Optimum quantizations
Optimum quantization, which minimizes mean square or peak error for constant number of quanta, based on probability density function of continuous variable
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Optimum quantization, which minimizes mean square or peak error for constant number of quanta, based on probability density function of continuous variable
Acoustic emission (AE) data were taken during hydroproof for three sets of ASTM standard 5.75 inch diameter filament wound graphite/epoxy bottles. All three sets of bottles had the same design and were wound from the same graphite fiber; the only difference was in the epoxies used. Two of the epoxies had similar mechanical properties, and because the acoustic properties of materials are a function of their stiffnesses, it was thought that the AE data from the two sets might also be similar; however, this was not the case. Therefore, the three resin types were categorized using dummy variables, which allowed the prediction of burst pressures all three sets of bottles using a single neural network. Three bottles from each set were used to train the network. The resin category, the AE amplitude distribution data taken up to 25 % of the expected burst pressure, and the actual burst pressures were used as inputs. Architecturally, the network consisted of a forty-three neuron input layer (a single categorical variable defining the resin type plus forty-two continuous variables for the AE amplitude frequencies), a fifteen neuron hidden layer for mapping, and a single output neuron for burst pressure prediction. The network trained on all three bottle sets was able to predict burst pressures in the remaining bottles with a worst case error of + 6.59%, slightly greater than the desired goal of + 5%. This larger than desired error was due to poor resolution in the amplitude data for the third bottle set. When the third set of bottles was eliminated from consideration, only four hidden layer neurons were necessary to generate a worst case prediction error of - 3.43%, well within the desired goal.
NASA and the USAF have conducted a program to investigate aircraft performance improvements utilizing a mission adaptive wing (MAW). The MAW was designed and developed for the AFTI/F-111 variable-sweep aircraft to provide a hydraulically driven, smooth, and continuous variable camber of the trailing and leading edges as a function of maneuvering requirements or of flight conditions. The remotely augmented vehicle facility (RAV) at the NASA DFRF, as utilized in the MAW investigations, is described. The RAV was a dedicated, ground based, general purpose facility capable of receiving a data stream downlinked from a test vehicle, processing this data stream in a digital computer, and transmitting processed data back to the test vehicle. It is shown that this method of flight testing provides a technique that can evaluate highly dynamic maneuvers.
The recent linking of Cloud-Resolving Models (CRMs) to Ocean-Mixed Layer (OML) models has provided a powerful new means of quantifying the role of cloud systems in ocean-atmosphere coupling. This is due to the fact that the CRM can better resolve clouds and cloud systems and allow for explicit cloud-radiation interaction. For example, Anderson (1997) applied an atmospheric forcing associated with a CRM simulated squall line to a 3-D OML model (one way or passive interaction). His results suggested that the spatial variability resulting from the squall forcing can last at least 24 hours when forced with otherwise spatially uniform fluxes. In addition, the sea surface salinity (SSS) variability continuously decreased following the forcing, while some of the SST variability remained when a diurnal mixed layer capped off the surface structure. The forcing used in the OML model, however, focused on shorter time (8 h) and smaller spatial scales (100-120 km). In this study, the 3-D Goddard Cumulus Ensemble Model (GCE; 512 x 512 x 23 cu km, 2-km horizontal resolution) is used to simulate convective active episodes occurring in the Western Pacific warm pool and Eastern Atlantic regions. The model is integrated for seven days, and the simulated results are coupled to an OML model to better understand the impact of precipitation and changes in the planetary boundary layer upon SST variation. We will specifically examine and compare the results of linking the OML model with various spatially-averaged outputs from GCE simulations (i.e., 2 km vs. 10-50 km horizontal resolutions), in order to help understand the SST sensitivity to multi-scale influences. This will allow us to assess the importance of explicitly simulated deep and shallow clouds, as well as the subgrid-scale effects (in coarse-model runs) upon SST variation. Results using both 1-D and 2-D OML models will be evaluated to assess the effects of horizontal advection.
A variable pressure diamond anvil cell is described for operation at temperatures continuously variable from 300 down to 2 K and controllable within 10 mK. Polycrystalline X-ray data are collected from the pressure cavity by means of either (1) standard photographic techniques, (2) diffractometer measurements, or (3) energy dispersive diffractometry. The facility has been used to examine parts of the phase diagram of Bi. Results from this study indicate that the Bi-I and Bi-III structures are retained to low temperatures; however, there is no evidence to support a structural transition from Bi-V to Bi-VIII.
Surveys of brown dwarf variability continue to find that roughly half of all brown dwarfs are variable. While variability is observed amongst all types of brown dwarfs, amplitudes are typically greatest for L-T transition objects. In my talk I will discuss the possible physical mechanisms that are responsible for the observed variability. I will particularly focus on comparing and contrasting the effects of changes in atmospheric thermal profile and cloud opacity. The two different mechanisms will produce different variability signatures and I will discuss the extent to which the current datasets constrain both mechanisms. By combining constraints from studies of variability with existing spectral and photometric datasets we can begin to construct and test self-consistent models of brown dwarf atmospheres. These models not only aid in the interpretation of existing objects but also inform studies of directly imaged giant planets.
A planning system must reason about the uncertainty of continuous variables in order to accurately project the possible system state over time. A method is devised for directly reasoning about the uncertainty in continuous activity duration and resource usage for planning problems. By representing random variables as parametric distributions, computing projected system state can be simplified in some cases. Common approximation and novel methods are compared for over-constrained and lightly constrained domains. The system compares a few common approximation methods for an iterative repair planner. Results show improvements in robustness over the conventional non-probabilistic representation by reducing the number of constraint violations witnessed by execution. The improvement is more significant for larger problems and problems with higher resource subscription levels but diminishes as the system is allowed to accept higher risk levels.
Airborne lidar systems are used to determine wind velocity and to measure aerosol or cloud backscatter variability. Atmospheric aerosols, being affected by local and regional sources, show tremendous variability. Continuous wave (cw) lidar can obtain detailed aerosol loading with unprecedented high resolution (3 sec) and sensitivity (1 mg/cubic meter) as was done during the 1995 NASA Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS) mission over western North America and the Pacific Ocean. Backscatter variability was measured at a 9.1 micron wavelength cw focused CO2 Doppler lidar for approximately 52 flight hours, covering an equivalent horizontal distance of approximately 30,000 km in the troposphere. Some quasi-vertical backscatter profiles were also obtained during various ascents and descents at altitudes that ranged from approximately 0.1 to 12 km. Similarities and differences for aerosol loading over land and ocean were observed. Mid-tropospheric aerosol backscatter background mode was approximately 6 x 10(exp -11)/ms/r, consistent with previous lidar datasets. While these atmospheric measurements were made, the lidar also retrieved a distinct backscatter signal from the Earth's surface from the unfocused part of the focused cw lidar beam during aircraft rolls. Atmospheric backscatter can be highly variable both spatially and temporally, whereas, Earth-surface backscatter is relatively much less variant and can be quite predictable. Therefore, routine atmospheric backscatter measurements by an airborne lidar also give Earth surface backscatter which can allow for investigating the Earth terrain. In the case where the Earth's surface backscatter is coming from a well-known and fairly uniform region, then it can potentially offer lidar calibration opportunities during flight. These Earth surface measurements over varying Californian terrain during the mission were compared with laboratory backscatter measurements using the same lidar of various Earth surfaces giving good agreement, suggesting that the lidar efficiency, and thus a lidar calibration factor for detection, can be estimated fairly well using Earth's surface signal.
Temperature controlled by altering infrared radiative properties. Infrared emissivity of electrochromically active layer changed by applying voltage to insert or remove Li atoms electrochemically. Change reversible and continuously variable between specified limits of layered structure.
Monograph on state variable approach to continuous estimation of random processes with applications to analog communication theory
The question is posed whether forced air flow should be incorporated into flammability tests as a relevant variable. A test apparatus is described which permits tests to be conducted on small test specimens in a forced flow which is (continuously) variable over flow velocities from zero to 300 feet per minute (1.52 m/s). The effects of air-flow rate and oxygen concentration on flame propagation rate, maximum smoke density, and pyrolytic product toxicity were measured for a single material and were statistically evaluated. Regression analysis was used to graph the resulting relationships. It is concluded that air velocity is an important variable for laboratory flammability testing.
Current helicopter flight and propulsion controls are typically designed with the assumption that rotor speed will be held to a constant setpoint. A new flight and propulsion control system using a continuously variable rotor speed command is proposed to improve the maneuverability and agility of helicopter systems. In this new approach, the flight control system generates an optimal variable rotor speed command in addition to conventional control commands in a framework of integrated flight/propulsion control. The benefits (i.e. improved maneuverability and agility) of varying rotor speed during transient maneuvers are demonstrated using a bob-up maneuver as an example. In particular, two types of benefits are identified in different maneuver conditions. One comes from a thrust augmentation, while the other comes from an exchange of rotational and translational energy. In the example, a simple linear dynamic hover model is used with an optimal control design method to generate the optimal rotor speed command.
By introducing variable section silencers in divergent and convergent sections or elbows of ventilation plants, the length of classical silencers can be reduced. Presented is an original calculation method for active noise silencers with a continuously variable section, as well as calculation relations worked out by this method for eight common practical cases.
Design concepts for an improved automotive gas turbine powertrain are discussed. Twenty percent fuel economy improvement (over 1976), competitive costs (initial and life cycle), high reliability/life, low emissions, and noise/safety compliance were among the factors considered. The powertrain selected consists of a two shaft gas turbine engine with variable geometry aerodynamic components and a single disk rotating regenerator. The regenerator disk, gasifier turbine rotor, and several hot section flowpath parts are ceramic. The powertrain utilizes a conventional automatic transmission. The closest competitor was a single shaft turbine engine matched to a continuously variable transmission (CVT). Both candidate powertrain systems were found to be similar in many respects; however, the CVT represented a significant increase in development cost, technical risk, and production start-up costs over the conventional automatic transmission. Installation of the gas turbine powertrain was investigated for a transverse mounted, front wheel drive vehicle.
In recent years there have been several hierarchic multilevel optimization algorithms proposed and implemented in design studies. Equality constraints are often imposed between levels in these multilevel optimizations to maintain system and subsystem variable continuity. Equality constraints of this nature will be referred to as coupling equality constraints. In many implementation studies these coupling equality constraints have been handled indirectly. This indirect handling has been accomplished using the coupling equality constraints' explicit functional relations to eliminate design variables (generally at the subsystem level), with the resulting optimization taking place in a reduced design space. In one multilevel optimization study where the coupling equality constraints were handled directly, the researchers encountered numerical difficulties which prevented their multilevel optimization from reaching the same minimum found in conventional single level solutions. The researchers did not explain the exact nature of the numerical difficulties other than to associate them with the direct handling of the coupling equality constraints. The coupling equality constraints are handled directly, by employing the Generalized Reduced Gradient (GRG) method as the optimizer within a multilevel linear decomposition scheme based on the Sobieski hierarchic algorithm. Two engineering design examples are solved using this approach. The results show that the direct handling of coupling equality constraints in a multilevel optimization does not introduce any problems when the GRG method is employed as the internal optimizer. The optimums achieved are comparable to those achieved in single level solutions and in multilevel studies where the equality constraints have been handled indirectly.
Many complex real-world decision and control problems contain an underlying constraint reasoning problem. This is particularly evident in a recently developed approach to planning, where almost all planning decisions are represented by constrained variables. This translates a significant part of the planning problem into a constraint network whose consistency determines the validity of the plan candidate. Since higher-level choices about control actions can add or remove variables and constraints, the underlying constraint network is invariably highly dynamic. Arbitrary domain-dependent constraints may be added to the constraint network and the constraint reasoning mechanism must be able to handle such constraints effectively. Additionally, real problems often require handling constraints over continuous variables. These requirements present a number of significant challenges for a constraint reasoning mechanism. In this paper, we introduce a general framework for handling dynamic constraint networks with real-valued variables, by using procedures to represent and effectively reason about general constraints. The framework is based on a sound theoretical foundation, and can be proven to be sound and complete under well-defined conditions. Furthermore, the framework provides hybrid reasoning capabilities, as alternative solution methods like mathematical programming can be incorporated into the framework, in the form of procedures.
A control-augmented structural synthesis methodology is presented in which actuator and sensor placement is treated in terms of (0,1) variables. Structural member sizes and control variables are treated simultaneously as design variables. A multiobjective utopian approach is used to obtain a compromise solution for inherently conflicting objective functions such as strucutal mass control effort and number of actuators. Constraints are imposed on transient displacements, natural frequencies, actuator forces and dynamic stability as well as controllability and observability of the system. The combinatorial aspects of the mixed - (0,1) continuous variable design optimization problem are made tractable by combining approximation concepts with branch and bound techniques. Some numerical results for example problems are presented to illustrate the efficacy of the design procedure set forth.
Emission from Sagittarius A* is highly variable at both X-ray and infrared (IR) wavelengths. Observations over the last ∼20 yr have revealed X-ray flares that rise above a quiescent thermal background about once per day, while faint X-ray flares from Sgr A* are undetectable below the constant thermal emission. In contrast, the IR emission of Sgr A* is observed to be continuously variable. Recently, simultaneous observations have indicated a rise in IR flux density around the same time as every distinct X-ray flare, while the opposite is not always true (peaks in the IR emission may not be coincident with an X-ray flare). Characterizing the behavior of these simultaneous X-ray/IR events and measuring any time lag between them can constrain models of Sgr A* ʼs accretion flow and the flare emission mechanism. Using 100+ hours of data from a coordinated campaign between the Spitzer Space Telescope and the Chandra X-ray Observatory, we present results of the longest simultaneous IR and X-ray observations of Sgr A* taken to date. The cross-correlation between the IR and X-ray light curves in this unprecedented data set, which includes four modest X-ray/IR flares, indicates that flaring in the X-ray may lead the IR by approximately 10–20 min with 68% confidence. However, the 99.7% confidence interval on the time-lag also includes zero, i.e., the flaring remains statistically consistent with simultaneity. Long-duration and simultaneous multi-wavelength observations of additional bright flares will improve our ability to constrain the flare timing characteristics and emission mechanisms, and must be a priority for Galactic Center observing campaigns.