carbon (C) exchanges. We use an ensemble Kalman filter (EnKF) to link a series of measurements with a simple box model of C transformations. Measurements were collected at a young ponderosa pine stand in central Oregon over a 3-year period, and include eddy flux and soil C02 efflux data, litterfall collections, stem surveys, root and soil cores, and leaf area index data. The simple C model is a mass balance model with nine unknown parameters, tracking changes in C storage among five pools; foliar, wood and fine root pools in vegetation, and also fresh litter and soil organic matter (SOM) plus coarse woody debris pools. We nested the EnKF within an optimization routine to generate estimates from the data of the unknown parameters and the five initial conditions for the pools. The efficacy of the DA process can be judged by comparing the probability distributions of estimates produced with the EnKF analysis vs. those produced with reduced data or model alone. Using the model alone, estimated net ecosystem exchange of C (NEE)= -251 f 197g Cm-2 over the 3 years, compared with an estimate of -419 f 29gCm-2 when all observations were assimilated into the model. The uncertainty on daily measurements of NEE via eddy fluxes was estimated at 0.5gCm-2 day-1, but the uncertainty on assimilated estimates averaged 0.47 g Cm-2 day-1, and only exceeded 0.5gC m-2 day-1 on days where neither eddy flux nor soil efflux data were available. In generating C budgets, the assimilation process reduced the uncertainties associated with using data or model alone and the forecasts of NEE were statistically unbiased estimates. The results of the analysis emphasize the importance of time series as constraints. Occasional, rare measurements of stocks have limited use in constraining the estimates of other components of the C cycle. Long time series are particularly crucial for improving the analysis of pools with long time constants, such as SOM, woody biomass, and woody debris. Long-running forest stem surveys, and tree ring data, offer a rich resource that could be assimilated to provide an important constraint on C cycling of slow pools. For extending estimates of NEE across regions, DA can play a further important role, by assimilating remote-sensing data into the analysis of C cycles. We show, via sensitivity analysis, how assimilating an estimate of photosynthesis - which might be provided indirectly by remotely sensed data - improves the analysis of NEE.

Williams, Mathew↗
NASA NTRS2018

PIV and Rotational Raman-Based Temperature Measurements for CFD Validation in a Single Injector Cooling Flow

Film cooling is used in a wide variety of engineering applications for protection of surfaces from hot or combusting gases. The design of more efficient thin film cooling geometries/configurations could be facilitated by an ability to accurately model and predict the effectiveness of current designs using computational fluid dynamics (CFD) code predictions. Hence, a benchmark set of flow field property data were obtained for use in assessing current CFD capabilities and for development of better turbulence models. Both Particle Image Velocimetry (PIV) and spontaneous rotational Raman scattering (SRS) spectroscopy were used to acquire high quality, spatially-resolved measurements of the mean velocity, turbulence intensity and also the mean temperature and normalized root mean square (rms) temperatures in a single injector cooling flow arrangement. In addition to flowfield measurements, thermocouple measurements on the plate surface enabled estimates of the film effectiveness. Raman spectra in air were obtained across a matrix of radial and axial locations downstream from a 68.07 mm square nozzle blowing heated air over a range of temperatures and Mach numbers, across a 30.48 cm long plate equipped with a single injector cooling hole. In addition, both centerline streamwise 2-component PIV and cross-stream 3-component Stereo PIV data at 15 axial stations were collected in the same flows. The velocity and temperature data were then compared against Wind-US CFD code predictions for the same flow conditions. The results of this and planned follow-on studies will support NASA's development and assessment of turbulence models for heated flows.

Raman Scattering↗
NASA NTRS2018

PIV and Rotational Raman-Based Temperature Measurements for CFD Validation in a Single Injector Cooling Flow

Film cooling is used in a wide variety of engineering applications for protection of surfaces from hot or combusting gases. The design of more efficient thin film cooling geometries/configurations could be facilitated by an ability to accurately model and predict the effectiveness of current designs using computational fluid dynamics (CFD) code predictions. Hence, a benchmark set of flow field property data were obtained for use in assessing current CFD capabilities and for development of better turbulence models. Both Particle Image Velocimetry (PIV) and spontaneous rotational Raman scattering (SRS) spectroscopy were used to acquire high quality, spatially-resolved measurements of the mean velocity, turbulence intensity and also the mean temperature and normalized root mean square (rms) temperatures in a single injector cooling flow arrangement. In addition to flowfield measurements, thermocouple measurements on the plate surface enabled estimates of the film effectiveness. Raman spectra in air were obtained across a matrix of radial and axial locations downstream from a 68.07 mm square nozzle blowing heated air over a range of temperatures and Mach numbers, across a 30.48cm long plate equipped with a single injector cooling hole. In addition, both centerline streamwise 2-component PIV and cross-stream 3-component Stereo PIV data at 15 axial stations were collected in the same flows. The velocity and temperature data were then compared against Wind-US CFD code predictions for the same flow conditions. The results of this and planned follow-on studies will support NASA's development and assessment of turbulence models for heated flows.

Wernet, Mark P.↗
NASA NTRS2018

PIV and Rotational Raman-Based Temperature Measurements for CFD Validation in a Single Injector Cooling Flow

Film cooling is used in a wide variety of engineering applications for protection of surfaces from hot or combusting gases. The design of more efficient thin film cooling geometries/configurations could be facilitated by an ability to accurately model and predict the effectiveness of current designs using computational fluid dynamics (CFD) code predictions. Hence, a benchmark set of flow field property data were obtained for use in assessing current CFD capabilities and for development of better turbulence models. Both Particle Image Velocimetry (PIV) and spontaneous rotational Raman scattering (SRS) spectroscopy were used to acquire high quality, spatially-resolved measurements of the mean velocity, turbulence intensity and also the mean temperature and normalized root mean square (rms) temperatures in a single injector cooling flow arrangement. In addition to flowfield measurements, thermocouple measurements on the plate surface enabled estimates of the film effectiveness. Raman spectra in air were obtained across a matrix of radial and axial locations downstream from a 68.07 mm square nozzle blowing heated air over a range of temperatures and Mach numbers, across a 30.48cm long plate equipped with a single injector cooling hole. In addition, both centerline streamwise 2-component PIV and cross-stream 3-component Stereo PIV data at 15 axial stations were collected in the same flows. The velocity and temperature data were then compared against Wind-US CFD code predictions for the same flow conditions. The results of this and planned follow-on studies will support NASA's development and assessment of turbulence models for heated flows.

Turbulence Modeling↗
DOE OSTI2024

Connecting Nitrogen Transformations Mediated by the Rhizosphere Microbiome to Perennial Cropping System Productivity in Marginal Lands

The demand for energy from biofuel production is increasing, prompting concerns about the environmental impact and long-term sustainability of bioenergy cropping systems. These cropping systems will make up much of our future landscapes, and threaten to take the place of food cropping systems. Many life cycle analyses of bioenergy sustainability focus on carbon accrual and budgets, since they want to maximize carbon accrual while producing alternative fuel. Less attention has been given to nitrogen (N) dynamics in these systems. N is the most commonly limiting nutrient for plants, but applying nitrogen fertilizer- as we do for most cropping systems – is harmful to the environment, energetically costly, and produces greenhouse gases. In other words, adding nitrogen by fertilizer bioenergy systems could add to the very problems (climate change) it is trying to address. This is especially true for the areas that are proposed for bioenergy systems: marginal lands. These more degraded lands do not complete with food crops, but do have limited nitrogen. If we are to use these marginal lands for bioenergy, we need to understand the mechanisms regulating nutrient acquisition, and identify ways that bioenergy crops can get nitrogen in sustainable ways. Nutrient acquisition in the soil is performed by microbes in the root zone, or rhizosphere. Microbes can either mineralize nitrogen in the soil (from organic forms) or fix nitrogen from the air, in a process called nitrogen fixation. The goal of our project was thus to understand how the rhizosphere microbiome provides nutrients to bioenergy crops on marginal lands. We focus especially on the process of nitrogen fixation, since it has potential to get “fertilizer for free” that has much less environmental harm. We investigated this goal using sites from the DOE Great Lakes Bioenergy Research Center (GLBRC) in the upper Midwest, and associated lab and ‘omics methods. We group our findings into three major areas. First, we showed that nitrogen fixation, the conversion of N2 gas from the air to ammonium that is usable by plants, is performed in bioenergy soils, and benefits switchgrass crops. While more well-studied in leguminous plants, free-living nitrogen fixation can occur in some systems, and represents a potential opportunity to gain ‘free’ sustainable nitrogen source. We identified the nitrogen fixing bacteria that were most active in providing switchgrass with N, and showed that the drivers of nitrogen fixation occurred at a microscale; it is not well-predicted by bulk variables like soil moisture or plant phenology. Second, we showed that nitrogen fixation is not suppressed by long-term fertilizer. We expected that plentiful nitrogen would reduce the symbiotic relationship between nitrogen fixers and plants, and ‘downregulate’ fixation. We did not find evidence for this, either after long-term fertilizer in the field, or short-term fertilizer in the greenhouse. Finally, we identified the root exudates, carbon compounds that are emitted from the root, that best stimulate nitrogen fixation. We found that carbohydrates were better at stimulating fixation than organic acids. We expected these exudates to be emitted from the plant in periods of high N demand, but we found they are emitted when N is plentiful. This suggests that the stimulation of N fixation by plants is a passive process. Overall, we show that nitrogen fixation has potential to support bioenergy cropping system, and future management could develop ways to maximize it. However, this may not be best achieved via the plant – we found very little evidence of a ‘transactional’ system by which plants are controlling when and where nitrogen fixation is stimulated. It will be better to understand how management practices like planting and fertilizer application affect the microscale soil dynamics, which will determine nitrogen fixation rates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Isotherm Modeling and Techno-Economic Analysis of Contactor Technologies for New Tetraamine-Appended MOF for NGCC Applications

Recently, a family of tetraamine-functionalized metal-organic frameworks (MOF) has been reported as promising sorbent materials for capturing CO2 from flue gas conditions relevant to natural gas combined cycle (NGCC) applications. The main advantages of these materials are their two-step cooperative CO2 adsorption, which gives rise to unusual two step-shaped CO2 adsorption profiles and their high thermal stability. This work presents the modelling of the two-transition isotherm of the tetraamine-appended MOF, N,N'-bis(3-aminopropyl)-1,4-diaminobutane (3-4-3)-appended Mg2(dobpdc), and the techno-economic analysis (TEA) of carbon capture processes utilizing this sorbent. Due to the unusual isotherm shapes of the experimental CO2 adsorption data for tetraamine-appended Mg2(dobpdc) and the strong nonlinearity of CO2 loading with respect to temperature and pressure, we tested two different models which use logistic functions for representing the different isotherm behaviors in the different pressure ranges. The first model uses the quadratic isotherm model in the low-pressure region, the Langmuir isotherm model in the middle pressure range, and the dual site Langmuir isotherm model in the high-pressure range. To model the transition between regions we used the arctangent functions independent of temperature and the thermal effect was accounted by using the Clausius-Clapeyron relation]. The second model is an extension of the weighted dual-site Langmuir isotherm model presented by Hughes et al.. In this extended model, the dual-site Langmuir isotherm is employed in the three transition regions, using temperature-dependent logistic functions to activate or deactivate the isotherm model in the low, middle, and high-pressure ranges. Both models fit the experimental data quite well with root mean squared errors (RMSE’s) of 0.41 and 0.17 for model 1 and model 2, respectively. Since model 2 resulted in a lower RMSE, it was leveraged for the development of the gas/solid contactor models used by the TEA. Specifically, two different contactor models, an axial-flow fixed bed and moving bed contactor, were developed as part of this work. These models are dynamic, pressure-driven, and consist of mass, energy, and momentum conservation equations. A kinetic model was also developed by performing parameter estimation using experimental fixed bed breakthrough data. These models are then used to simulate CO2 capture processes from the flue gas generated from a ~600 gross MW NGCC power plant. A cost model was developed which considers the capital cost of the reactors and the significant operating costs such as steam and electricity. Using NETL’s Framework for the Optimization and Quantification of Uncertainty of Uncertainty and Surrogates tool (FOQUS), which has the capability of linking models built using numerous modelling platforms with derivative-free optimization solvers, a techno-economic optimization of the carbon capture processes was performed which minimizes the cost of capture.

Caballero, Daison↗
NASA NTRS1978

Applications of the hybrid coordinate method to the TOPS autopilot

Preliminary results are presented from the application of the hybrid coordinate method to modeling TOPS (thermoelectric outer planet spacecraft) structural dynamics. Computer simulated responses of the vehicle are included which illustrate the interaction of relatively flexible appendages with an autopilot control system. Comparisons were made between simplified single-axis models of the control loop, with spacecraft flexibility represented by hinged rigid bodies, and a very detailed three-axis spacecraft model whose flexible portions are described by modal coordinates. While single-axis system, root loci provided reasonable qualitative indications of stability margins in this case, they were quantitatively optimistic when matched against responses of the detailed model.

Fleischer, G. E.↗
NASA NTRS1990

Measured forces and moments on a delta wing during pitch-up

A series of low-speed wind tunnel tests on a 70-deg, sharp, leading-edge delta wing undergoing ramp pitching motion of high amplitude were performed to investigate the aerodynamic forces and moments. Forces and moments were obtained from a six-component interanl balance. Large amplitude oscillatory motion was produced by sinusoidally oscillating the model over a range of reduced frequencies. Ramp motion was produced by pitching the model through a half cycle of sinusoidal motion at a root chord Reynolds number of 1.54 million. The effect of ramp and oscillatory motions on the forces and moments are almost identical at matched pitch rates. Pitch rate had strong effect on the magnitude of the aerodynamic forces and moments. Upon completion of the model motion, some time is required for the forces and moments to decay to their static values. This convergence of the dynamic values to the static ones was a function of the pitch rate.

Bragg, M. B.↗
NASA NTRS2020

PIV and Rotational Raman-Based Temperature Measurements for CFD Validation of a Perforated Plate Cooling Flow: Part I

Film cooling is used in a wide variety of engineering applications for protection of surfaces from hot or combusting gases. The design of more efficient film cooling geometries/configurations could be facilitated by an ability to accurately model and predict the effectiveness of current designs using computational fluid dynamics (CFD) code predictions. Hence, a benchmark set of flow field property data was obtained to assess current CFD capabilities and develop better modeling approaches for these turbulent flow fields where accurate calculation of turbulent heat flux is important. Both Particle Image Velocimetry (PIV) and spontaneous rotational Raman scattering (SRS) spectroscopy were used to acquire high quality, spatially-resolved measurements of the mean and root mean square (rms) velocities as well as the mean and rms temperatures in a film cooling flow field. In addition to off-body flow field measurements, infrared thermography (IR) and thermocouple measurements on the plate surface enabled estimates of the film effectiveness. Raman spectra in air were obtained across a matrix of axial locations downstream from a 68.07 mm square nozzle blowing heated air over a range of temperatures (up to TR = 2.7) and Mach numbers (up to Mach 0.9), across a 30.48 cm long plate equipped with three patches of 45 small (~1 mm) diameter cooling holes arranged in a staggered configuration. In addition, both streamwise 2-component PIV (on the plate centerline) and cross-stream 3-component Stereo PIV data at 14 axial stations were collected in the same flows. Only a subset of the data collected in the test program is included in this Part I report. The rest of the data will be published in a future report, Part II, along with planned CFD predictions of the complex cooling film flow. The entire data set of Raman temperature data, PIV velocity data and IR camera data covering the Set Points 23 and 49 in the test matrix in Table 1 is available in an accompanying DVD (available online from www.sti.nasa.gov) for those interested in further analysis.

Nozzle↗
NASA NTRS2020

PIV and Rotational Raman-Based Temperature Measurements for CFD Validation of a Perforated Plate Cooling Flow Part I

Film cooling is used in a wide variety of engineering applications for protection of surfaces from hotor combusting gases. The design of more efficient film cooling geometries/configurations could be facilitated by an ability to accurately model and predict the effectiveness of current designs using computational fluid dynamics (CFD) code predictions. Hence, a benchmark set of flow field property data were obtained to assess current CFD capabilities and develop better modeling approaches for these turbulent flow fields where accurate calculation of turbulent heat flux is important. Both Particle Image Velocimetry (PIV) and spontaneous rotational Raman scattering (SRS) spectroscopy were used to acquire high quality, spatially-resolved measurements of the mean and root mean square (rms) velocities as well as the mean and rms temperatures in a film cooling flow field. In addition to off-body flow field measurements, infrared thermography (IR) and thermocouple measurements on the plate surface enabled estimates of the film effectiveness. Raman spectra in air were obtained across a matrix of axial locations downstream from a 68.07 mm square nozzle blowing heated air over a range of temperatures (up to TR =2.7) and Mach numbers (up to Mach 0.9), across a 30.48 cm long plate equipped with three patches of 45 small (~1 mm) diameter cooling holes arranged in a staggered configuration. In addition, both streamwise 2-component PIV (along the plate centerline) and cross-stream 3-component Stereo PIV data at 14 axial stations were collected in the same flows. Only a subset of the data collected in the test program is included in this Part 1 report. The rest of the data will be published in a future report, Part 2, along with planned CFD predictions of the complex cooling film flow.The entire data set of Raman temperature data, PIV velocity data and IR camera data covering the Set Points 23 and 49 in the test matrix in Table 1 is available in an accompanying DVD (available online from www.sti.nasa.gov) for those interested in further analysis.

Mark P Wernet↗
DOE OSTI2020

Disruption of Very-Long-Chain-Fatty Acid Synthesis Has an Impact on the Dynamics of Cellulose Synthase in Arabidopsis thaliana

In higher plants, cellulose is synthesized by membrane-spanning large protein complexes named cellulose synthase complexes (CSCs). In this study, the Arabidopsis PASTICCINO2 (PAS2) was identified as an interacting partner of cellulose synthases. PAS2 was previously characterized as the plant 3-hydroxy-acyl-CoA dehydratase, an ER membrane-localized dehydratase that is essential for very-long-chain-fatty acid (VLCFA) elongation. The pas2-1 mutants show defective cell elongation and reduction in cellulose content in both etiolated hypocotyls and light-grown roots. Although disruption of VLCFA synthesis by a genetic alteration had a reduction in VLCFA in both etiolated hypocotyls and light-grown roots, it had a differential effect on cellulose content in the two systems, suggesting the threshold level of VLCFA for efficient cellulose synthesis may be different in the two biological systems. pas2-1 had a reduction in both CSC delivery rate and CSC velocity at the PM in etiolated hypocotyls. Interestingly, Golgi but not post-Golgi endomembrane structures exhibited a severe defect in motility. Experiments using pharmacological perturbation of VLCFA content in etiolated hypocotyls strongly indicate a novel function of PAS2 in the regulation of CSC and Golgi motility. Through a combination of genetic, biochemical and cell biology studies, our study demonstrated that PAS2 as a multifunction protein has an important role in the regulation of cellulose biosynthesis in Arabidopsis hypocotyl.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Silica nanocluster binding rate coefficients from molecular dynamics trajectory calculations

Oxide nanoparticle growth from vapor phase precursors occurs in high temperature aerosol reactors first via the formation of nanoclusters, which are nanometer-scale condensed-phase species composed of 10 1 -10 2 atoms. The binding rate for nanoclusters, defined as the rate at which two nanoclusters collide with and stick to one another, is hence of interest in predicting nanoparticle size distribution functions in an aerosol. We have utilized molecular dynamics (MD) trajectory calculations to determine the homogeneous (equal-sized) and heterogeneous (disparate-sized) binding rate coefficients of SiO2 (silica) nanoclusters composed of 18, 144, and 333 atoms. MD trajectory calculations incorporated all-atom models of nanoclusters using a combined Born–Huggins–Mayer-Lennard-Jones potential model, which accounts for both short range interactions and electrostatic interactions. MD calculations were utilized to determine the binding probability as a function of both initial relative velocity and impact parameter; integration of the binding probability across impact parameter and relative velocity space yields the binding rate coefficient. MD trajectory calculations reveal that the most common type of encounters between nanoclusters leading to binding are grazing collisions, i.e. instances where collision would not occur without induced dipole potential influences. The resulting binding rate coefficients are found to be extremely weakly dependent on system temperature, which is in contrast to the use of rate coefficient models which are the product of a hard-sphere collision rate coefficient and a constant enhancement factor (leading to a rate coefficient proportional to the square root of temperature). Enhancement factors defined from MD trajectory calculations fall in the range of 3–9 as system temperature decreases from 1500 K to 300 K. Furthermore, such large values suggest that potential interactions need to be considered when modeling oxide nanocluster growth in the gas phase.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1986

A robust adaptive flightpath reconstruction technique

Computational schemes are presented that allow accurate reconstruction of an aircraft's flightpath in real-time. The reconstruction of the flightpath is formulated as a linear state reconstruction problem, which can be solved via Kalman filtering (KF) techniques. This imposes some conditions upon the flight-test equipment. A reliable square root covariance KF (SRCF) implementation is chosen and further developed into a fully adaptive flightpath reconstruction scheme. Therefore, the basic SRCF is modified in order to cope with several practical problems such as: the automatic control of the convergence of the recursive KF calculations, time varying zero-bias errors on the input signal of the system model used in the KF, and the changing aircraft dynamics owing to a change in reference flight condition. The developed solutions for these problems are all implemented in a numerically stable way, which guarantees the overall flightpath reconstruction scheme to be robust. Furthermore, some special features of the used system model are exploited to make the algorithmic implementation very efficient. An experimental simulation study using simulated flight test data demonstrated these different capabilities.

Verhaegen, M. H.↗