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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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A fuel control system is reported for automotive-type gas turbines and particulary advanced gas turbines utilizing variable geometry components to improve mileage and reduce pollution emission. The fuel control system compensates for fuel density variations, inlet temperature variations, turbine vane actuation, acceleration, and turbine braking. These parameters are utilized to control various orifices, spool valves and pistons.
Two-dimensional wind-tunnel tests were conducted to determine effectiveness of spoilers applied to the GA(W)-1 airfoil. Tests of several spoiler configurations show adequate control effectiveness with flap nested. It is found that providing a vent path allowing lower surface air to escape to the upper surface as the spoiler opens alleviates control reversal and hysteresis tendencies. Spoiler cross-sectional shape variations generally have a modest influence on control characteristics. A series of comparative tests of vortex generators applied to the (GA-W)-1 airfoil show that triangular planform vortex generators are superior to square planform vortex generators of the same span.
Understanding the spatial variability of the snowpack is valuable for hydrologists and ecologists seeking to predict hydrological processes in a cold region. Snow distribution is a function of interactions among static variables, such as terrain, vegetation, and soil properties, and dynamic meteorological variables, such as solar radiation, wind speed and direction, and soil moisture. However, identifying the dominant physical drivers responsible for spatial patterns of the snowpack, particularly for ephemeral, shallow snowpacks, has been challenging due to the lack of the high-resolution snowpack and physical variables with high vertical accuracy as well as inherent limitations in traditional approaches. This study uses an Unpiloted Aerial System (UAS) lidar-based snow depth and static variables (1-m spatial resolution) to analyze field-scale spatial structures of snow depth and apply the Maximum Entropy (MaxEnt) model to identify primary controls over open terrain and forests at the University of New Hampshire Thompson Farm Research Observatory, New Hampshire, United States. We found that, among nine topographic and soil variables, plant functional type and terrain roughness contribute up to 80% and 76% of relative importance in the MaxEnt framework to predict locations of deeper or shallower snowpacks, respectively, across a mixed temperate forested and field landscape. Soil variables, such as organic matter and saturated hydraulic conductivity, were also important controls (up to 70% and 81%) on snow depth spatial variations for both open and forested landscapes suggesting spatial variations in soil variables under snow can control thermal transfer among soil, snowpack, and surface-atmosphere. This work contributes to improving land surface and snow models by informing parameterization of the sub-grid scale snow depths, down-scaling remotely sensed snow products, and understanding field scale snow states.
Abstract In the Arctic, the spatiotemporal variation of net methane uptake in upland soils depends on unresolved interactive controls between edaphic and microbial factors not yet included in current models, underpinning the uncertainty of upscaling the Arctic methane budget. Here we show that upland soils in Greenland are consistent methane sinks (−1.83 ± 0.19 nmol methane g −1 dw d −1 ) across a N-S (64–83 °N) pedoclimatic transect. We demonstrate that methane oxidizers abundance, soil pH, and available soil copper are important controls on the spatial variation in methane oxidation. We revised a soil biogeochemical model with a high-resolution land classification and meteorological data for Greenland and tested it against our methane uptake measurements. The model simulated well the magnitudes of observed methane uptake but not the spatial variation across all sites. This work provides novel insights into the controls of methane uptake, which are critical for the accuracy of methane budgets.
We investigate how processing pathways control micelle formation during dissolution of lamellar diblock copolymers using dissipative particle dynamics (DPD) simulations and DPD-selfconsistent field theory (DPD-SCFT). Comparing thin film (TF) and cosolvent-assisted (CS) dissolution reveals fundamentally different micellization mechanisms and final states. In the TF pathway, dissolution proceeds through a metastable cylindrical intermediate that dictates final micelle dimensions. The lamellar melt first transforms into cylindrical micelles, which then fragment into spherical micelles. The final spherical radius is intrinsically linked to the cylinder radius by a constant ratio, Rsphere ≈ 1.4Rcylinder. DPD-SCFT confirms that both cylinders and spheres are near their equilibrium dimensions. In contrast, CS dissolution produces kinetically trapped micelles with sizes significantly below equilibrium. Micellization is hindered by high free energy barriers to single-chain exchange and fusion. Growth occurs primarily via fusion, but increasing corona repulsion suppresses further coarsening, preventing equilibration. These results demonstrate that, when starting from a bulk copolymer phase, the metastable cylindrical intermediate plays a central role in determining final micelle size.
Approximately half of the nitrogen and phosphorus entering deep waters of the contemporary ocean are transported from the surface in inorganic form as preformed nutrients. A simple model for ocean chemistry is presented and shown to account for the present level of atmospheric CO2. Fluctuations in preformed nutrients, modulated by changes in insolation and circulation at high latitudes, can result in significant variations in CO2. It is suggested that these changes may account for the apparent control on climate exercised by secular variations in the orbital parameters of the earth.
The study applies mathematical methods of control theory to the problem of control of fluid flow with the long-range objective of developing effective methods for the control of turbulent flows. Model problems are employed through the formalism and language of control theory to present the procedure of how to cast the problem of controlling turbulence into a problem in optimal control theory. Methods of calculus of variations through the adjoint state and gradient algorithms are used to present a suboptimal control and feedback procedure for stationary and time-dependent problems. Two types of controls are investigated: distributed and boundary controls. Several cases of both controls are numerically simulated to investigate the performances of the control algorithm. Most cases considered show significant reductions of the costs to be minimized. The dependence of the control algorithm on the time-descretization method is discussed.
Young pine seedlings, and mung bean and oat seeds were flown on shuttle flights, STS-3 and STS-51F, in March, 1982 and July/August, 1985, respectively. The plant growth units built to support the two experiments functioned mechanically as anticipated and provided the necessary support data. Pine seedlings exposed to the microgravity environment of the space shuttle for 8 days continued to grow at a rate similar to ground controls. Pine stems in flight seedlings, however, averaged 10 to 12% less lignin than controls. Flight mung beans grew slower than control beans and their stems contained about 25% less lignin than control seedlings. Reduced mung bean growth in microgravity was partly due to slower germination rate. Lignin also was reduced in flight oats as compared to controls. Oats and mung beans exhibited upward growing roots which were not observed in control seedlings. Chlorophyll A/B ratios were lower in flight tissues than controls. The sealed PGCs exhibited large variations in atmospheric gas composition but the changes were similar between flight and ground controls. Ethylene was present in low concentrations in all chambers.
Statistical Process Control (SPC) charts are one of several tools used in quality control. Other tools include flow charts, histograms, cause and effect diagrams, check sheets, Pareto diagrams, graphs, and scatter diagrams. A control chart is simply a graph which indicates process variation over time. The purpose of drawing a control chart is to detect any changes in the process signalled by abnormal points or patterns on the graph. The Artificial Intelligence Support Center (AISC) of the Acquisition Logistics Division has developed a hybrid machine learning expert system prototype which automates the process of constructing and interpreting control charts.
Conventional spectroscopy uses classical light to detect matter properties through the variation of its response with frequencies or time delays. Quantum light opens up new avenues for spectroscopy by utilizing parameters of the quantum state of light as novel control knobs and through the variation of photon statistics by coupling to matter. This Roadmap article focuses on using quantum light as a powerful sensing and spectroscopic tool to reveal novel information about complex molecules that is not accessible by classical light. It aims at bridging the quantum optics and spectroscopy communities which normally have opposite goals: manipulating complex light states with simple matter e.g. qubits versus studying complex molecules with simple classical light, respectively. Here, articles cover advances in the generation and manipulation of state-of-the-art quantum light sources along with applications to sensing, spectroscopy, imaging and interferometry.
Previous work comparing power take-off (PTO) architectures for ocean wave-powered reverse osmosis suggests that variable displacement in the wave energy converter (WEC)-driven pump does not offer a significant performance advantage. A limitation of that study is that the WEC was subject to a constant load within a given sea state (“Coulomb damping”) and did not account for controlled, moment-to-moment variation of the PTO load enabled by a variable displacement pump. This study explores the potential performance advantage of a variable PTO load over Coulomb damping. Model predictive control is used to provide optimal load control with constraints on the PTO load. The constraints include minimum and maximum loads and a limit on the rate of load adjustment. Parameter studies on these constraints enable conclusions about PTO design requirements in addition to providing an estimated performance advantage over Coulomb damping. Numerical simulation of the Oyster 1 WEC is carried out with performance weighted by historical sea state data from Humboldt Bay, CA. The results show a performance advantage of up to 20% higher yearly-average power absorption over Coulomb damping. Additionally, the parameter studies suggest that the PTO load should be adjustable down to at least 25% of the maximum load and should be adjustable between the minimum and maximum loads within a few seconds.
An approach for combined control-structure optimization keyed to enhancing early design trade-offs is outlined and illustrated by numerical examples. The approach employs a homotopic strategy and appears to be effective for generating families of designs that can be used in these early trade studies. Analytical results were obtained for classes of structure/control objectives with linear quadratic Gaussian (LQG) and linear quadratic regulator (LQR) costs. For these, researchers demonstrated that global optima can be computed for small values of the homotopy parameter. Conditions for local optima along the homotopy path were also given. Details of two numerical examples employing the LQR control cost were given showing variations of the optimal design variables along the homotopy path. The results of the second example suggest that introducing a second homotopy parameter relating the two parts of the control index in the LQG/LQR formulation might serve to enlarge the family of Pareto optima, but its effect on modifying the optimal structural shapes may be analogous to the original parameter lambda.
Abstract The genetic control of many plant traits can be highly complex. Both allelic variation (sequence change) and dosage variation (copy number change) contribute to a plant's phenotype. While numerous studies have investigated the effect of allelic or dosage variation, very few have documented both within the same system, leaving their relative contribution to phenotypic effects unclear. The Populus genome is highly polymorphic, and poplars are fairly tolerant of gene dosage variation. Here, using a previously established Populus hybrid F1 population, we assessed and compared the effect of natural allelic variation and induced dosage variation on biomass, phenology, and leaf morphology traits. We identified QTLs for many of these traits, but our results indicate limited overlap between the QTLs associated with natural allelic variation and induced dosage variation. Additionally, the integration of data from both allelic and dosage variation identifies a larger set of QTLs that together explain a larger percentage of the phenotypic variance. Finally, our results suggest that the effect of the large indels might mask that of allelic QTLs. Our study helps clarify the relationship between allelic and dosage variation and their effects on quantitative traits.
Variations in the structure of the neocortex induced by single gene mutations may be extreme or subtle. They differ from variations in neocortical structure encountered across and within species in that these "normal" structural variations are adaptive (both structurally and behaviorally), whereas those associated with disorders of development are not. Here we propose that they also differ in principle in that they represent disruptions of molecular mechanisms that are not normally regulatory to variations in the histogenetic sequence. We propose an algorithm for the operation of the neuronogenetic sequence in relation to the overall neocortical histogenetic sequence and highlight the restriction point of the G1 phase of the cell cycle as the master regulatory control point for normal coordinate structural variation across species and importantly within species. From considerations based on the anatomic evidence from neocortical malformation in humans, we illustrate in principle how this overall sequence appears to be disrupted by molecular biological linkages operating principally outside the control mechanisms responsible for the normal structural variation of the neocortex. MRDD Research Reviews 6:22-33, 2000. Copyright 2000 Wiley-Liss, Inc.
Experimental aerodynamic investigations were carried out in the Boeing transonic and supersonic wind tunnels on a 0.008899-scale model of a proposed pressure-fed ballistic recoverable booster (BRB) configuration. The purpose of the test program was to determine the stability and control effectiveness of the basic configuration at high and low angles of attack, and to conduct parametric studies of various engine shroud, fin, and drag petal configurations. Six-component force data and base pressure data were obtained over a Mach number range of 0.35 to 4.0 at angles of attack of -5 to 25 and 55 to 85 at zero degrees sideslip and over a sideslip range of -10 to +10 at angles of attack ranging from -10 to 72.5. Two-component force data were also obtained with a fin balance on selected runs.
We performed computational investigation of the adsorption of bimetallic Pd 3 M 2 (where M changes from Ag, Au, Co, Cu, Mn, Ni, Pt, and Ru) cluster on the hydroxylated alumina surface. Previously, it was shown that small silver cluster can control the rate of discharge at the cathode of lithium-oxygen battery. The gap near the fermi energy was shown to control the oxygen reduction, an important reaction for LiO 2 formation. Controlling the gap would ultimately control the rate of LiO 2 formation. One can vary the size of the cluster to vary the gap, however, this "knob" provides limited variance in the gap. Alloying, in combination with size variation offer a much wider control of the gap, hence the LiO 2 formation. Using Density Functional Theory (DFT), we determined the most stable geometry of the bimetallic clusters Pd 3 M 2 and calculated the binding energies of these clusters on the alumina substrate which ranges from 0.2 eV to 0.25 eV depending upon the composition of the alloy-cluster, its orientation and the adsorption site. We also find that Pd atoms bind strongly with the substrate oxygen atoms with an average short bond-length of about 2.2 angstrom. We explored how the gap at the Fermi level of the system varies as a function of elemental composition and the calculated gap ranges from 0 meV to 90 meV. Charges distribution using Bader analysis was also performed to probe how charges are transferred between the cluster and the substrate. These preliminary results will open the door for more systematic studies of alloy clusters of different size and stoichiometry for Li-O 2 battery cathode design.
The Icing Research Tunnel in Building 11 at the NASA Glenn Research Center is committed to researching the effects of in flight icing on aircraft and testing ways to stop the formation of hazardous icing conditions on planes. During this summer, I worked here with Richard DelRosa, the lead engineer for this area. address one of the major concerns of aviation: icing conditions. During the war, many planes crashed (especially supply planes going over the.Himalayas) because ice built up in their wings and clogged the engines. To this day, it remains the largest ice tunnel in the world, with a test section that measures 6 feet high, 9 feet long, and 20 feet wide. It can simulate airspeeds from 50 to 300 miles per hour at temperatures as low as -50 Fahrenheit. Using these capabilities, IRT can simulate actual conditions at high altitudes. The first thing I did was creating a cross reference in Microsoft Excel. It lists commands for the DPU units that control the pressure and temperature variations in the tunnel, as well as the type of command (keyboard, multiplier, divide, etc). The cross reference also contains the algorithm for every command, and which page it is listed in on the control sheet (visual Auto-CAD graphs, which I helped to make). I actually spent most of the time on the computer using Auto-CAD. I drew a diagram of the entire icing tunnel and then drew diagrams of its various parts. Between my mentor and me, we have drawings of every part of it, from the spray bars to the thermocouples, power cabinets, input-output connectors for power systems, and layouts of various other machines. I was also responsible for drawing schematics for the Escort system (which controls the spray bars), the power system, DPUs, and other electrical systems. In my spare time, I am attempting to build and program the "toddler". Toddler is a walking robot that I have to program in PBASIC language. When complete, it should be able to walk on level terrain while avoiding obstacles in real-time. It features an infrared detector that can keep it from falling over edges, as well as follow or avoid a light source. The toddler is giving me a much better understanding of the basics of electronic circuitry and computer programming.
The Marshall Space Flight Center (MSFC) Flight Mechanics and Analysis Division developed an adaptive augmenting control (AAC) algorithm for launch vehicles that improves robustness and performance on an as-needed basis by adapting a classical control algorithm to unexpected environments or variations in vehicle dynamics. This was baselined as part of the Space Launch System (SLS) flight control system. The NASA Engineering and Safety Center (NESC) was asked to partner with the SLS Program and the Space Technology Mission Directorate (STMD) Game Changing Development Program (GCDP) to flight test the AAC algorithm on a manned aircraft that can achieve a high level of dynamic similarity to a launch vehicle and raise the technology readiness of the algorithm early in the program. This document reports the outcome of the NESC assessment.